Swing Suite (SMT/Divergences + Gann Swings)Hello Traders!
TRN Swing Suite (SMT/Divergences + Gann Swings) is an indicator which identifies, and highlights pivot points (swings) and prints a lot of information about the swings in the chart (e.g. length, duration, cumulative Delta, ...). Furthermore, it detects divergences in connection with any given indicator, even custom ones. In addition to this, you can choose the algorithm to compute the swings. The famous Gann-Swing algorithm and the extremely precise TRN Swing algorithm (called Standard) are available for selection, as well as two other variants. Compared to other swing or zig-zag indicators it works in real-time, does not need a look-a-head to find swings and is not repainting. Moreover, equal (double) highs and lows are detected and displayed. The TRN Swing Suite helps traders to visualize the pure price action and identify key turning points or trends. The indicator comes with the following features:
Precise real-time swing detection without repainting
Divergence detecting for any given (custom) indicator - with 11 different preset indicators
SMT (Smart Money Technique)/Divergence detecting in relation to other instruments
Swing Performance Statistics
Swing support and resistance levels
Swing trend for multiple swing sizes
Equal/double high and low detection
4 different swing computation styles
Displaying of swing labels, values and information
Customizable settings as well as look and feel
It's important to note that the TRN Swing Suite is a visual tool and does not provide specific buy or sell signals. It serves as a guide for traders to analyze market structure in depth and make well-informed trading decisions based on their trading strategy and additional technical analysis.
Divergence Detection for any given (Custom) Indicator
The divergence detector finds with unrivaled precision bullish and bearish as well as regular and hidden divergences. The main difference compared to other divergences indicators is that this indicator finds rigorously the extreme peaks of each swing, both in price and in the corresponding indicator. This precision is unmatched and therefore this is one of the best divergences detectors.
The build in divergence detector works with any given indicator, even custom ones. In addition, there are 11 built-in indicators. Most noticeable is the cumulative delta indicator, which works astonishingly well as a divergence indicator. Full list:
External Indicator (see next section for the setup)
Awesome Oscillator (AO)
Commodity Channel Index (CCI)
Cumulative Delta Volume (CDV)
Chaikin Money Flow (CMF)
Moving Average Convergence Divergence (MACD)
Money Flow Index (MFI)
Momentum
On Balance Volume (OBV)
Relative Strength Index (RSI)
Stochastic
Williams Percentage Range (W%R)
The divergences are colored with vivid lines and labels. Bullish divergences are distinguished with luminous blue lines, while bearish divergences are denoted by striking red lines. Upon detecting a divergence, the colored lines act as a visual indicator for traders, signaling an imminent possibility of a trend reversal. In response, traders can leverage this valuable insight to make informed decisions in their trading activities.
Choose Your Custom Divergence Indicator
Handpick your custom indicator, and the TRN Swing Suite will hunt for divergences on your preferred market and timeframe. Importantly, you must add the indicator to your chart. Afterwards, simply go to the “Divergence Detection” section in the TRN Swing Suite indicator settings and choose "External Indicator". If the custom indicator has one reference value, then choose this value in the “External Indicator (High)” field. If there are high and low values (e.g. candles), then you also must set the “External Indicator Low” field.
In the provided graphic, we've chosen the stochastic RSI as our example, and as you can see, the TRN Swing Suite instantly identifies and plots bullish and bearish divergences on your chart.
Smart Money Technique (SMT)/Divergence detecting in Relation to other Instruments
Smart Money Technique/Tool (SMT) means the divergence detection between two related instruments. The TRN Swing Suite finds divergence in relation to other instruments, e.g. NQ vs ES or BTCUSDT vs ETHUSDT. Just add another instrument to the chart. As representation style you can choose lines or candles/bars. Afterwards, simply go to the “Divergence Detection” section in the TRN Swing Suite indicator settings and choose "External Indicator". If the second instrument is represented as line, then choose this value in the “External Indicator (High)” field. If there are high and low values (e.g. candles/bars), then you also must set the “External Indicator Low” field.
The detection of SMTs can help traders to decide whether the trend continues, or a reversal is imminent. E.g. if the NQ makes a new higher high but the ES fails to do so and makes a new lower high, then the TRN Swing Suite shows a divergence. As a result, the probability is high that the trend will not continue, and the trader can make an informed decision about what to do next.
How to Set Parameters for Divergence Indicators
To begin, access the indicator settings and find the “Divergence Detection”. Look for the "Parameters" sections where you can fine-tune Parameters 1-3. The default settings are already optimized for the oscillators AO, RSI, CDV, W%R, MFI and Stochastic. For other divergence indicators, you might want to adjust the settings to your liking. The parameter order is the same as in the corresponding divergence indicator.
TRN Swing Suite Statistics
Unveil the untapped potential of advanced Swing Statistics! Gain invaluable insights into historical swings and turning points. Elevate your expertise by harnessing this treasure trove of data to supercharge signal reliability, while masterfully planning stop loss and take profit strategies with unrivaled accuracy. Within the TRN Swing Suite lie two powerful statistics, each offering distinct insights to empower your trading prowess.
Swing Statistic
The Swing Statistic comprises of two series, one for up swings (Up) and one for down swings (Down), with values given in points. The columns have the following meaning:
Up or down
# - total number of analyzed swings
Overall ∅ Length - average length of all swings in points
Overall ∅ Duration - average duration of swings in bars
∅ Length - average lengths for custom-defined swing counts
∅ Duration - average durations for custom-defined swing counts
The custom-defined swing count is used to determine the swing length/duration for the last x swings. Note, in the case of well-established assets like Microsoft or Nvidia, which have undergone one or more stock splits, the overall average in column three may deviate significantly from those in column five. That is why column 5 is useful.
Relation Statistic
The Relation Statistic highlights percentages representing the historical occurrence of specific high and low sequences. In the first column (in %), various types of highs and lows are listed as reference points.
For example, the first row corresponds to "HH followed by", where the second column (#) displays the total count of higher highs (HH) considered. The subsequent columns showcase the percentages of how often certain patterns follow the initial HH.
Fields marked in blue represent sequences that occurred in over 50% of cases. The darker the shade of blue in each field, the higher the percentage.
Use Swing Statistics to Validate Stop-Loss and Take-Profit Levels
No matter which signals you choose to trade, consulting Swing Statistics can significantly enhance the reliability of these signals.
For example, when looking for a long entry after a lower low (LL), you can examine the likelihood of a subsequent lower high (LH) or even a higher high (HH). Combining this valuable information with your predetermined Take Profit level allows you to better assess whether your target can be achieved successfully. Additionally, you can add the average up swing length to the lower low for an alternative Take Profit level. Similarly, you can verify the probability of the next low being a higher low (HL) or another lower low (LL) to determine the likelihood of your Stop Loss being triggered. Align the length of the last down swing with the average down swing length for an alternative Stop Loss.
Swing Support and Resistance Levels
Swing support and resistance levels are horizontal lines starting from a swing high or swing low and representing natural support and resistance levels. Price tends to respect this levels one way or another. In most cases, old swing highs and swing lows provide a lot of liquidity to the market. For example, for a swing high there are at least three different market players at work:
Traders put there stop loss above the swing high
Breakout traders go long above the swing high
Turtle soup (reverse) trader go short above the swing high
Swing Trend (Multiple Sizes)
The TRN Swing Suite can display either at the top or at the bottom the prevailing swing trends for the main trend seen in the chart and for two additional swing sizes. This is useful to see the swing trend for medium and bigger swings to get a clear picture of the market.
Getting an Edge with the TRN Swing Suite
The indicator clearly displays up trends, defined as a sequence of higher highs (HH) and higher lows (HL), with green labels and down trends, defined as a sequence of lower lows (LL) and lower highs (LH), with red labels. Equal highs/double tops (DT) and equal lows/ double bottoms (DB) are highlighted in gold.
In addition, the labels show a full stack of valuable information about the swings to maximize your accuracy.
Length
Length percentage in relation to the last swing length
Duration
Time
Volume
Cumulative Delta
In an uptrend the up swings should have higher volume und higher cumulative delta than the down swings. The duration and time for down swings in an uptrend should be shorter than for the up swings.
Use Cases for Swing Detection
Trend Identification
By connecting the swing highs and lows, traders can identify and analyze the prevailing trend in the market. An uptrend is characterized by higher swing highs and lows, while a downtrend is characterized by lower highs and lower lows. The indicator helps traders visually assess the strength and continuity of the trend.
Support And Resistance Levels
The swing highs and lows can act as support and resistance levels. Swing highs may act as resistance levels where selling pressure increases, while swing lows may act as support levels where buying pressure increases. Traders often pay attention to these levels as potential areas for trade entries, exits, or placing stop-loss orders.
Pattern Recognition
The swings identified by the indicator can help traders recognize chart patterns, such as equal high/lows, consolidations, wedges, triangles or more complex patterns like Gartley or Head and Shoulders. These patterns can provide insights into potential trend continuation or reversal.
Trade Entry and Exit
Traders may use TRN Swing to determine potential trade entry and exit points. For example, in an uptrend, traders may look for opportunities to enter long positions near swing lows or on pullbacks to support levels. Conversely, in a downtrend, traders may consider short positions near swing highs or on retracements to resistance levels.
Swing Styles
In addition to the standard swings, you have the flexibility to choose between various swing styles, including ticks, percent, or even the famous Gann swings.
Standard
Gann
Ticks
Percent
Conclusion
While signals from TRN Swings can be informative, it is important to recognize that their reliability may vary. Various external factors can impact market prices, and it is essential to consider your risk tolerance and investment goals when executing trades.
Risk Disclaimer
The content, tools, scripts, articles, and educational resources offered by TRN Trading are intended solely for informational and educational purposes. Remember, past performance does not ensure future outcomes.
חפש סקריפטים עבור "high low"
MTF Smart Money ConceptsOverview
This indicator displays major elements of Smart Money Concepts and price action trading with multi-timeframes(MTF) and layered market structures with color visualization.
What is Smart Money Concepts?
Smart Money Concepts(SMC) is one of the methodologies to interpret how financial market moves and to analyze it and execute trades, focusing on liquidity and order flow of financial institutions.
Smart money means the funds invested by large financial institutions such as banks, institutional traders/investors, market makers, hedge funds etc. contrary to retail traders/investors' money.
It is important to note that there is no proof or evidence that those institutions move the market as described in Smart Money Concepts.
Personally speaking, it is one of the interpretation of the market and another angle to view the market just like other technical analysis methodologies such as Elliott Wave Principle, Gann Theory, Wyckoff Method and even traditional price action trading.
Importance of MTF Analysis
MTF analysis(a.k.a Topdown analysis) is the foundation to technically analyze charts and the most fundamental skill in trading because lower timeframes are always influenced by upper timeframes where large financial institutions operate.
How to use
This indicator is designed to help traders analyze how the market moves in terms of SMC and price action with multi-timeframes and color visualization of the market structures, which makes this indicator unique and different from other indicators.
There is two key settings that you can use based on your trading style.
1.Upper timeframe selection
You have two options to determine upper timeframe; Auto mode and Manual mode.
When Auto mode selected, upper timeframe will be determined based on chart timeframe as follows.
Chart timeframe => Upper timeframe
1M=>15M
5M/15M=>1H
30M/1H=>4H
4H=>D
D=>W
W=>M
If you select Manual mode, you can fix an upper timeframe.
2.High/low settings
This affects all other settings of the indicator and most importantly designs the market structure.
This is the key setting to determine how you view the market as price action trading is all about highs and lows and story of how highs and lows have been created with the market structure.
You can specify left bars and right bars to identify swing highs/lows and these highs/lows become the basis to design the market structure and determine how SMC elements are displayed.
Example:
Left bar&right bar: 10
You can see bigger wave(magenta line) in the market structure(stepped line).
(Magenta line is a drawn object by manual)
Left bar&right bar: 4
With this setting, you can see smaller wave in the market structure.
Since market moves like wave as there is a lot of wave theories in financial investment/trading industry such as Elliott wave, Wolf wave etc., users can define market structure with this setting depending on what degree of wave they aim to trade.
Functions:
MTF Order Block
Concept
Order block is a block of orders where buying orders and selling orders are accumulated. Order blocks are created when the institutions move the market up and down, temporality placing orders in an opposite direction to the way they want to move, in order to match their own orders with counter-orders.
Visualization by the indicator
The indicator displays both chart timeframe's order blocks and upper timeframe's order blocks(MTF).
You can also select from two options how to display order blocks;
1. Show all order blocks
2. Show strong order blocks only
Note: Strong order blocks mean order blocks created at strong highs/lows. See also strong high/low below.
Alerts can be set when prices reach strong order blocks.
MTF Fair Value Gap(FVG)/Imbalance
Concept
Fair Value Gap(FVG)(Imbalance) is a void generated among three consecutive candlesticks.
FVG(s) is created when the market moves so rapidly generating buy side or sell side order imbalances.
FVG(s) is characterized by price action that prices tend to come back to the area where FVG(s) exists, filling in the space among the candlesticks.
Visualization by the indicator
The indicator displays both chart timeframe's FVG and upper timeframe's FVG.
MTF Liquidity Grab
Concept
Liquidity grab is price action to sweep liquidity for the institutions to move the market.
This price action often happens because the size of their orders is so huge and they need a bunch of counter-orders to match their orders. This is why prices sometimes come to areas where liquidity rest and swipe them before the market goes up/down.
Liquidity visualization
Where does liquidity rest?
The answer is above highs(buy side liquidity) and below lows(sell side liquidity).
Among all highs and lows, swing highs and lows are where liquidity is accumulated the most because swing highs and lows can be created only by the institutions, therefore massive liquidity is indicated.
Visualization by the indicator
The indicator displays liquidity dots so that users can easily identify where liquidity rests and liquidity grab of both a chart timeframe and an upper timeframe.
Alerts can be set when liquidity grab happens.
MTF Strong High/Low
Concept
Strong high/low literally means strong highs and lows among all highs and lows including swing highs and lows.
There is a few different definitions of strong high/low in price action trading and the definition in this indicator is as follows.
Strong high
A high that that breaks higher low or lower low
Strong low
A low that breaks lower high or higher high
Visualization by the indicator
The indicator displays strong highs and lows of both a chart timeframe and an upper timeframe.
MTF Market Structure Visualization
Concept
Market structure is a series of price movement with highs and lows which outlines the way the market directs. It is a basis to see trend occurrence, trend reversal and sideways and analyzing the market structures in multi-timeframes is the most fundamental technical skill in trading/investment.
Visualization by the indicator
The indicator displays market structures of both a chart timeframe and an upper timeframe and provide color visualization depending on bullish and bearish market structures.
The definition of bullish and bearish market structure is as follows.
Bullish market structure
When a price breaks a Lower High or Higher High
Bearish market structure
When a price breaks a Higher Low or Lower Low
Settings
All the functions above, colors and line settings are parameterized and can be turned on/off depending on users’ needs.
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概要
Smart Money Concepts(SMC)およびプライスアクショントレードにおける重要な要素をマルチタイムフレームで表示することのできるインジケーターです。
相場構造(Market structure)をマルチタイムフレームで表示し、相場構造の強弱を色で可視化することができます。
Smart Money Concepts(スマートマネーコンセプト)とは？
Smart Money Concepts(以下SMC) は金融市場がどのように動くかを解釈し、分析し、取引を執行するための相場理論の一つであり、Liquidity(リクイディティ)および機関投資家のオーダーフロー(注文の流れ)に焦点を置いていることが特徴です。
Smart Money(スマートマネー)とは、銀行や機関投資家、マーケットメーカー、ヘッジファンドといった金融機関が動かす資金を意味し、個人投資家の資金と対をなす概念です。
重要な点は、実際に上記の金融機関がSmart Money Conceptsで語られているような相場の動かし方をしているかどうかを証明する明確なエビデンスはないということです。
個人的には、エリオット波動理論やギャン理論、ワイコフ理論、伝統的なプライスアクショントレーディングの方法論と同様に、マーケットの動きを解釈するための一つの方法論であり、マーケットの動きを別の角度から見る枠組みと捉えています。
マルチタイムフレーム(MTF)分析の重要性
MTF分析はチャートをテクニカルに分析する上での基礎であり、トレードにおいて最も重要なスキルです。なぜなら下位のタイムフレームは上記のような金融機関が資金運用を行う上位のタイムフレームの影響を常に受けるためです。
使い方
このインジケーターは、SMCまたはプライスアクショントレードの観点から、トレーダーがマーケットをマルチタイムフレームで分析することを支援するために開発しています。
相場構造(Market structure/マーケットストラクチャー)を方向性に応じて色で可視化することができるため、視覚的に相場の構造を判断できることがこのインジケータのユニークな点であり、他のインジケーターと異なる点です。
ユーザーのトレードスタイルに応じて、以下の二つの設定を行うことができます。
1.上位足の決定方法
ユーザーは上位足のタイムフレームを決定するにあたり、AutoモードとManualモードを選択することができます。
Autoモードを選択した場合、上位足はチャートのタイムフレームに応じて以下のように決定されます。
チャートタイムフレーム => 上位足タイムフレーム
1M=>15M
5M/15M=>1H
30M/1H=>4H
4H=>D
D=>W
W=>M
Manualモードを選択すると上位足のタイムフレームを固定することができます。
2.High/low(高値/安値) 設定
当設定はインジケーターの他の全ての機能に影響し、また最も重要である相場構造の定義に影響します。
当設定はユーザーがマーケットをどのように見るか(=どの程度の粒度)を決定する重要な設定です。なぜならプライスアクショントレードは、高値、安値とそれらが相場構造をどのように構築してきたかの一連の流れを分析することが全てだからです。
ユーザーは相場構造を決定付けるスイングハイ·スイングローを特定するためのバーの本数を設定することができます。ここで設定した内容が、相場構造を定義し、以下で説明するSMCの要素の表示を決定することになります。
例:
Left bar&right bar(左右のバーの数): 10
この場合、ステップラインで示した相場構造の中に大きな波(マゼンタの波)を見ることができます。
(マゼンタのラインは手動で描いたオブジェクト)
Left bar&right bar: 4
この設定では、上記に比べて小さい波を描いていることが確認できます。
相場理論の中にエリオット波動理論やウォルフ波動といった数多くの波動理論があることからわかるように、相場は波として動きます。どの粒度の波を狙うかというトレーダーのスタイルに応じて、設定を変更することができます。
機能
MTFオーダーブロック
コンセプト
オーダーブロックとは買い注文と売り注文が一連となって蓄積されたオーダー(注文)のブロックのことです。
オーダーブロックは機関投資家が相場を動かす際に、本来意図する方向とは一時的に逆に動かすことで、彼ら自身の注文をマッチングさせるための反対注文を発生させることで形成されます。
インジケーターによる表示
インジケーターはチャートタイムフレームのオーダーブロックと上位足のオーダーブロックの両方を表示することができます。
また、オーダーブロックの表示オプションとして、
1.全てのオーダーブロックを表示
2.Strong(ストロング)オーダーブロックのみを表示
を選択することが可能です。
注: StrongオーダーブロックはStrong High/Lowで形成されるオーダーブロックを指します。(下記参照)
また、オーダーブロック到達でのアラート設定も可能です。
MTFフェアーバリューギャップ(FVG)/インバランス
コンセプト
フェアーバリューギャップ(FVG)/インバランスとは連続する3つのローソク足の間に形成される溝(Gap)のことです。
フェアーバリューギャップはマーケットが非常に早く動いたことにより、買いオーダーと売りオーダーの需給バランスが崩れることによって発生します。
フェアーバリューギャップには、価格がフェアーバリューギャップが発生したエリアまで戻ってくる傾向があるという特徴が存在します。
インジケーターによる表示
インジケーターはチャートタイムフレームのフェアーバリューギャップと上位足のフェアーバリューギャップの両方を表示することができます。
MTF Liquidity Grab(リクイディティ·グラブ)
コンセプト
Liquidity(リクイディティ)とはマネー、つまり注文です。
Liquidity Grab(リクイディティ·グラブ)とは、機関投資家がマーケットを動かす際にLiquidityを取得するプライスアクションのことを指します。
このプライスアクションは、機関投資家が処理する注文サイズが非常に大きいため、自身の注文を出す際に大量の反対注文を必要とすることからしばしば発生します。
これが、価格がLiquidity(注文)の集まっているエリアに接近し、それら注文をスワイプ(狩り取る)した後に上昇·下落する理由です。
Liquidityの可視化
一般的にLiquidityは高値の上(buy side liquidity)、安値の下(sell side liquidity)に存在します。
全ての高値·安値の中で、スイングハイ·ローがliquidityが最も蓄積されているエリアということができます。なぜならスイングハイ·ローは機関投資家の注文によってのみ形成されるからです。
インジケーターによる表示
ユーザーがLiquidityポイントを簡単に識別できるようにLiquidityをドット表示することが可能です。またチャートタイムフレームと上位足の両方のLiquidity Grabを表示することができます。
Liquidity Grab発生時にアラートも設定可能です。
MTF Strong High/Low(ストロングハイ·ロー)
コンセプト
Strong high/lowは文字通り、強い高値·安値のことを指します。
トレーダーの間でいくつかの異なる定義が存在しますが、当インジケーターでの定義は以下の通りです。
Strong high
Higher low(ハイアーロー) または Lower low(ロワーロー)をブレイクした高値
Strong low
Lower higher (ロワーハイ) または Higher High(ハイアーハイ)をブレイクした安値
インジケーターによる表示
チャートタイムフレーム、上位足のStrong High/Lowを表示することが可能です。
相場構造可視化
コンセプト
相場構造(Market structure/マーケットストラクチャー)とは、相場の流れを成り立たせる高値と安値を元にした一連の値動きです。建物における骨組みに該当します。
トレンドの発生、転換、レンジを見極めるための基礎であり、マルチタイムフレームで相場構造を分析することは、投資·トレードにおいて最も重要なテクニカルスキルです。
インジケーターによる表示
チャートタイムフレームと上位足タイムフレーム両方の相場構造を表示することができます。
また、相場構造が強気の状態か弱気の状態かを色で可視化するため、上位足含めた相場の流れを視覚的に判断することが可能です。
相場構造の強弱の定義は以下の通りです。
強気の相場構造(Bullish market structure)
価格がLower HighまたはHigher Highをブレイクしたとき
弱気の相場構造(Bearish market structure)
価格がHigher LowまたはLower Lowをブレイクしたとき
設定
上記の全ての機能は色やライン設定含めパラメーターで設定が可能です。またユーザの必要に応じて表示·非表示を切り替えることができます。
Tug-of-War Fast/Slow Technical IndicatorThe script Tug-of-War (ToW) Fast/Slow has a couple of lines (red and purple) and areas (purple and greenish) which give the trend. It also has one line (blue) and dots (green) that give the up-and-down swing.
HOW THE INDICATOR WORKS
It is based on moving averages run on normal OHLC bars, Heikin Ashi bars as well as customized bars (which modify the open/high/low/close values similar to how Haikin Ashi bars do). These moving averages are weighted by volume and related to each other (for example differences are calculated) to produce the final lines. Since the script requires volume, it may not work for tickers which don't have volume (however for some tickers the script uses a proxy-volume so that they work; for example it uses the SPY volume for VIX). There is a different but similar script that I'll be publishing (ToW Simple) which doesn't use volume and runs on any ticker.
HOW TO SETUP THE INDICATOR
The indicator can be run on "close" prices as well as "open", "high", "low" and several mini-max modes ("MM ..."). They pick highs and lows (minim and maxim values, hence the mini-max name) to generate the indicator lines. See the drop down box options under "Adjust Close Type" (the very fist options in the script settings). The multiple MM modes use different formulas to calculate the mini-max values. The more significant MM modes are MM ZZ (zig-zag), MM HL/HL (determines highs and lows based on highs and lows), MM HL/C (determines highs and lows based on close) and MM Close. Note: if the MM ZZ mode show you the highs for the current bar and you actually want the lows (or vice versa) check "MM ZZ Reverse".
The indicator has two fast lines:
the green dots (called F1 since it's the 1st Fast line, actually dots)
the blue line (called F2--the 2nd Fast line)
They are called "fast" because they move up and down faster. In previous iterations of the script I called them "swing lines" since they capture the prices swing up and down. The blue line is the more significant one (since the green one I set, by default to dots instead of an actual line).
The indicator has two slow lines:
the purple line (called S1 since it's the 1st Slow line)
the blue line (called S2--the 2nd Slow line)
They move slower than the fast line and they are better at determining the trend.
The order of lines, from fast to slow, is: F1 (green), F2 (blue), S1 (purple) and S2 (red).
The indicator also has two areas:
the greenish area (called FA since it's the Fast Area)
the purple area (called SA since it's the Slow Area)
Additional lines (but less significant are displayed if you uncheck the "Clean look" option).
The script allows to display up to for sets of lines (see the top "Adjust Close Type (Set #)" options). For example one set may show "Highs" and the other "Lows" or "Close" and "MM HL/HL". Additionally it can run in multi-set mode when it shows the chosen one line (F1, F2, S1, S2, FA, SA) for each OHLC (open, high, low, close). See "Only Show Related Lines" option. In this display purple is the line for Open, green is the line for High, red is the line for Low and black is the line for Close.
The indicator also has a custom mode (see the "Enable custom bars" checkbox and the options following it). With it you can change the open/high/low/close value (see "Custom #1 OHLC to Modify") of a bar ("Custom #1 Index To Modify" determines which bare to modify, 0 being the most recent bar). Then "Custom #1 Modifier Type" specifies to use open/high/low/close value of the same or different bar (use "Custom #1 Modifier Index/Value ..." to choose which bar's OHLC value to use for the custom value; 0 means the O/H/L/C value of the same bar as the one being modified; 1 means previous bar, etc.). If "Custom" is selected instead (under Modifier Type) then you can enter the custom value in the "Custom #1 Modifier Index/Value ..." field. This will show you how the indicator lines look like if the price was different. Three different bars can be modified this way. You can try different custom values and see for what price value one of the lines reaches a high or low point. That is an estimate of how far the price may go. Note: the indicator values depends depends on all OHLC values (plus volume) not just on the one chosen. That is, if the indicators is based on close values it is still affected to some extent by high, low and volume. Therefore the price value determined using the custom mode may not be exact but only a rough estimate (and the bigger changes in OHLC the bigger affect on the indicator and the actual price may not be exactly what was calculated using the custom mode.
HOW TO USE THE INDICATOR
Strategies and tools that apply to price such as resistance and support levels and trend lines, pitchforks (particularly Schiff pitchforks in case of the indicator) also apply to these lines. Because the indicator lines are within a range it is generally easier and faster to see and find such support/resistance levels and trend lines.
Additionally, the lines or the areas crossing the 0 line often indicate a change in trend (however if earlier indicator highs/lows bounce off around the 0 line that may happen this time around as well). The more significant 0 crossing is for the slow lines (red first and then purple) as well as the areas.
The slow lines and the areas, as mentioned already, show the trend (in previous iterations of the indicator I called them direction lines).
The fast lines (blue line, green dots) show the swing, as mentioned earlier. They often swing up and down. When they reach a high (you can thin of it as overbought) they may move back down on the next bar (or vice-versa when reaching a low). However, sometimes they don't swing but rather move in a line closer to a straight line (more like the slow lines). That indicates that the trend is stronger.
The fast lines can also indicate the trend by looking if their highs and/or lows are trending up or down. Thus, if the highs and lows are trending down then it's likely the price will go down.
Another thing to look at is divergence between the price and the slow lines or the high/lows trend of the fast lines (that I mentioned above). If the price is going up but the these are trending down then over the same bars then the price may be coming closer to a reversal.
STRATEGIES
Swing-in-trend. Find a ticker with the slow lines showing an upward trend (i.e., the red line crossing 0 or being above 0) and a the slow line (such as the blue line) reaching a previous low level (draw support levels and/or trend lines to determine that). Go long when the fast line reaches the support level or bottom trendline. The expectation is that the price will move up by the close of the next bar (when the position should normally be closed). The "go-short" setup is just reversed (slow lines trending down and the fast lines reaching high levels). You can use the "High", "Low", "MM ZZ" or one of the other MM modes instead of "Close" to get a better entry and exist point (in this case you enter when the the "Low" or "MM ZZ" modes reached a low and you enter if the "High" or "MM ZZ" reached a high or else exit at close of the next bar).
Trend-on-swing. When the red line is about to cross or just crossed the 0 line and wait for the swing line to go down first (you can use "High", "Low" or an MM mode, as explained dabove, for a better entry point) and then you enter the position and exit when either the slow (red) line reaches a resistance level, it crosses 0 the other way or when the fast line reaches a very high resistance level. This strategy will take longer, it won't be closed on the next bar.
Mini-max strategy. This is a new strategy I've developed. It uses MM ZZ mode (and a second MM ZZ set to "reverse") as well as "High", "Low" and "MM HL/HL" mode. I basically draw resistance and support lines on these, usually 2-3 lines for high and the same for low, for multiple tickers that seem a good match (they show a nice, consistent up/down pattern for MM ZZ). When the F2/blue lines reaches one of the horizontal lines further from the 0 lines (I setup alerts for this), then I enter expecting a move in the opposite direction. If it reaches the 2nd or 3rd low horizontal line then I go long. Then on the next bar when the F2 line reaches the 1st high horizontal line then I close the position (alternatively, I close half and keep half for when the second high horizontal line is reached). Alternatively, I may close the same bar, when the reversed MM ZZ setup reaches the 1st high horizontal line. I usually use this setup on weekly charts and use weekly options but it can be used on other charts such as daily charts as well.
I recommend to setup alerts on the indicator. After you draw a horizontal line or a trend line and you select it, its bar has a clock icon with a "+" sign. If you click on it you can setup an alert. In the setup dialog, under "Condition" select the indicator and then select the line of the indicator (such as "F2 (f_s/Blue)") then select "Once Per Bar" under "Options" (that's my recommendation, it will alert you only one time per bar). Finally customize the message for example: "ZZ: F2/blue /lo hl 1/3, TQQQ, 1D" (which means it's for MM ZZ mode when F2 (blue) line intersects the 1st (out of 3) low horizontal line (HL) and it's for TQQQ on 1D chart. When I use the reverse mode for ZZ then I write: "ZZr: ..."
In the chart above, the first indicator shows the "Close" mode and the second the "MM ZZ" mode (along with 2 levels for high and low).
Dynamic Equity Allocation Model"Cash is Trash"? Not Always. Here's Why Science Beats Guesswork.
Every retail trader knows the frustration: you draw support and resistance lines, you spot patterns, you follow market gurus on social media—and still, when the next bear market hits, your portfolio bleeds red. Meanwhile, institutional investors seem to navigate market turbulence with ease, preserving capital when markets crash and participating when they rally. What's their secret?
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This document presents exactly such a system—not a proprietary black box available only to hedge funds, but a fully transparent, academically grounded framework that any serious investor can understand and apply. The Dynamic Equity Allocation Model (DEAM) synthesizes decades of financial research from Nobel laureates and leading academics into a practical tool for tactical asset allocation.
Stop drawing colorful lines on your chart and start thinking like a quant. This isn't about predicting where the market goes next week—it's about systematically adjusting your risk exposure based on what the data actually tells you. When valuations scream danger, when volatility spikes, when credit markets freeze, when multiple warning signals align—that's when cash isn't trash. That's when cash saves your portfolio.
The irony of "cash is trash" rhetoric is that it ignores timing. Yes, being 100% cash for decades would be disastrous. But being 100% equities through every crisis is equally foolish. The sophisticated approach is dynamic: aggressive when conditions favor risk-taking, defensive when they don't. This model shows you how to make that decision systematically, not emotionally.
Whether you're managing your own retirement portfolio or seeking to understand how institutional allocation strategies work, this comprehensive analysis provides the theoretical foundation, mathematical implementation, and practical guidance to elevate your investment approach from amateur to professional.
The choice is yours: keep hoping your chart patterns work out, or start using the same quantitative methods that professionals rely on. The tools are here. The research is cited. The methodology is explained. All you need to do is read, understand, and apply.
The Dynamic Equity Allocation Model (DEAM) is a quantitative framework for systematic allocation between equities and cash, grounded in modern portfolio theory and empirical market research. The model integrates five scientifically validated dimensions of market analysis—market regime, risk metrics, valuation, sentiment, and macroeconomic conditions—to generate dynamic allocation recommendations ranging from 0% to 100% equity exposure. This work documents the theoretical foundations, mathematical implementation, and practical application of this multi-factor approach.
1. Introduction and Theoretical Background
1.1 The Limitations of Static Portfolio Allocation
Traditional portfolio theory, as formulated by Markowitz (1952) in his seminal work "Portfolio Selection," assumes an optimal static allocation where investors distribute their wealth across asset classes according to their risk aversion. This approach rests on the assumption that returns and risks remain constant over time. However, empirical research demonstrates that this assumption does not hold in reality. Fama and French (1989) showed that expected returns vary over time and correlate with macroeconomic variables such as the spread between long-term and short-term interest rates. Campbell and Shiller (1988) demonstrated that the price-earnings ratio possesses predictive power for future stock returns, providing a foundation for dynamic allocation strategies.
The academic literature on tactical asset allocation has evolved considerably over recent decades. Ilmanen (2011) argues in "Expected Returns" that investors can improve their risk-adjusted returns by considering valuation levels, business cycles, and market sentiment. The Dynamic Equity Allocation Model presented here builds on this research tradition and operationalizes these insights into a practically applicable allocation framework.
1.2 Multi-Factor Approaches in Asset Allocation
Modern financial research has shown that different factors capture distinct aspects of market dynamics and together provide a more robust picture of market conditions than individual indicators. Ross (1976) developed the Arbitrage Pricing Theory, a model that employs multiple factors to explain security returns. Following this multi-factor philosophy, DEAM integrates five complementary analytical dimensions, each tapping different information sources and collectively enabling comprehensive market understanding.
2. Data Foundation and Data Quality
2.1 Data Sources Used
The model draws its data exclusively from publicly available market data via the TradingView platform. This transparency and accessibility is a significant advantage over proprietary models that rely on non-public data. The data foundation encompasses several categories of market information, each capturing specific aspects of market dynamics.
First, price data for the S&P 500 Index is obtained through the SPDR S&P 500 ETF (ticker: SPY). The use of a highly liquid ETF instead of the index itself has practical reasons, as ETF data is available in real-time and reflects actual tradability. In addition to closing prices, high, low, and volume data are captured, which are required for calculating advanced volatility measures.
Fundamental corporate metrics are retrieved via TradingView's Financial Data API. These include earnings per share, price-to-earnings ratio, return on equity, debt-to-equity ratio, dividend yield, and share buyback yield. Cochrane (2011) emphasizes in "Presidential Address: Discount Rates" the central importance of valuation metrics for forecasting future returns, making these fundamental data a cornerstone of the model.
Volatility indicators are represented by the CBOE Volatility Index (VIX) and related metrics. The VIX, often referred to as the market's "fear gauge," measures the implied volatility of S&P 500 index options and serves as a proxy for market participants' risk perception. Whaley (2000) describes in "The Investor Fear Gauge" the construction and interpretation of the VIX and its use as a sentiment indicator.
Macroeconomic data includes yield curve information through US Treasury bonds of various maturities and credit risk premiums through the spread between high-yield bonds and risk-free government bonds. These variables capture the macroeconomic conditions and financing conditions relevant for equity valuation. Estrella and Hardouvelis (1991) showed that the shape of the yield curve has predictive power for future economic activity, justifying the inclusion of these data.
2.2 Handling Missing Data
A practical problem when working with financial data is dealing with missing or unavailable values. The model implements a fallback system where a plausible historical average value is stored for each fundamental metric. When current data is unavailable for a specific point in time, this fallback value is used. This approach ensures that the model remains functional even during temporary data outages and avoids systematic biases from missing data. The use of average values as fallback is conservative, as it generates neither overly optimistic nor pessimistic signals.
3. Component 1: Market Regime Detection
3.1 The Concept of Market Regimes
The idea that financial markets exist in different "regimes" or states that differ in their statistical properties has a long tradition in financial science. Hamilton (1989) developed regime-switching models that allow distinguishing between different market states with different return and volatility characteristics. The practical application of this theory consists of identifying the current market state and adjusting portfolio allocation accordingly.
DEAM classifies market regimes using a scoring system that considers three main dimensions: trend strength, volatility level, and drawdown depth. This multidimensional view is more robust than focusing on individual indicators, as it captures various facets of market dynamics. Classification occurs into six distinct regimes: Strong Bull, Bull Market, Neutral, Correction, Bear Market, and Crisis.
3.2 Trend Analysis Through Moving Averages
Moving averages are among the oldest and most widely used technical indicators and have also received attention in academic literature. Brock, Lakonishok, and LeBaron (1992) examined in "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns" the profitability of trading rules based on moving averages and found evidence for their predictive power, although later studies questioned the robustness of these results when considering transaction costs.
The model calculates three moving averages with different time windows: a 20-day average (approximately one trading month), a 50-day average (approximately one quarter), and a 200-day average (approximately one trading year). The relationship of the current price to these averages and the relationship of the averages to each other provide information about trend strength and direction. When the price trades above all three averages and the short-term average is above the long-term, this indicates an established uptrend. The model assigns points based on these constellations, with longer-term trends weighted more heavily as they are considered more persistent.
3.3 Volatility Regimes
Volatility, understood as the standard deviation of returns, is a central concept of financial theory and serves as the primary risk measure. However, research has shown that volatility is not constant but changes over time and occurs in clusters—a phenomenon first documented by Mandelbrot (1963) and later formalized through ARCH and GARCH models (Engle, 1982; Bollerslev, 1986).
DEAM calculates volatility not only through the classic method of return standard deviation but also uses more advanced estimators such as the Parkinson estimator and the Garman-Klass estimator. These methods utilize intraday information (high and low prices) and are more efficient than simple close-to-close volatility estimators. The Parkinson estimator (Parkinson, 1980) uses the range between high and low of a trading day and is based on the recognition that this information reveals more about true volatility than just the closing price difference. The Garman-Klass estimator (Garman and Klass, 1980) extends this approach by additionally considering opening and closing prices.
The calculated volatility is annualized by multiplying it by the square root of 252 (the average number of trading days per year), enabling standardized comparability. The model compares current volatility with the VIX, the implied volatility from option prices. A low VIX (below 15) signals market comfort and increases the regime score, while a high VIX (above 35) indicates market stress and reduces the score. This interpretation follows the empirical observation that elevated volatility is typically associated with falling markets (Schwert, 1989).
3.4 Drawdown Analysis
A drawdown refers to the percentage decline from the highest point (peak) to the lowest point (trough) during a specific period. This metric is psychologically significant for investors as it represents the maximum loss experienced. Calmar (1991) developed the Calmar Ratio, which relates return to maximum drawdown, underscoring the practical relevance of this metric.
The model calculates current drawdown as the percentage distance from the highest price of the last 252 trading days (one year). A drawdown below 3% is considered negligible and maximally increases the regime score. As drawdown increases, the score decreases progressively, with drawdowns above 20% classified as severe and indicating a crisis or bear market regime. These thresholds are empirically motivated by historical market cycles, in which corrections typically encompassed 5-10% drawdowns, bear markets 20-30%, and crises over 30%.
3.5 Regime Classification
Final regime classification occurs through aggregation of scores from trend (40% weight), volatility (30%), and drawdown (30%). The higher weighting of trend reflects the empirical observation that trend-following strategies have historically delivered robust results (Moskowitz, Ooi, and Pedersen, 2012). A total score above 80 signals a strong bull market with established uptrend, low volatility, and minimal losses. At a score below 10, a crisis situation exists requiring defensive positioning. The six regime categories enable a differentiated allocation strategy that not only distinguishes binarily between bullish and bearish but allows gradual gradations.
4. Component 2: Risk-Based Allocation
4.1 Volatility Targeting as Risk Management Approach
The concept of volatility targeting is based on the idea that investors should maximize not returns but risk-adjusted returns. Sharpe (1966, 1994) defined with the Sharpe Ratio the fundamental concept of return per unit of risk, measured as volatility. Volatility targeting goes a step further and adjusts portfolio allocation to achieve constant target volatility. This means that in times of low market volatility, equity allocation is increased, and in times of high volatility, it is reduced.
Moreira and Muir (2017) showed in "Volatility-Managed Portfolios" that strategies that adjust their exposure based on volatility forecasts achieve higher Sharpe Ratios than passive buy-and-hold strategies. DEAM implements this principle by defining a target portfolio volatility (default 12% annualized) and adjusting equity allocation to achieve it. The mathematical foundation is simple: if market volatility is 20% and target volatility is 12%, equity allocation should be 60% (12/20 = 0.6), with the remaining 40% held in cash with zero volatility.
4.2 Market Volatility Calculation
Estimating current market volatility is central to the risk-based allocation approach. The model uses several volatility estimators in parallel and selects the higher value between traditional close-to-close volatility and the Parkinson estimator. This conservative choice ensures the model does not underestimate true volatility, which could lead to excessive risk exposure.
Traditional volatility calculation uses logarithmic returns, as these have mathematically advantageous properties (additive linkage over multiple periods). The logarithmic return is calculated as ln(P_t / P_{t-1}), where P_t is the price at time t. The standard deviation of these returns over a rolling 20-trading-day window is then multiplied by √252 to obtain annualized volatility. This annualization is based on the assumption of independently identically distributed returns, which is an idealization but widely accepted in practice.
The Parkinson estimator uses additional information from the trading range (High minus Low) of each day. The formula is: σ_P = (1/√(4ln2)) × √(1/n × Σln²(H_i/L_i)) × √252, where H_i and L_i are high and low prices. Under ideal conditions, this estimator is approximately five times more efficient than the close-to-close estimator (Parkinson, 1980), as it uses more information per observation.
4.3 Drawdown-Based Position Size Adjustment
In addition to volatility targeting, the model implements drawdown-based risk control. The logic is that deep market declines often signal further losses and therefore justify exposure reduction. This behavior corresponds with the concept of path-dependent risk tolerance: investors who have already suffered losses are typically less willing to take additional risk (Kahneman and Tversky, 1979).
The model defines a maximum portfolio drawdown as a target parameter (default 15%). Since portfolio volatility and portfolio drawdown are proportional to equity allocation (assuming cash has neither volatility nor drawdown), allocation-based control is possible. For example, if the market exhibits a 25% drawdown and target portfolio drawdown is 15%, equity allocation should be at most 60% (15/25).
4.4 Dynamic Risk Adjustment
An advanced feature of DEAM is dynamic adjustment of risk-based allocation through a feedback mechanism. The model continuously estimates what actual portfolio volatility and portfolio drawdown would result at the current allocation. If risk utilization (ratio of actual to target risk) exceeds 1.0, allocation is reduced by an adjustment factor that grows exponentially with overutilization. This implements a form of dynamic feedback that avoids overexposure.
Mathematically, a risk adjustment factor r_adjust is calculated: if risk utilization u > 1, then r_adjust = exp(-0.5 × (u - 1)). This exponential function ensures that moderate overutilization is gently corrected, while strong overutilization triggers drastic reductions. The factor 0.5 in the exponent was empirically calibrated to achieve a balanced ratio between sensitivity and stability.
5. Component 3: Valuation Analysis
5.1 Theoretical Foundations of Fundamental Valuation
DEAM's valuation component is based on the fundamental premise that the intrinsic value of a security is determined by its future cash flows and that deviations between market price and intrinsic value are eventually corrected. Graham and Dodd (1934) established in "Security Analysis" the basic principles of fundamental analysis that remain relevant today. Translated into modern portfolio context, this means that markets with high valuation metrics (high price-earnings ratios) should have lower expected returns than cheaply valued markets.
Campbell and Shiller (1988) developed the Cyclically Adjusted P/E Ratio (CAPE), which smooths earnings over a full business cycle. Their empirical analysis showed that this ratio has significant predictive power for 10-year returns. Asness, Moskowitz, and Pedersen (2013) demonstrated in "Value and Momentum Everywhere" that value effects exist not only in individual stocks but also in asset classes and markets.
5.2 Equity Risk Premium as Central Valuation Metric
The Equity Risk Premium (ERP) is defined as the expected excess return of stocks over risk-free government bonds. It is the theoretical heart of valuation analysis, as it represents the compensation investors demand for bearing equity risk. Damodaran (2012) discusses in "Equity Risk Premiums: Determinants, Estimation and Implications" various methods for ERP estimation.
DEAM calculates ERP not through a single method but combines four complementary approaches with different weights. This multi-method strategy increases estimation robustness and avoids dependence on single, potentially erroneous inputs.
The first method (35% weight) uses earnings yield, calculated as 1/P/E or directly from operating earnings data, and subtracts the 10-year Treasury yield. This method follows Fed Model logic (Yardeni, 2003), although this model has theoretical weaknesses as it does not consistently treat inflation (Asness, 2003).
The second method (30% weight) extends earnings yield by share buyback yield. Share buybacks are a form of capital return to shareholders and increase value per share. Boudoukh et al. (2007) showed in "The Total Shareholder Yield" that the sum of dividend yield and buyback yield is a better predictor of future returns than dividend yield alone.
The third method (20% weight) implements the Gordon Growth Model (Gordon, 1962), which models stock value as the sum of discounted future dividends. Under constant growth g assumption: Expected Return = Dividend Yield + g. The model estimates sustainable growth as g = ROE × (1 - Payout Ratio), where ROE is return on equity and payout ratio is the ratio of dividends to earnings. This formula follows from equity theory: unretained earnings are reinvested at ROE and generate additional earnings growth.
The fourth method (15% weight) combines total shareholder yield (Dividend + Buybacks) with implied growth derived from revenue growth. This method considers that companies with strong revenue growth should generate higher future earnings, even if current valuations do not yet fully reflect this.
The final ERP is the weighted average of these four methods. A high ERP (above 4%) signals attractive valuations and increases the valuation score to 95 out of 100 possible points. A negative ERP, where stocks have lower expected returns than bonds, results in a minimal score of 10.
5.3 Quality Adjustments to Valuation
Valuation metrics alone can be misleading if not interpreted in the context of company quality. A company with a low P/E may be cheap or fundamentally problematic. The model therefore implements quality adjustments based on growth, profitability, and capital structure.
Revenue growth above 10% annually adds 10 points to the valuation score, moderate growth above 5% adds 5 points. This adjustment reflects that growth has independent value (Modigliani and Miller, 1961, extended by later growth theory). Net margin above 15% signals pricing power and operational efficiency and increases the score by 5 points, while low margins below 8% indicate competitive pressure and subtract 5 points.
Return on equity (ROE) above 20% characterizes outstanding capital efficiency and increases the score by 5 points. Piotroski (2000) showed in "Value Investing: The Use of Historical Financial Statement Information" that fundamental quality signals such as high ROE can improve the performance of value strategies.
Capital structure is evaluated through the debt-to-equity ratio. A conservative ratio below 1.0 multiplies the valuation score by 1.2, while high leverage above 2.0 applies a multiplier of 0.8. This adjustment reflects that high debt constrains financial flexibility and can become problematic in crisis times (Korteweg, 2010).
6. Component 4: Sentiment Analysis
6.1 The Role of Sentiment in Financial Markets
Investor sentiment, defined as the collective psychological attitude of market participants, influences asset prices independently of fundamental data. Baker and Wurgler (2006, 2007) developed a sentiment index and showed that periods of high sentiment are followed by overvaluations that later correct. This insight justifies integrating a sentiment component into allocation decisions.
Sentiment is difficult to measure directly but can be proxied through market indicators. The VIX is the most widely used sentiment indicator, as it aggregates implied volatility from option prices. High VIX values reflect elevated uncertainty and risk aversion, while low values signal market comfort. Whaley (2009) refers to the VIX as the "Investor Fear Gauge" and documents its role as a contrarian indicator: extremely high values typically occur at market bottoms, while low values occur at tops.
6.2 VIX-Based Sentiment Assessment
DEAM uses statistical normalization of the VIX by calculating the Z-score: z = (VIX_current - VIX_average) / VIX_standard_deviation. The Z-score indicates how many standard deviations the current VIX is from the historical average. This approach is more robust than absolute thresholds, as it adapts to the average volatility level, which can vary over longer periods.
A Z-score below -1.5 (VIX is 1.5 standard deviations below average) signals exceptionally low risk perception and adds 40 points to the sentiment score. This may seem counterintuitive—shouldn't low fear be bullish? However, the logic follows the contrarian principle: when no one is afraid, everyone is already invested, and there is limited further upside potential (Zweig, 1973). Conversely, a Z-score above 1.5 (extreme fear) adds -40 points, reflecting market panic but simultaneously suggesting potential buying opportunities.
6.3 VIX Term Structure as Sentiment Signal
The VIX term structure provides additional sentiment information. Normally, the VIX trades in contango, meaning longer-term VIX futures have higher prices than short-term. This reflects that short-term volatility is currently known, while long-term volatility is more uncertain and carries a risk premium. The model compares the VIX with VIX9D (9-day volatility) and identifies backwardation (VIX > 1.05 × VIX9D) and steep backwardation (VIX > 1.15 × VIX9D).
Backwardation occurs when short-term implied volatility is higher than longer-term, which typically happens during market stress. Investors anticipate immediate turbulence but expect calming. Psychologically, this reflects acute fear. The model subtracts 15 points for backwardation and 30 for steep backwardation, as these constellations signal elevated risk. Simon and Wiggins (2001) analyzed the VIX futures curve and showed that backwardation is associated with market declines.
6.4 Safe-Haven Flows
During crisis times, investors flee from risky assets into safe havens: gold, US dollar, and Japanese yen. This "flight to quality" is a sentiment signal. The model calculates the performance of these assets relative to stocks over the last 20 trading days. When gold or the dollar strongly rise while stocks fall, this indicates elevated risk aversion.
The safe-haven component is calculated as the difference between safe-haven performance and stock performance. Positive values (safe havens outperform) subtract up to 20 points from the sentiment score, negative values (stocks outperform) add up to 10 points. The asymmetric treatment (larger deduction for risk-off than bonus for risk-on) reflects that risk-off movements are typically sharper and more informative than risk-on phases.
Baur and Lucey (2010) examined safe-haven properties of gold and showed that gold indeed exhibits negative correlation with stocks during extreme market movements, confirming its role as crisis protection.
7. Component 5: Macroeconomic Analysis
7.1 The Yield Curve as Economic Indicator
The yield curve, represented as yields of government bonds of various maturities, contains aggregated expectations about future interest rates, inflation, and economic growth. The slope of the yield curve has remarkable predictive power for recessions. Estrella and Mishkin (1998) showed that an inverted yield curve (short-term rates higher than long-term) predicts recessions with high reliability. This is because inverted curves reflect restrictive monetary policy: the central bank raises short-term rates to combat inflation, dampening economic activity.
DEAM calculates two spread measures: the 2-year-minus-10-year spread and the 3-month-minus-10-year spread. A steep, positive curve (spreads above 1.5% and 2% respectively) signals healthy growth expectations and generates the maximum yield curve score of 40 points. A flat curve (spreads near zero) reduces the score to 20 points. An inverted curve (negative spreads) is particularly alarming and results in only 10 points.
The choice of two different spreads increases analysis robustness. The 2-10 spread is most established in academic literature, while the 3M-10Y spread is often considered more sensitive, as the 3-month rate directly reflects current monetary policy (Ang, Piazzesi, and Wei, 2006).
7.2 Credit Conditions and Spreads
Credit spreads—the yield difference between risky corporate bonds and safe government bonds—reflect risk perception in the credit market. Gilchrist and Zakrajšek (2012) constructed an "Excess Bond Premium" that measures the component of credit spreads not explained by fundamentals and showed this is a predictor of future economic activity and stock returns.
The model approximates credit spread by comparing the yield of high-yield bond ETFs (HYG) with investment-grade bond ETFs (LQD). A narrow spread below 200 basis points signals healthy credit conditions and risk appetite, contributing 30 points to the macro score. Very wide spreads above 1000 basis points (as during the 2008 financial crisis) signal credit crunch and generate zero points.
Additionally, the model evaluates whether "flight to quality" is occurring, identified through strong performance of Treasury bonds (TLT) with simultaneous weakness in high-yield bonds. This constellation indicates elevated risk aversion and reduces the credit conditions score.
7.3 Financial Stability at Corporate Level
While the yield curve and credit spreads reflect macroeconomic conditions, financial stability evaluates the health of companies themselves. The model uses the aggregated debt-to-equity ratio and return on equity of the S&P 500 as proxies for corporate health.
A low leverage level below 0.5 combined with high ROE above 15% signals robust corporate balance sheets and generates 20 points. This combination is particularly valuable as it represents both defensive strength (low debt means crisis resistance) and offensive strength (high ROE means earnings power). High leverage above 1.5 generates only 5 points, as it implies vulnerability to interest rate increases and recessions.
Korteweg (2010) showed in "The Net Benefits to Leverage" that optimal debt maximizes firm value, but excessive debt increases distress costs. At the aggregated market level, high debt indicates fragilities that can become problematic during stress phases.
8. Component 6: Crisis Detection
8.1 The Need for Systematic Crisis Detection
Financial crises are rare but extremely impactful events that suspend normal statistical relationships. During normal market volatility, diversified portfolios and traditional risk management approaches function, but during systemic crises, seemingly independent assets suddenly correlate strongly, and losses exceed historical expectations (Longin and Solnik, 2001). This justifies a separate crisis detection mechanism that operates independently of regular allocation components.
Reinhart and Rogoff (2009) documented in "This Time Is Different: Eight Centuries of Financial Folly" recurring patterns in financial crises: extreme volatility, massive drawdowns, credit market dysfunction, and asset price collapse. DEAM operationalizes these patterns into quantifiable crisis indicators.
8.2 Multi-Signal Crisis Identification
The model uses a counter-based approach where various stress signals are identified and aggregated. This methodology is more robust than relying on a single indicator, as true crises typically occur simultaneously across multiple dimensions. A single signal may be a false alarm, but the simultaneous presence of multiple signals increases confidence.
The first indicator is a VIX above the crisis threshold (default 40), adding one point. A VIX above 60 (as in 2008 and March 2020) adds two additional points, as such extreme values are historically very rare. This tiered approach captures the intensity of volatility.
The second indicator is market drawdown. A drawdown above 15% adds one point, as corrections of this magnitude can be potential harbingers of larger crises. A drawdown above 25% adds another point, as historical bear markets typically encompass 25-40% drawdowns.
The third indicator is credit market spreads above 500 basis points, adding one point. Such wide spreads occur only during significant credit market disruptions, as in 2008 during the Lehman crisis.
The fourth indicator identifies simultaneous losses in stocks and bonds. Normally, Treasury bonds act as a hedge against equity risk (negative correlation), but when both fall simultaneously, this indicates systemic liquidity problems or inflation/stagflation fears. The model checks whether both SPY and TLT have fallen more than 10% and 5% respectively over 5 trading days, adding two points.
The fifth indicator is a volume spike combined with negative returns. Extreme trading volumes (above twice the 20-day average) with falling prices signal panic selling. This adds one point.
A crisis situation is diagnosed when at least 3 indicators trigger, a severe crisis at 5 or more indicators. These thresholds were calibrated through historical backtesting to identify true crises (2008, 2020) without generating excessive false alarms.
8.3 Crisis-Based Allocation Override
When a crisis is detected, the system overrides the normal allocation recommendation and caps equity allocation at maximum 25%. In a severe crisis, the cap is set at 10%. This drastic defensive posture follows the empirical observation that crises typically require time to develop and that early reduction can avoid substantial losses (Faber, 2007).
This override logic implements a "safety first" principle: in situations of existential danger to the portfolio, capital preservation becomes the top priority. Roy (1952) formalized this approach in "Safety First and the Holding of Assets," arguing that investors should primarily minimize ruin probability.
9. Integration and Final Allocation Calculation
9.1 Component Weighting
The final allocation recommendation emerges through weighted aggregation of the five components. The standard weighting is: Market Regime 35%, Risk Management 25%, Valuation 20%, Sentiment 15%, Macro 5%. These weights reflect both theoretical considerations and empirical backtesting results.
The highest weighting of market regime is based on evidence that trend-following and momentum strategies have delivered robust results across various asset classes and time periods (Moskowitz, Ooi, and Pedersen, 2012). Current market momentum is highly informative for the near future, although it provides no information about long-term expectations.
The substantial weighting of risk management (25%) follows from the central importance of risk control. Wealth preservation is the foundation of long-term wealth creation, and systematic risk management is demonstrably value-creating (Moreira and Muir, 2017).
The valuation component receives 20% weight, based on the long-term mean reversion of valuation metrics. While valuation has limited short-term predictive power (bull and bear markets can begin at any valuation), the long-term relationship between valuation and returns is robustly documented (Campbell and Shiller, 1988).
Sentiment (15%) and Macro (5%) receive lower weights, as these factors are subtler and harder to measure. Sentiment is valuable as a contrarian indicator at extremes but less informative in normal ranges. Macro variables such as the yield curve have strong predictive power for recessions, but the transmission from recessions to stock market performance is complex and temporally variable.
9.2 Model Type Adjustments
DEAM allows users to choose between four model types: Conservative, Balanced, Aggressive, and Adaptive. This choice modifies the final allocation through additive adjustments.
Conservative mode subtracts 10 percentage points from allocation, resulting in consistently more cautious positioning. This is suitable for risk-averse investors or those with limited investment horizons. Aggressive mode adds 10 percentage points, suitable for risk-tolerant investors with long horizons.
Adaptive mode implements procyclical adjustment based on short-term momentum: if the market has risen more than 5% in the last 20 days, 5 percentage points are added; if it has declined more than 5%, 5 points are subtracted. This logic follows the observation that short-term momentum persists (Jegadeesh and Titman, 1993), but the moderate size of adjustment avoids excessive timing bets.
Balanced mode makes no adjustment and uses raw model output. This neutral setting is suitable for investors who wish to trust model recommendations unchanged.
9.3 Smoothing and Stability
The allocation resulting from aggregation undergoes final smoothing through a simple moving average over 3 periods. This smoothing is crucial for model practicality, as it reduces frequent trading and thus transaction costs. Without smoothing, the model could fluctuate between adjacent allocations with every small input change.
The choice of 3 periods as smoothing window is a compromise between responsiveness and stability. Longer smoothing would excessively delay signals and impede response to true regime changes. Shorter or no smoothing would allow too much noise. Empirical tests showed that 3-period smoothing offers an optimal ratio between these goals.
10. Visualization and Interpretation
10.1 Main Output: Equity Allocation
DEAM's primary output is a time series from 0 to 100 representing the recommended percentage allocation to equities. This representation is intuitive: 100% means full investment in stocks (specifically: an S&P 500 ETF), 0% means complete cash position, and intermediate values correspond to mixed portfolios. A value of 60% means, for example: invest 60% of wealth in SPY, hold 40% in money market instruments or cash.
The time series is color-coded to enable quick visual interpretation. Green shades represent high allocations (above 80%, bullish), red shades low allocations (below 20%, bearish), and neutral colors middle allocations. The chart background is dynamically colored based on the signal, enhancing readability in different market phases.
10.2 Dashboard Metrics
A tabular dashboard presents key metrics compactly. This includes current allocation, cash allocation (complement), an aggregated signal (BULLISH/NEUTRAL/BEARISH), current market regime, VIX level, market drawdown, and crisis status.
Additionally, fundamental metrics are displayed: P/E Ratio, Equity Risk Premium, Return on Equity, Debt-to-Equity Ratio, and Total Shareholder Yield. This transparency allows users to understand model decisions and form their own assessments.
Component scores (Regime, Risk, Valuation, Sentiment, Macro) are also displayed, each normalized on a 0-100 scale. This shows which factors primarily drive the current recommendation. If, for example, the Risk score is very low (20) while other scores are moderate (50-60), this indicates that risk management considerations are pulling allocation down.
10.3 Component Breakdown (Optional)
Advanced users can display individual components as separate lines in the chart. This enables analysis of component dynamics: do all components move synchronously, or are there divergences? Divergences can be particularly informative. If, for example, the market regime is bullish (high score) but the valuation component is very negative, this signals an overbought market not fundamentally supported—a classic "bubble warning."
This feature is disabled by default to keep the chart clean but can be activated for deeper analysis.
10.4 Confidence Bands
The model optionally displays uncertainty bands around the main allocation line. These are calculated as ±1 standard deviation of allocation over a rolling 20-period window. Wide bands indicate high volatility of model recommendations, suggesting uncertain market conditions. Narrow bands indicate stable recommendations.
This visualization implements a concept of epistemic uncertainty—uncertainty about the model estimate itself, not just market volatility. In phases where various indicators send conflicting signals, the allocation recommendation becomes more volatile, manifesting in wider bands. Users can understand this as a warning to act more cautiously or consult alternative information sources.
11. Alert System
11.1 Allocation Alerts
DEAM implements an alert system that notifies users of significant events. Allocation alerts trigger when smoothed allocation crosses certain thresholds. An alert is generated when allocation reaches 80% (from below), signaling strong bullish conditions. Another alert triggers when allocation falls to 20%, indicating defensive positioning.
These thresholds are not arbitrary but correspond with boundaries between model regimes. An allocation of 80% roughly corresponds to a clear bull market regime, while 20% corresponds to a bear market regime. Alerts at these points are therefore informative about fundamental regime shifts.
11.2 Crisis Alerts
Separate alerts trigger upon detection of crisis and severe crisis. These alerts have highest priority as they signal large risks. A crisis alert should prompt investors to review their portfolio and potentially take defensive measures beyond the automatic model recommendation (e.g., hedging through put options, rebalancing to more defensive sectors).
11.3 Regime Change Alerts
An alert triggers upon change of market regime (e.g., from Neutral to Correction, or from Bull Market to Strong Bull). Regime changes are highly informative events that typically entail substantial allocation changes. These alerts enable investors to proactively respond to changes in market dynamics.
11.4 Risk Breach Alerts
A specialized alert triggers when actual portfolio risk utilization exceeds target parameters by 20%. This is a warning signal that the risk management system is reaching its limits, possibly because market volatility is rising faster than allocation can be reduced. In such situations, investors should consider manual interventions.
12. Practical Application and Limitations
12.1 Portfolio Implementation
DEAM generates a recommendation for allocation between equities (S&P 500) and cash. Implementation by an investor can take various forms. The most direct method is using an S&P 500 ETF (e.g., SPY, VOO) for equity allocation and a money market fund or savings account for cash allocation.
A rebalancing strategy is required to synchronize actual allocation with model recommendation. Two approaches are possible: (1) rule-based rebalancing at every 10% deviation between actual and target, or (2) time-based monthly rebalancing. Both have trade-offs between responsiveness and transaction costs. Empirical evidence (Jaconetti, Kinniry, and Zilbering, 2010) suggests rebalancing frequency has moderate impact on performance, and investors should optimize based on their transaction costs.
12.2 Adaptation to Individual Preferences
The model offers numerous adjustment parameters. Component weights can be modified if investors place more or less belief in certain factors. A fundamentally-oriented investor might increase valuation weight, while a technical trader might increase regime weight.
Risk target parameters (target volatility, max drawdown) should be adapted to individual risk tolerance. Younger investors with long investment horizons can choose higher target volatility (15-18%), while retirees may prefer lower volatility (8-10%). This adjustment systematically shifts average equity allocation.
Crisis thresholds can be adjusted based on preference for sensitivity versus specificity of crisis detection. Lower thresholds (e.g., VIX > 35 instead of 40) increase sensitivity (more crises are detected) but reduce specificity (more false alarms). Higher thresholds have the reverse effect.
12.3 Limitations and Disclaimers
DEAM is based on historical relationships between indicators and market performance. There is no guarantee these relationships will persist in the future. Structural changes in markets (e.g., through regulation, technology, or central bank policy) can break established patterns. This is the fundamental problem of induction in financial science (Taleb, 2007).
The model is optimized for US equities (S&P 500). Application to other markets (international stocks, bonds, commodities) would require recalibration. The indicators and thresholds are specific to the statistical properties of the US equity market.
The model cannot eliminate losses. Even with perfect crisis prediction, an investor following the model would lose money in bear markets—just less than a buy-and-hold investor. The goal is risk-adjusted performance improvement, not risk elimination.
Transaction costs are not modeled. In practice, spreads, commissions, and taxes reduce net returns. Frequent trading can cause substantial costs. Model smoothing helps minimize this, but users should consider their specific cost situation.
The model reacts to information; it does not anticipate it. During sudden shocks (e.g., 9/11, COVID-19 lockdowns), the model can only react after price movements, not before. This limitation is inherent to all reactive systems.
12.4 Relationship to Other Strategies
DEAM is a tactical asset allocation approach and should be viewed as a complement, not replacement, for strategic asset allocation. Brinson, Hood, and Beebower (1986) showed in their influential study "Determinants of Portfolio Performance" that strategic asset allocation (long-term policy allocation) explains the majority of portfolio performance, but this leaves room for tactical adjustments based on market timing.
The model can be combined with value and momentum strategies at the individual stock level. While DEAM controls overall market exposure, within-equity decisions can be optimized through stock-picking models. This separation between strategic (market exposure) and tactical (stock selection) levels follows classical portfolio theory.
The model does not replace diversification across asset classes. A complete portfolio should also include bonds, international stocks, real estate, and alternative investments. DEAM addresses only the US equity allocation decision within a broader portfolio.
13. Scientific Foundation and Evaluation
13.1 Theoretical Consistency
DEAM's components are based on established financial theory and empirical evidence. The market regime component follows from regime-switching models (Hamilton, 1989) and trend-following literature. The risk management component implements volatility targeting (Moreira and Muir, 2017) and modern portfolio theory (Markowitz, 1952). The valuation component is based on discounted cash flow theory and empirical value research (Campbell and Shiller, 1988; Fama and French, 1992). The sentiment component integrates behavioral finance (Baker and Wurgler, 2006). The macro component uses established business cycle indicators (Estrella and Mishkin, 1998).
This theoretical grounding distinguishes DEAM from purely data-mining-based approaches that identify patterns without causal theory. Theory-guided models have greater probability of functioning out-of-sample, as they are based on fundamental mechanisms, not random correlations (Lo and MacKinlay, 1990).
13.2 Empirical Validation
While this document does not present detailed backtest analysis, it should be noted that rigorous validation of a tactical asset allocation model should include several elements:
In-sample testing establishes whether the model functions at all in the data on which it was calibrated. Out-of-sample testing is crucial: the model should be tested in time periods not used for development. Walk-forward analysis, where the model is successively trained on rolling windows and tested in the next window, approximates real implementation.
Performance metrics should be risk-adjusted. Pure return consideration is misleading, as higher returns often only compensate for higher risk. Sharpe Ratio, Sortino Ratio, Calmar Ratio, and Maximum Drawdown are relevant metrics. Comparison with benchmarks (Buy-and-Hold S&P 500, 60/40 Stock/Bond portfolio) contextualizes performance.
Robustness checks test sensitivity to parameter variation. If the model only functions at specific parameter settings, this indicates overfitting. Robust models show consistent performance over a range of plausible parameters.
13.3 Comparison with Existing Literature
DEAM fits into the broader literature on tactical asset allocation. Faber (2007) presented a simple momentum-based timing system that goes long when the market is above its 10-month average, otherwise cash. This simple system avoided large drawdowns in bear markets. DEAM can be understood as a sophistication of this approach that integrates multiple information sources.
Ilmanen (2011) discusses various timing factors in "Expected Returns" and argues for multi-factor approaches. DEAM operationalizes this philosophy. Asness, Moskowitz, and Pedersen (2013) showed that value and momentum effects work across asset classes, justifying cross-asset application of regime and valuation signals.
Ang (2014) emphasizes in "Asset Management: A Systematic Approach to Factor Investing" the importance of systematic, rule-based approaches over discretionary decisions. DEAM is fully systematic and eliminates emotional biases that plague individual investors (overconfidence, hindsight bias, loss aversion).
References
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Contrarian Period High & LowContrarian Period High & Low
This indicator pairs nicely with the Contrarian 100 MA and can be located here:
Overview
The "Contrarian Period High & Low" indicator is a powerful technical analysis tool designed for traders seeking to identify key support and resistance levels and capitalize on contrarian trading opportunities. By tracking the highest highs and lowest lows over user-defined periods (Daily, Weekly, or Monthly), this indicator plots historical levels and generates buy and sell signals when price breaks these levels in a contrarian manner. A unique blue dot counter and action table enhance decision-making, making it ideal for swing traders, trend followers, and those trading forex, stocks, or cryptocurrencies. Optimized for daily charts, it can be adapted to other timeframes with proper testing.
How It Works
The indicator identifies the highest high and lowest low within a specified period (e.g., daily, weekly, or monthly) and draws horizontal lines for the previous period’s extremes on the chart. These levels act as dynamic support and resistance zones. Contrarian signals are generated when the price crosses below the previous period’s low (buy signal) or above the previous period’s high (sell signal), indicating potential reversals. A blue dot counter tracks consecutive buy signals, and a table displays the count and recommended action, helping traders decide whether to hold or flip positions.
Key Components
Period High/Low Levels: Tracks the highest high and lowest low for each period, plotting red lines for highs and green lines for lows from the bar where they occurred, extending for a user-defined length (default: 200 bars).
Contrarian Signals: Generates buy signals (blue circles) when price crosses below the previous period’s low and sell signals (white circles) when price crosses above the previous period’s high, designed to capture potential reversals.
Blue Dot Tracker: Counts consecutive buy signals (“blue dots”). If three or more occur, it suggests a stronger trend, with the table recommending whether to “Hold Investment” or “Flip Investment.”
Action Table: A 2x2 table in the bottom-right corner displays the blue dot count and action (“Hold Investment” if count ≥ 4, else “Flip Investment”) for quick reference.
Mathematical Concepts
Period Detection: Uses an approximate bar count to define periods (1 bar for Daily, 5 bars for Weekly, 20 bars for Monthly on a daily chart). When a new period starts, the previous period’s high/low is finalized and plotted.
High/Low Tracking:
Highest high (periodHigh) and lowest low (periodLow) are updated within the period.
Lines are drawn at these levels when the period ends, starting from the bar where the extreme occurred (periodHighBar, periodLowBar).
Signal Logic:
Buy signal: ta.crossunder(close , prevPeriodLow) and not lowBroken and barstate.isconfirmed
Sell signal: ta.crossover(close , prevPeriodHigh) and not highBroken and barstate.isconfirmed
Flags (highBroken, lowBroken) prevent multiple signals for the same level within a period.
Blue Dot Counter: Increments on each buy signal, resets on a sell signal or if price exceeds the entry price after three or more buy signals.
Entry and Exit Rules
Buy Signal (Blue Circle): Triggered when the price crosses below the previous period’s low, suggesting a potential oversold condition and buying opportunity. The signal appears as a blue circle below the price bar.
Sell Signal (White Circle): Triggered when the price crosses above the previous period’s high, indicating a potential overbought condition and selling opportunity. The signal appears as a white circle above the price bar.
Blue Dot Tracker:
Increments blueDotCount on each buy signal and sets an entryPrice on the first buy.
Resets on a sell signal or if price exceeds entryPrice after three or more buy signals.
If blueDotCount >= 3, the table suggests holding; if >= 4, it reinforces “Hold Investment.”
Exit Rules: Exit a buy position on a sell signal or when price exceeds the entry price after three or more buy signals. Combine with other tools (e.g., trendlines, support/resistance) for additional confirmation. Always apply proper risk management.
Recommended Usage
The "Contrarian Period High & Low" indicator is optimized for daily charts but can be adapted to other timeframes (e.g., 1H, 4H) with adjustments to the period bar count. It excels in markets with clear support/resistance levels and potential reversal zones. Traders should:
Backtest the indicator on their chosen asset and timeframe to validate signal reliability.
Combine with other technical tools (e.g., moving averages, Fibonacci levels) for stronger trade confirmation.
Adjust barsPerPeriod (e.g., ~120 bars for Weekly on hourly charts) based on the chart timeframe and market volatility.
Monitor the action table to guide position management based on blue dot counts.
Customization Options
Period Type: Choose between Daily, Weekly, or Monthly periods (default: Monthly).
Line Length: Set the length of high/low lines in bars (default: 200).
Show Highs/Lows: Toggle visibility of period high (red) and low (green) lines.
Max Lines to Keep: Limit the number of historical lines displayed (default: 10).
Hide Signals: Toggle buy/sell signal visibility for a cleaner chart.
Table Display: A fixed table in the bottom-right corner shows the blue dot count and action, with yellow (Hold) or green (Flip) backgrounds based on the count.
Why Use This Indicator?
The "Contrarian Period High & Low" indicator offers a unique blend of support/resistance visualization and contrarian signal generation, making it a versatile tool for identifying potential reversals. Its clear visual cues (lines and signals), blue dot tracker, and actionable table provide traders with an intuitive way to monitor market structure and manage trades. Whether you’re a beginner or an experienced trader, this indicator enhances your ability to spot key levels and time entries/exits effectively.
Tips for Users
Test the indicator thoroughly on your chosen market and timeframe to optimize settings (e.g., adjust barsPerPeriod for non-daily charts).
Use in conjunction with price action or other indicators for stronger trade setups.
Monitor the action table to decide whether to hold or flip positions based on blue dot counts.
Ensure your chart timeframe aligns with the selected period type (e.g., daily chart for Monthly periods).
Apply strict risk management to protect against false breakouts.
Happy trading with the Contrarian Period High & Low indicator! Share your feedback and strategies in the TradingView community!
SuperTrend - Dynamic Lines and ChannelsSuperTrend Indicator: Comprehensive Description
Overview
The SuperTrend indicator is Pine Script V6 designed for TradingView to plot dynamic trend lines & channels across multiple timeframes (Daily, Weekly, Monthly, Quarterly, and Yearly/All-Time) to assist traders in identifying potential support, resistance, and trend continuation levels. The script calculates trendlines based on high and low prices over specified periods, projects these trendlines forward, and includes optional reflection channels and heartlines to provide additional context for price action analysis. The indicator is highly customizable, allowing users to toggle the visibility of trendlines, projections, and heartlines for each timeframe, with a focus on the DayTrade channel, which includes unique reflection channel features.
This description provides a detailed explanation of the indicator’s features, functionality, and display, with a specific focus on the DayTrade channel’s anchoring, the role of static and dynamic channels in projecting future price action, the heartline’s potential as a volume indicator, and how traders can use the indicator for line-to-line trading strategies.
Features and Functionality
1. Dynamic Trend Channels
The SuperTrend indicator calculates trend channels for five timeframes:
DayTrade Channel: Tracks daily highs and lows, updating before 12 PM each trading day.
Weekly Channel: Tracks highs and lows over a user-selected period (1, 2, or 3 weeks).
Monthly Channel: Tracks monthly highs and lows.
Quarterly Channel: Tracks highs and lows over a user-selected period (1 or 2 quarters).
Yearly/All-Time Channel: Tracks highs and lows over a user-selected period (1 to 10 years or All Time).
Each channel consists of:
Upper Trendline: Connects the high prices of the previous and current periods.
Lower Trendline: Connects the low prices of the previous and current periods.
Projections: Extends the trendlines forward based on the trend’s slope.
Heartline: A dashed line drawn at the midpoint between the upper and lower trendlines or their projections.
DayTrade Channel Anchoring
The DayTrade channel anchors its trendlines to the high and low prices of the previous and current trading days, with updates restricted to before 12 PM to capture significant price movements during the morning session, which is often more volatile due to market openings or news events. The "Show DayTrade Trend Lines" toggle enables this channel, and after 12 PM, the trendlines and projections remain static for the rest of the trading day. This static anchoring provides a consistent reference for potential support and resistance levels, allowing traders to anticipate price reactions based on historical highs and lows from the previous day and the morning session of the current day.
The static nature of the DayTrade channel after 12 PM ensures that the trendlines and projections do not shift mid-session, providing a stable framework for traders to assess whether price action respects or breaks these levels, potentially indicating trend continuation or reversal.
Static vs. Dynamic Channels
Static Channels: Once set (e.g., after 12 PM for the DayTrade channel or at the start of a new period for other timeframes), the trendlines remain fixed until the next period begins. This static behavior allows traders to use the channels as reference levels for potential price targets or reversal points, as they are based on historical price extremes.
Dynamic Projections: The projections extend the trendlines forward, providing a visual guide for potential future price action, assuming the trend’s momentum continues. When a trendline is broken (e.g., price closes above the upper projection or below the lower projection), it may suggest a breakout or reversal, prompting traders to reassess their positions.
2. Reflection Channels (DayTrade Only)
The DayTrade channel includes optional lower and upper reflection channels, which are additional trendlines positioned symmetrically around the main channel to provide extended support and resistance zones. These are controlled by the "Show Reflection Channel" dropdown.
Lower Reflection Channel:
Position: Drawn below the lower trendline at a distance equal to the range between the upper and lower trendlines.
Projection: Extends forward as a dashed line.
Heartline: A dashed line drawn at the midpoint between the lower trendline and the lower reflection trendline, controlled by the "Show Lower Reflection Heartline" toggle.
Upper Reflection Channel:
Position: Drawn above the upper trendline at the same distance as the main channel’s range.
Projection: Extends forward as a dashed line.
Heartline: A dashed line drawn at the midpoint between the upper trendline and the upper reflection trendline, controlled by the "Show Upper Reflection Heartline" toggle.
Display Control: The "Show Reflection Channel" dropdown allows users to select:
"None": No reflection channels are shown.
"Lower": Only the lower reflection channel is shown.
"Upper": Only the upper reflection channel is shown.
"Both": Both reflection channels are shown.
Purpose: Reflection channels extend the price range analysis by providing additional levels where price may react, acting as potential targets or reversal zones after breaking the main trendlines.
3. Heartlines
Each timeframe, including the DayTrade channel and its reflection channels, can display a heartline, which is a dashed line plotted at the midpoint between the upper and lower trendlines or their projections. For the DayTrade channel:
Main DayTrade Heartline: Midpoint between the upper and lower trendlines, controlled by the "Show DayTrade Heartline" toggle.
Lower Reflection Heartline: Midpoint between the lower trendline and the lower reflection trendline, controlled by the "Show Lower Reflection Heartline" toggle.
Upper Reflection Heartline: Midpoint between the upper trendline and the upper reflection trendline, controlled by the "Show Upper Reflection Heartline" toggle.
Independent Toggles: Visibility is controlled by:
"Show DayTrade Heartline": For the main DayTrade heartline.
"Show Lower Reflection Heartline": For the lower reflection heartline.
"Show Upper Reflection Heartline": For the upper reflection heartline.
Potential Volume Indicator: The heartline represents the average price level between the high and low of a period, which may correlate with areas of high trading activity or volume concentration, as these midpoints often align with price levels where buyers and sellers have historically converged. A break above or below the heartline, especially with strong momentum, may indicate a shift in market sentiment, potentially leading to accelerated price movement in the direction of the break. However, this is an observation based on the heartline’s position, not a direct measure of volume, as the script does not incorporate volume data.
4. Alerts
The script includes alert conditions for all timeframes, triggered when a candle closes fully above the upper projection or below the lower projection. For the DayTrade channel:
Upper Trend Break: Triggers when a candle closes fully above the upper projection.
Lower Trend Break: Triggers when a candle closes fully below the lower projection.
Alerts are combined across all timeframes, so a break in any timeframe triggers a general "Upper Trend Break" or "Lower Trend Break" alert with the message: "Candle closed fully above/below one or more projection lines." Alerts fire once per bar close.
5. Customization Options
The script provides extensive customization through input settings, grouped by timeframe:
DayTrade Channel:
"Show DayTrade Trend Lines": Toggle main trendlines and projections.
"Show DayTrade Heartline": Toggle main heartline.
"Show Lower Reflection Heartline": Toggle lower reflection heartline.
"Show Upper Reflection Heartline": Toggle upper reflection heartline.
"DayTrade Channel Color": Set color for trendlines.
"DayTrade Projection Channel Color": Set color for projections.
"Heartline Color": Set color for all heartlines.
"Show Reflection Channel": Dropdown to show "None," "Lower," "Upper," or "Both" reflection channels.
Other Timeframes (Weekly, Monthly, Quarterly, Yearly/All-Time):
Toggles for trendlines (e.g., "Show Weekly Trend Lines," "Show Monthly Trend Lines") and heartlines (e.g., "Show Weekly Heartline," "Show Monthly Heartline").
Period selection (e.g., "Weekly Period" for 1, 2, or 3 weeks; "Yearly Period" for 1 to 10 years or All Time).
Separate colors for trendlines (e.g., "Weekly Channel Color"), projections (e.g., "Weekly Projection Channel Color"), and heartlines (e.g., "Weekly Heartline Color").
Max Bar Difference: Limits the distance between anchor points to ensure relevance to recent price action.
Display
The indicator overlays the following elements on the chart:
Trendlines: Solid lines connecting the high and low anchor points for each timeframe, using user-specified colors (e.g., set via "DayTrade Channel Color").
Projections: Dashed lines extending from the current anchor points, indicating potential future price levels, using colors set via "DayTrade Projection Channel Color" or equivalent.
Heartlines: Dashed lines at the midpoint of each channel, using the color set via "Heartline Color" or equivalent.
Reflection Channels (DayTrade Only):
Lower reflection trendline and projection: Below the lower trendline, using the same colors as the main channel.
Upper reflection trendline and projection: Above the upper trendline, using the same colors.
Reflection heartlines: Midpoints between the main trendlines and their respective reflection trendlines, using the "Heartline Color."
Visual Clarity: Lines are only drawn if the relevant toggles (e.g., "Show DayTrade Trend Lines") are enabled and data is available. Lines are deleted when their conditions are not met to avoid clutter.
Trading Applications: Line-to-Line Trading
The SuperTrend indicator can be used to inform trading decisions by providing a framework for line-to-line trading, where traders use the trendlines, projections, and heartlines as reference points for entries, exits, and risk management. Below is a detailed explanation of how to use the DayTrade channel and its reflection channels for trading, focusing on their anchoring, static/dynamic behavior, and the heartline’s role.
1. Why DayTrade Channel Anchoring
The DayTrade channel’s anchoring to the previous day’s high/low and the current day’s high/low before 12 PM, controlled by the "Show DayTrade Trend Lines" toggle, captures significant price levels during high-volatility periods:
Previous Day High/Low: These represent key levels where price found resistance (high) or support (low) in the prior session, often acting as psychological or technical barriers in the current session.
Current Day High/Low Before 12 PM: The morning session (before 12 PM) often sees increased volatility due to market openings, news releases, or institutional activity. Anchoring to these early highs/lows ensures the channel reflects the most relevant price extremes, which are likely to influence intraday price action.
Static After 12 PM: By fixing the anchor points after 12 PM, the trendlines and projections become stable references for the afternoon session, allowing traders to anticipate price reactions at these levels without the lines shifting unexpectedly.
This anchoring makes the DayTrade channel particularly useful for intraday traders, as it provides a consistent framework based on recent price history, which can guide decisions on trend continuation or reversal.
2. Using Static Channels and Projections
The static nature of the DayTrade channel after 12 PM, enabled by "Show DayTrade Trend Lines," and the dynamic projections, set via "DayTrade Projection Channel Color," provide a structured approach to trading:
Support and Resistance:
The upper trendline and lower trendline act as dynamic support/resistance levels based on the previous and current day’s price extremes.
Traders may observe price reactions (e.g., bounces or breaks) at these levels. For example, if price approaches the lower trendline and bounces, it may indicate support, suggesting a potential long entry.
Projections as Price Targets:
The projections extend the trendlines forward, offering potential price targets if the trend continues. For instance, if price breaks above the upper trendline and continues toward the upper projection, traders might consider it a bullish continuation signal.
A candle closing fully above the upper projection or below the lower projection (triggering an alert) may indicate a breakout, prompting traders to enter in the direction of the break or reassess if the break fails.
Static Channels for Breakouts:
Because the trendlines are static after 12 PM, they serve as fixed reference points. A break above the upper trendline or its projection may suggest bullish momentum, while a break below the lower trendline or projection may indicate bearish momentum.
Traders can use these breaks to set entry points (e.g., entering a long position after a confirmed break above the upper projection) and place stop-losses below the broken level to manage risk.
3. Line-to-Line Trading Strategy
Line-to-line trading involves using the trendlines, projections, and reflection channels as sequential price targets or reversal zones:
Trading Within the Main Channel:
Long Setup: If price bounces off the lower trendline and moves toward the heartline (enabled by "Show DayTrade Heartline") or upper trendline, traders might enter a long position near the lower trendline, targeting the heartline or upper trendline for profit-taking. A stop-loss could be placed below the lower trendline to protect against a breakdown.
Short Setup: If price rejects from the upper trendline and moves toward the heartline or lower trendline, traders might enter a short position near the upper trendline, targeting the heartline or lower trendline, with a stop-loss above the upper trendline.
Trading to Reflection Channels:
If price breaks above the upper trendline and continues toward the upper reflection trendline or its projection (enabled by "Show Reflection Channel" set to "Upper" or "Both"), traders might treat this as a breakout trade, entering long with a target at the upper reflection level and a stop-loss below the upper trendline.
Similarly, a break below the lower trendline toward the lower reflection trendline or its projection (enabled by "Show Reflection Channel" set to "Lower" or "Both") could signal a short opportunity, with a target at the lower reflection level and a stop-loss above the lower trendline.
Reversal Trades:
If price reaches the upper reflection trendline and shows signs of rejection (e.g., a bearish candlestick pattern), traders might consider a short position, anticipating a move back toward the main channel’s upper trendline or heartline.
Conversely, a rejection at the lower reflection trendline could prompt a long position targeting the lower trendline or heartline.
Risk Management:
Use the heartline as a midpoint to gauge whether price is likely to continue toward the opposite trendline or reverse. For example, a failure to break above the heartline after bouncing from the lower trendline might suggest weakening bullish momentum, prompting a tighter stop-loss.
The static nature of the channels after 12 PM allows traders to set precise stop-loss and take-profit levels based on historical price levels, reducing the risk of chasing moving targets.
4. Heartline as a Volume Indicator
The heartline, controlled by toggles like "Show DayTrade Heartline," "Show Lower Reflection Heartline," and "Show Upper Reflection Heartline," may serve as an indirect proxy for areas of high trading activity:
Rationale: The heartline represents the average price between the high and low of a period, which often aligns with price levels where significant buying and selling have occurred, as these midpoints can correspond to areas of consolidation or high volume in the order book. While the script does not directly use volume data, the heartline’s position may reflect price levels where market participants have historically balanced supply and demand.
Breakout Potential: A break above or below the heartline, particularly with a strong candle (e.g., wide range or high momentum), may indicate a shift in market sentiment, potentially leading to accelerated price movement in the direction of the break. For example:
A close above the main DayTrade heartline could suggest buyers are overpowering sellers, potentially leading to a move toward the upper trendline or upper reflection channel.
A close below the heartline could indicate seller dominance, targeting the lower trendline or lower reflection channel.
Trading Application:
Traders might use heartline breaks as confirmation signals for trend continuation. For instance, after a bounce from the lower trendline, a close above the heartline could confirm bullish momentum, prompting a long entry.
The heartline can also act as a dynamic stop-loss or trailing stop level. For example, in a long trade, a trader might exit if price falls below the heartline, indicating a potential reversal.
For reflection heartlines, a break above the upper reflection heartline or below the lower reflection heartline could signal strong momentum, as these levels are further from the main channel and may require significant buying or selling pressure to breach.
5. Practical Trading Considerations
Timeframe Context: The DayTrade channel, enabled by "Show DayTrade Trend Lines," is best suited for intraday trading due to its daily anchoring and morning update behavior. Traders should consider higher timeframe channels (e.g., enabled by "Show Weekly Trend Lines" or "Show Monthly Trend Lines") for broader context, as breaks of the DayTrade channel may align with or be influenced by larger trends.
Confirmation Tools: Use additional indicators (e.g., RSI, MACD, or volume-based indicators) or candlestick patterns to confirm signals at trendlines, projections, or heartlines. The script’s alerts can help identify breakouts, but traders should verify with other technical or fundamental factors.
Risk Management: Always define risk-reward ratios before entering trades. For example, a 1:2 risk-reward ratio might involve risking a stop-loss below the lower trendline to target the heartline or upper trendline.
Market Conditions: The effectiveness of the channels and heartlines depends on market conditions (e.g., trending vs. ranging markets). In choppy markets, price may oscillate within the main channel, favoring range-bound strategies. In trending markets, breaks of projections or reflection channels may signal continuation trades.
Limitations: The indicator relies on historical price data and does not incorporate volume, news, or other external factors. Traders should use it as part of a broader strategy and avoid relying solely on its signals.
How to Use in TradingView
Add the Indicator: Copy the script into TradingView’s Pine Editor, compile it, and add it to your chart.
Configure Settings:
Enable "Show DayTrade Trend Lines" to display the main DayTrade trendlines and projections.
Use the "Show Reflection Channel" dropdown to select "Lower," "Upper," or "Both" to display reflection channels.
Toggle "Show DayTrade Heartline," "Show Lower Reflection Heartline," and "Show Upper Reflection Heartline" to control heartline visibility.
Adjust colors using "DayTrade Channel Color," "DayTrade Projection Channel Color," and "Heartline Color."
Enable other timeframes (e.g., "Show Weekly Trend Lines," "Show Monthly Trend Lines") for additional context, if desired.
Set Alerts: Configure alerts in TradingView for "Upper Trend Break" or "Lower Trend Break" to receive notifications when a candle closes fully above or below any timeframe’s projections.
Analyze the Chart:
Monitor price interactions with the trendlines, projections, and heartlines.
Look for bounces, breaks, or rejections at these levels to plan entries and exits.
Use the heartline breaks as potential confirmation of momentum shifts.
Test Strategies: Backtest line-to-line trading strategies in TradingView’s strategy tester or demo account to evaluate performance before trading with real capital.
Conclusion
The SuperTrend indicator provides a robust framework for technical analysis by plotting dynamic trend channels, projections, and heartlines across multiple timeframes, with advanced features for the DayTrade channel, including lower and upper reflection channels. The DayTrade channel’s anchoring to previous and current day highs/lows before 12 PM, enabled by "Show DayTrade Trend Lines," creates a stable reference for intraday trading, while static trendlines and dynamic projections guide traders in anticipating price movements. The heartlines, controlled by toggles like "Show DayTrade Heartline," offer potential insights into high-activity price levels, with breaks possibly indicating momentum shifts. Traders can use the indicator for line-to-line trading by targeting moves between trendlines, projections, and reflection channels, while managing risk with stop-losses and confirmations from other tools. The indicator should be used as part of a comprehensive trading plan.
Fibonacci Retracement levels Automatically D/W/MIndicator Description: Fibonacci Retracement levels Automatically
Fibonacci retracement levels based on the day, week, month High Low range and Fibonacci retracement levels draws automatically .This Pine Script indicator is designed to plot Fibonacci retracement levels based on the high and low prices of a user-selected timeframe (Daily, Weekly, or Monthly). It identifies bullish or bearish candles in the chosen timeframe, draws key price levels, and overlays Fibonacci retracement lines and semi-transparent colored boxes to highlight potential support and resistance zones. The indicator dynamically updates with each new period and extends lines, labels, and boxes to the current bar for real-time visualization. Key Features
1. Timeframe Selection: Users can choose the timeframe for analysis: Daily, Weekly, or Monthly via an input dropdown. The indicator retrieves the open, high, low, and close prices for the selected timeframe using `request.security`.
2. High and Low Tracking : Tracks the highest high and lowest low within the selected timeframe. Stores these values and their corresponding bar indices in arrays (`whigh`, `wlow`, `whighIdx`,`wlowIdx`). Limits the array size to the most recent period to optimize performance.
3. Bullish and Bearish Candle Detection : Identifies whether the previous period’s candle is bullish (`close > open`) or bearish (`close < open`). Uses this to determine the direction for Fibonacci retracement calculations. Bullish candle: Fibonacci levels are drawn from low to high
Bearish candle: Fibonacci levels are drawn from high to low
4. Fibonacci Retracement Levels : Plots Fibonacci levels at 0.236, 0.382, 0.5, 0.618, and 0.786 between the high and low of the period. For bullish candles, levels are calculated from the low (support) to the high (resistance). For bearish candles, levels are calculated from the high (resistance) to the low (support). Each Fibonacci level is drawn as a horizontal line with a unique color:
- 0.236: Blue
- 0.382: Purple
- 0.5: Yellow
- 0.618: Teal
- 0.786: Fuchsia
5. Visual Elements: - High/Low Lines and Labels: Draws a red line and label for the previous period’s high. Draws a green line and label for the previous period’s low. Fibonacci Lines and Labels: Each Fibonacci level has a horizontal line and a label displaying the ratio.
Colored Boxes: Semi-transparent boxes are drawn between consecutive Fibonacci levels (including high and low) to highlight zones.
6. Dynamic Updates:
- At the start of a new period (e.g., new week for Weekly timeframe), the indicator:
- Clears previous Fibonacci lines, labels, and boxes.
- Recalculates the high and low for the new period.
- Redraws lines, labels, and boxes based on the new data.
- Extends all lines, labels, and boxes to the current bar index for real-time tracking.
7. Performance Optimization:
- Deletes old lines, labels, and boxes to prevent clutter.
- Limits the storage of highs and lows to the most recent period.
How It Works
1. Initialization: Defines variables for tracking bullish/bearish candles, lines, labels, and arrays for Fibonacci levels and boxes. Sets up color arrays for Fibonacci lines and boxes with distinct, semi-transparent colors.
2. Data Collection: Fetches the previous period’s OHLC (open, high, low, close) using `request.security`. Detects new periods (e.g., new week or month) using `ta.change(time(tf))`.
3. Fibonacci Calculation: On a new period, stores the high and low prices and their bar indices.
- Identifies the maximum high and minimum low from the stored data. - Calculates Fibonacci levels based on the range (`maxHigh - minLow`) and the direction (bullish or bearish).
4. Drawing:
- Draws high/low lines and labels at the identified price levels. Plots Fibonacci retracement lines and labels for each ratio. Creates semi-transparent boxes between Fibonacci levels to visually distinguish zones.
5. Updates:
- Extends all lines, labels, and boxes to the current bar index when a new period is detected. Clears old Fibonacci elements to avoid overlap and ensure clarity.
Usage
- Purpose: This indicator is useful for traders who use Fibonacci retracement levels to identify potential support and resistance zones in financial markets.
- Application:
- Select the desired timeframe (Daily, Weekly, Monthly) via the input settings.
- The indicator automatically plots the previous period’s high/low and Fibonacci levels on the chart.
- Use the labeled Fibonacci levels and colored boxes to identify key price zones for trading decisions.
- Customization:
- Modify the `timeframe` input to switch between Daily, Weekly, or Monthly analysis.
- Adjust the `fibLineColors` and `fibFillColors` arrays to change the visual appearance of lines and boxes.
- The indicator is designed for use on TradingView with Pine Script.
- The maximum array size for highs/lows is limited to 1 period in this version (can be adjusted by modifying the `array.shift` logic).
- The indicator dynamically updates with each new period, ensuring real-time relevance.
This indicator make educational purpose use only
LiquidEdge Original1️⃣ Why Most Traders Miss Key Market Turning Points
Most traders (you) struggle to identify true market pivots THE REAL TOP and BOTTOMS where reversals begin.
❌ You enter too early or too late because price alone doesn’t give enough confirmation
❌ You follow price blindly, unaware of the volume pressure building underneath
❌ You get caught in sideways markets, not realizing they’re often accumulation or distribution zones
❌ You can’t tell if momentum is building or fading, which leads to low confidence and inconsistent results
👉 LiquidEdge helps solve this by tracking volume momentum through a modified MFI slope and scoring system. It highlights potential pivots with real context, so you can see where smart money might be entering or exiting before price makes it obvious.
2️⃣ What LiquidEdge Actually Does and How
LiquidEdge helps solve common trading problems by adding structure and clarity to volume analysis.
✅ It builds on the classic Money Flow Index (MFI), but instead of just showing overbought/oversold levels, it calculates the slope of MFI to track real-time changes in volume momentum
✅ Each setup is scored based on a combination of factors: divergence strength, trend alignment using EMA, and whether the signal occurs inside a liquidity zone
✅ Hidden accumulation or distribution is revealed when volume pressure increases or fades while price remains flat or moves slightly, a sign of smart money positioning
✅ Divergences are only flagged when they occur near pivot zones and align with overall trend conditions, helping reduce false signals
✅ Potential pivots are identified when multiple factors overlap such as a liquidity zone breach, volume slope shift, and valid divergence which often signals entry or exit points for institutional players
👉 The result is a structured interpretation of price and volume flow, helping traders read momentum shifts and potential reversals more clearly in both trending and ranging markets.
3️⃣ What Makes LiquidEdge Different
LiquidEdge is built on top of the classic Money Flow Index (MFI), but adds structure that transforms it from a basic momentum tool into a decision-support system.
Instead of simply showing highs and lows, it scores each potential setup based on:
✅ The steepness and direction of the MFI slope (used to measure volume pressure)
✅ Whether the setup aligns with the broader trend using an EMA filter (default: 200 EMA)
✅ Whether the signal appears inside predefined liquidity zones (MFI above 80 or below 20)
👉 This scoring system reduces noise and helps you focus only on high-probability setups.
👉 It also checks volume pressure across multiple timeframes using MFI slope on 5M, 15M, 1H, 4H, and Daily charts. This reveals whether short-term moves are backed by longer-term volume momentum.
Color changes in the line and histogram are not decorative they reflect real shifts in volume pressure. Every visual cue is linked to live market logic.
What Makes It Stand Out
👉 Setup Scoring That Makes Sense
Each setup is scored by combining:
Signal strength (MFI slope intensity and stability)
Trend direction (via customizable EMA)
Liquidity zone relevance (MFI range filtering)
This structured scoring means you spend less time second-guessing and more time reading clean signals.
👉 Flow That Follows Real Momentum
The slope of the MFI tracks whether volume pressure is rising or falling:
🟢 Green = increasing inflow (buying pressure)
🔴 Red = increasing outflow (selling pressure)
👉 Multi-Timeframe Volume Context
LiquidEdge calculates flow direction independently on each major timeframe. You’ll know if short-term setups are confirmed by higher timeframe volume or going against it.
👉 Smart Divergence Filtering
Unlike simple divergence tools that compare price highs/lows directly, LiquidEdge filters divergences based on:
Local pivot zones (defined by lookback periods)
Trend confirmation (to eliminate countertrend noise)
4️⃣ How LiquidEdge Works (Under the Hood)
LiquidEdge tracks directional momentum using the slope of the Money Flow Index (MFI) giving you a real-time read on buying and selling pressure.
When the slope rises, it means buyers are stepping in and volume is supporting the move.
When it falls, sellers are taking control and volume outflow is increasing.
This slope acts like a pressure gauge for the market, helping you spot when a trend has strength or when it's starting to fade.
💡 Quick Comparison
RSI = momentum from price
MFI = momentum from price + volume
LiquidEdge takes it one step further by calculating the rate of change (slope) in MFI. That’s where the pressure signal comes from not just value, but directional flow.
Core Calculations (Simplified)
Typical Price = (High + Low + Close) ÷ 3
Raw Money Flow = Typical Price × Volume
MFI = 100 −
MFI ranges from 0 to 100.
High = strong buying volume
Low = growing selling pressure
LiquidEdge then calculates the slope of this MFI over time to track volume momentum dynamically.
Divergence Engine
LiquidEdge detects divergence by comparing price pivots with the direction of MFI slope.
❌ If price makes a higher high but MFI slope turns down, it’s a bearish divergence
✅ If price makes a lower low but MFI slope rises, it’s a bullish divergence
Divergences are only confirmed when they occur:
Near local pivot zones (defined by configurable lookback windows)
And, optionally, in alignment with the broader trend using an EMA filter
This filtering helps reduce false positives and keeps you focused on clean setups.
Structured Confidence Scoring
Each signal is visually scored based on:
➡️ Whether a valid divergence is detected
➡️ Whether the signal occurs inside a liquidity zone (MFI > 80 or < 20)
➡️ Whether the setup aligns with the overall trend direction (EMA filter)
More confluence = higher confidence
The scoring system helps prioritize setups that meet multiple criteria, not just one.
Liquidity Zones
Above 80: Signals possible buying exhaustion 👉 risk of reversal
Below 20: Indicates potential selling exhaustion 👉 watch for a bounce
Zones are shaded directly on the chart to highlight pressure extremes in real time.
Price + Volume Fusion
LiquidEdge blends price action with volume pressure using MFI slope and histogram behavior. It doesn’t just show you where price is moving. it shows whether the move is backed by real volume.
This lets you see:
Whether volume is confirming or fading behind a move
If a reversal is building even before price confirms it
Visual Feedback That Speaks Clearly
🟢 Green slope = increasing buying pressure
🔴 Red slope = increasing selling pressure
5️⃣ When Price Is Flat but LiquidEdge Moves: Volume Tells the Truth
One of the most useful things LiquidEdge can do is reveal pressure shifts when price looks neutral.
If price is moving sideways but the MFI slope or histogram rises, it may suggest that buying pressure is quietly increasing possibly pointing to early accumulation.
If price stays flat while the volume slope or histogram drops, this could indicate distribution, where sellers are exiting without moving the market noticeably.
These changes don’t guarantee a breakout or breakdown, but they often precede key moves especially when combined with other confluences like trend alignment or liquidity zones.
👉 LiquidEdge helps spot these setups by measuring volume momentum shifts beneath price action.
It doesn’t predict the future, but it gives you additional context to evaluate what may be developing before it’s visible on price alone.
6️⃣ Multi-Timeframe Flow Table
LiquidEdge includes a real-time table that tracks volume pressure across multiple timeframes including 5-minute, 15-minute, 1-hour, 4-hour, and daily charts.
Each row reflects the direction of the MFI slope on that timeframe, indicating whether volume pressure is increasing (inflow) or decreasing (outflow).
🟢 A rising slope suggests that buying momentum is building
🔴 A falling slope suggests selling pressure may be increasing
👉 This lets traders quickly assess whether short-term setups are aligned with higher timeframe volume trends a useful layer of confirmation for both intraday and swing strategies.
Rather than flipping between charts, the table gives you a snapshot of flow strength across the board, helping you stay focused on opportunities that align with broader market pressure.
7️⃣ Timeframes & Assets
Where LiquidEdge Works Best:
✅ Crypto: Supports major coins and high-volume altcoins (BTC, ETH, Top 100)
✅ Stocks: Effective on large-cap and mid-cap equities with consistent volume
✅ Futures: Tested on instruments like NQ, MNQ, ES, and MES
✅ Any liquid market where volume data is reliable and stable
For best results, use LiquidEdge on assets with consistent trading volume. It’s not recommended for ultra-low volume crypto pairs or micro-cap stocks, where irregular volume can distort signals.
Recommended Timeframes:
👉 Intraday trading: Works well on 3-minute, 5-minute, 15-minute, and 1-hour charts
👉 Swing trading: Performs reliably on 4-hour, daily, and weekly charts
👉 Ultra short-term (1-minute or less): Not recommended due to high noise and low reliability
LiquidEdge adapts to various trading styles from scalping short-term momentum shifts to analyzing broader volume trends across swing and positional setups. The key is choosing assets and timeframes with reliable volume flow for the tool to work effectively.
8️⃣ Common Mistakes to Avoid When Using LiquidEdge
❌ Using It in Isolation
LiquidEdge offers valuable context, but it’s not designed to function as a standalone trading system. Always combine it with key tools such as trendlines, support/resistance zones, chart structure, or fundamental data. The more supporting evidence you have, the stronger your analysis becomes.
❌ Relying on a Single Indicator
No indicator, including LiquidEdge, can account for every market condition. It’s important to use it alongside other forms of confirmation to avoid making decisions based on limited data.
❌ Misinterpreting Divergences as Reversals
A divergence between price and volume pressure doesn't always signal the end of a trend. If the broader direction remains strong (based on EMAs or higher timeframe volume flow), a divergence could reflect temporary consolidation rather than reversal.
❌ Ignoring Trend Alignment and Confidence Scoring
LiquidEdge includes confidence scoring to help validate signals. Disregarding this structure can lead to reacting to weak or out-of-context divergences, especially in choppy or low-volume environments.
❌ Using It on Second-Based or Tick Charts
Very low timeframes introduce too much noise, which can distort volume slope and divergence signals. For intraday analysis, start with 3-minute charts or higher. For swing trading, use 4H and up for clearer, more reliable structure.
9️⃣ LiquidEdge Settings Overview
A quick breakdown of what you can customize in the indicator and how each option affects what you see:
➡️ LiquidEdge Length
Controls how sensitive the indicator is to changes in volume pressure (via MFI slope).
Shorter values = faster response, more frequent signals
Longer values = smoother output, less noise
👉 Default: 14
➡️ EMA Trend Filter
Determines overall trend direction based on EMA slope. Used to filter out signals that go against the broader move.
Helps reduce countertrend entries
Adjustable to suit your strategy
👉 Recommended: 200 EMA
➡️ Pivot Lookback (Left & Right)
Defines how many bars the system looks back and forward to identify swing highs/lows for divergence detection.
Narrow: more responsive but can be noisy
Wide: slower but more stable pivot zones
👉 Default: 5 left / 5 right
➡️ Histogram Toggle
Enables a visual histogram showing how volume pressure deviates from its recent average.
Useful for spotting shifts in flow intensity
👉 Optional for added visual detail
➡️ Liquidity Zones
Highlights potential exhaustion zones based on MFI value:
Above 80 = potential distribution (buying pressure peaking)
Below 20 = possible accumulation (selling pressure fading)
👉 Zones are fully customizable (color, opacity, background)
➡️ Custom Threshold Zones
Set your own upper/lower boundaries for liquidity extremes helpful when adapting to different markets or asset classes.
👉 Especially useful outside of crypto/forex
➡️ Show LiquidEdge Line
Toggle the main MFI slope line. When turned off, liquidity zones and levels also disappear.
👉 Use if you prefer to focus only on histogram/divergences
➡️ Style Settings
Customize line colors, histogram appearance, and background shading
👉 Helps tailor visuals to your chart layout
➡️ Simplified Mode
Removes all colors and replaces visuals with a clean, grayscale output.
👉 Ideal for minimalist or distraction-free charting
➡️ Signal Score Label
Displays the confidence score of the current setup, based on:
Divergence presence
Liquidity zone positioning
Trend alignment (EMA)
👉 Tooltip explains how the score is calculated
➡️ Divergence Labels
Shows “Bullish” or “Bearish” labels at divergence points.
Optional Filters based on trend if EMA filter is active
➡️ Multi-Timeframe Flow Table
Shows directional flow (based on MFI slope) across: 5M, 15M, 1H, 4H, 1D
Color-coded (faded green/red) for clarity
👉 Table position is customizable on your chart
➡️ Alerts
Get notified when any of these conditions are met:
✅ Bullish or bearish divergence detected
✅ Price enters high/low liquidity zones
✅ Signal score reaches a defined value
➡️ Visibility Settings
Control which timeframes display the LiquidEdge indicator
👉 Best used on 3-minute and above
⚠️ Not recommended on ultra-low or second-based charts due to noise
🔟 Q&A – What Traders Usually Ask
➡️ Can this help reduce bad trades?
To a degree, yes. LiquidEdge is built to highlight areas where price may react, based on volume pressure, liquidity zones, and divergence patterns. It can offer clarity in sideways or messy markets, helping traders avoid impulsive or poorly timed entries.
That said, it’s not predictive or guaranteed. It works best when used with broader context including structure, support/resistance, trend, and volume-based confluence.
👉 Reminder: LiquidEdge is not a signal tool. It’s a decision-support framework designed to help you assess potential shifts, not replace judgment or trading rules.
➡️ Is this just another flashy signal tool?
No. LiquidEdge doesn’t give buy/sell alerts. Instead, it visualizes volume shifts using MFI slope, divergence filtering, and trend-based scoring. It’s built to help you understand why price action may be changing not just react to a one-dimensional signal.
You’re seeing how volume pressure evolves across timeframes, which gives added context to what’s unfolding in the market.
➡️ How do I know this isn’t just another overhyped tool?
LiquidEdge is based on real trading logic: volume pressure (via MFI slope), price behavior, and divergence within trend and liquidity zones. It was developed and tested by traders, not packaged by marketers.
No performance is guaranteed. It’s designed to support your decisions not promise results.
➡️ Will this work with my trading style?
If you trade any market with volume crypto, stocks, or futures LiquidEdge can add value.
✔️ Scalpers: Best from 3-minute and up
✔️ Swing traders: Works well on 4H, Daily, Weekly
✔️ Investors: Weekly charts show pressure buildup over time
⚠️ Avoid ultra-low timeframes (under 1M) or illiquid markets, as noise and irregular data can reduce reliability.
➡️ Can I trust the signals?
These are not buy/sell signals. LiquidEdge offers confidence-weighted insights based on:
✔️ Valid divergence
✔️ Zone positioning (above 80 / below 20)
✔️ Optional trend alignment (via EMA)
Each setup is scored visually to reflect how much confluence exists. You can combine that information with structure, price action, or your existing tools to evaluate opportunities.
👉 Think of LiquidEdge as a decision filter not a trigger.
It’s meant to slow down impulsive trades and help you make more context-aware decisions.
1️⃣1️⃣ Limitations – Know When It’s Less Effective
LiquidEdge performs best in stable, high-volume markets where volume data is consistent and structure is visible.
It’s not recommended for:
❌ Low-volume tokens
❌ Micro-cap or penny stocks
❌ Newly listed assets with limited trading history
These types of markets often show inconsistent or erratic volume behavior, making it difficult for LiquidEdge to accurately assess pressure or identify reliable divergences.
⚠️ During major news events or sudden volatility spikes, volume and price behavior can become disconnected or extreme. This may distort MFI slope calculations and reduce the accuracy of divergence or confidence scoring.
LiquidEdge is built to read structured volume flow. When market conditions become highly erratic or unpredictable, it's best to:
Wait for structure to return
Use it alongside other filters for additional confirmation
This isn't a flaw it's simply the nature of tools that rely on consistency in price and volume data.
1️⃣2️⃣ Real Chart Examples – See It in Action
Now that you’ve seen how LiquidEdge works, here are real-world chart examples from various asset classes
including:
✅ Crypto
✅ Stocks
✅ Futures
✅ Commodities
These examples demonstrate how LiquidEdge behaves under different conditions, and how both the line (MFI slope) and histogram (volume deviation) can be used to interpret market flow.
In each walkthrough, you’ll see:
How the histogram can highlight potential momentum shifts
When the slope line provides stronger directional clarity
Examples of possible hidden accumulation or distribution (before price responds)
What to watch out for such as weak volume, false divergences, or conflicting flow signals
👉 These are real examples based on live market data not theoretical setups. They’re meant to help you recognize how LiquidEdge reacts across multiple styles and timeframes.
Let’s walk through each one and break down the logic step by step, so you can understand how to evaluate setups using structure, volume behavior, and context-driven confluence.
Example: Microsoft (MSFT) – Possible Hidden Accumulation
In this setup, price was moving lower within a short-term downtrend. However, LiquidEdge began showing signs of increasing inflow pressure a common characteristic of accumulation, where volume rises even as price declines.
This divergence suggested that buying interest may have been increasing behind the scenes, despite weak price action on the surface.
Step-by-step breakdown:
👉 Trend context – Price was clearly trending down at the time
👉 Volume divergence – Price made lower lows, but LiquidEdge slope was rising = possible bullish divergence
👉 Accumulation clue – The rising slope, despite falling price, pointed to volume inflow often seen during quiet accumulation
👉 Histogram support – Volume pressure (via the histogram) also increased, confirming the flow shift
👉 Anticipating reaction – When liquidity pressure rises ahead of price, it can signal potential reversal interest
In this case, price later moved sharply higher. While not guaranteed, setups like this illustrate how divergence + volume flow may help highlight early accumulation zones before price confirms the shift.
Same Setup – Focusing on the Histogram Alone
Here, we’re revisiting the Microsoft setup but this time focusing only on the histogram, without the MFI slope line.
Even without the directional slope, the histogram showed rising volume pressure while price continued to drift lower. This visual pattern may indicate that buying interest was quietly increasing, despite weak price movement.
This is where the histogram adds value: it helps visualize the intensity of volume flow over time. When volume pressure builds during a flat or declining price phase, it can be consistent with accumulation where larger participants begin positioning before the market responds.
This example highlights how the histogram alone can provide early insight into underlying volume dynamics even before price shifts noticeably.
Filtering with EMA and why It Matters
Here, we revisit the Microsoft example this time applying the 200 EMA filter, which helps define the broader trend.
Once enabled, LiquidEdge automatically removed any bullish or bearish divergence signals that were against the prevailing trend. This helped reduce noise and focus only on setups aligned with market structure.
✅ The EMA acts as a contextual filter.
For example, if a bullish divergence occurs during a confirmed downtrend, LiquidEdge suppresses that signal helping you avoid setups that may carry more risk.
This filtering mechanism is especially useful in fast or choppy markets, where not all divergences are meaningful.
Want More Flexibility? Adjust the Filter
If you're a more aggressive trader or prefer shorter-term signals, you can reduce the EMA length (e.g., to 150, 50, or even 25). This increases the number of setups shown but also raises the importance of additional context and confirmation.
⚠️ Keep in mind:
❌ More signals doesn’t always mean better outcomes
✅ Focused, context-aware signals tend to be more consistent with broader market pressure
If you’re using this in combination with strategies like options trading, this filter can help refine your entry zones especially when paired with other structure or volatility tools.
Distribution Example and Bitcoin Setup Before a Major Drop
In this example, Bitcoin was trading in a relatively tight range while price continued to push upward. However, LiquidEdge began to show signs of volume outflow, which can suggest potential distribution.
Here’s what was observed:
🔴 Price was moving up inside a horizontal range
🔴 LiquidEdge’s slope indicated declining volume pressure
🔴 Several bearish divergence signals appeared during this consolidation phase
🔴 The histogram also showed weakening flow, even before price broke down
These overlapping signals pointed to a possible distribution phase, where buying momentum was fading despite price still holding up.
🧭 Signs to Watch for in Potential Distribution:
1️⃣ Price holding flat or rising slightly within a tight range
2️⃣ Volume pressure (line or histogram) sloping downward
3️⃣ Repeated bearish divergences forming at the highs
4️⃣ Lack of follow-through on bullish setups signaling hesitation in demand
While LiquidEdge can’t predict market outcomes, this scenario demonstrates how a combination of divergence, outflow, and failure to break out may serve as early warnings that momentum is shifting beneath the surface.
Failed Auction Example – Volume Shift Before a Breakdown
In this example, price attempted to break out above a recent high, creating the appearance of a bullish continuation. However, LiquidEdge began to signal volume outflow, despite the upward price move a potential sign of a failed auction.
Here’s what was observed:
👉 Price made a new high, appearing to break resistance
👉 LiquidEdge slope and histogram both showed declining liquidity
👉 The indicator formed lower lows, even as price pushed higher
👉 This divergence suggested that volume wasn’t supporting the breakout
Shortly after, price reversed and returned back inside the range which is a common characteristic of failed auction behavior.
🧭 Spotting a Potential Failed Auction with LiquidEdge:
1️⃣ Price breaks above a recent high
2️⃣ Volume flow (line + histogram) shows outflow, not inflow
3️⃣ Indicator forms lower lows while price makes higher highs (bearish divergence)
4️⃣ Market reverts back into the previous range without follow-through
While no tool can predict outcomes, this setup demonstrated how volume pressure and divergence can help identify moments where a breakout may lack real support offering context before price action confirms the shift.
Reading the Histogram - Spotting Pressure Fades
In this example, price was still rising but the LiquidEdge histogram showed falling volume pressure. This type of divergence between price and volume can serve as a potential early signal that momentum may be fading.
🔻 Histogram levels declined while price continued higher
🔻 This suggested that buying pressure was weakening, even though price hadn’t turned
🔻 Volume flow behavior didn’t support the continuation possibly indicating buyer exhaustion
Just before the peak, the histogram nearly reached its lower threshold, despite price still being near its highs.
💡 How to Read It:
When volume pressure (shown by the histogram) starts to fade while price is still rising, it can indicate that momentum is weakening. This may precede a pullback or reversal particularly if other factors like divergence or zone exhaustion are also present.
Conversely, rising histogram values during a price drop may suggest potential accumulation.
👉 Use the histogram as a volume intensity gauge, not a signal on its own especially when evaluating whether a move is supported by actual flow, or just price momentum.
The Table – Fast, Visual Multi-Timeframe Flow Insight
The multi-timeframe flow table in LiquidEdge provides a consolidated view of volume momentum across several key timeframes so you don’t need to switch between charts to compare flow strength.
👉 Instead of flipping from 5-minute to 15M, 1H, 4H, and Daily, the table displays flow direction on all of them at a glance.
Example layout:
🔼 Daily: Up
🔽 1H: Down
🔼 15M: Up
🔽 5M: Down
This setup gives you a quick read on whether volume momentum is aligned across multiple timeframes or diverging which can help frame your trade approach.
🧠 Why It’s Useful:
✅ Supports timeframe alignment
If higher timeframes show strong inflow while lower ones are mixed, you may interpret it as a swing-based opportunity. If short timeframes show pressure but higher frames are flat, it might suggest short-term setups with caution.
✅ Improves context awareness
Instead of interpreting a move in isolation, the table helps you assess whether short-term signals are part of a broader shift or going against higher timeframe flow.
💡 Pro Tip: Use the table as a starting point in your analysis. It’s a simple but effective snapshot of current liquidity pressure across the board helping you plan trades with broader context, rather than reacting chart-by-chart.
🔚 Final Thoughts
If you're focused on trading with better clarity and structure, LiquidEdge is designed to help you interpret what’s happening beneath the surface not just follow price movement.
While many tools highlight price alone, LiquidEdge combines volume pressure, divergence filtering, and trend-based context to help identify potential areas of accumulation, distribution, or momentum shifts even before they become obvious on a chart.
👉 This isn’t just another signal tool. It’s a framework to support smarter decision-making:
✔️ One that helps you filter out noise
✔️ One that scores setups using multiple layers of confirmation
✔️ One that brings volume context into every trade idea
Whether you're scalping on a 5-minute chart or managing a longer-term swing trade, LiquidEdge is built to help you stay aligned with volume-driven behavior not just react to price alone.
If you've struggled with late entries, unreliable setups, or second-guessing trades, this tool was designed to bring more structure to your process. It won’t remove all uncertainty but it can help you stay more selective, confident, and intentional.
✅ Trade with clarity
✅ Stay process-driven
✅ Focus on structure, not noise
LiquidEdge is not meant to replace your strategy. It’s here to enhance it.
In this chart, the 200 EMA filter was applied. As a result, only signals that aligned with the dominant trend direction were displayed helping to reduce distractions and focus on setups with stronger context.
💡 Using a higher EMA setting like 200 can reduce the number of signals shown, but may help you focus on higher-conviction opportunities.
That said, every trader is different:
Longer EMAs = fewer signals, but more trend-filtered setups
Shorter EMAs = more signals, faster entries but with potentially more noise
👉 Adjust the filter based on your trading style. Use a 200 EMA for swing trading, or reduce it to 50, 25, or even 5 if you're trading more aggressively or intraday.
LiquidEdge adapts to you not the other way around.
🔁 Adjusting EMA for Your Trading Style
Personal Tip: When trading more aggressively, I often use a 5 EMA filter especially when combining histogram strength with other tools. This increases signal responsiveness and may help highlight short-term flow shifts more quickly.
Below are visual examples that show how different EMA lengths impact the behavior of LiquidEdge:
50 EMA ON
25 EMA ON
5 EMA ON
Lower EMA Example – Gold with the 5 EMA
In this example, the 5 EMA filter was applied to Gold. As expected, more signals were plotted compared to higher EMA settings. The tool became more responsive to rapid shifts in volume momentum, making it more suitable for fast-paced trading environments.
This setting can help traders who prefer early entries but it also introduces more sensitivity, so context and additional confirmation become even more important.
Each setting affects signal frequency and filtering:
Higher EMA → fewer signals, more trend-confirmed setups
Lower EMA → more signals, quicker responses, but with more potential for noise
Choose what fits your approach:
Long-term swing → Stick with 200 EMA
Intraday or scalping → Consider shorter EMAs (50, 25, or 5)
💡 Reminder: EMA filtering is fully adjustable. LiquidEdge doesn’t lock you into one trading style it’s meant to adapt to your process, whether you’re swing trading or scalping short-term moves.
But There’s a Catch…
Using a lower EMA setting (like 5) opens up faster, more frequent signals but it also increases the need for precision and stronger trade management.
❗ More signals = More responsiveness
❗ Faster setups mean quicker decisions
❗ Risk control becomes even more important
💡 Lower Timeframes = More Detail, Less Margin for Error
A short EMA (like 5) can help you:
✅ Identify early momentum shifts
✅ Respond before traditional trend-followers
✅ Highlight short-term divergence and volume changes
But it also comes with tradeoffs:
❌ Greater signal noise
❌ Higher potential for misreads or fakeouts
❌ Requires clear structure and disciplined entries
🚩 Watch Out for Liquidity Grabs
In lower timeframes, a common trap is the liquidity grab where price pushes beyond recent highs or lows, triggers stops, then quickly reverses.
📌 These moves can look like breakouts, but often reverse quickly possibly reflecting institutional order placement or low-liquidity manipulation.
🧭 How to Approach It Smartly
✅ Use structure: Mark support and resistance to frame moves
✅ Confirm volume behavior: Is histogram strength rising or fading?
✅ Avoid chasing: Look for confluence, not just a single signal
✅ Be intentional with stops: Place them with structure in mind to avoid being swept out
NASDAQ Futures Example – Low Timeframe Setups with LiquidEdge
In this example, we look at how LiquidEdge was used to identify both short and long setups on the NASDAQ Futures (NQ) particularly on a low timeframe (5M), where quick decision-making and volume precision matter most.
⚠️ A Note on Futures and Volume
When trading futures, especially on intraday charts, it’s important to separate overnight volume from regular session activity.
🕒 Overnight Volume ≠ Real Volume Context
Overnight price action is informative, but the volume data itself may not reflect true market participation. In LiquidEdge, histogram and pressure calculations emphasize regular session flow helping avoid skewed signals that could come from low-volume overnight moves.
Using the Histogram to Spot Potential Shifts
One of the key cues I use is color transition in the histogram:
🔴 A flip from strong green to red can signal fading buying pressure, sometimes marking the beginning of a potential short setup.
🟢 A shift from red to green may indicate that buyers are returning, suggesting possible accumulation.
These shifts serve as early visual cues of changing pressure especially when confirmed by other tools or context.
🔁 Adding Context with the Line + Structure
After spotting a histogram shift, I look at:
1️⃣ Slope Line – Is it confirming the same directional pressure?
2️⃣ Support/Resistance – Are we near a meaningful zone?
3️⃣ Additional Tools – This includes trendlines, VWAP, EMAs, and overall price structure.
On lower timeframes like 5M, these pieces become even more important. LiquidEdge gives directional insight, but your full setup provides confirmation and execution logic.
⚠️ Disclaimer
LiquidEdge is not a signal tool. It’s a visual representation of market pressure and flow designed to help you make more informed trading and investing decisions. It shows you what’s happening beneath the price action but you are still responsible for your decisions.
Always combine LiquidEdge with your own strategy, research, and supporting tools. That includes trend analysis, support/resistance levels, chart patterns, and fundamentals (like P/E ratios, price-to-sales, debt ratios, etc.).
This tool should never be used alone or treated as financial advice.
Some content may include AI-powered enhancements for clarity or formatting.
Always do your own research. For personal financial guidance, speak with a licensed financial advisor.
GEEKSDOBYTE IFVG w/ Buy/Sell Signals1. Inputs & Configuration
Swing Lookback (swingLen)
Controls how many bars on each side are checked to mark a swing high or swing low (default = 5).
Booleans to Toggle Plotting
showSwings – Show small triangle markers at swing highs/lows
showFVG – Show Fair Value Gap zones
showSignals – Show “BUY”/“SELL” labels when price inverts an FVG
showDDLine – Show a yellow “DD” line at the close of the inversion bar
showCE – Show an orange dashed “CE” line at the midpoint of the gap area
2. Swing High / Low Detection
isSwingHigh = ta.pivothigh(high, swingLen, swingLen)
Marks a bar as a swing high if its high is higher than the highs of the previous swingLen bars and the next swingLen bars.
isSwingLow = ta.pivotlow(low, swingLen, swingLen)
Marks a bar as a swing low if its low is lower than the lows of the previous and next swingLen bars.
Plotting
If showSwings is true, small red downward triangles appear above swing highs, and green upward triangles below swing lows.
3. Fair Value Gap (3‐Bar) Identification
A Fair Value Gap (FVG) is defined here using a simple three‐bar logic (sometimes called an “inefficiency” in price):
Bullish FVG (bullFVG)
Checks if, two bars ago, the low of that bar (low ) is strictly greater than the current bar’s high (high).
In other words:
bullFVG = low > high
Bearish FVG (bearFVG)
Checks if, two bars ago, the high of that bar (high ) is strictly less than the current bar’s low (low).
In other words:
bearFVG = high < low
When either condition is true, it identifies a three‐bar “gap” or unfilled imbalance in the market.
4. Drawing FVG Zones
If showFVG is enabled, each time a bullish or bearish FVG is detected:
Bullish FVG Zone
Draws a semi‐transparent green box from the bar two bars ago (where the gap began) at low up to the current bar’s high.
Bearish FVG Zone
Draws a semi‐transparent red box from the bar two bars ago at high down to the current bar’s low.
These colored boxes visually highlight the “fair value imbalance” area on the chart.
5. Inversion (Fill) Detection & Entry Signals
An inversion is defined as the price “closing through” that previously drawn FVG:
Bullish Inversion (bullInversion)
Occurs when a bullish FVG was identified on bar-2 (bullFVG), and on the current bar the close is greater than that old bar-2 low:
bullInversion = bullFVG and close > low
Bearish Inversion (bearInversion)
Occurs when a bearish FVG was identified on bar-2 (bearFVG), and on the current bar the close is lower than that old bar-2 high:
bearInversion = bearFVG and close < high
When an inversion is true, the indicator optionally draws two lines and a label (depending on input toggles):
Draw “DD” Line (yellow, solid)
Plots a horizontal yellow line from the current bar’s close price extending five bars forward (bar_index + 5). This is often referred to as a “Demand/Daily Demand” line, marking where price inverted the gap.
Draw “CE” Line (orange, dashed)
Calculates the midpoint (ce) of the original FVG zone.
For a bullish inversion:
ce = (low + high) / 2
For a bearish inversion:
ce = (high + low) / 2
Plots a horizontal dashed orange line at that midpoint for five bars forward.
Plot Label (“BUY” / “SELL”)
If showSignals is true, a green “BUY” label is placed at the low of the current bar when a bullish inversion occurs.
Likewise, a red “SELL” label at the high of the current bar when a bearish inversion happens.
6. Putting It All Together
Swing Markers (Optional):
Visually confirm recent swing highs and swing lows with small triangles.
FVG Zones (Optional):
Highlight areas where price left a 3-bar gap (bullish in green, bearish in red).
Inversion Confirmation:
Wait for price to close beyond the old FVG boundary.
Once that happens, draw the yellow “DD” line at the close, the orange dashed “CE” line at the zone’s midpoint, and place a “BUY” or “SELL” label exactly on that bar.
User Controls:
All of the above elements can be individually toggled on/off (showSwings, showFVG, showSignals, showDDLine, showCE).
In Practice
A bullish FVG forms whenever a strong drop leaves a gap in liquidity (three bars ago low > current high).
When price later “fills” that gap by closing above the old low, the script signals a potential long entry (BUY), draws a demand line at the closing price, and marks the midpoint of that gap.
Conversely, a bearish FVG marks a potential short zone (three bars ago high < current low). When price closes below that gap’s high, it signals a SELL, with similar lines drawn.
By combining these elements, the indicator helps users visually identify inefficiencies (FVGs), confirm when price inverts/fills them, and place straightforward buy/sell labels alongside reference lines for trade management.
MMM @MaxMaserati 2.0MMM @MaxMaserati 2.0 - TradingView Indicator
The Backbone of the Max Maserati Method
The MMM @MaxMaserati 2.0 indicator is the core of the proprietary Max Maserati Method (MMM), a trading system designed to decode institutional price action. It integrates candle bias analysis, market structure identification, volume-based signals, and precise entry zones to align traders with smart money.
Core Components of the MMM System
1. Six Core Candle Classifications
Master these patterns to reveal institutional behavior:
Bullish Body Close: Closes above previous high, signaling strong buying.
Bearish Body Close: Closes below previous low, indicating intense selling.
Bullish Affinity: High tests previous low, closes within range, showing hidden bullish strength.
Bearish Affinity: Low tests previous high, closes within range, reflecting bearish pressure.
Seek & Destroy: Breaks both previous high/low, closes inside, direction depends on close.
Close Inside: High/low within previous range, bias based on close.
2. Plus/Minus Strength System
Quantifies candle conviction:
Bullish Strength: Low to close distance.
Bearish Strength: High to close distance.
Plus (+): Dominant strength signals strong follow-through.
Minus (-): Balanced strengths suggest caution.
3. PO4 Candles (Power of OHLC (4))
Analyzes OHLC for body-closed candles after swing high/low fractals:
C2: Body close above high/below low post fractal with strength conditions.
C3: Stronger body close with pronounced low/high breakouts.
C4: Body close which show strength and might trigger a BeB/BuB
Visualization: Green (bullish), purple (bearish) bars; triangle markers for fractals.
4. MC2 (High Volume Reversal Candles)
High buy/sell volume candles reversed by opposing volume:
Bullish MC2: Buy volume flipped by sell volume, signaling exhaustion.
Bearish MC2: Sell volume flipped by buy volume, indicating reversal.
Visualization: Dark green (bullish), dark red (bearish) bars.
5. MMM Blocks (eBlocks and iBlocks)
Marks institutional order blocks:
External Blocks (eBlocks): At market structure changes (MSC), labeled BuB/BeB.
Internal Blocks (iBlocks): Within trends, labeled L/S.
Volume: Normalized with indicators (🔥 high, ↑ above average, ↓ low).
Filters: Discount (0-50), premium (50-100), extreme (0-20, 80-100), mid-range (20-50, 50-80).
6. Entry Blocks - Specific Entry Areas
Entry Blocks are precise zones for framing trades based on the MMM system, triggered post-MSC to capitalize on institutional momentum:
Purpose: Pinpoint high-probability entry areas following a Market Structure Change (MSC), aligning with smart money direction.
Formation:
MMM Entry Block Long: Forms after a bullish MSC (BuB), typically at the swing low (e.g., lowerValueMSC) of the fractal pattern, marking a long entry zone.
MMM Entry Block Short: Forms after a bearish MSC (BeB), typically at the swing high (e.g., upperValueMSC), marking a short entry zone.
Styles :
Close-to-Swing High/Low: Box drawn from the candle’s close to the swing high/low level, emphasizing the fractal pivot.
High/Low-to-Close: Box drawn from the candle’s high/low to its close, capturing the full price action range.
Visualization:
Labeled “MMM Entry Block Long” (cyan background/border) or “Short” (pink background/border).
Includes a dashed midline for reference.
Volume displayed if enabled, normalized with markers (🔥 >150%, ⚡ >120%, ❄️ <70%).
Behavior:
Deletes when price touches the level (On Level Touch) or closes beyond it (On Candle Close)
Limited to a configurable number ( default 5) to avoid clutter.
Trade Framing:
Entry: Enter within the eBreak box, ideally on a pullback or confirmation candle aligning with MMM bias (e.g., Bullish Body Close or Affinity).
Stop-Loss: Placed below the eBreak low (bullish) or above the high (bearish), leveraging the swing level as support/resistance.
Take-Profit: Targets higher timeframe high (bullish) or low (bearish), with ratio (default 2.0) for risk-reward.
MMM Integration: Use candle bias (Plus/Minus), PO4 signals, and MMPD consensus to confirm entry direction and strength.
Significance: eBreaks frame trades by isolating institutional entry points post-MSC, reducing noise and enhancing precision.
7. Market Structure Change (MSC)
Tracks structure shifts:
Detection: Fractal highs/lows with adjustable candle count.
Visualization: Green (BuB), red (BeB) lines/labels; numbered breaks (Bub1/Beb1).
Counter: Tracks consecutive MSCs for trend strength.
8. MMPD (Market Momentum Price Delivery)
Analyzes momentum/trend:
Conditions: Red (bearish), Green (bullish), Pink (modifying bearish), Pale Green (modifying bullish).
Traps: Flags bullish/bearish traps when MMPD conflicts with body close.
Metrics: SuperMaxTrend, momentum (K/D), MMPD level.
Consensus: Rated signals (e.g., “Very Strong Buy ★★★★★”).
9. Trade and Risk Management
Disciplined trading:
Entry Visualization: Entry, stop-loss, take-profit lines/labels with customizable risk (riskAmount, default $50) and reward (ratio).
Behavior: Shows last/all entries, removes on MSC shift or breach.
Text Size: Tiny, Small, Normal.
NB: The Trade and risk management is to use with caution, it is not fully implemented yet.
10. Stats Table
Real-time dashboard:
Elements: Timeframe, symbol, candle bias, strength, MMPD, momentum, SuperMaxTrend, MMPD level, volume, consensus, divergence, delta MA, price delivery, note (“Analyze | Wait | Repeat”).
Customization: Position, size, element visibility.
Colors: Green (bullish), red (bearish), orange (warnings), gray (neutral).
11. Delta MA and Divergence
Monitors volume delta:
Delta MA: Smoothed delta with direction arrows (↗↘→).
Divergence: Flags MMPD-momentum divergences (⚠️).
Key Features
Automated Analysis: Detects PO4, MSC, blocks, MC2, Entry Block via OHLC.
Color-Coded Visualization: Bars, lines, table cells reflect bias/strength.
Dynamic Bias Lines: Higher timeframe high/low lines with labels.
Volume Analysis: Normalized volume across blocks, entries, MC2.
Flexible Filters: Tailors block/entry Block display to strategies.
Real-Time Metrics: Tracks strength, delta, trend points.
Trading Advantages
Institutional Insight: Decodes manipulation via OHLC and volume.
Early Reversals: Spots shifts via PO4, MC2, MSC, Entry Blocks.
Precise Entries: entry block frame high-probability trades.
Robust Risk Management: Stop-loss, take-profit, risk-reward.
Simplified Complexity: Actionable signals from complex action.
Profit Target Framework
Bullish: Higher timeframe high.
Bearish: Higher timeframe low.
Plus Strength: Direct move.
Minus Strength: Pullbacks expected.
Entry Blocks/MSC-Driven: Entry anchor entries to MSC targets.
Trader’s Mantra
“Analyze | Wait | Repeat” - Discipline drives profits.
The MMM @MaxMaserati 2.0 indicator, with Entry Blocks as specific trade-framing zones, offers a professional-grade framework for precise, institutional-aligned trading.
Note: Based on the proprietary Max Maserati Method for educational and analytical use.
CandelaCharts - ICT Weekly Profiles📝 Overview
The indicator provides a pattern-based approach to the ICT Weekly Profiles, emphasizing a line that marks the Open, High, Low, and Close of the week. This line allows you to instantly visualize and identify the Weekly Profile.
The profile detection relies on the week’s high and low, delivering a clear and concise representation of the weekly profile.
ICT Weekly Profiles are structured conceptual frameworks designed to outline typical patterns of price behavior over the course of a trading week. These profiles serve as analytical tools, offering traders insights into recurring market tendencies and helping them identify potential opportunities and risks.
The ICT Weekly Profiles indicator offers two distinct types of profiles to provide a clearer understanding of weekly price action:
ICT Weekly Profiles
ICT Missing Weekly Profiles
The toolkit automatically detects and marks these ICT Weekly Profiles and ICT Missing Weekly Profiles on the chart, enabling traders to quickly pinpoint critical zones for analysis and decision-making.
📦 Features
The ICT Weekly Profiles toolkit offers a comprehensive set of features designed to enhance trading precision and decision-making. Key features include:
Weekly Profiles
Missing Weekly Profiles
Advanced Styling
Scanner
The indicator supports the following profiles:
ICT Weekly Profiles
Classic Tuesday Low Of The Week Bullish
Classic Tuesday High Of The Week Bearish
Wednesday Low Of The Week Bullish
Wednesday High Of The Week Bearish
Consolidation Thursday Reversal Bullish
Consolidation Thursday Reversal Bearish
Consolidation Midweek Rally Bullish
Consolidation Midweek Rally Bearish
Wednesday Weekly Reversal Bullish
Wednesday Weekly Reversal Bearish
Seek And Destroy Bullish Friday
Seek And Destroy Bearish Friday
ICT Missing Weekly Profiles
Monday Low Tuesday High Bullish
Monday High Tuesday Low Bearish
Monday Low Wednesday High Bullish
Monday High Wednesday Low Bearish
Monday Low Thursday High Bullish
Monday High Thursday Low Bearish
Tuesday Low Wednesday High Bullish
Tuesday High Wednesday Low Bearish
Tuesday Low Friday High Bullish
Tuesday High Friday Low Bearish
Wednesday Low Thursday High Bullish
Wednesday High Thursday Low Bearish
Monday Low Friday High Bullish
Monday Friday Bearish Rally
Monday High/Low Range
Tuesday High/Low Range
Wednesday High/Low Range
Thursday High/Low Range
Friday High/Low Range
⚙️ Settings
History: Controls how many profiles are displayed on the chart.
Timeframe Limit: Sets the timeframe up to which profiles will be drawn.
Show OHLC Lines: Display the lines for OHLC.
Show Profile Line: Display the Weekly Profile line.
Use NY Midnight Open: Controls from where a profile will start detection.
Open: Style for Open line.
High: Style for High line.
Low: Style for Low line.
Midline: Style for Profile Midline.
Label: Controls the position of the Weekly Profile name.
Scanner: Display the Scanner
⚡️ Showcase
ICT (Inner Circle Trader) weekly profile templates are analytical frameworks that categorize and describe typical patterns of price action observed during a trading week.
ICT Weekly Profiles
ICT Missing Weekly Profiles
Scanner
📒 Usage
The primary objective of the ICT Weekly Profiles indicator is to provide traders with a comprehensive and actionable overview of the Weekly Previous, Current, and Future Profile. This allows traders to interpret market structure, anticipate price behavior, and align their trading decisions with higher time-frame trends.
Load the indicator on the chart
Enable Scanner
See the Predicted Profiles list
Predicted Profiles represent all potential scenarios for the current week, generated by a profile detection algorithm.
By visualizing potential outcomes through Predicted Profiles, the ICT Weekly Profiles indicator provides traders with a strategic edge, allowing them to remain flexible, prepared, and aligned with the most probable market movements.
🚨 Alerts
The indicator does not provide any alerts!
🔹 Notes
ICT Weekly Profiles
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ICT Missing Weekly Profiles
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⚠️ Disclaimer
These tools are exclusively available on the TradingView platform.
Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products.
By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable.
We do not offer reimbursements, refunds, or chargebacks. Once these Terms are accepted at the time of purchase, no reimbursements, refunds, or chargebacks will be issued under any circumstances.
By continuing to use these charting tools, the user confirms their understanding and acceptance of these Terms as outlined in this disclaimer.
PERFECT PIVOT RANGE DR ABIRAM SIVPRASAD (PPR)PERFECT PIVOT RANGE (PPR) by Dr. Abhiram Sivprasad
The Perfect Pivot Range (PPR) indicator is designed to provide traders with a comprehensive view of key support and resistance levels based on pivot points across different timeframes. This versatile tool allows users to visualize daily, weekly, and monthly pivots along with high and low levels from previous periods, helping traders identify potential areas of price reversals or breakouts.
Features:
Multi-Timeframe Pivots:
Daily, weekly, and monthly pivot levels (Pivot Point, Support 1 & 2, Resistance 1 & 2).
Helps traders understand price levels across various timeframes, from short-term (daily) to long-term (monthly).
Previous High-Low Levels:
Displays the previous week, month, and day high-low levels to highlight key zones of historical support and resistance.
Traders can easily see areas of price action from prior periods, giving context for future price movements.
Customizable Options:
Users can choose which pivot levels and high-lows to display, allowing for flexibility based on trading preferences.
Visual settings can be toggled on and off to suit different trading strategies and timeframes.
Real-Time Data:
All pivot points and levels are dynamically calculated based on real-time price data, ensuring accurate and up-to-date information for decision-making.
How to Use:
Pivot Points: Use daily, weekly, or monthly pivot points to find potential support or resistance levels. Prices above the pivot suggest bullish sentiment, while prices below indicate bearishness.
Previous High-Low: The high-low levels from previous days, weeks, or months can serve as critical zones where price may reverse or break through, indicating potential trade entries or exits.
Confluence: When pivot points or high-low levels overlap across multiple timeframes, they become even stronger levels of support or resistance.
This indicator is suitable for all types of traders (scalpers, swing traders, and long-term investors) looking to enhance their technical analysis and make more informed trading decisions.
Here are three detailed trading strategies for using the Perfect Pivot Range (PPR) indicator for options, stocks, and commodities:
1. Options Buying Strategy with PPR Indicator
Strategy: Buying Call and Put Options Based on Pivot Breakouts
Objective: To capitalize on sharp price movements when key pivot levels are breached, leading to high returns with limited risk in options trading.
Timeframe: 15-minute to 1-hour chart for intraday option trading.
Steps:
Identify the Key Levels:
Use weekly pivots for intraday trading, as they provide more significant levels for options.
Enable the "Previous Week High-Low" to gauge support and resistance from the previous week.
Call Option Setup (Bullish Breakout):
Condition: If the price breaks above the weekly pivot point (PP) with high momentum (indicated by a strong bullish candle), it signifies potential bullishness.
Action: Buy Call Options at the breakout of the weekly pivot.
Confirmation: Check if the price is sustaining above the pivot with a minimum of 1-2 candles (depending on timeframe) and the first resistance (R1) isn’t too far away.
Target: The first resistance (R1) or previous week’s high can be your target for exiting the trade.
Stop-Loss: Set a stop-loss just below the pivot point (PP) to limit risk.
Put Option Setup (Bearish Breakdown):
Condition: If the price breaks below the weekly pivot (PP) with strong bearish momentum, it’s a signal to expect a downward move.
Action: Buy Put Options on a breakdown below the weekly pivot.
Confirmation: Ensure that the price is closing below the pivot, and check for declining volumes or bearish candles.
Target: The first support (S1) or the previous week’s low.
Stop-Loss: Place the stop-loss just above the pivot point (PP).
Example:
Let’s say the weekly pivot point (PP) is at 1500, the price breaks above and sustains at 1510. You buy a Call Option with a strike price near 1500, and the target will be the first resistance (R1) at 1530.
2. Stock Trading Strategy with PPR Indicator
Strategy: Swing Trading Using Pivot Points and Previous High-Low Levels
Objective: To capture mid-term stock price movements using pivot points and historical high-low levels for better trade entries and exits.
Timeframe: 1-day or 4-hour chart for swing trading.
Steps:
Identify the Trend:
Start by determining the overall trend of the stock using the weekly pivots. If the price is consistently above the pivot point (PP), the trend is bullish; if below, the trend is bearish.
Buy Setup (Bullish Trend Reversal):
Condition: When the stock bounces off the weekly pivot point (PP) or previous week’s low, it signals a bullish reversal.
Action: Enter a long position near the pivot or previous week’s low.
Confirmation: Look for a bullish candle pattern or increasing volumes.
Target: Set your first target at the first resistance (R1) or the previous week’s high.
Stop-Loss: Place your stop-loss just below the previous week’s low or support (S1).
Sell Setup (Bearish Trend Reversal):
Condition: When the price hits the weekly resistance (R1) or previous week’s high and starts to reverse downwards, it’s an opportunity to short-sell the stock.
Action: Enter a short position near the resistance.
Confirmation: Watch for bearish candle patterns or decreasing volume at the resistance.
Target: Your first target would be the weekly pivot point (PP), with the second target as the previous week’s low.
Stop-Loss: Set a stop-loss just above the resistance (R1).
Use Previous High-Low Levels:
The previous week’s high and low are key levels where price reversals often occur, so use them as reference points for potential entry and exit.
Example:
Stock XYZ is trading at 200. The previous week’s low is 195, and it bounces off that level. You enter a long position with a target of 210 (previous week’s high) and place a stop-loss at 193.
3. Commodity Trading Strategy with PPR Indicator
Strategy: Trend Continuation and Reversal in Commodities
Objective: To capitalize on the strong trends in commodities by using pivot points as key support and resistance levels for trend continuation and reversal.
Timeframe: 1-hour to 4-hour charts for commodities like Gold, Crude Oil, Silver, etc.
Steps:
Identify the Trend:
Use monthly pivots for long-term commodities trading since commodities often follow macroeconomic trends.
The monthly pivot point (PP) will give an idea of the long-term trend direction.
Trend Continuation Setup (Bullish Commodity):
Condition: If the price is consistently trading above the monthly pivot and pulling back towards the pivot without breaking below it, it indicates a bullish continuation.
Action: Enter a long position when the price tests the monthly pivot (PP) and starts moving up again.
Confirmation: Look for a strong bullish candle or an increase in volume to confirm the continuation.
Target: The first resistance (R1) or previous month’s high.
Stop-Loss: Place the stop-loss below the monthly pivot (PP).
Trend Reversal Setup (Bearish Commodity):
Condition: When the price reverses from the monthly resistance (R1) or previous month’s high, it’s a signal for a bearish reversal.
Action: Enter a short position at the resistance level.
Confirmation: Watch for bearish candle patterns or decreasing volumes at the resistance.
Target: Set your first target as the monthly pivot (PP) or the first support (S1).
Stop-Loss: Stop-loss should be placed just above the resistance level.
Using Previous High-Low for Swing Trades:
The previous month’s high and low are important in commodities. They often act as barriers to price movement, so traders should look for breakouts or reversals near these levels.
Example:
Gold is trading at $1800, with a monthly pivot at $1780 and the previous month’s high at $1830. If the price pulls back to $1780 and starts moving up again, you enter a long trade with a target of $1830, placing your stop-loss below $1770.
Key Points Across All Strategies:
Multiple Timeframes: Always use a combination of timeframes for confirmation. For example, a daily chart may show a bullish setup, but the weekly pivot levels can provide a larger trend context.
Volume: Volume is key in confirming the strength of price movement. Always confirm breakouts or reversals with rising or declining volume.
Risk Management: Set tight stop-loss levels just below support or above resistance to minimize risk and lock in profits at pivot points.
Each of these strategies leverages the powerful pivot and high-low levels provided by the PPR indicator to give traders clear entry, exit, and risk management points across different markets
Alligator + Fractals + Divergent & Squat Bars + Signal AlertsThe indicator includes Williams Alligator, Williams Fractals, Divergent Bars, Market Facilitation Index, Highest and Lowest Bars, maximum and minimum peak of Awesome Oscillator, and signal alerts based on Bill Williams' Profitunity strategy.
MFI and Awesome Oscillator
According to the Market Facilitation Index Oscillator, the Squat bar is colored blue, all other bars are colored according to the Awesome Oscillator color, except for the Fake bars, colored with a lighter AO color. In the indicator settings, you can enable the display of "Green" bars (in the "Green Bars > Show" field). In the indicator style settings, you can disable changing the color of bars in accordance with the AO color (in the "AO bars" field), including changing the color for Fake bars (in the "Fake AO bars" field).
MFI is calculated using the formula: (high - low) / volume.
A Squat bar means that, compared to the previous bar, its MFI has decreased and at the same time its volume has increased, i.e. MFI < previous bar and volume > previous bar. A sign of a possible price reversal, so this is a particularly important signal.
A Fake bar is the opposite of a Squat bar and means that, compared to the previous bar, its MFI has increased and at the same time its volume has decreased, i.e. MFI > previous bar and volume < previous bar.
A "Green" bar means that, compared to the previous bar, its MFI has increased and at the same time its volume has increased, i.e. MFI > previous bar and volume > previous bar. A sign of trend continuation. But a more significant trend confirmation or warning of a possible reversal is the Awesome Oscillator, which measures market momentum by calculating the difference between the 5 Period and 34 Period Simple Moving Averages (SMA 5 - SMA 34) based on the midpoints of the bars (hl2). Therefore, by default, the "Green" bars and their opposite "Fade" bars are colored according to the color of the Awesome Oscillator.
According to Bill Williams' Profitunity strategy, using the Awesome Oscillator, the third Elliott wave is determined by the maximum peak of AO in the range from 100 to 140 bars. The presence of divergence between the maximum AO peak and the subsequent lower AO peak in this interval also warns of a possible correction, especially if the AO crosses the zero line between these AO peaks. Therefore, the chart additionally displays the prices of the highest and lowest bars, as well as the maximum or minimum peak of AO in the interval of 140 bars from the last bar. In the indicator settings, you can hide labels, lines, change the number of bars and any parameters for the AO indicator - method (SMA, Smoothed SMA, EMA and others), length, source (open, high, low, close, hl2 and others).
Bullish Divergent bar
🟢 A buy signal (Long) is a Bullish Divergent bar with a green circle displayed above it if such a bar simultaneously meets all of the following conditions:
The high of the bar is below all lines of the Alligator indicator.
The closing price of the bar is above its middle, i.e. close > (high + low) / 2.
The low of the bar is below the low of 2 previous bars or below the low of one previous bar, and the low of the second previous bar is a lower fractal (▼). By default, Divergent bars are not displayed, the low of which is lower than the low of only one previous bar and the low of the 2nd previous bar is not a lower fractal (▼), but you can enable the display of any Divergent bars in the indicator settings (by setting the value "no" in the " field Divergent Bars > Filtration").
The following conditions strengthen the Bullish Divergent bar signal:
The opening price of the bar, as well as the closing price, is higher than its middle, i.e. Open > (high + low) / 2.
The high of the bar is below all lines of the open Alligator indicator, i.e. the green line (Lips) is below the red line (Teeth) and the red line is below the blue line (Jaw). In this case, the color of the circle above the Bullish Divergent bar is dark green.
Squat Divergent bar.
The bar following the Bullish Divergent bar corresponds to the green color of the Awesome Oscillator.
Divergence on Awesome Oscillator.
Formation of the lower fractal (▼), in which the low of the Divergent bar is the peak of the fractal.
Bearish Divergent bar
🔴 A signal to sell (Short) is a Bearish Divergent bar under which a red circle is displayed if such a bar simultaneously meets all the following conditions:
The low of the bar is above all lines of the Alligator indicator.
The closing price of the bar is below its middle, i.e. close < (high + low) / 2.
The high of the bar is higher than the high of 2 previous bars or higher than the high of one previous bar, and the high of the second previous bar is an upper fractal (▲). By default, Divergent bars are not displayed, the high of which is higher than the high of only one previous bar and the high of the 2nd previous bar is not an upper fractal (▲), but you can enable the display of any Divergent bars in the indicator settings (by setting the value "no" in the " field Divergent Bars > Filtration").
The following conditions strengthen the Bearish Divergent bar signal:
The opening price of the bar, as well as the closing price, is below its middle, i.e. open < (high + low) / 2.
The low of the bar is above all lines of the open Alligator indicator, i.e. the green line (Lips) is above the red line (Teeth) and the red line is above the blue line (Jaw). In this case, the color of the circle under the Bearish Divergent bar is dark red.
Squat Divergent bar.
The bar following the Bearish Divergent bar corresponds to the red color of the Awesome Oscillator.
Divergence on Awesome Oscillator.
Formation of the upper fractal (▲), in which the high of the Divergent bar is the peak of the fractal.
Alligator lines crossing
Bars crossing the green line (Lips) of the open Alligator indicator is the first warning of a possible correction (price rollback) if one of the following conditions is met:
If the bar closed below the Lips line, which is above the Teeth line, and the Teeth line is above the Jaw line, while the closing price of the previous bar is above the Lips line.
If the bar closed above the Lips line, which is below the Teeth line, and the Teeth line is below the Jaw line, while the closing price of the previous bar is below the Lips line.
The intersection of all open Alligator lines by bars is a sign of a deep correction and a warning of a possible trend change.
Frequent intersection of Alligator lines with each other is a sign of a sideways trend (flat).
Signal Alerts
To receive notifications about signals when creating an alert, you must select the condition "Any alert() function is call", in which case notifications will arrive in the following format:
D — timeframe, for example: D, 4H, 15m.
🟢 BDB⎾ - a signal for a Bullish Divergent bar to buy (Long), triggers once after the bar closes and includes additional signals:
/// — if Alligator is open.
⏉ — if the opening price of the bar, as well as the closing price, is above its middle.
+ Squat 🔷 - Squat bar or + Green ↑ - "Green" bar or + Fake ↓ - Fake bar.
+ AO 🟩 - if after the Divergent bar closes, the oscillator color change for the next bar corresponds the green color of the Awesome Oscillator. ┴/┬ — AO above/below the zero line. ∇ — if there is divergence on AO in the interval of 140 bars from the last bar.
🔴 BDB⎿ - a signal for a Bearish Divergent bar to sell (Short), triggers once after the bar closes and includes additional signals:
/// — if Alligator is open.
⏊ — if the opening price of the bar, as well as the closing price, is below its middle.
+ Squat 🔷 - Squat bar or + Green ↑ - "Green" bar or + Fake ↓ - Fake bar.
+ AO 🟥 - if after the Divergent bar closes, the oscillator color change for the next bar corresponds to the red color of the Awesome Oscillator. ┴/┬ — AO above/below the zero line. ∇ — if there is divergence on AO in the interval of 140 bars from the last bar.
Alert for bars crossing the green line (Lips) of the open Alligator indicator (can be disabled in the indicator settings in the "Alligator > Enable crossing lips alerts" field):
🔴 Crossing Lips ↓ - if the bar closed below the Lips line, which is above than the other lines, while the closing price of the previous bar is above the Lips line.
🟢 Crossing Lips ↑ - if the bar closed above the Lips line, which is below the other lines, while the closing price of the previous bar is below the Lips line.
The fractal signal is triggered after the second bar closes, completing the formation of the fractal, if alerts about fractals are enabled in the indicator settings (the "Fractals > Enable alerts" field):
🟢 Fractal ▲ - upper (Bearish) fractal.
🔴 Fractal ▼ — lower (Bullish) fractal.
⚪️ Fractal ▲/▼ - both upper and lower fractal.
↳ (H=high - L=low) = difference.
If you redirect notifications to a webhook URL, for example, to a Telegram bot, then you need to set the notification template for the webhook in the indicator settings in the "Webhook > Message" field (contains a tooltip with an example), in which you just need to specify the text {{message}}, which will be automatically replaced with the alert text with a ticker and a link to TradingView.
‼️ A signal is not a call to action, but only a reason to analyze the chart to make a decision based on the rules of your strategy.
***
Индикатор включает в себя Williams Alligator, Williams Fractals, Дивергентные бары, Market Facilitation Index, самый высокий и самый низкий бары, максимальный и минимальный пик Awesome Oscillator, а также оповещения о сигналах на основе стратегии Profitunity Билла Вильямса.
MFI и Awesome Oscillator
В соответствии с осциллятором Market Facilitation Index Приседающий бар окрашен в синий цвет, все остальные бары окрашены в соответствии с цветом Awesome Oscillator, кроме Фальшивых баров, которые окрашены более светлым цветом AO. В настройках индикатора вы можете включить отображение "Зеленых" баров (в поле "Green Bars > Show"). В настройках стиля индикатора вы можете выключить изменение цвета баров в соответствии с цветом AO (в поле "AO bars"), в том числе изменить цвет для Фальшивых баров (в поле "Fake AO bars").
MFI рассчитывается по формуле: (high - low) / volume.
Приседающий бар означает, что по сравнению с предыдущим баром его MFI снизился и в тоже время вырос его объем, т.е. MFI < предыдущего бара и объем > предыдущего бара. Признак возможного разворота цены, поэтому это особенно важный сигнал.
Фальшивый бар является противоположностью Приседающему бару и означает, что по сравнению с предыдущим баром его MFI увеличился и в тоже время снизился его объем, т.е. MFI > предыдущего бара и объем < предыдущего бара.
"Зеленый" бар означает, что по сравнению с предыдущим баром его MFI увеличился и в тоже время вырос его объем, т.е. MFI > предыдущего бара и объем > предыдущего бара. Признак продолжения тренда. Но более значимым подтверждением тренда или предупреждением о возможном развороте является Awesome Oscillator, который измеряет движущую силу рынка путем вычисления разницы между 5 Периодной и 34 Периодной Простыми Скользящими Средними (SMA 5 - SMA 34) по средним точкам баров (hl2). Поэтому по умолчанию "Зеленые" бары и противоположные им "Увядающие" бары окрашены в соответствии с цветом Awesome Oscillator.
По стратегии Profitunity Билла Вильямса с помощью осциллятора Awesome Oscillator определяется третья волна Эллиота по максимальному пику AO в интервале от 100 до 140 баров. Наличие дивергенции между максимальным пиком AO и следующим за ним более низким пиком AO в этом интервале также предупреждает о возможной коррекции, особенно если AO переходит через нулевую линию между этими пиками AO. Поэтому на графике дополнительно отображаются цены самого высокого и самого низкого баров, а также максимальный или минимальный пик АО в интервале 140 баров от последнего бара. В настройках индикатора вы можете скрыть метки, линии, изменить количество баров и любые параметры для индикатора AO – метод (SMA, Smoothed SMA, EMA и другие), длину, источник (open, high, low, close, hl2 и другие).
Бычий Дивергентный бар
🟢 Сигналом на покупку (Long) является Бычий Дивергентный бар над которым отображается зеленый круг, если такой бар соответствует одновременно всем следующим условиям:
Максимум бара ниже всех линий индикатора Alligator.
Цена закрытия бара выше его середины, т.е. close > (high + low) / 2.
Минимум бара ниже минимума 2-х предыдущих баров или ниже минимума одного предыдущего бара, а минимум второго предыдущего бара является нижним фракталом (▼). По умолчанию не отображаются Дивергентные бары, минимум которых ниже минимума только одного предыдущего бара и минимум 2-го предыдущего бара не является нижним фракталом (▼), но вы можете включить отображение любых Дивергентных баров в настройках индикатора (установив значение "no" в поле "Divergent Bars > Filtration").
Усилением сигнала Бычьего Дивергентного бара являются следующие условия:
Цена открытия бара, как и цена закрытия, выше его середины, т.е. Open > (high + low) / 2.
Максимум бара ниже всех линий открытого индикатора Alligator, т.е. зеленая линия (Lips) ниже красной линии (Teeth) и красная линия ниже синей линии (Jaw). В этом случае цвет круга над Бычьим Дивергентным баром окрашен в темно-зеленый цвет.
Приседающий Дивергентный бар.
Бар, следующий за Бычьим Дивергентным баром, соответствует зеленому цвету Awesome Oscillator.
Дивергенция на Awesome Oscillator.
Образование нижнего фрактала (▼), у которого минимум Дивергентного бара является пиком фрактала.
Медвежий Дивергентный бар
🔴 Сигналом на продажу (Short) является Медвежий Дивергентный бар под которым отображается красный круг, если такой бар соответствует одновременно всем следующим условиям:
Минимум бара выше всех линий индикатора Alligator.
Цена закрытия бара ниже его середины, т.е. close < (high + low) / 2.
Максимум бара выше маскимума 2-х предыдущих баров или выше максимума одного предыдущего бара, а максимум второго предыдущего бара является верхним фракталом (▲). По умолчанию не отображаются Дивергентные бары, максимум которых выше максимума только одного предыдущего бара и максимум 2-го предыдущего бара не является верхним фракталом (▲), но вы можете включить отображение любых Дивергентных баров в настройках индикатора (установив значение "no" в поле "Divergent Bars > Filtration").
Усилением сигнала Медвежьего Дивергентного бара являются следующие условия:
Цена открытия бара, как и цена закрытия, ниже его середины, т.е. open < (high + low) / 2.
Минимум бара выше всех линий открытого индикатора Alligator, т.е. зеленая линия (Lips) выше красной линии (Teeth) и красная линия выше синей линии (Jaw). В этом случае цвет круга под Медвежьим Дивергентным Баром окрашен в темно-красный цвет.
Приседающий Дивергентный бар.
Бар, следующий за Медвежьим Дивергентным баром, соответствует красному цвету Awesome Oscillator.
Дивергенция на Awesome Oscillator.
Образование верхнего фрактала (▲), у которого максимум Дивергентного бара является пиком фрактала.
Пересечение линий Alligator
Пересечение барами зеленой линии (Lips) открытого индикатора Alligator является первым предупреждением о возможной коррекции (откате цены) при выполнении одного из следующих условий:
Если бар закрылся ниже линии Lips, которая выше линии Teeth, а линия Teeth выше линии Jaw, при этом цена закрытия предыдущего бара находится выше линии Lips.
Если бар закрылся выше линии Lips, которая ниже линии Teeth, а линия Teeth ниже линии Jaw, при этом цена закрытия предыдущего бара находится ниже линии Lips.
Пересечение барами всех линий открытого Alligator является признаком глубокой коррекции и предупреждением о возможной смене тренда.
Частое пересечение линий Alligator между собой является признаком бокового тренда (флэт).
Оповещения о сигналах
Для получения уведомлений о сигналах при создании оповещения необходимо выбрать условие "При любом вызове функции alert()", в таком случае уведомления будут приходить в следующем формате:
D — таймфрейм, например: D, 4H, 15m.
🟢 BDB⎾ — сигнал Бычьего Дивергентного бара на покупку (Long), срабатывает один раз после закрытия бара и включает дополнительные сигналы:
/// — если Alligator открыт.
⏉ — если цена открытия бара, как и цена закрытия, выше его середины.
+ Squat 🔷 — Приседающий бар или + Green ↑ — "Зеленый" бар или + Fake ↓ — Фальшивый бар.
+ AO 🟩 — если после закрытия Дивергентного бара, изменение цвета осциллятора для следующего бара соответствует зеленому цвету Awesome Oscillator. ┴/┬ — AO выше/ниже нулевой линии. ∇ — если есть дивергенция на AO в интервале 140 баров от последнего бара.
🔴 BDB⎿ — сигнал Медвежьего Дивергентного бара на продажу (Short), срабатывает один раз после закрытия бара и включает дополнительные сигналы:
/// — если Alligator открыт.
⏊ — если цена открытия бара, как и цена закрытия, ниже его середины.
+ Squat 🔷 — Приседающий бар или + Green ↑ — "Зеленый" бар или + Fake ↓ — Фальшивый бар.
+ AO 🟥 — если после закрытия Дивергентного бара, изменение цвета осциллятора для следующего бара соответствует красному цвету Awesome Oscillator. ┴/┬ — AO выше/ниже нулевой линии. ∇ — если есть дивергенция на AO в интервале 140 баров от последнего бара.
Сигнал пересечения барами зеленой линии (Lips) открытого индикатора Alligator (можно отключить в настройках индикатора в поле "Alligator > Enable crossing lips alerts"):
🔴 Crossing Lips ↓ — если бар закрылся ниже линии Lips, которая выше остальных линий, при этом цена закрытия предыдущего бара находится выше линии Lips.
🟢 Crossing Lips ↑ — если бар закрылся выше линии Lips, которая ниже остальных линий, при этом цена закрытия предыдущего бара находится ниже линии Lips.
Сигнал фрактала срабатывает после закрытия второго бара, завершающего формирование фрактала, если оповещения о фракталах включены в настройках индикатора (поле "Fractals > Enable alerts"):
🟢 Fractal ▲ — верхний (Медвежий) фрактал.
🔴 Fractal ▼ — нижний (Бычий) фрактал.
⚪️ Fractal ▲/▼ — одновременно верхний и нижний фрактал.
↳ (H=high - L=low) = разница.
Если вы перенаправляете оповещения на URL вебхука, например, в бота Telegram, то вам необходимо установить шаблон оповещения для вебхука в настройках индикатора в поле "Webhook > Message" (содержит подсказку с примером), в котором в качестве текста сообщения достаточно указать текст {{message}}, который будет автоматически заменен на текст оповещения с тикером и ссылкой на TradingView.
‼️ Сигнал — это не призыв к действию, а лишь повод проанализировать график для принятия решения на основе правил вашей стратегии.
Price Action Toolkit | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Price Action Toolkit indicator! Price Action Toolkit integrates key level strategy , traditional supply-demand analysis , and market structures to help traders in their decisions. Now with features that are available to use in multiple timeframes!
Features of the new Price Action Toolkit indicator :
Volumized Fair Value Gaps (FVGs)
Volumized Order & Breaker Blocks
Identification of Market Structures
Equal Highs & Lows
Buyside & Sellside Liquidity
Premium & Discount Zones
MTF Highs & Lows (Daily, Weekly, Monthly, Pre-Market)
Customizable Settings
📌 HOW DOES IT WORK ?
We believe that the analytical elements that are within this indicator work best when they co-exist with each other on the chart. Trading often requires taking multiple elements into consideration for better accuracy on market analysis. Thus, we combined some of the useful strategies in one indicator for ease of use.
1. Volumized Fair Value Gaps
Fair value gaps often occur when there is an imbalance in the market, and can be spotted with a specific formation on the chart.
The volume when the FVG occurs plays an important role when determining the strength of it, so we've placed two bars on the FVG zone, indicating the high & low volumes of the FVG. The high volume is the total volume of the last two bars on a bullish FVG, while the low volume is - of the FVG. For a bearish FVG, the total volume of the last two bars is the low volume. The indicator can also detect FVGs that exist in other timeframes than the current chart.
2. Volumized Order Blocks
Order blocks occur when there is a high amount of market orders exist on a price range. It is possible to find order blocks using specific formations on the chart.
The high & low volume of order blocks should be taken into consideration while determining their strengths. The determination of the high & low volume of order blocks are similar to FVGs, in a bullish order block, the high volume is the last 2 bars' total volume, while the low volume is the oldest bar's volume. In a bearish order block scenerio, the low volume becomes the last 2 bars' total volume.
3. Volumized Breaker Blocks
Breaker blocks form when an order block fails, or "breaks". It is often associated with market going in the opposite direction of the broken order block, and they can be spotted by following order blocks and finding the point they get broken, ie. price goes below a bullish order block.
The volume of a breaker block is simply the total volume of the bar that the original order block is broken. Often the higher the breaking bar's volume, the stronger the breaker block is.
4. Market Structures
Sometimes specific market structures form and break as the market fills buy & sell orders. Formed Change of Character (CHoCH) and Break of Structure (BOS) often mean that market will change direction, and they can be spotted by inspecting low & high pivot points of the chart.
5. Equal Highs & Lows
Equal Highs & Lows occur when there is a significant amount of difference between a candle's close price and it's high / low value, and it happens again in a specific range. EQH and EQL usually mean there is a resistance that blocks the price from going further up / down.
6. Buyside & Sellside Liquidity
Buyside & Sellside Liquidity zones are where most traders place their take-profits and stop-losses in their long / short positions. They are spotted by using high & low pivot points on the chart.
7. Premium & Discount Zones
The premium zone is a zone that is over the fair value of the asset's price, and the discount zone is the opposite. They are formed by the latest high & low pivot points.
8. MTF Highs / Lows
MTF Highs / Lows are actually pretty self-explanatory, you can enable / disable Daily, Weekly, Monthly & Pre-Market Highs and Lows.
🚩UNIQUENESS
Our new indicator offers a comprehensive toolkit for traders, combining multiple analytical elements with customizable settings to aid in decision-making across different market conditions and timeframes. The volumetric information of both FVGs and Order & Breaker Blocks will be present in your chart to serve you greater detail about them. The indicator also efficiently identifies market structures, liquidity zones and premium & discount zones to give you an insight about the current state of the market. And finally with the use of multiple timeframes , you can easily take a look at the bigger picture. We recommend reading the "How Does It Work" section of the descripton to get a better understanding about how this indicator is unique to others.
⚙️SETTINGS
1. General Configuration
Show Historic Zones -> This will show historic Fair Value Gaps, Order & Breaker Blocks and Sellside & Buyside liquidities which are expired.
2. Fair Value Gaps
Enabled -> Enables / Disables Fair Value Gaps
Volumetric Info -> The volumetric information of the FVG Zones will be rendered if activated.
Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
3. Order Blocks
Enabled -> Enables / Disables Order Blocks
Volumetric Info -> The volumetric information of the Order Blocks will be rendered if activated.
Zone Invalidation -> Select between Wick & Close price for Order Block Invalidation.
Swing Length -> Swing length is used when finding order block formations. Smaller values will result in finding smaller order blocks.
4. Breaker Blocks
Enabled -> Enables / Disables Breaker Blocks
Volumetric Info -> The volumetric information of the Breaker Blocks will be rendered if activated.
Zone Invalidation -> Select between Wick & Close price for Breaker Block Invalidation.
5. Timeframes
You can set and enable / disable up to 3 timeframes. Note that only higher timeframes than the current chart will work.
6. Market Structures
Break Of Structure ( BOS ) -> If the current structure of the market is broken in a bullish or bearish direction, it will be displayed.
Change Of Character ( CHoCH ) -> If the market shifts into another direction, it will be displayed.
Change Of Character+ ( CHoCH+ ) -> This will display stronger Change Of Characters if enabled.
7. Equal Highs & Lows
EQH -> Enables / Disables Equal Highs.
EQL -> Enables / Disables Equal Lows.
ATR Multiplier (0.1 - 1.0) -> Determines the maximum difference between highs / lows to be considered as equal. Lower values will result in more accurate results.
8. Buyside & Sellside Liquidity
Zone Width -> Determines the width of the liquidity zones, 1 = 0.025%, 2 = 0.05%, 3 = 0.1%.
9. Premium & Discount Zones
Enabled -> Enables / Disables Premium & Discount Zones.
10. MTF Highs / Lows
You can enable / disable Daily, Weekly, Monthly & Pre-Market Highs and Lows using this setting. You can also switch their line shapes between solid, dashed and dotted.
YD_Divergence_RSI+CMFThe ‘YD_Divergence_RSI+CMF’ indicator can find divergence using RSI (Relative Strength Index) and CMF (Chaikin Money Flow) indicators.
📌 Key functions
1. Search pivot high and pivot low points in a certain length of price.
2. Connect pivot high to pivot high , pivot low to pivot low , forming two standards for divergence in result.
The marker then plots only the higher high, lower low lines.
(higher low and lower high in prices are referred to hidden divergence, which are not considered in this indicator)
3. Compare the two standards with RSI and CMF indicators, send an alert if there is a divergence. As a result, the indicator will find four combination of divergence.
A. Higher high price / Lower RSI (Bearish RSI Divergence)
B. Lower low price / Higher RSI (Bullish RSI Divergence)
C. Higher high price / Lower CMF (Bearish CMF Divergence)
D. Lower low price / Higher CMF (Bullish CMF Divergence)
📌 Details
Developing the indicators, we put a lot of effort in making a customizable and user-friendly interface.
#1. Pivot Setting
Users can set the length to find the pivot high / pivot low in ‘Pivot Settings – Pivot Length.’
Increased pivot Length takes more candles to interpret the chart but reduce false signals since the it uses only the most certain pivot high / pivot low values. Obviously, decreased pivot length will act the opposite.
Users can choose whether to use ‘High/Low’ or ‘Close’ in ‘Pivot Reference’ to set the swing point of prices.
Users can also choose whether to display the pivot high / pivot low marker on the chart.
#2 RSI & CMF Settings
Users can adjust the length of RSI & CMF separately. (The default values are set to 14 and 20 each.)
#3 Label Setting
Users can adjust the text displayed on the chart label. (The default values is set to ‘Bullish / Bearish’, ‘RSI/CMF’, ‘Divergence’.)
Users can reduce the length of text label or simply turn the label off. Just click the ‘Bull/Bear’ or ‘None’ button. ‘Divergence’ works the same.
Users can decide whether to display the ‘Divergence Line and Label’, set custom settings for the label and line. (color, thickness, style, etc)
📌 Alert
Alert are provided as a combination of the chart's symbol and the set label text. For example,
‘BINANCE:BTCUSDT.P, Bullish RSI Divergence’
====================================================
"YD_Divergence_RSI+CMF" 지표 는 RSI와 CMF 지표를 이용해서 Divergence 를 찾아낼 수 있습니다.
📌 주요 기능
1. 정해진 가격 움직임 안에서 pivot high와 pivot low 포인트 를 찾아냅니다.
2. Pivot high로만 이어진 라인과, Pivot low로만 이어진 두 라인을 작도한 뒤 divergence의 기준으로 삼습니다.
이 지표에서는 normal divergence만 사용하기 때문에 차트에 higher high와 lower low만 표기 합니다.
(higher low와 lower high는 hidden divergence로 정의되며, 이 지표에서는 다루지 않습니다.
3. 두 기준선과 RSI, CMF 지표를 각각 비교하고, 결과적으로 4개의 조합을 구할 수 있습니다.
A. Higher high price / Lower RSI (Bearish RSI Divergence)
B. Lower low price / Higher RSI (Bullish RSI Divergence)
C. Higher high price / Lower CMF (Bearish CMF Divergence)
D. Lower low price / Higher CMF (Bullish CMF Divergence)
📌 세부 사항
지표를 개발하며 사용자들이 원하는 방향으로 지표를 설정할 수 있게 작업에 많은 공을 들였습니다. 굉장히 다양한 옵션을 선택할 수 있으며, 원하는 방식으로 지표를 사용할 수 있습니다.
#1 Pivot Setting
Pivot setting에서는 Pivot Length를 변경할 수 있습니다.
Pivot Length를 늘릴 경우, 보다 확실한 Swing High와 Swing Low만을 사용하게 되므로, False signal이 줄어들 수 있습니다. 하지만 Swing High/ Low를 판정하는 데에 더 긴 시간이 걸리게 되므로, Signal이 다소 늦게 발생하는 단점이 생기게 됩니다.
Pivot Length를 줄일 경우, 반대로 Swing High/Low의 판정이 더 빨리 일어나기 때문에, Signal을 거래에 이용하기는 좋을 수 있습니다. 다만, Swing High와 Low가 훨씬 더 잦은 빈도로 발생하기 때문에 False Signal을 줄 가능성이 높아집니다.
Pivot Reference에서는 가격의 Swing Point를 설정함에 있어, High/Low(고가/저가)를 이용할 지 Close (종가)를 이용할 지 선택할 수 있습니다.
Pivot High/Low Marker를 선택할 경우 Pivot High/ Low에 Marker가 찍히게 됩니다.
#2 RSI와 CMF Setting
RSI와 CMF Setting에서는 RSI와 CMF의 길이를 각각 설정할 수 있습니다. 기본값은 14와 20으로 설정되어 있습니다.
#3 Label Setting
Label Setting에서는 Label에 표시되는 글자를 선택할 수 있습니다.
기본값은 "Bullish / Bearish", "RSI/CMF", "Divergence"로 선택되어 있으며, 너무 길다고 느껴질 경우 "Bull/Bear" 혹은 "None"을 클릭하여 길이를 줄일 수 있습니다. 마찬가지로 Divergence의 경우도 생략이 가능합니다.
하단에서는 Divergence Line과 Label을 켜고 끌 수 있으며, 선의 색깔, 굵기, 종류, 그리고 Label의 색깔, 크기, 종류를 선택할 수 있습니다. Label의 Text 색 역시 변경이 가능합니다.
📌 얼러트
얼러트는 자신이 설정한 차트의 심볼과 Label의 문구의 조합으로 제공되며 예를 들면 다음과 같습니다.
"BINANCE:BTCUSDT.P, Bullish RSI Divergence"
HL ATRUnlocking Market Volatility: The Adaptive Highest High Lowest Low Indicator
As seasoned traders know, accurately identifying and leveraging market highs and lows can significantly impact your trading performance. One innovative tool for harnessing these inflection points is the Adaptive Highest High Lowest Low Indicator. Built for intuitive trading, this indicator offers a distinctive edge in identifying key trading signals in volatile markets.
1. Understanding the Indicator
At its core, the Adaptive Highest High Lowest Low Indicator operates by pinpointing the highest highs and lowest lows within a specified lookback period. What sets it apart is its ability to adapt and respond to market volatility, enhancing its utility in various market conditions.
Key parameters include the lookback period, the number of confirmation candles, the number of previous high/low lines to display, and the Average True Range (ATR) period. Each of these inputs offers the trader flexibility to fine-tune the indicator to suit their specific trading style and the prevailing market conditions.
2. Harnessing the Power of Highs and Lows
The indicator begins by charting the highest high and the lowest low within your chosen lookback period. These highs and lows are treated as levels of resistance and support, respectively. Once identified, lines are drawn at these points, offering visual cues for strategic trading.
However, the indicator doesn't stop at identifying these levels. It waits for the price to confirm these levels, using a user-defined number of 'Confirmation Candles'. This ensures that the highs and lows are robust and significant, thereby minimizing the risk of false breakouts or breakdowns.
3. Volatility Filter: The ATR
The incorporation of the ATR into this indicator is a key distinguishing feature. The ATR measures market volatility by calculating the range of price movements over a given period. By incorporating the ATR, this indicator can adapt to changes in volatility. Specifically, the ATR acts as a filter for the buy and sell signals, helping to avoid false signals during low volatility periods and highlight meaningful breaks during high volatility periods.
4. Deciphering Buy and Sell Signals
The Adaptive Highest High Lowest Low Indicator offers clear signals for potential entry points. A 'Buy' label appears when the price breaks and closes above a previously identified high by an amount greater than the ATR. Conversely, a 'Sell' label is generated when the price breaks and closes below a previously identified low by an amount greater than the ATR.
5. Where Does This Indicator Shine?
This indicator thrives in markets characterized by high volatility. The ATR component allows the tool to adjust itself to changing market conditions, enhancing its effectiveness in volatile markets. It suits various financial markets, including stocks, forex, commodities, and cryptocurrencies, among others.
However, it's crucial to remember that this tool should not be used in isolation. It's most effective when used in conjunction with other indicators and within the context of a well-planned trading strategy. Always remember to use good risk management and adjust the settings of the indicator as per changing market conditions.
In conclusion, the Adaptive Highest High Lowest Low Indicator is a versatile and powerful tool for traders seeking to capitalize on market volatility. By combining the power of highs, lows, and the ATR, this indicator offers an innovative approach to navigating the financial markets.
Basic steps of how you could use this indicator for trading.
Identify Highs and Lows: The indicator draws lines at the highest high and lowest low of a given lookback period. Use these lines to identify key levels of support (lows) and resistance (highs).
Confirm the Trend: Wait for the price to confirm these levels. This is done by the number of 'Confirmation Candles'. For example, if 'Confirmation Candles' is set to 7, then a high or low is confirmed if the price has not broken that level in the past 7 candles.
Use the ATR as a Filter: The Average True Range (ATR) is used as a volatility filter. It can help to filter out signals that occur during low volatility periods, which might be false breakouts or breakdowns.
Entry Points: Entry points are determined by the labels "Buy" and "Sell" that appear on the chart.
Buy Signal: When a 'Buy' label appears, this indicates the price has broken above a previously identified high and closed above it by an amount greater than the ATR. This could be considered a bullish signal and a potential point to enter a long position.
Sell Signal: When a 'Sell' label appears, this indicates the price has broken below a previously identified low and closed below it by an amount greater than the ATR. This could be considered a bearish signal and a potential point to enter a short position.
Exit Points: The indicator does not provide specific exit points. These would need to be based on your risk tolerance, trading strategy, and other factors. You might consider exiting a position when the price reaches a new high/low, when a contrary signal appears, or when the price breaks a certain level of support or resistance.
Risk Management: It's important to set stop-loss levels and take-profit levels for each trade. This could be based on a fixed percentage, the ATR, or the highs and lows identified by the indicator.
Periodically Adjust Settings: Depending on market conditions, you might need to adjust the settings of the indicator, like the lookback period, confirmation candles, and ATR period.
Remember, this indicator should not be used in isolation. It's best to use it in combination with other tools and techniques, and always in the context of a well-planned trading strategy. It's also important to backtest any strategy before using it in live trading.
GKD-M Baseline Optimizer [Loxx]Giga Kaleidoscope GKD-M Baseline Optimizer is a Metamorphosis module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
The Baseline Optimizer enables traders to backtest over 60 moving averages using variable period inputs. It then exports the baseline with the highest cumulative win rate per candle to any baseline-enabled GKD backtest. To perform the backtesting, the trader selects an initial period input (default is 60) and a skip value that increments the initial period input up to seven times. For instance, if a skip value of 5 is chosen, the Baseline Optimizer will run the backtest for the selected moving average on periods such as 60, 65, 70, 75, and so on, up to 90. If the user selects an initial period input of 45 and a skip value of 2, the Baseline Optimizer will conduct backtests for the chosen moving average on periods like 45, 47, 49, 51, and so forth, up to 57.
The Baseline Optimizer provides a table displaying the output of the backtests for a specified date range. The table output represents the cumulative win rate for the given date range.
On the Metamorphosis side of the Baseline Optimizer, a cumulative backtest is calculated for each candle within the date range. This means that each candle may exhibit a different distribution of period inputs with the highest win rate for a particular moving average. The Baseline Optimizer identifies the period input combination with the highest win rates for long and short positions and creates a win-rate adaptive long and short moving average chart. The moving average used for shorts differs from the moving average used for longs, and the moving average for each candle may vary from any other candle. This customized baseline can then be exported to all baseline-enabled GKD backtests.
The backtest employed in the Baseline Optimizer is a Solo Confirmation Simple, allowing only one take profit and one stop loss to be set.
Lastly, the Baseline Optimizer incorporates Goldie Locks Zone filtering, which can be utilized for signal generation in advanced GKD backtests.
█ Moving Averages included in the Baseline Optimizer
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE /2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Kaufman Adaptive Moving Average - KAMA
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
One More Moving Average - OMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Regularized EMA - REMA
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Simple Decycler - SDEC
Simple Jurik Moving Average - SJMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Adaptive Moving Average - AMA
The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile.
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA .
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Deviation Scaled Moving Average - DSMA
The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes.
Donchian
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required.
Double Smoothed FEMA - DSFEMA
Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation.
Double Smoothed Range Weighted EMA - DSRWEMA
Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing.
Double Smoothed Wilders EMA - DSWEMA
Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values.
Double Weighted Moving Average - DWMA
Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA .
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Generalized DEMA - GDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable.
Generalized Double DEMA - GDDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Hull Moving Average (Type 1) - HMA1
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing.
Hull Moving Average (Type 2) - HMA2
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing.
Hull Moving Average (Type 3) - HMA3
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing.
Hull Moving Average (Type 4) - HMA4
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing.
IE /2 - Early T3 by Tim Tilson and T3 new
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Kaufman Adaptive Moving Average - KAMA
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA ( Least Squares Moving Average )
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non-lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Ocean NMA Moving Average - ONMAMA
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction"
One More Moving Average (OMA)
The One More Moving Average (OMA) is a technical indicator that calculates a series of Jurik-style moving averages in order to reduce noise and provide smoother price data. It uses six exponential moving averages to generate the final value, with the length of the moving averages determined by an adaptive algorithm that adjusts to the current market conditions. The algorithm calculates the average period by comparing the signal to noise ratio and using this value to determine the length of the moving averages. The resulting values are used to generate the final value of the OMA, which can be used to identify trends and potential changes in trend direction.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Probability Density Function Moving Average - PDFMA
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters.
Quadratic Regression Moving Average - QRMA
A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008.
Regularized EMA - REMA
The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag.
Range Weighted EMA - RWEMA
This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone".
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price.
Simple Decycler - SDEC
The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments.
Simple Loxx Moving Average - SLMA
A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA .
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed LWMA - SLWMA
A smoothed version of the LWMA
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three-pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three-pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two-pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two-pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers .
Variable Index Dynamic Average - VIDYA
Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging.
Variable Moving Average - VMA
The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility.
Volume Weighted EMA - VEMA
An EMA that uses a volume and price weighted calculation instead of the standard price input.
Volume Weighted Moving Average - VWMA
A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted.
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero-Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
█ Volatility Goldie Locks Zone
The Goldie Locks Zone volatility filter is the standard first-pass filter used in all advanced GKD backtests (Complex, Super Complex, and Full GKd). This filter requires the price to fall within a range determined by multiples of volatility. The Goldie Locks Zone is separate from the core Baseline and utilizes its own moving average with Loxx's Exotic Source Types you can read about below.
On the chart, you will find green and red dots positioned at the top, indicating whether a candle qualifies for a long or short trade respectively. Additionally, green and red triangles are located at the bottom of the chart, signifying whether the trigger has crossed up or down and qualifies within the Goldie Locks zone. The Goldie Locks zone is represented by a white color on the mean line, indicating low volatility levels that are not suitable for trading.
█ Volatility Types Included in the Baseline Optimizer
The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. Users can also adjust the multiplier values in the settings.
This module includes 17 types of volatility:
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Various volatility estimators and indicators that investors and traders can use to measure the dispersion or volatility of a financial instrument's price. Each estimator has its strengths and weaknesses, and the choice of estimator should depend on the specific needs and circumstances of the user.
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
For this indicator, a manual recreation of the quantile function in Pine Script is used. This is so users have a full inside view into how this is calculated.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
█ Loxx's Expanded Source Types Included in Baseline Optimizer
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
-Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
-Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
-Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
-Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
-Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Full GKD Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Kase Peak Oscillator
Confirmation 2: uf2018
Continuation: Vortex
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer as shown on the chart above
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Basline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
█ Connecting to Backtests
All GKD indicators are chained indicators meaning you export the value of the indicators to specialized backtest to creat your GKD trading system. Each indicator contains a proprietary signal generation algo that will only work with GKD backtests. You can find these backtests using the links below.
GKD-BT Giga Confirmation Stack Backtest:
GKD-BT Giga Stacks Backtest:
GKD-BT Full Giga Kaleidoscope Backtest:
GKD-BT Solo Confirmation Super Complex Backtest:
GKD-BT Solo Confirmation Complex Backtest:
GKD-BT Solo Confirmation Simple Backtest:
Market Structure & Liquidity: CHoCHs+Nested Pivots+FVGs+Sweeps//Purpose:
This indicator combines several tools to help traders track and interpret price action/market structure; It can be divided into 4 parts;
1. CHoCHs, 2. Nested Pivot highs & lows, 3. Grade sweeps, 4. FVGs.
This gives the trader a toolkit for determining market structure and shifts in market structure to help determine a bull or bear bias, whether it be short-term, med-term or long-term.
This indicator also helps traders in determining liquidity targets: wether they be voids/gaps (FVGS) or old highs/lows+ typical sweep distances.
Finally, the incorporation of HTF CHoCH levels printing on your LTF chart helps keep the bigger picture in mind and tells traders at a glance if they're above of below Custom HTF CHoCH up or CHoCH down (these HTF CHoCHs can be anything from Hourly up to Monthly).
//Nomenclature:
CHoCH = Change of Character
STH/STL = short-term high or low
MTH/MTL = medium-term high or low
LTH/LTL = long-term high or low
FVG = Fair value gap
CE = consequent encroachement (the midline of a FVG)
~~~ The Four components of this indicator ~~~
1. CHoCHs:
•Best demonstrated in the below charts. This was a method taught to me by @Icecold_crypto. Once a 3 bar fractal pivot gets broken, we count backwards the consecutive higher lows or lower highs, then identify the CHoCH as the opposite end of the candle which ended the consecutive backwards count. This CHoCH (UP or DOWN) then becomes a level to watch, if price passes through it in earnest a trader would consider shifting their bias as market structure is deemed to have shifted.
•HTF CHoCHs: Option to print Higher time frame chochs (default on) of user input HTF. This prints only the last UP choch and only the last DOWN choch from the input HTF. Solid line by default so as to distinguish from local/chart-time CHoCHs. Can be any Higher timeframe you like.
•Show on table: toggle on show table(above/below) option to show in table cells (top right): is price above the latest HTF UP choch, or is price below HTF DOWN choch (or is it sat between the two, in a state of 'uncertainty').
•Most recent CHoCHs which have not been met by price will extend 10 bars into the future.
• USER INPUTS: overall setting: SHOW CHOCHS | Set bars lookback number to limit historical Chochs. Set Live CHoCHs number to control the number of active recent chochs unmet by price. Toggle shrink chochs once hit to declutter chart and minimize old chochs to their origin bars. Set Multi-timeframe color override : to make Color choices auto-set to your preference color for each of 1m, 5m, 15m, H, 4H, D, W, M (where up and down are same color, but 'up' icon for up chochs and down icon for down chochs remain printing as normal)
2. Nested Pivot Highs & Lows; aka 'Pivot Highs & Lows (ST/MT/LT)'
•Based on a seperate, longer lookback/lookforward pivot calculation. Identifies Pivot highs and lows with a 'spikeyness' filter (filtering out weak/rounded/unimpressive Pivot highs/lows)
•by 'nested' I mean that the pivot highs are graded based on whether a pivot high sits between two lower pivot highs or vice versa.
--for example: STH = normal pivot. MTH is pivot high with a lower STH on either side. LTH is a pivot high with a lower MTH on either side. Same applies to pivot lows (STL/MTL/LTL)
•This is a useful way to measure the significance of a high or low. Both in terms of how much it might be typically swept by (see later) and what it would imply for HTF bias were we to break through it in earnest (more than just a sweep).
• USER INPUTS: overall setting: show pivot highs & lows | Bars lookback (historical pivots to show) | Pivots: lookback/lookforward length (determines the scale of your pivot highs/lows) | toggle on/off Apply 'Spikeyness' filter (filters out smooth/unimpressive pivot highs/lows). Set Spikeyness index (determines the strength of this filter if turned on) | Individually toggle on each of STH, MTH, LTH, STL, MTL, LTL along with their label text type , and size . Toggle on/off line for each of these Pivot highs/lows. | Set label spacer (atr multiples above / below) | set line style and line width
3. Grade Sweeps:
•These are directly related to the nested pivots described above. Most assets will have a typical sweep distance. I've added some of my expected sweeps for various assets in the indicator tooltips.
--i.e. Eur/Usd 10-20-30 pips is a typical 'grade' sweep. S&P HKEX:5 - HKEX:10 is a typical grade sweep.
•Each of the ST/MT/LT pivot highs and lows have optional user defined grade sweep boxes which paint above until filled (or user option for historical filled boxes to remain).
•Numbers entered into sweep input boxes are auto converted into appropriate units (i.e. pips for FX, $ or 'handles' for indices, $ for Crypto. Very low $ units can be input for low unit value crypto altcoins.
• USER INPUTS: overall setting: Show sweep boxes | individually select colors of each of STH, MTH, LTH, STL, MTL, LTL sweep boxes. | Set Grade sweep ($/pips) number for each of ST, MT, LT. This auto converts between pips and $ (i.e. FX vs Indices/Crypto). Can be a float as small or large as you like ($0.000001 to HKEX:1000 ). | Set box text position (horizontal & vertical) and size , and color . | Set Box width (bars) (for non extended/ non-auto-terminating at price boxes). | toggle on/off Extend boxes/lines right . | Toggle on/off Shrink Grade sweeps on fill (they will disappear in realtime when filled/passed through)
4. FVGs:
•Fair Value gaps. Represent 'naked' candle bodies where the wicks to either side do not meet, forming a 'gap' of sorts which has a tendency to fill, or at least to fill to midline (CE).
•These are ICT concepts. 'UP' FVGS are known as BISIs (Buyside imbalance, sellside inefficiency); 'DOWN' FVGs are known as SIBIs (Sellside imbalance, buyside inefficiency).
• USER INPUTS: overall setting: show FVGs | Bars lookback (history). | Choose to display: 'UP' FVGs (BISI) and/or 'DOWN FVGs (SIBI) . Choose to display the midline: CE , the color and the line style . Choose threshold: use CE (as opposed to Full Fill) |toggle on/off Shrink FVG on fill (CE hit or Full fill) (declutter chart/see backtesting history)
////••Alerts (general notes & cautionary notes)::
•Alerts are optional for most of the levels printed by this indicator. Set them via the three dots on indicator status line.
•Due to dynamic repainting of levels, alerts should be used with caution. Best use these alerts either for Higher time frame levels, or when closely monitoring price.
--E.g. You may set an alert for down-fill of the latest FVG below; but price will keep marching up; form a newer/higher FVG, and the alert will trigger on THAT FVG being down-filled (not the original)
•Available Alerts:
-FVG(BISI) cross above threshold(CE or full-fill; user choice). Same with FVG(SIBI).
-HTF last CHoCH down, cross below | HTF last CHoCH up, cross above.
-last CHoCH down, cross below | last CHoCH up, cross above.
-LTH cross above, MTH cross above, STH cross above | LTL cross below, MTL cross below, STL cross below.
////••Formatting (general)::
•all table text color is set from the 'Pivot highs & Lows (ST, MT, LT)' section (for those of you who prefer black backgrounds).
•User choice of Line-style, line color, line width. Same with Boxes. Icon choice for chochs. Char or label text choices for ST/MT/LT pivot highs & lows.
////••User Inputs (general):
•Each of the 4 components of this indicator can be easily toggled on/off independently.
•Quite a lot of options and toggle boxes, as described in full above. Please take your time and read through all the tooltips (hover over '!' icon) to get an idea of formatting options.
•Several Lookback periods defined in bars to control how much history is shown for each of the 4 components of this indicator.
•'Shrink on fill' settings on FVGs and CHoCHs: Basically a way to declutter chart; toggle on/off depending on if you're backtesting or reading live price action.
•Table Display: applies to ST/MT/LT pivot highs and to HTF CHoCHs; Toggle table on or off (in part or in full)
////••Credits:
•Credit to ICT (Inner Circle Trader) for some of the concepts used in this indicator (FVGS & CEs; Grade sweeps).
•Credit to @Icecold_crypto for the specific and novel concept of identifying CHoCHs in a simple, objective and effective manner (as demonstrated in the 1st chart below).
CHoCH demo page 1: shifting tweak; arrow diagrams to demonstrate how CHoCHs are defined:
CHoCH demo page 2: Simplified view; short lookback history; few CHoCHs, demo of 'latest' choch being extended into the future by 10 bars:
USAGE: Bitcoin Hourly using HTF daily CHoCHs:
USAGE-2: Cotton Futures (CT1!) 2hr. Painting a rather bullish picture. Above HTF UP CHoCH, Local CHoCHs show bullish order flow, Nice targets above (MTH/LTH + grade sweeps):
Full Demo; 5min chart; CHoCHs, Short term pivot highs/lows, grade sweeps, FVGs:
Full Demo, Eur/Usd 15m: STH, MTH, LTH grade sweeps, CHoCHs, Usage for finding bias (part A):
Full Demo, Eur/Usd 15m: STH, MTH, LTH grade sweeps, CHoCHs, Usage for finding bias, 3hrs later (part B):
Realtime Vs Backtesting(A): btc/usd 15m; FVGs and CHoCHs: shrink on fill, once filled they repaint discreetly on their origin bar only. Realtime (Shrink on fill, declutter chart):
Realtime Vs Backtesting(B): btc/usd 15m; FVGs and CHoCHs: DON'T shrink on fill; they extend to the point where price crosses them, and fix/paint there. Backtesting (seeing historical behaviour):
Parallel Projections [theEccentricTrader]█ OVERVIEW
This indicator automatically projects parallel trendlines or channels, from a single point of origin. In the example above I have applied the indicator twice to the 1D SPXUSD. The five upper lines (green) are projected at an angle of -5 from the 1-month swing high anchor point with a projection ratio of -72. And the seven lower lines (blue) are projected at an angle of 10 with a projection ratio of 36 from the 1-week swing low anchor point.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Support and Resistance
• Support refers to a price level where the demand for an asset is strong enough to prevent the price from falling further.
• Resistance refers to a price level where the supply of an asset is strong enough to prevent the price from rising further.
Support and resistance levels are important because they can help traders identify where the price of an asset might pause or reverse its direction, offering potential entry and exit points. For example, a trader might look to buy an asset when it approaches a support level , with the expectation that the price will bounce back up. Alternatively, a trader might look to sell an asset when it approaches a resistance level , with the expectation that the price will drop back down.
It's important to note that support and resistance levels are not always relevant, and the price of an asset can also break through these levels and continue moving in the same direction.
Trendlines
Trendlines are straight lines that are drawn between two or more points on a price chart. These lines are used as dynamic support and resistance levels for making strategic decisions and predictions about future price movements. For example traders will look for price movements along, and reactions to, trendlines in the form of rejections or breakouts/downs.
█ FEATURES
Inputs
• Anchor Point Type
• Swing High/Low Occurrence
• HTF Resolution
• Highest High/Lowest Low Lookback
• Angle Degree
• Projection Ratio
• Number Lines
• Line Color
Anchor Point Types
• Swing High
• Swing Low
• Swing High (HTF)
• Swing Low (HTF)
• Highest High
• Lowest Low
• Intraday Highest High (intraday charts only)
• Intraday Lowest Low (intraday charts only)
Swing High/Swing Low Occurrence
This input is used to determine which historic peak or trough to reference for swing high or swing low anchor point types.
HTF Resolution
This input is used to determine which higher timeframe to reference for swing high (HTF) or swing low (HTF) anchor point types.
Highest High/Lowest Low Lookback
This input is used to determine the lookback length for highest high or lowest low anchor point types.
Intraday Highest High/Lowest Low Lookback
When using intraday highest high or lowest low anchor point types, the lookback length is calculated automatically based on number of bars since the daily candle opened.
Angle Degree
This input is used to determine the angle of the trendlines. The output is expressed in terms of point or pips, depending on the symbol type, which is then passed through the built in math.todegrees() function. Positive numbers will project the lines upwards while negative numbers will project the lines downwards. Depending on the market and timeframe, the impact input values will have on the visible gaps between the lines will vary greatly. For example, an input of 10 will have a far greater impact on the gaps between the lines when viewed from the 1-minute timeframe than it would on the 1-day timeframe. The input is a float and as such the value passed through can go into as many decimal places as the user requires.
It is also worth mentioning that as more lines are added the gaps between the lines, that are closest to the anchor point, will get tighter as they make their way up the y-axis. Although the gaps between the lines will stay constant at the x2 plot, i.e. a distance of 10 points between them, they will gradually get tighter and tighter at the point of origin as the slope of the lines get steeper.
Projection Ratio
This input is used to determine the distance between the parallels, expressed in terms of point or pips. Positive numbers will project the lines upwards while negative numbers will project the lines downwards. Depending on the market and timeframe, the impact input values will have on the visible gaps between the lines will vary greatly. For example, an input of 10 will have a far greater impact on the gaps between the lines when viewed from the 1-minute timeframe than it would on the 1-day timeframe. The input is a float and as such the value passed through can go into as many decimal places as the user requires.
Number Lines
This input is used to determine the number of lines to be drawn on the chart, maximum is 500.
█ LIMITATIONS
All green and red candle calculations are based on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. This may cause some unexpected behaviour on some markets and timeframes. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with.
If the lines do not draw or you see a study error saying that the script references too many candles in history, this is most likely because the higher timeframe anchor point is not present on the current timeframe. This problem usually occurs when referencing a higher timeframe, such as the 1-month, from a much lower timeframe, such as the 1-minute. How far you can lookback for higher timeframe anchor points on the current timeframe will also be limited by your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000.
█ RAMBLINGS
It is my current thesis that the indicator will work best when used in conjunction with my Wavemeter indicator, which can be used to set the angle and projection ratio. For example, the average wave height or amplitude could be used as the value for the angle and projection ratio inputs. Or some factor or multiple of such an average. I think this makes sense as it allows for objectivity when applying the indicator across different markets and timeframes with different energies and vibrations.
“If you want to find the secrets of the universe, think in terms of energy, frequency and vibration.”
― Nikola Tesla
Fan Projections [theEccentricTrader]█ OVERVIEW
This indicator automatically projects trendlines in the shape of a fan, from a single point of origin. In the example above I have applied the indicator twice to the 1D SPXUSD. The seven upper lines (green) are projected at an angle of -5 from the 1-month swing high anchor point. And the five lower lines (blue) are projected at an angle of 10 from the 1-week swing low anchor point.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Support and Resistance
• Support refers to a price level where the demand for an asset is strong enough to prevent the price from falling further.
• Resistance refers to a price level where the supply of an asset is strong enough to prevent the price from rising further.
Support and resistance levels are important because they can help traders identify where the price of an asset might pause or reverse its direction, offering potential entry and exit points. For example, a trader might look to buy an asset when it approaches a support level , with the expectation that the price will bounce back up. Alternatively, a trader might look to sell an asset when it approaches a resistance level , with the expectation that the price will drop back down.
It's important to note that support and resistance levels are not always relevant, and the price of an asset can also break through these levels and continue moving in the same direction.
Trendlines
Trendlines are straight lines that are drawn between two or more points on a price chart. These lines are used as dynamic support and resistance levels for making strategic decisions and predictions about future price movements. For example traders will look for price movements along, and reactions to, trendlines in the form of rejections or breakouts/downs.
█ FEATURES
Inputs
• Anchor Point Type
• Swing High/Low Occurrence
• HTF Resolution
• Highest High/Lowest Low Lookback
• Angle Degree
• Number Lines
• Line Color
Anchor Point Types
• Swing High
• Swing Low
• Swing High (HTF)
• Swing Low (HTF)
• Highest High
• Lowest Low
• Intraday Highest High (intraday charts only)
• Intraday Lowest Low (intraday charts only)
Swing High/Swing Low Occurrence
This input is used to determine which historic peak or trough to reference for swing high or swing low anchor point types.
HTF Resolution
This input is used to determine which higher timeframe to reference for swing high (HTF) or swing low (HTF) anchor point types.
Highest High/Lowest Low Lookback
This input is used to determine the lookback length for highest high or lowest low anchor point types.
Intraday Highest High/Lowest Low Lookback
When using intraday highest high or lowest low anchor point types, the lookback length is calculated automatically based on number of bars since the daily candle opened.
Angle Degree
This input is used to determine the angle of the trendlines. The output is expressed in terms of point or pips, depending on the symbol type, which is then passed through the built in math.todegrees() function. Positive numbers will project the lines upwards while negative numbers will project the lines downwards. Depending on the market and timeframe, the impact input values will have on the visible gaps between the lines will vary greatly. For example, an input of 10 will have a far greater impact on the gaps between the lines when viewed from the 1-minute timeframe than it would on the 1-day timeframe. The input is a float and as such the value passed through can go into as many decimal places as the user requires.
It is also worth mentioning that as more lines are added the gaps between the lines, that are closest to the anchor point, will get tighter as they make their way up the y-axis. Although the gaps between the lines will stay constant at the x2 plot, i.e. a distance of 10 points between them, they will gradually get tighter and tighter at the point of origin as the slope of the lines get steeper.
Number Lines
This input is used to determine the number of lines to be drawn on the chart, maximum is 500.
█ LIMITATIONS
All green and red candle calculations are based on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. This may cause some unexpected behaviour on some markets and timeframes. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with.
If the lines do not draw or you see a study error saying that the script references too many candles in history, this is most likely because the higher timeframe anchor point is not present on the current timeframe. This problem usually occurs when referencing a higher timeframe, such as the 1-month, from a much lower timeframe, such as the 1-minute. How far you can lookback for higher timeframe anchor points on the current timeframe will also be limited by your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000.
█ RAMBLINGS
It is my current thesis that the indicator will work best when used in conjunction with my Wavemeter indicator, which can be used to set the angle. For example, the average wave height or amplitude could be used as the value for the angle input. Or some factor or multiple of such an average. I think this makes sense as it allows for objectivity when applying the indicator across different markets and timeframes with different energies and vibrations.
“If you want to find the secrets of the universe, think in terms of energy, frequency and vibration.”
― Nikola Tesla
Swing Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed swing high and swing low scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Peak and Trough Prices (Advanced)
• The advanced peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the highest preceding green candle high price, depending on which is higher.
• The advanced trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the lowest preceding red candle low price, depending on which is lower.
Green and Red Peaks and Troughs
• A green peak is one that derives its price from the green candle/s that constitute the swing high.
• A red peak is one that derives its price from the red candle that completes the swing high.
• A green trough is one that derives its price from the green candle that completes the swing low.
• A red trough is one that derives its price from the red candle/s that constitute the swing low.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
█ FEATURES
Inputs
• Start Date
• End Date
• Position
• Text Size
• Show Sample Period
• Show Plots
• Show Lines
Table
The table is colour coded, consists of three columns and nine rows. Blue cells denote neutral scenarios, green cells denote return line uptrend and uptrend scenarios, and red cells denote downtrend and return line downtrend scenarios.
The swing scenarios are listed in the first column with their corresponding total counts to the right, in the second column. The last row in column one, row nine, displays the sample period which can be adjusted or hidden via indicator settings.
Rows three and four in the third column of the table display the total higher peaks and higher troughs as percentages of total peaks and troughs, respectively. Rows five and six in the third column display the total lower peaks and lower troughs as percentages of total peaks and troughs, respectively. And rows seven and eight display the total double-top peaks and double-bottom troughs as percentages of total peaks and troughs, respectively.
Plots
I have added plots as a visual aid to the swing scenarios listed in the table. Green up-arrows with ‘HP’ denote higher peaks, while green up-arrows with ‘HT’ denote higher troughs. Red down-arrows with ‘LP’ denote higher peaks, while red down-arrows with ‘LT’ denote lower troughs. Similarly, blue diamonds with ‘DT’ denote double-top peaks and blue diamonds with ‘DB’ denote double-bottom troughs. These plots can be hidden via indicator settings.
Lines
I have also added green and red trendlines as a further visual aid to the swing scenarios listed in the table. Green lines denote return line uptrends (higher peaks) and uptrends (higher troughs), while red lines denote downtrends (lower peaks) and return line downtrends (lower troughs). These lines can be hidden via indicator settings.
█ HOW TO USE
This indicator is intended for research purposes and strategy development. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe. It can, for example, give you an idea of any inherent biases such as a greater proportion of higher peaks to lower peaks. Or a greater proportion of higher troughs to lower troughs. Such information can be very useful when conducting top down analysis across multiple timeframes, or considering entry and exit methods.
What I find most fascinating about this logic, is that the number of swing highs and swing lows will always find equilibrium on each new complete wave cycle. If for example the chart begins with a swing high and ends with a swing low there will be an equal number of swing highs to swing lows. If the chart starts with a swing high and ends with a swing high there will be a difference of one between the two total values until another swing low is formed to complete the wave cycle sequence that began at start of the chart. Almost as if it was a fundamental truth of price action, although quite common sensical in many respects. As they say, what goes up must come down.
The objective logic for swing highs and swing lows I hope will form somewhat of a foundational building block for traders, researchers and developers alike. Not only does it facilitate the objective study of swing highs and swing lows it also facilitates that of ranges, trends, double trends, multi-part trends and patterns. The logic can also be used for objective anchor points. Concepts I will introduce and develop further in future publications.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
The green and red candle calculations are based solely on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with. Alternatively, you can replace the scenarios with your own logic to account for the gap anomalies, if you are feeling up to the challenge.
The sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
█ NOTES
I feel it important to address the mention of advanced peak and trough price logic. While I have introduced the concept, I have not included the logic in my script for a number of reasons. The most pertinent of which being the amount of extra work I would have to do to include it in a public release versus the actual difference it would make to the statistics. Based on my experience, there are actually only a small number of cases where the advanced peak and trough prices are different from the basic peak and trough prices. And with adequate multi-timeframe analysis any high or low prices that are not captured using basic peak and trough price logic on any given time frame, will no doubt be captured on a higher timeframe. See the example below on the 1H FOREXCOM:USDJPY chart (Figure 1), where the basic peak price logic denoted by the indicator plot does not capture what would be the advanced peak price, but on the 2H FOREXCOM:USDJPY chart (Figure 2), the basic peak logic does capture the advanced peak price from the 1H timeframe.
Figure 1.
Figure 2.
█ RAMBLINGS
“Never was there an age that placed economic interests higher than does our own. Never was the need of a scientific foundation for economic affairs felt more generally or more acutely. And never was the ability of practical men to utilize the achievements of science, in all fields of human activity, greater than in our day. If practical men, therefore, rely wholly on their own experience, and disregard our science in its present state of development, it cannot be due to a lack of serious interest or ability on their part. Nor can their disregard be the result of a haughty rejection of the deeper insight a true science would give into the circumstances and relationships determining the outcome of their activity. The cause of such remarkable indifference must not be sought elsewhere than in the present state of our science itself, in the sterility of all past endeavours to find its empirical foundations.” (Menger, 1871, p.45).
█ BIBLIOGRAPHY
Menger, C. (1871) Principles of Economics. Reprint, Auburn, Alabama: Ludwig Von Mises Institute: 2007.
Black RSI (Pro Suite)Black RSI (Pro Suite) is combination of RSI (Relative Strength Index), Volume RSI, Heikin Ashi RSI & other multi Oscillators with multi features into one indicator, features like (Quad Divergences, Multi Time Frame RSI, MTF RSI Panel, Oscillator Support/Resistance/Wedges/Trendlines, Oscillator Moving Average/BBs, Smooth RSI, RSI Price Estimator, Oscillator Over bought/sold Bars, Osc OB/OS Zones, Osc OB/OS Highlights, additionally Black RSI indicator is flexible & completely customizable).
Indicator goal: I have tried my best to organized RSI & other suitable oscillators and oscillator useful tools into one simple and free indicator for Tradingview users (specifically for Tradingview 'basic' subscription users). suggestions are always welcome. please give feedback & appreciate if you like my work.
Black RSI Indicator Features Summary:
Black RSI indicator includes many features mainly relevant to RSI and other Oscillators, these are briefly highlighted below:
Black RSI Dashboard
Multi Oscillators: Choose between multiple oscillators. All oscillators settings are customizable.
Multi Symbol: Multi Symbol Support, applicable on all oscillators
RSI (Relative Strength Index)
VRSI (Volume Relative Strength Index)
HA RSI (Heikin Ashi Relative Strength Index)
OBV (On Balance Volume)
CVD (Comulative Volume Delta)
MFI (Money Flow Index)
UO (Ultimate Oscillator)
MOM (Momentum Oscillator)
ATR (Average True Range)
Stoch (Stochastic Oscillator)
Stoch RSI (Stochastic RSI)
Oscillator Primary Tools ◢
Oscillator Moving Average/Bollinger Bands
Smooth RSI
Multi Timeframe RSI
Multi Timeframe RSI Panel
RSI Price Estimator
Oscillator Support/Resistance/Wedges/Trendlines
Oscillator Moving Average/BBs: Shows Moving Average for selected oscillator.
Smooth Smooth: Smooths out RSI
Multi Timeframe RSI: Displays Multiple Time Frame/Multiple Symbol RSI and converts it and shows it as it is in current time frame without effecting Primary RSI
Multi Timeframe RSI Panel: Displays Multiple Time Frame/Multiple Symbol RSI values of user input specific timeframes in compact panel (max 8 Time frames)
RSI Price Estimator: Calculates RSI estimate price values of 3 different user specific RSI input levels, RSI x MA cross price and RSI future value of user specific price input level.
Oscillator Support/Resistance/Wedges/Trendlines: Draws Trendlines, Wedges and Support & Resistance lines on selected oscillator
Oscillator Quad Divergence ◢
1st Oscillator Divergence: Traditional divergence indicator with enhancements & customization
2nd Oscillator Divergence: Traditional divergence indicator with enhancements & customization
3rd Oscillator Divergence: Advanced Divergence indicator with source selection, RSI/Price threshold, potential divergences & customization
4th Oscillator Divergence: Pivots divergence indicator with flexible pivots selection & customization
Regular bullish divergences are indicated when price is forming lower lows while an oscillator shows higher lows.
Regular bearish divergences are indicated when price is forming higher highs while an oscillator shows lower highs.
While regular divergences indicate trend reversals, hidden divergences indicate a trend continuation.
When the price is making higher lows and the oscillator is showing lower lows, we speak of a bullish hidden divergence.
When the price is making lower highs and the oscillator shows higher highs, it's a bearish hidden divergence.
Oscillator Secondary Tools ◢
Oscillator HH/LL pivots
Osc OB/OS Color Bars
Osc OB/OS Zones
Osc OB/OS Highlights
Background
Oscillator HH/LL pivots: Shows HH/LL pivot points on selected oscillator
Osc OB/OS Color Bars: Plots color chart bars based on RSI, MFI, Stochastic, Stochastic RSI or combine overbought/oversold conditions
Osc OB/OS Zones: Plots Osc OB/OS Zones with user input levels
Osc OB/OS Highlights: Highlight oscillator OB/OS background area
Background: background color customization
+ Primary RSI Settings ▾
- Primary RSI Length: User input RSI Length value
- Primary RSI Source: User RSI Source selection
- RSI Overbought Threshold: Allows the user to set the RSI overbought threshold value. This Overbought Threshold value will also be applied on "RSI Divergence overbought condition", "RSI OB Color Bars" and "Primary RSI Color Schemes
- RSI Oversold Threshold: Allows the user to set the RSI oversold threshold value. The lower band (oversold line) of RSI. This Oversold Threshold value will also be applied on "RSI Divergence oversold condition", "RSI OS Color Bars" and "Primary RSI Color Schemes
- RSI Middle Band: Allows the user to set the RSI middle band value. This value will also applied to "Center Line" color scheme from "Primary RSI Color Schemes" drop menu
- Primary RSI Colors:
Range color specifies a gradient of colors from the overbought to the oversold threshold user inputs from "Primary RSI" section. Color interpolation also a gradient but smoother than Range color. Center Line is similar but is not a gradient, linked to Middle Band ("Primary RSI" section) and changes color with RSI Middle Band. Traditional is simple with Overbought and Oversold colors change.
- RSI Bullish Band: Allows the user to plot extra/optional RSI band on RSI Oscillator (Note: it will not be plotted if "OB/OS Zone only" enabled from "OB/OS Zone Settings" section)
- RSI Bearish Band: Allows the user to plot extra/optional RSI band on RSI Oscillator (Note: it will not be plotted if "OB/OS Zone only" enabled from "OB/OS Zone Settings" section)
+ Primary RSI Smooth Settings ▾
- Smooth Moving Average Type: User selected Smooth MA type. With RSI Smooth enabled, will also effect all RSI Divergences detection (all divergences will be plot according to "Smoothed RSI line")
- Smooth Moving Average Length: User input Smooth MA length value
+ Oscillator Moving Average Settings ▾
- Osc Moving Average Colors: Allows user to select Bullish/Bearish colors of Oscillator Moving Average
- Osc Moving Average Type: Allows user to select Oscillator MA Type
- Osc Moving Average Length: User input Oscillator MA length value
- Osc Moving Average Thickness: User input Oscillator MA thickness
- BB StdDev: user input Bollinger Bands standard deviation value
+ Stochastic Oscillator Settings ▾
- Same as Traditional/Default indicator
+ Stochastic RSI Oscillator Settings ▾
- Same as Traditional/Default indicator
+ Money Index Flow Settings ▾
- Same as Traditional/Default indicator
+ Ultimate Oscillator Settings ▾
- Same as Traditional/Default indicator
+ Momentum Oscillator Settings ▾
- Same as Traditional/Default indicator
+ Average True Range Settings ▾
- Same as Traditional/Default indicator
+ Multi Timeframe RSI Settings ▾
- MTF RSI Time Frame: Allows user to select MTF RSI Time Frame
- MTF RSI Symbol: Allows user to select MTF RSI Time Symbol
- MTF RSI Length: User input MTF RSI length value
- MTF RSI Source: User selected MTF RSI source
- MTF RSI Line Width: User input MTF RSI line thickness value
- Number of Bars for MTF RSI plot
- MTF RSI Color > OB color > OS color : Allows user to select MTF RSI color with additionally Overbought/Oversold colors
+ MTF RSI Panel Settings ▾
- Select MTF RSI Type: If "Primary RSI" or "Volume RSI" selected MTF RSI Panel will show output values based on "Primary RSI" or "Volume RSI" parameters e.g. source, length, but without smooth.
- MTF RSI Panel Symbol: Allows user to select MTF RSI Panel symbol, leave symbol blank or uncheck "checkbox" for current chart symbol
- Show Symbol in Panel: Shows symbol ticker(current or user selected) in MTF RSI Panel
- Panel Background: Allows user to select MTF RSI Panel Background (enable/disable) and Background color selection
- TF1: MTF RSI Timeframe 1 user selection
- TF2: MTF RSI Timeframe 2 user selection
- TF3: MTF RSI Timeframe 3 user selection
- TF4: MTF RSI Timeframe 4 user selection
- TF5: MTF RSI Timeframe 5 user selection
- TF6: MTF RSI Timeframe 6 user selection
- TF7: MTF RSI Timeframe 7 user selection
- TF8: MTF RSI Timeframe 8 user selection
- Panel Top Offset: MTF RSI Panel offset input value
- Position: MTF RSI Panel position selection
- Text Size: MTF RSI Panel text size selection
- Bullish Colors: MTF RSI Panel bullish color selection. (Bullish colors range RSI >75, <75 to >65, <65 to >55)
- Bearish Colors: MTF RSI Panel bearish color selection. (Bearish colors range RSI <45 to >35, <35 to >25, <25)
+ RSI Price Estimator Settings ▾
- Price 1: User input value for RSI future price
- Price 2: User input value for RSI future price
- Price 3: User input value for RSI future price
- Panel Position Offset: User input value for panel position offset
- Price Decimals: User input value for output price decimals in panel
- Show RSI/OscMA cross Price: Enable/Disable RSIxOscillator MA cross future price
- Show RSI Level for Input Price: User input price for future RSI level
- Invisible Background: Enable/Disable Background
Auto Text Color > Auto color change of Panel text according to Dark/Light chart theme
+ Oscillator Support/Resistance Settings ▾
- Show Support line: Allows user to Enable/Disable Oscillator support line
Color > Auto Color: Auto color change of support line according to Dark/Light chart theme
- Show Resistance line: Allows user to Enable/Disable Oscillator resistance line
Color > Auto Color: Auto color display of resistance line according to Dark/Light chart theme
- Lookback lows/highs: User input of Lookback lows/highs value
- Distance threshold: Distance from the line to the low
- Line touch points: Number of points that have to be around the line
- Low/High left bars: User input of Low/High left bars value
- Low/High right bars: User input of Low/High right bars value
- Line style: User selection of line style
- Line thickness: User input of line thickness value
+ Oscillator 1st Divergence Settings ▾
- Divergence Source: User selection of divergence source. "High/Low" (high/low of oscillator/price divergence detection), "Close" (close of oscillator/price divergence detection) and "Both" (Both Close + High/Low of oscillator/price divergence detection). (Note: Traditional Divergence indicator default source is "High/Low")
- Pivot Lookback Right: How many candle to compare on the right side of a candle when deciding whether it is a pivot. The lower the number is, the earlier pivots (and therefore divergences) will be signaled, but the quality of those detections could be lower.
- Pivot Lookback Left: How many candle to compare on the left side of a candle when deciding whether it is a pivot. The lower the number is, the earlier pivots (and therefore divergences) will be signaled, but the quality of those detections could be lower.
- Divergence Max Length (Bars): The maximum length of a divergence (number of bars). If a detected divergence is longer than this, it will be discarded
- Divergence Min Length (Bars): The minimum length of a divergence (number of bars). If a detected divergence is shorter than this, it will be discarded
- Show Divergence as:
- Line Thickness: User input divergence line thickness value
- Label Transparency: it could reduce labels mess on oscillator line, input "100" for label text only without label background
- Labels Text Color: User label text color selection
Auto Text Color > Auto color change of label text according to Dark/Light chart theme
- Bull Divergences: Enable/Disable of Bull divergences
> Color: User selection of Bull divergence color
> Oversold only: It will show Regular Bullish RSI divergences in oversold zone only, RSI oversold threshold can be configure in "Primary RSI Settings" section.
- Bear Divergences: Enable/Disable of Bear divergences
> Color: User selection of Bear divergence color
> Overbought only: It will show Regular Bearish RSI divergences in overbought zone only, RSI overbought threshold can be configure in "Primary RSI Settings" section.
- Hidden Bull Div: Enable/Disable of Hidden Bull divergences
> Color: User selection of Hidden Bull divergence color
- Hidden Bear Div: Enable/Disable of Hidden Bear divergences
> Color: User selection of Hidden Bear divergence color
+ Oscillator 2nd Divergence Settings ▾
- Same as Oscillator 1st Divergence Settings
+ Oscillator 3rd Divergence Settings ▾
- Divergence source: User selection of divergence source . "oscillator" (divergence detection with high/low or close of selected oscillator), "price" (divergence detection with high/low or close of price)
- Bull price source: User selection of Bull price source. Bull price source: "Low" (low of price divergence detection), "Close" (close of price divergence detection) (linked to "price" in "Divergence source")
- Bear price source: User selection of Bear price source. Bear price source: "High" (high of price divergence detection), "Close" (close of price divergence detection) (linked to "price" in "Divergence source")
- Low/High left bars: How many candle to compare on the left side of a candle when deciding whether it is a pivot. The lower the number is, the earlier pivots (and therefore divergences) will be signaled, but the quality of those detections could be lower.
- Low/High right bars: How many candle to compare on the right side of a candle when deciding whether it is a pivot. The lower the number is, the earlier pivots (and therefore divergences) will be signaled, but the quality of those detections could be lower.
- Maximum lookback bars: The maximum length of a divergence (number of bars). If a detected divergence is longer than this, it will be discarded.
- Price threshold: User selection of Price threshold, higher values more lines
- RSI threshold: User selection of RSI threshold, higher values more lines
- Show Lows: Displays lows of RSI
- Show Highs: Displays highs of RSI
- Show Divergence as:
- Line Style:
- Line thickness: User input divergence line thickness value
- Label Transparency: it could reduce labels mess on oscillator line, input "100" for label text only without label background
- Labels Text Color: User label text color selection
Auto Text Color > Auto color change of label text according to Dark/Light chart theme
- Bull Divergences: Enable/Disable of Bull divergences
> Color: User selection of Bull divergence color
> Potential Bull: It will plot potential regular bull divergence with dotted line.
- Bear Divergences: Enable/Disable of Bear divergences
> Color: User selection of Bear divergence color
> Potential Bear: It will plot potential regular bear divergence with dotted line.
- Hidden Bull Div: Enable/Disable of Hidden Bull divergences
> Color: User selection of Hidden Bull divergence color
> Potential H.Bull: It will plot potential hidden bull divergence with dotted line.
- Hidden Bear Div: Enable/Disable of Hidden Bear divergences
> Color: User selection of Hidden Bear divergence color
> Hidden Bear divergence: It will plot potential hidden bear divergence with dotted line.
> Regular Bull oversold only: It will show Regular Bullish RSI divergences in oversold zone only, RSI oversold threshold can be configure in "Primary RSI Settings" section.
> Regular Bear overbought only: It will show Regular Bearish RSI divergences in overbought zone only, RSI overbought threshold can be configure in "Primary RSI Settings" section.
+ Oscillator 4th Divergences Settings ▾
- Upper Length: User pivot input value of draw upper divergence line From
- To Pivot:
- Lower Length: User pivot input value of draw lower divergence line From
- To Pivot:
- Show Divergence as:
- Line Style:
- Line thickness: User input divergence line thickness value
- Label Transparency: it could reduce labels mess on oscillator line, input "100" for label text only without label background
- Labels Text Color: User label text color selection
Auto Text Color > Auto color change of label text according to Dark/Light chart theme
- Bull Divergences: Enable/Disable of Bull divergences
> Color: User selection of Bull divergence color
- Bear Divergences: Enable/Disable of Bear divergences
> Color: User selection of Bear divergence color
- Regular Bull oversold only: It will show Regular Bullish RSI divergences in oversold zone only, RSI oversold threshold can be configure in "Primary RSI Settings" section.
- Regular Bear overbought only: It will show Regular Bearish RSI divergences in overbought zone only, RSI overbought threshold can be configure in "Primary RSI Settings" section.
+ Oscillator HHLL Pivots Settings ▾
- Pivot Length: User input value of HH/LL pivot length
> L.Text Color: User label text color selection
- HH color: User HH Label color selection
- HL color: User HL Label color selection
- LH color: User LH Label color selection
- LL color: User LL Label color selection
+ Oscillator OB/OS Colored Bars Settings▾
- Overbought/Oversold Bars Oscillator: Plots Overbought/Oversold color bars based on RSI, MFI, Stoch, Stoch RSI overbought/oversold threshold conditions separately or combined(when every oscillator reach its OB or OS threshold condition at same time).
- Overbought Bar Color: User RSI OB Bars color selection
- Oversold Bar Color: User RSI OS Bars color selection
+ Primary RSI Range Color ▾
- OB: Overbought Color
- OS: Oversold Color
- Bullish: Bullish Color
- Bearish: Bearish Color
+ Primary RSI Color interpolation ▾
- RSI Color: RSI Color
- OB: Overbought Color
- OS: Oversold Color
+ Primary RSI Center Line Color ▾
- OB: Overbought Color
- Bullish: Bullish Color
- Bearish: Bearish Color
- OS: Oversold Color
+ Primary RSI Traditional Color ▾
- RSI Color: RSI Color
- OB: Overbought Color
- OS: Oversold Color
Osc Overbought/Oversold Zones Settings ▾
- OB/OS Zone Band Lines: Enable/Disable OB/OS Zone Band Lines
- OB/OS Zones only: Only shows OB/OS Zones and disable all RSI band lines except Middle Band. Background will not be effected by this setting.
- Overbought Zone: User input value of Overbought Zone from
> To:
- Oversold Zone: User input value of Oversold Zone from
> To:
Osc Overbought/Oversold Highlights ▾
- Overbought Highlights : Enable/Disable Overbought Highlights
- Oversold Highlights : Enable/Disable Oversold Highlights
- Transparency: Gradient transparency of highlighted area
+ 'Oscillators Color Settings ▾
- Show Osc Symbol label : Enable/Disable of oscillator symbol label. Displays current oscillator symbol, but with "Override Oscillator Symbol" enabled from "Black RSI Dashboard" it will Auto/forcefully displays Override Oscillator Symbol on Oscillator
- Fade out Oscillator line: Fade out the oscillator line color, focusing only the most recent periods prominent for a clearer chart
- Fill Stoch/StochRSI lines: Fills Stoch/Stoch RSI lines
- Oscillator line thickness: user input value of oscillator line thickness
- Oscillator line offset: Shifts the oscillator to the left or to the right on the given number of bars, Default is 0
- OBV Color
- MFI Color
- ATR Color
- UO Color
- MOM Color
- CVD Bullish Color
- CVD Bearish Color
+ Background Setting ▾
- Custom Background Color: User selection of Background color
Authors & Credits: I'd like to THANK to Nabeel Black(myself), LonesomeTheBlue, iFuSiiOnzZ, jmosullivan, zdmre, creengrack, and TradingView for the locally sourced ingredients.
Disclaimer: DYOR. Not financial advice. Not a trading system. I am not affiliated with TradingView or any authors mentioned here; You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely. Always trade with confluence and Risk Management.
Feedback & Bug report
if you found any bug in this indicator or any suggestion, please let me know. Please give feedback & appreciate if you like to see more future updates and indicators. Thank you
Poor ReversalsPoor Reversals Indicator
This indicator finds Poor Reversals. Poor reversals are reversals in price with consecutive highs or lows that are close together. Look for the different types of highs and lows. Some say candle patterns don't matter, but they forget it's the orderflow that makes the pattern. Find poor, tweezer, and 1 tic rejections and study what happens next. We don't need to read the depth of market to see what the orderflow is saying. They are called poor because the auction didn't run its course. It didn't continue the direction until all activity in that direction was exhausted. Proper reversals create excess. Excess is a long tail/wick. A proper reversal leaves a long tailed excess unfilled.
The different highs and lows give clues to what kind of orderflow happened there. The difference between them is which high or low happened first. Price does often come back to these areas and clears them up with a proper reversal. We can see them on all timeframes. Knowing what they mean in the orderflow helps with reading charts.
The Poor Reversals are:
Poor
1 Tick Rejection
Tweezer
When looking at 2 bars that have very close high or lows, there are a few different types. They are each poor and can be further defined as each are price action clues.
If next low is higher, it's a poor low
If next low is lower, it's 1 tic rejection
If next low is equal, it's tweezer bottom
If next high is lower, it's a poor low
If next high is higher it's 1 tic rejection
If next high is equal it's tweezer bottom
Poor Highs and Lows:
The high or low comes first. The next bar does not go past it. Poor highs and lows are often created from price exhaustions. This means at poor highs buyers are trapped. At poor lows sellers are trapped. Price ran out of steam to continue in that direction. There wasn't enough activity and participation to continue the auction in that direction.
Poor lows are defined when 2 lows are very close, and the 1st bar is lower. The 2nd comes very close to a new low. It happens most when shorts, at the moment, "run out of steam". They were "too aggressive" and got themselves "short in the hole". When a poor low is made, price will bounce because shorts are buying to protect profits.
Poor highs are defined when 2 highs are very close. The 1st bar is higher. The 2nd comes very close to a new high. It happens most when longs, at the moment, "run out of steam". They were "too aggressive" and got themselves "long in the tooth". When a poor high is made, price will pullback because longs are selling to protect profits.
1 Tick Rejections:
The high or low comes last. The next bar goes just a little bit beyond it. A "1 tic rejection" happens when a new low is made and quickly rejects. The name is misleading. It doesn't have to be "1 tic". Different markets have different measurements. For ES, it's less than 8 tics. For NQ, it's about 5-20 points. It varies depending on relative market volatility.
1 Tick highs are defined when 2 highs are very close, and the 1st bar is lower. This happens when longs are aggressive and drive price up. Price makes a newer high and longs rapidly start taking profits. Their selling activity drives price lower. In the orderflow, longs likely closed at the same time new shorts sell. This competition to sell drives price lower. At the high, it says longs saw it wouldn't go higher and they took rapid exit.
1 Tick lows are defined when 2 lows are very close, and the 1st bar is lower. This happens when shorts are aggressive and drive price down. Price makes a newer low and shorts rapidly start taking profits. Their buying activity drives price higher. In the orderflow, shorts likely closed at the same time new longs buy. This competition to buy drives price higher. At the low, it says shorts saw it wouldn't go lower and they took rapid exit.
Tweezer Tops and Bottoms
The highs or lows of the bars are equal. Tweezers most often mean that an aggressive trader is influencing price. They drove price in one direction and then quickly reversed sentiment. Tweezers most often happens in stop hunts. An aggressive trader found where the stops were located and then entered an aggressive order to turn the market.
Tweezer Tops are defined when 2 highs are equal. The first bar sets the high. The second bar matches the high. This happens when there is an active seller entering. It could be simple profit taking from longs or new aggressive shorts. In bull trends, price will move up to find short stop. When the stops are found, the market reverses sharply lower.
Tweezer Bottoms are defined when 2 lows are equal. The first bar sets the low. The second bar matches the low. This happens when there is an active buyer entering. It could be simple profit taking from shorts or new aggressive longs. In bull trends, price will move up to find long stops. When the stops are found, the market reverses sharply higher.
Poor Reversals can be poor, 1 Tick Rejections, or Tweezers. They are all considered poor and upon further investigation we can see they are created from different conditions in the orderflow. They are not called Poor Reversals because they are weak. They are called poor because of the action that happened there. One side got caught in a bad position. Other sharks in the market smelled blood and ripped them apart.
This indicator is a work in process. While the concepts are great for real time trading, this indicator is not designed to be used in real time trading. It will repaint based on the bar close. The purpose of this indicator is to train our brains to see these nuances on candle charts. Some say candle patterns don't matter, but they forget it's the orderflow that makes the pattern. We must make split second decisions and knowing the context behind the orderflow reduces response time. These poor reversals don't have to retest, and the best ones won't come back. I use these concepts to find exits, where my trades might be wrong, confirmation I'm on the right side. It's amazing how these simple nuances can turn the markets. But sure enough, they do. Check them out in all time frames.
It's a fun indicator to play with. Some markets do require tweaks to the “Ticks” setting. Too big and charts will be noisy. Too low and not much will show up. A general rule of thumb is more volatile markets need higher tick values while less volatile need lower Tick values. Higher timeframes are also more reliable than lower time frames. I've included some customizable settings and I plan on adding more in the future. Enjoy!
