Scoopy StacksWaffle Around Multiple
(Open, High, Low, Close) Stacks On
Pre/Post Market & (Daily, Weekly,
Monthly, Yearly) Sessions With
Meticulous Columns, Rows, Tooltips,
Colors, Custom Ideas, and Alerts.
Sessions Use Two Step Incremental Values
Default Value: (1) Shows Two Previous
(O, H, L, C); Increasing Value Swaps
Sessions With Next Two Stacks.
⬛️ KEY WORDS:
🟢 Crossover | 🔴 Crossunder
📗 High | 📕 Low
📔 Open | 📓 Close
🥇 First Idea | 🥈 Second Idea
🥉 Third Idea | 🎖️ Fourth Idea
🟥 ALERTS:
Default Option: (Per Bar)
Alerts Once Conditions Are Met
(Bar Close) Alerts When Bar Closes
Default Option: (Reg)
Alerts During Regular Market
Trading Hours, (0930-1600)
(Ext) Alerts During Extended
Market Hours, (1600-0930)
(24/7) Alerts All Day
Optional Preferences:
Regular Alerts - Stocks
Extended Alerts - Futures
24/7 Alerts - Crypto
🟧 STACKS:
Default Value: (1)
Incremental Stack Value, Increasing Value
Swaps Sessions With the Next Two Stacks
(✓) Swap Stacks?
Pre/Post Market High/Lows,
1-2 Day High/Lows, 1-2 Week High/Lows,
1-2 Month High/Lows, 1-2 Year High/Lows
( ) Swap Stacks?
Pre/Post Market Open/Close,
1-2 Day Open/Close, 1-2 Week Open/Close,
1-2 Month Open/Close, 1-2 Year Open/Close
🟨 EXAMPLES:
Default Stack:
🟢 | 📗 Pre Market High (PRE) | 4600.00
🔴 | 📕 Post Market Low (POST) | 420.00
Optional: (Open)
🟢 | 📔 Post Market Open (POST) | 4400.00
Optional: (Close)
🔴 | 📓 Pre Market Close (PRE) | 430.00
Default Stack Value: (1)
🔴 | 📗 1 Day High (1DH) | 460.00
Next Stack Value: (3)
🟢 | 📕 4 Day Low (4DL) | 420.00
Optional: (Open)
🔴 | 📔 2 Day Open (2DO) | 440.00
Optional: (Close)
🟢 | 📓 3 Day Close (3DC) | 430.00
Default Stack Value: (5)
🟢 | 📗 5 Week High (5WH) | 460.00
Next Stack Value: (7)
🔴 | 📕 8 Week Low (8WL) | 420.00
Optional: (Open)
🔴 | 📔 7 Week Open (7WO) | 4400.00
Optional: (Close)
🟢 | 📓 6 Week Close (6WC) | 430.00
Default Stack Value: (9)
🔴 | 📗 9 Month High (9MH) | 460.00
Next Stack Value: (11)
🟢 | 📕 12 Month Low (12ML) | 420.00
Optional: (Open)
🟢 | 📔 11 Month Open (11MO) | 4400.00
Optional: (Close)
🔴 | 📓 10 Month Close (10MC) | 430.00
Default Stack Value: (13)
🟢 | 📗 13 Year High (13YH) | 460.00
Next Stack Value: (15)
🟢 | 📕 16 Year Low (16YL) | 420.00
Optional: (Open)
🔴 | 📔 15 Year Open (15YO) | 4400.00
Optional: (Close)
🔴 | 📓 14 Year Close (14YC) | 430.00
🟩 TABLES:
Default Value: (1)
Moves Table Up, Down, Left, or Right
Based on Second Default Value
First Default Value: (Top Right)
Sets Table Placement, Middle Center
Allows Table To Move In All Directions
Second Default Value: (Default)
Fixed Table Position, Switching Values
Moves Direction of the Table
🟦 IDEAS:
(✓) Show Ideas?
Shows Four Ideas With Custom Texts
and Values; Ideas Are Based Around
Post-It Note Reminders with Alerts
Suggestions For Text Ideas:
Take Profit, Stop Loss, Trim, Hold,
Long, Short, Bounce Spot, Retest,
Chop, Support, Resistance, Buy, Sell
🟪 EXAMPLES:
Default Value: (5)
Shows the Custom Table Value For
Sorted Table Positions and Alerts
Default Text: (🥇)
Shown On First Table Cell and
Message Appearing On Alerts
Alert Shows: 🟢 | 🥇 | 5.00
Default Value: (10)
Shows the Custom Table Value For
Sorted Table Positions and Alerts
Default Text: (🥈)
Shown On Second Table Cell and
Message Appearing On Alerts
Alert Shows: 🔴 | 🥈 | 10.00
Default Value: (50)
Shows the Custom Table Value For
Sorted Table Positions and Alerts
Default Text: (🥉)
Shown On Third Table Cell and
Message Appearing On Alerts
Alert Shows: 🟢 | 🥉 | 50.00
Default Value: (100)
Shows the Custom Table Value For
Sorted Table Positions and Alerts
Default Text: (🎖️)
Shown On Fourth Table Cell and
Message Appearing On Alerts
Alert Shows: 🔴 | 🎖️ | 100.00
⬛️ REFERENCES:
Pre-market Highs & Lows on regular
trading hours (RTH) chart
By Twingall
Previous Day Week Highs & Lows
By Sbtnc
Screener for 40+ instruments
By QuantNomad
Daily Weekly Monthly Yearly Opens
By Meliksah55
חפש סקריפטים עבור "high low"
Ribbit RangesBounce Around Multiple
(Open, High, Low, Close) Ranges
On Pre/Post Market & (Daily, Weekly,
Monthly, Yearly) Sessions With
Meticulous Lines, Labels, Tooltips,
Colors, Custom Ideas, and Alerts.
Sessions Use Two Step Incremental Values
Default Value: (1) Shows Two Previous
(O, H, L, C); Increasing Value Swaps
Sessions With Next Two Ranges.
⬛️ KEY WORDS:
🟢 Crossover | 🔴 Crossunder
📗 High | 📕 Low
📔 Open | 📓 Close
🥇 First Idea | 🥈 Second Idea
🥉 Third Idea | 🎖️ Fourth Idea
🟥 ALERTS:
Default Option: (Per Bar)
Alerts Once Conditions Are Met
(Bar Close) Alerts When Bar Closes
Default Option: (Reg)
Alerts During Regular Market
Trading Hours, (0930-1600)
(Ext) Alerts During Extended
Market Hours, (1600-0930)
(24/7) Alerts All Day
Optional Preferences:
Regular Alerts - Stocks
Extended Alerts - Futures
24/7 Alerts - Crypto
🟧 RANGES:
Default Value: (1)
Incremental Range Value, Increasing Value
Swaps Sessions With the Next Two Ranges
(✓) Swap Ranges?
Pre/Post Market High/Lows,
1-2 Day High/Lows, 1-2 Week High/Lows,
1-2 Month High/Lows, 1-2 Year High/Lows
( ) Swap Ranges?
Pre/Post Market Open/Close,
1-2 Day Open/Close, 1-2 Week Open/Close,
1-2 Month Open/Close, 1-2 Year Open/Close
🟨 EXAMPLES:
Default Range:
🟢 | 📗 Pre Market High (PRE) | 4600.00
🔴 | 📕 Post Market Low (POST) | 420.00
Optional: (Open)
🟢 | 📔 Post Market Open (POST) | 4400.00
Optional: (Close)
🔴 | 📓 Pre Market Close (PRE) | 430.00
Default Range Value: (1)
🔴 | 📗 1 Day High (1DH) | 460.00
Next Range Value: (3)
🟢 | 📕 4 Day Low (4DL) | 420.00
Optional: (Open)
🔴 | 📔 2 Day Open (2DO) | 440.00
Optional: (Close)
🟢 | 📓 3 Day Close (3DC) | 430.00
Default Range Value: (5)
🟢 | 📗 5 Week High (5WH) | 460.00
Next Range Value: (7)
🔴 | 📕 8 Week Low (8WL) | 420.00
Optional: (Open)
🔴 | 📔 7 Week Open (7WO) | 4400.00
Optional: (Close)
🟢 | 📓 6 Week Close (6WC) | 430.00
Default Range Value: (9)
🔴 | 📗 9 Month High (9MH) | 460.00
Next Range Value: (11)
🟢 | 📕 12 Month Low (12ML) | 420.00
Optional: (Open)
🟢 | 📔 11 Month Open (11MO) | 4400.00
Optional: (Close)
🔴 | 📓 10 Month Close (10MC) | 430.00
Default Range Value: (13)
🟢 | 📗 13 Year High (13YH) | 460.00
Next Range Value: (15)
🟢 | 📕 16 Year Low (16YL) | 420.00
Optional: (Open)
🔴 | 📔 15 Year Open (15YO) | 4400.00
Optional: (Close)
🔴 | 📓 14 Year Close (14YC) | 430.00
🟩 COLORS:
(✓) Swap Colors?
Text Color Is Shown Using
Background Color
( ) Swap Colors?
Background Color Is Shown
Using Text Color
🟦 IDEAS:
(✓) Show Ideas?
Plots Four Ideas With Custom Lines
and Labels; Ideas Are Based Around
Post-It Note Reminders with Alerts
Suggestions For Text Ideas:
Take Profit, Stop Loss, Trim, Hold,
Long, Short, Bounce Spot, Retest,
Chop, Support, Resistance, Buy, Sell
🟪 EXAMPLES:
Default Value: (5)
Shows the Custom Value For
Lines, Labels, and Alerts
Default Text: (🥇)
Shown On First Label and
Message Appearing On Alerts
Alert Shows: 🟢 | 🥇 | 5.00
Default Value: (10)
Shows the Custom Value For
Lines, Labels, and Alerts
Default Text: (🥈)
Shown On Second Label and
Message Appearing On Alerts
Alert Shows: 🔴 | 🥈 | 10.00
Default Value: (50)
Shows the Custom Value For
Lines, Labels, and Alerts
Default Text: (🥉)
Shown On Third Label and
Message Appearing On Alerts
Alert Shows: 🟢 | 🥉 | 50.00
Default Value: (100)
Shows the Custom Value For
Lines, Labels, and Alerts
Default Text: (🎖️)
Shown On Fourth Label and
Message Appearing On Alerts
Alert Shows: 🔴 | 🎖️ | 100.00
⬛️ REFERENCES:
Pre-market Highs & Lows on regular
trading hours (RTH) chart
By Twingall
Previous Day Week Highs & Lows
By Sbtnc
Screener for 40+ instruments
By QuantNomad
Daily Weekly Monthly Yearly Opens
By Meliksah55
Z-Score Based Momentum Zones with Advanced Volatility ChannelsThe indicator "Z-Score Based Momentum Zones with Advanced Volatility Channels" combines various technical analysis components, including volatility, price changes, and volume correction, to calculate Z-Scores and determine momentum zones and provide a visual representation of price movements and volatility based on multi timeframe highest high and lowest low values.
Note: THIS IS A IMPROVEMNT OF "Multi Time Frame Composite Bands" INDICATOR OF MINE WITH MORE EMPHASIS ON MOMENTUM ZONES CALULATED BASED ON Z-SCORES
Input Options
look_back_length: This input specifies the look-back period for calculating intraday volatility. correction It is set to a default value of 5.
lookback_period: This input sets the look-back period for calculating relative price change. The default value is 5.
zscore_period: This input determines the look-back period for calculating the Z-Score. The default value is 500.
avgZscore_length: This input defines the length of the momentum block used in calculations, with a default value of 14.
include_vc: This is a boolean input that, if set to true, enables volume correction in the calculations. By default, it is set to false.
1. Volatility Bands (Composite High and Low):
Composite High and Low: These are calculated by combining different moving averages of the high prices (high) and low prices (low). Specifically:
a_high and a_low are calculated as the average of the highest (ta.highest) and lowest (ta.lowest) high and low prices over various look-back periods (5, 8, 13, 21, 34) to capture short and long-term trends.
b_high and b_low are calculated as the simple moving average (SMA) of the high and low prices over different look-back periods (5, 8, 13) to smooth out the trends.
high_c and low_c are obtained by averaging a_high with b_high and a_low with b_low respectively.
IDV Correction Calulation : In this script the Intraday Volatility (IDV) is calculated as the simple moving average (SMA) of the daily high-low price range divided by the closing price. This measures how much the price fluctuates in a given period.
Composite High and Low with Volatility: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots.
Composite High and Low with Volatility Correction: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots.
2. Momentum Blocks Based on Z-Score:
Relative Price Change (RPC):
The Relative Price Change (rpdev) is calculated as the difference between the current high-low-close average (hlc3) and the previous simple moving average (psma_hlc3) of the same quantity. This measures the change in price over time.
Additionally, std_hlc3 is calculated as the standard deviation of the hlc3 values over a specified look-back period. The standard deviation quantifies the dispersion or volatility in the price data.
The rpdev is then divided by the std_hlc3 to normalize the price change by the volatility. This normalization ensures that the price change is expressed in terms of standard deviations, which is a common practice in quantitative analysis.
Essentially, the rpdev represents how many standard deviations the current price is away from the previous moving average.
Volume Correction (VC): If the include_vc input is set to true, volume correction is applied by dividing the trading volume by the previous simple moving average of the volume (psma_volume). This accounts for changes in trading activity.
Volume Corrected Relative Price Change (VCRPD): The vcrpd is calculated by multiplying the rpdev by the volume correction factor (vc). This incorporates both price changes and volume data.
Z-Scores: The Z-scores are calculated by taking the difference between the vcrpd and the mean (mean_vcrpd) and then dividing it by the standard deviation (stddev_vcrpd). Z-scores measure how many standard deviations a value is away from the mean. They help identify whether a value is unusually high or low compared to its historical distribution.
Momentum Blocks: The "Momentum Blocks" are essentially derived from the Z-scores (avgZScore). The script assigns different colors to the "Fill Area" based on predefined Z-score ranges. These colored areas represent different momentum zones:
Positive Z-scores indicate bullish momentum, and different shades of green are used to fill the area.
Negative Z-scores indicate bearish momentum, and different shades of red are used.
Z-scores near zero (between -0.25 and 0.25) suggest neutrality, and a yellow color is used.
Moving Average - TREND POWER v1.1- (AS)0)NOTE:
This is first version of this indicator. It's way more complicated than it should be. Check out Moving Average-TREND POWER v2.1-(AS), its waaaaay less complicated and might be better.Enjoy...
1)INTRODUCTION/MAIN IDEA:
In simpliest form this script is a trend indicator that rises if Moving average if below price or falling if above and going back to zero if there is a crossover with a price. To use this indicator you will have to adjust settings of MAs and choose conditions for calculation.
While using the indicator we might have to define CROSS types or which MAs to use. List of what cross types are defined in the script and Conditiones to choose from.The list will be below.
2) COMPOSITION:
-MA1 can be defined by user in settings, possible types: SMA, EMA, RMA, HMA, TEMA, DEMA, LSMA, WMA.
-MA2 is always ALMA
3) OVERLAY:
Default is false but if you want to see MA1/2 on chart you can change code to true and then turn on overlay in settings. Most plot settings are avalible only in OV=false.
if OV=true possible plots ->MA1/2, plotshape when choosen cross type
if OV=false -> main indicator,TSHs,Cross counter
4)PRESETS :
Indicator has three modes that can be selected in settings. First two are presets and do not require selecting conditions as they set be default.
-SIMPLE - most basic
-ABSOLUTE - shows only positive values when market is trending or zero when in range
-CUSTOM - main and the most advanced form that will require setting conditions to use in calculating trend
4.1)SIMPLE – this is the most basic form of conditions that uses only First MA. If MA1 is below selected source (High/Low(High for Uptrend and Low for DNtrend or OHLC4) on every bar value rises by 0.02. if it above Low or OHLC4 it falls by 0.02 with every bar. If there is a cross of MA with price value is zero. This preset uses CROSS_1_ULT(list of all cross types below)
4.2) ABSOLUTE – does not show direction of the trend unlike others and uses both MA1 and MA2. Uses CROSS type 123_ULT
4.3) CUSTOM – here we define conditions manually. This mode is defined in parts (5-8 of description)
5)SETTINGS:
SOURCE/OVERLAY(line1) – select source of calculation form MA1/MA2, select for overlay true (look point 3)
TRESHOLDS(line2). – set upper and lower THS, turn TSHs on/off
MA1(line3) – Length/type of MA/Offset(only if MA type is LSM)
MA2(line4) – length/offset/sigma -(remember to set ma in the way that in Uptrend MA2MA1 in DNtrend)
Use faster MA types for short term trends and slower types / bigger periods for longer term trends, defval MA1/2 settings
are pretty much random so using them is not recomended.
CROSSshape(line5) – choose which cross type you want to plot on chart(only in OV=true) or what type you want to use in counting via for loops,
CROSScount(line6) – set lookback for type of cross choosen above
BOOLs in lines 5 and 6 - plotshape if OV=true/plot CROSScount histogram (if OV=false)
Lines 7 and 8 – PRESET we want to use /SRC for calculation of indicator/are conditions described below/which MAs to use/Condition for
reducing value t 0 - (if PRESET is ABSOLUTE or SIMPLE only SRC should be set(Line 8 does not matter if not CUSTOM))
5)SOURCE for CONDS:
Here you can choose between H/L and OHLC. If H/L value grow when MAlow. If OHLC MAOHLC. H/L is set by default and recommended. This can be selected for all presets not only CUSTOM
6)CROSS types LIST:
“1 means MA1, 2 is MA2 and 3 I cross of MA1/MA2. L stands for low and H for high so for example 2H means cross of MA2 and high”
NAME -DEFINITION Number of possible crosses
1L - cross of MA1 and low 1
1H - cross of MA1 and high 1
1HL - cross of MA1 and low or MA1 and high 2 -1L/1H
2L - cross of MA2 and low 1
2H - cross of MA2 and high 1
2HL - cross of MA2 and low or MA1 and high 2 -2L/2H
12L - cross of MA1 and low or MA2 and low 2 -1L/2L
12H - cross of MA1 and high or MA2 and high 2 -1H/2H
12HL - MA1/2 and high/low 4 -1H/1L/2H/2L
3 -cross of MA1 and MA2 1
123HL -crosses from 12HL or 3 5 -12HL/3
1_ULT - cross of MA1 with any of price sources(close,low,high,ohlc4 etc…)
2_ULT - cross of MA2 with any of price sources(close,low,high,ohlc4 etc…)
123_ULT – all crosses possible of MA1/2 (all of the above so a lot)
7)CRS CONDS:
“conditions to reduce value back to zero”
>/< - 0 if indicator shows Uptrend and there’s a cross with high of selected MA or 0 if in DNtrend and cross with low. Better for UP/DN trend detection
ALL – 0 if cross of MA with high or low no matter the trend, better for detecting consolidation
ULT – if any cross of selected MA, most crosses so goes to 0 most often
8)MA selection and CONDS:
-MA1: only MA1 is used,if MA1 below price value grows and the other way around
MA1price =-0.02
-MA2 – only MA2 is used, same conditions as MA1 but using MA2
MA2price =-0.02
-BOTH – MA1 and MA2 used, grows when MA1 if below, grows faster if MA1 and MA2 are below and fastest when MA1 and MA2 are below and MA2price=-0.02
-MA1 and MA2 >price=-0.03
-MA1 and MA2 ?price and MA2>MA1=-0.04
9)CONDITIONS SELECTION SUMMARRY:
So when CUSTOM we choose :
1)SOURCE – H/L or OHLC
2)MAs – MA1/MA2/BOTH
3)CRS CONDS (>/<,ALL,ULT)
So for example...
if we take MA1 and ALL value will go to zero if 1HL
if MA1 and >/< - 0 if 1L or 1H (depending if value is positive or negative).(1L or 1H)
If ALL and BOTH zero when 12HL
If BOTH and ULT value goes back to zero if Theres any cross of MA1/MA2 with price or cross of MA1 and MA2.(123_ULT)
If >/< and BOTH – 0 if 12L in DNtrend or 12H if UPtrend
10) OTHERS
-script was created on EURUSD 5M and wasn't tested on different markets
-default values of MA1/MA2 aren't optimalized so do not
-There might be a logical error in the script so let me know if you find it (most probably in 'BOTH')
-thanks to @AlifeToMake for help
-if you have any ideas to improve let me know
-there are also tooltips to help
CNTLibraryLibrary "CNTLibrary"
Custom Functions To Help Code In Pinescript V5
Coded By Christian Nataliano
First Coded In 10/06/2023
Last Edited In 22/06/2023
Huge Shout Out To © ZenAndTheArtOfTrading and his ZenLibrary V5, Some Of The Custom Functions Were Heavily Inspired By Matt's Work & His Pine Script Mastery Course
Another Shout Out To The TradingView's Team Library ta V5
//====================================================================================================================================================
// Custom Indicator Functions
//====================================================================================================================================================
GetKAMA(KAMA_lenght, Fast_KAMA, Slow_KAMA)
Calculates An Adaptive Moving Average Based On Perry J Kaufman's Calculations
Parameters:
KAMA_lenght (int) : Is The KAMA Lenght
Fast_KAMA (int) : Is The KAMA's Fastes Moving Average
Slow_KAMA (int) : Is The KAMA's Slowest Moving Average
Returns: Float Of The KAMA's Current Calculations
GetMovingAverage(Source, Lenght, Type)
Get Custom Moving Averages Values
Parameters:
Source (float) : Of The Moving Average, Defval = close
Lenght (simple int) : Of The Moving Average, Defval = 50
Type (string) : Of The Moving Average, Defval = Exponential Moving Average
Returns: The Moving Average Calculation Based On Its Given Source, Lenght & Calculation Type (Please Call Function On Global Scope)
GetDecimals()
Calculates how many decimals are on the quote price of the current market © ZenAndTheArtOfTrading
Returns: The current decimal places on the market quote price
Truncate(number, decimalPlaces)
Truncates (cuts) excess decimal places © ZenAndTheArtOfTrading
Parameters:
number (float)
decimalPlaces (simple float)
Returns: The given number truncated to the given decimalPlaces
ToWhole(number)
Converts pips into whole numbers © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
ToPips(number)
Converts whole numbers back into pips © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
GetPctChange(value1, value2, lookback)
Gets the percentage change between 2 float values over a given lookback period © ZenAndTheArtOfTrading
Parameters:
value1 (float)
value2 (float)
lookback (int)
BarsAboveMA(lookback, ma)
Counts how many candles are above the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are above the MA
BarsBelowMA(lookback, ma)
Counts how many candles are below the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are below the EMA
BarsCrossedMA(lookback, ma)
Counts how many times the EMA was crossed recently © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many times price recently crossed the EMA
GetPullbackBarCount(lookback, direction)
Counts how many green & red bars have printed recently (ie. pullback count) © ZenAndTheArtOfTrading
Parameters:
lookback (int)
direction (int)
Returns: The bar count of how many candles have retraced over the given lookback & direction
GetSwingHigh(Lookback, SwingType)
Check If Price Has Made A Recent Swing High
Parameters:
Lookback (int) : Is For The Swing High Lookback Period, Defval = 7
SwingType (int) : Is For The Swing High Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing High
GetSwingLow(Lookback, SwingType)
Check If Price Has Made A Recent Swing Low
Parameters:
Lookback (int) : Is For The Swing Low Lookback Period, Defval = 7
SwingType (int) : Is For The Swing Low Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing Low
//====================================================================================================================================================
// Custom Risk Management Functions
//====================================================================================================================================================
CalculateStopLossLevel(OrderType, Entry, StopLoss)
Calculate StopLoss Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLoss (float) : Is The Custom StopLoss Distance, Defval = 2x ATR Below Close
Returns: Float - The StopLoss Level In Actual Price As A
CalculateStopLossDistance(OrderType, Entry, StopLoss)
Calculate StopLoss Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
StopLoss (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The StopLoss Value In Pips
CalculateTakeProfitLevel(OrderType, Entry, StopLossDistance, RiskReward)
Calculate TakeProfit Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLossDistance (float)
RiskReward (float)
Returns: Float - The TakeProfit Level In Actual Price
CalculateTakeProfitDistance(OrderType, Entry, TakeProfit)
Get TakeProfit Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
TakeProfit (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The TakeProfit Value In Pips
CalculateConversionCurrency(AccountCurrency, SymbolCurrency, BaseCurrency)
Get The Conversion Currecny Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
AccountCurrency (simple string) : Is For The Account Currency Used
SymbolCurrency (simple string) : Is For The Current Symbol Currency (Front Symbol)
BaseCurrency (simple string) : Is For The Current Symbol Base Currency (Back Symbol)
Returns: Tuple Of A Bollean (Convert The Currency ?) And A String (Converted Currency)
CalculateConversionRate(ConvertCurrency, ConversionRate)
Get The Conversion Rate Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
ConvertCurrency (bool) : Is To Check If The Current Symbol Needs To Be Converted Or Not
ConversionRate (float) : Is The Quoted Price Of The Conversion Currency (Input The request.security Function Here)
Returns: Float Price Of Conversion Rate (If In The Same Currency Than Return Value Will Be 1.0)
LotSize(LotSizeSimple, Balance, Risk, SLDistance, ConversionRate)
Get Current Lot Size
Parameters:
LotSizeSimple (bool) : Is To Toggle Lot Sizing Calculation (Simple Is Good Enough For Stocks & Crypto, Whilst Complex Is For Forex)
Balance (float) : Is For The Current Account Balance To Calculate The Lot Sizing Based Off
Risk (float) : Is For The Current Risk Per Trade To Calculate The Lot Sizing Based Off
SLDistance (float) : Is The Current Position StopLoss Distance From Its Entry Price
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - Position Size In Units
ToLots(Units)
Converts Units To Lots
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots
ToUnits(Lots)
Converts Lots To Units
Parameters:
Lots (float) : Is For How Many Lots Need To Be Converted Into Units (Minimun 0.01 Units)
Returns: Int - Position Size In Units
ToLotsInUnits(Units)
Converts Units To Lots Than Back To Units
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots That Were Rounded To Units
ATRTrail(OrderType, SourceType, ATRPeriod, ATRMultiplyer, SwingLookback)
Calculate ATR Trailing Stop
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
SourceType (int) : Is To Determine Where To Calculate The ATR Trailing From, Defval = close
ATRPeriod (simple int) : Is To Change Its ATR Period, Defval = 20
ATRMultiplyer (float) : Is To Change Its ATR Trailing Distance, Defval = 1
SwingLookback (int) : Is To Change Its Swing HiLo Lookback (Only From Source Type 5), Defval = 7
Returns: Float - Number Of The Current ATR Trailing
DangerZone(WinRate, AvgRRR, Filter)
Calculate Danger Zone Of A Given Strategy
Parameters:
WinRate (float) : Is The Strategy WinRate
AvgRRR (float) : Is The Strategy Avg RRR
Filter (float) : Is The Minimum Profit It Needs To Be Out Of BE Zone, Defval = 3
Returns: Int - Value, 1 If Out Of Danger Zone, 0 If BE, -1 If In Danger Zone
IsQuestionableTrades(TradeTP, TradeSL)
Checks For Questionable Trades (Which Are Trades That Its TP & SL Level Got Hit At The Same Candle)
Parameters:
TradeTP (float) : Is The Trade In Question Take Profit Level
TradeSL (float) : Is The Trade In Question Stop Loss Level
Returns: Bool - True If The Last Trade Was A "Questionable Trade"
//====================================================================================================================================================
// Custom Strategy Functions
//====================================================================================================================================================
OpenLong(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Long Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Long"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Long Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
OpenShort(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Short Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Short"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Short Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
TP_SLExit(FromID, TPLevel, SLLevel, PercentageClose, Comment, CommentValue)
Exits Based On Predetermined TP & SL Levels
Parameters:
FromID (string) : Is The Trade ID That The TP & SL Levels Be Palced
TPLevel (float) : Is The Take Profit Level
SLLevel (float) : Is The StopLoss Level
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
CloseLong(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Long Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Long"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
CloseShort(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Short Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Short"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
BrokerCheck(Broker)
Checks Traded Broker With Current Loaded Chart Broker
Parameters:
Broker (string) : Is The Current Broker That Is Traded
Returns: Bool - True If Current Traded Broker Is Same As Loaded Chart Broker
OpenPC(LicenseID, OrderType, UseLimit, LimitPrice, SymbolPrefix, Symbol, SymbolSuffix, Risk, SL, TP, OrderComment, Spread)
Compiles Given Parameters Into An Alert String Format To Open Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Open
UseLimit (bool) : Is If We Want To Enter The Position At Exactly The Previous Closing Price
LimitPrice (float) : Is The Limit Price Of The Trade (Only For Pending Orders)
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Risk (float) : Is The Trade Risk Per Trade / Fixed Lot Sizing
SL (float) : Is The Trade SL In Price / In Pips
TP (float) : Is The Trade TP In Price / In Pips
OrderComment (string) : Is The Executed Trade Comment
Spread (float) : is The Maximum Spread For Execution
Returns: String - Pine Connector Order Syntax Alert Message
ClosePC(LicenseID, OrderType, SymbolPrefix, Symbol, SymbolSuffix)
Compiles Given Parameters Into An Alert String Format To Close Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Close
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Returns: String - Pine Connector Order Syntax Alert Message
//====================================================================================================================================================
// Custom Backtesting Calculation Functions
//====================================================================================================================================================
CalculatePNL(EntryPrice, ExitPrice, LotSize, ConversionRate)
Calculates Trade PNL Based On Entry, Eixt & Lot Size
Parameters:
EntryPrice (float) : Is The Trade Entry
ExitPrice (float) : Is The Trade Exit
LotSize (float) : Is The Trade Sizing
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - The Current Trade PNL
UpdateBalance(PrevBalance, PNL)
Updates The Previous Ginve Balance To The Next PNL
Parameters:
PrevBalance (float) : Is The Previous Balance To Be Updated
PNL (float) : Is The Current Trade PNL To Be Added
Returns: Float - The Current Updated PNL
CalculateSlpComm(PNL, MaxRate)
Calculates Random Slippage & Commisions Fees Based On The Parameters
Parameters:
PNL (float) : Is The Current Trade PNL
MaxRate (float) : Is The Upper Limit (In Percentage) Of The Randomized Fee
Returns: Float - A Percentage Fee Of The Current Trade PNL
UpdateDD(MaxBalance, Balance)
Calculates & Updates The DD Based On Its Given Parameters
Parameters:
MaxBalance (float) : Is The Maximum Balance Ever Recorded
Balance (float) : Is The Current Account Balance
Returns: Float - The Current Strategy DD
CalculateWR(TotalTrades, LongID, ShortID)
Calculate The Total, Long & Short Trades Win Rate
Parameters:
TotalTrades (int) : Are The Current Total Trades That The Strategy Has Taken
LongID (string) : Is The Order ID Of The Long Trades Of The Strategy
ShortID (string) : Is The Order ID Of The Short Trades Of The Strategy
Returns: Tuple Of Long WR%, Short WR%, Total WR%, Total Winning Trades, Total Losing Trades, Total Long Trades & Total Short Trades
CalculateAvgRRR(WinTrades, LossTrades)
Calculates The Overall Strategy Avg Risk Reward Ratio
Parameters:
WinTrades (int) : Are The Strategy Winning Trades
LossTrades (int) : Are The Strategy Losing Trades
Returns: Float - The Average RRR Values
CAGR(StartTime, StartPrice, EndTime, EndPrice)
Calculates The CAGR Over The Given Time Period © TradingView
Parameters:
StartTime (int) : Is The Starting Time Of The Calculation
StartPrice (float) : Is The Starting Price Of The Calculation
EndTime (int) : Is The Ending Time Of The Calculation
EndPrice (float) : Is The Ending Price Of The Calculation
Returns: Float - The CAGR Values
//====================================================================================================================================================
// Custom Plot Functions
//====================================================================================================================================================
EditLabels(LabelID, X1, Y1, Text, Color, TextColor, EditCondition, DeleteCondition)
Edit / Delete Labels
Parameters:
LabelID (label) : Is The ID Of The Selected Label
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
Text (string) : Is The Text Than Wants To Be Written In The Label
Color (color) : Is The Color Value Change Of The Label Text
TextColor (color)
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
EditLine(LineID, X1, Y1, X2, Y2, Color, EditCondition, DeleteCondition)
Edit / Delete Lines
Parameters:
LineID (line) : Is The ID Of The Selected Line
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
X2 (int) : Is The X2 Coordinate IN BARINDEX Xloc
Y2 (float) : Is The Y2 Coordinate IN PRICE Yloc
Color (color) : Is The Color Value Change Of The Line
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
//====================================================================================================================================================
// Custom Display Functions (Using Tables)
//====================================================================================================================================================
FillTable(TableID, Column, Row, Title, Value, BgColor, TextColor, ToolTip)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
Column (int) : Is The Current Column Of The Table That Wants To Be Edited
Row (int) : Is The Current Row Of The Table That Wants To Be Edited
Title (string) : Is The String Title Of The Current Cell Table
Value (string) : Is The String Value Of The Current Cell Table
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
ToolTip (string) : Is The ToolTip Of The Current Cell In The Table
Returns: Void
DisplayBTResults(TableID, BgColor, TextColor, StartingBalance, Balance, DollarReturn, TotalPips, MaxDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
StartingBalance (float) : Is The Account Starting Balance
Balance (float)
DollarReturn (float) : Is The Account Dollar Reture
TotalPips (float) : Is The Total Pips Gained / loss
MaxDD (float) : Is The Maximum Drawdown Over The Backtesting Period
Returns: Void
DisplayBTResultsV2(TableID, BgColor, TextColor, TotalWR, QTCount, LongWR, ShortWR, InitialCapital, CumProfit, CumFee, AvgRRR, MaxDD, CAGR, MeanDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
TotalWR (float) : Is The Strategy Total WR In %
QTCount (int) : Is The Strategy Questionable Trades Count
LongWR (float) : Is The Strategy Total WR In %
ShortWR (float) : Is The Strategy Total WR In %
InitialCapital (float) : Is The Strategy Initial Starting Capital
CumProfit (float) : Is The Strategy Ending Cumulative Profit
CumFee (float) : Is The Strategy Ending Cumulative Fee (Based On Randomized Fee Assumptions)
AvgRRR (float) : Is The Strategy Average Risk Reward Ratio
MaxDD (float) : Is The Strategy Maximum DrawDown In Its Backtesting Period
CAGR (float) : Is The Strategy Compounded Average GRowth In %
MeanDD (float) : Is The Strategy Mean / Average Drawdown In The Backtesting Period
Returns: Void
//====================================================================================================================================================
// Custom Pattern Detection Functions
//====================================================================================================================================================
BullFib(priceLow, priceHigh, fibRatio)
Calculates A Bullish Fibonacci Value (From Swing Low To High) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
BearFib(priceLow, priceHigh, fibRatio)
Calculates A Bearish Fibonacci Value (From Swing High To Low) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
GetBodySize()
Gets The Current Candle Body Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN POINTS
GetTopWickSize()
Gets The Current Candle Top Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Top Wick Size IN POINTS
GetBottomWickSize()
Gets The Current Candle Bottom Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Bottom Wick Size IN POINTS
GetBodyPercent()
Gets The Current Candle Body Size As A Percentage Of Its Entire Size Including Its Wicks © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN PERCENTAGE
GetTopWickPercent()
Gets The Current Top Wick Size As A Percentage Of Its Entire Body Size
Returns: Float - The Current Candle Top Wick Size IN PERCENTAGE
GetBottomWickPercent()
Gets The Current Bottom Wick Size As A Percentage Of Its Entire Bodu Size
Returns: Float - The Current Candle Bottom Size IN PERCENTAGE
BullishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Engulfing Candle
BearishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bearish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Engulfing Candle
Hammer(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Star(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Doji(MaxWickSize, MaxBodySize, DojiType, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Doji Candle
Parameters:
MaxWickSize (float) : To Specify The Maximum Lenght Of Its Upper & Lower Wick, Defval = 2
MaxBodySize (float) : To Specify The Maximum Lenght Of Its Candle Body IN PERCENT, Defval = 0.05
DojiType (int)
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Doji Candle
BullishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Harami Candle
BearishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Harami Candle
//====================================================================================================================================================
// Custom Time Functions
//====================================================================================================================================================
BarInSession(sess, useFilter)
Determines if the current price bar falls inside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls within the given time session
BarOutSession(sess, useFilter)
Determines if the current price bar falls outside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls outside the given time session
DateFilter(startTime, endTime)
Determines if this bar's time falls within date filter range © ZenAndTheArtOfTrading
Parameters:
startTime (int)
endTime (int)
Returns: A boolean - true if the current bar falls within the given dates
DayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)
Checks if the current bar's day is in the list of given days to analyze © ZenAndTheArtOfTrading
Parameters:
monday (bool)
tuesday (bool)
wednesday (bool)
thursday (bool)
friday (bool)
saturday (bool)
sunday (bool)
Returns: A boolean - true if the current bar's day is one of the given days
AUSSess()
Checks If The Current Australian Forex Session In Running
Returns: Bool - True If Currently The Australian Session Is Running
ASIASess()
Checks If The Current Asian Forex Session In Running
Returns: Bool - True If Currently The Asian Session Is Running
EURSess()
Checks If The Current European Forex Session In Running
Returns: Bool - True If Currently The European Session Is Running
USSess()
Checks If The Current US Forex Session In Running
Returns: Bool - True If Currently The US Session Is Running
UNIXToDate(Time, ConversionType, TimeZone)
Converts UNIX Time To Datetime
Parameters:
Time (int) : Is The UNIX Time Input
ConversionType (int) : Is The Datetime Output Format, Defval = DD-MM-YYYY
TimeZone (string) : Is To Convert The Outputed Datetime Into The Specified Time Zone, Defval = Exchange Time Zone
Returns: String - String Of Datetime
Wavemeter [theEccentricTrader]█ OVERVIEW
This indicator is a representation of my take on price action based wave cycle theory. The indicator counts the number of confirmed wave cycles, keeps a rolling tally of the average wave length, wave height and frequency, and displays the statistics in a table. The indicator also displays the current wave measurements as an optional feature.
█ 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.
Wave Cycles
A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. As can be seen in the example above, the first swing high or swing low will set the course for the sequence of wave cycles that follow; a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa.
Wave Length
Wave length is here measured in terms of bar distance between the start and end of a wave cycle. For example, if the current wave cycle ends on a swing low the wave length will be the difference in bars between the current swing low and current swing high. In such a case, if the current swing low completes on candle 100 and the current swing high completed on candle 95, we would simply subtract 95 from 100 to give us a wave length of 5 bars.
Average wave length is here measured in terms of total bars as a proportion as total waves. The average wavelength is calculated by dividing the total candles by the total wave cycles.
Wave Height
Wave height is here measured in terms of current range. For example, if the current peak price is 100 and the current trough price is 80, the wave height will be 20.
Amplitude
Amplitude is here measured in terms of current range divided by two. For example if the current peak price is 100 and the current trough price is 80, the amplitude would be calculated by subtracting 80 from 100 and dividing the answer by 2 to give us an amplitude of 10.
Frequency
Frequency is here measured in terms of wave cycles per second (Hertz). For example, if the total wave cycle count is 10 and the amount of time it has taken to complete these 10 cycles is 1-year (31,536,000 seconds), the frequency would be calculated by dividing 10 by 31,536,000 to give us a frequency of 0.00000032 Hz.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
█ FEATURES
Inputs
Show Sample Period
Start Date
End Date
Position
Text Size
Show Current
Show Lines
Table
The table is colour coded, consists of two columns and, as many as, nine rows. Blue cells display the total wave cycle count and average wave measurements. Green cells display the current wave measurements. And the final row in column one, coloured black, displays the sample period. Both current wave measurements and sample period cells can be hidden at the user’s discretion.
Lines
For a visual aid to the wave cycles, I have added a blue line that traces out the waves on the chart. These lines can be hidden at the user’s discretion.
█ HOW TO USE
The indicator is intended for research purposes, strategy development and strategy optimisation. 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.
For example, the indicator can be used to compare the current range and frequency with the average range and frequency, which can be useful for gauging current market conditions versus historic and getting a feel for how different markets and timeframes behave.
█ 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.
It is also worth noting that 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.
Candle Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed candle 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.
Upper Candle Trends
A higher high candle is one that closes with a higher high price than the high price of the preceding candle.
A lower high candle is one that closes with a lower high price than the high price of the preceding candle.
A double-top candle is one that closes with a high price that is equal to the high price of the preceding candle.
Lower Candle Trends
A higher low candle is one that closes with a higher low price than the low price of the preceding candle.
A lower low candle is one that closes with a lower low price than the low price of the preceding candle.
A double-bottom candle is one that closes with a low price that is equal to the low price of the preceding candle.
█ FEATURES
Inputs
Start Date
End Date
Position
Text Size
Show Sample Period
Show Plots
Table
The table is colour coded, consists of three columns and twenty-two rows. Blue cells denote all candle scenarios, green cells denote green candle scenarios and red cells denote red candle scenarios.
The candle 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 twenty-two, displays the sample period which can be adjusted or hidden via indicator settings.
Rows two and three in the third column of the table display the total green and red candles as percentages of total candles. Rows four to nine in column three, coloured blue, display the corresponding candle scenarios as percentages of total candles. Rows ten to fifteen in column three, coloured green, display the corresponding candle scenarios as percentages of total green candles. And lastly, rows sixteen to twenty-one in column three, coloured red, display the corresponding candle scenarios as percentages of total red candles.
Plots
I have added plots as a visual aid to the various candle scenarios listed in the table. Green up-arrows denote higher high candles when above bar and higher low candles when below bar. Red down-arrows denote lower high candles when above bar and lower low candles when below bar. Similarly, blue diamonds when above bar denote double-top candles and when below bar denote double-bottom candles. These plots can also 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 green candles to red. Or a greater proportion of higher low green candles to lower low green candles. Such information can be very useful when conducting top down analysis across multiple timeframes, or considering trailing stop loss methods.
What you do with these statistics and how far you decide to take your research is entirely up to you, the possibilities are endless.
This is just the first and most basic in a series of indicators that can be used to study objective price action scenarios and develop a systematic approach to trading.
█ 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.
It is also worth noting that 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.
MomentumIndicatorsLibrary "MomentumIndicators"
This is a library of 'Momentum Indicators', also denominated as oscillators.
The purpose of this library is to organize momentum indicators in just one place, making it easy to access.
In addition, it aims to allow customized versions, not being restricted to just the price value.
An example of this use case is the popular Stochastic RSI.
# Indicators:
1. Relative Strength Index (RSI):
Measures the relative strength of recent price gains to recent price losses of an asset.
2. Rate of Change (ROC):
Measures the percentage change in price of an asset over a specified time period.
3. Stochastic Oscillator (Stoch):
Compares the current price of an asset to its price range over a specified time period.
4. True Strength Index (TSI):
Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the
absolute price change.
The values of both are smoothed twice to reduce noise, and the final result is normalized
in a range between 100 and -100.
5. Stochastic Momentum Index (SMI):
Combination of the True Strength Index with a signal line to help identify turning points in the market.
6. Williams Percent Range (Williams %R):
Compares the current price of an asset to its highest high and lowest low over a specified time period.
7. Commodity Channel Index (CCI):
Measures the relationship between an asset's current price and its moving average.
8. Ultimate Oscillator (UO):
Combines three different time periods to help identify possible reversal points.
9. Moving Average Convergence/Divergence (MACD):
Shows the difference between short-term and long-term exponential moving averages.
10. Fisher Transform (FT):
Normalize prices into a Gaussian normal distribution.
11. Inverse Fisher Transform (IFT):
Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is through the
application of an inverse transformation to the hyperbolic tangent function.
This transformation takes the values of the FT, which range from -infinity to +infinity, to a scale limited
between -1 and +1, allowing them to be more easily visualized and compared.
12. Premier Stochastic Oscillator (PSO):
Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing average of
the %K value, resulting in a symmetric scale of 1 to -1
# Indicators of indicators:
## Stochastic:
1. Stochastic of RSI (Relative Strengh Index)
2. Stochastic of ROC (Rate of Change)
3. Stochastic of UO (Ultimate Oscillator)
4. Stochastic of TSI (True Strengh Index)
5. Stochastic of Williams R%
6. Stochastic of CCI (Commodity Channel Index).
7. Stochastic of MACD (Moving Average Convergence/Divergence)
8. Stochastic of FT (Fisher Transform)
9. Stochastic of Volume
10. Stochastic of MFI (Money Flow Index)
11. Stochastic of On OBV (Balance Volume)
12. Stochastic of PVI (Positive Volume Index)
13. Stochastic of NVI (Negative Volume Index)
14. Stochastic of PVT (Price-Volume Trend)
15. Stochastic of VO (Volume Oscillator)
16. Stochastic of VROC (Volume Rate of Change)
## Inverse Fisher Transform:
1.Inverse Fisher Transform on RSI (Relative Strengh Index)
2.Inverse Fisher Transform on ROC (Rate of Change)
3.Inverse Fisher Transform on UO (Ultimate Oscillator)
4.Inverse Fisher Transform on Stochastic
5.Inverse Fisher Transform on TSI (True Strength Index)
6.Inverse Fisher Transform on CCI (Commodity Channel Index)
7.Inverse Fisher Transform on Fisher Transform (FT)
8.Inverse Fisher Transform on MACD (Moving Average Convergence/Divergence)
9.Inverse Fisher Transfor on Williams R% (Williams Percent Range)
10.Inverse Fisher Transfor on CMF (Chaikin Money Flow)
11.Inverse Fisher Transform on VO (Volume Oscillator)
12.Inverse Fisher Transform on VROC (Volume Rate of Change)
## Stochastic Momentum Index:
1.Stochastic Momentum Index of RSI (Relative Strength Index)
2.Stochastic Momentum Index of ROC (Rate of Change)
3.Stochastic Momentum Index of VROC (Volume Rate of Change)
4.Stochastic Momentum Index of Williams R% (Williams Percent Range)
5.Stochastic Momentum Index of FT (Fisher Transform)
6.Stochastic Momentum Index of CCI (Commodity Channel Index)
7.Stochastic Momentum Index of UO (Ultimate Oscillator)
8.Stochastic Momentum Index of MACD (Moving Average Convergence/Divergence)
9.Stochastic Momentum Index of Volume
10.Stochastic Momentum Index of MFI (Money Flow Index)
11.Stochastic Momentum Index of CMF (Chaikin Money Flow)
12.Stochastic Momentum Index of On Balance Volume (OBV)
13.Stochastic Momentum Index of Price-Volume Trend (PVT)
14.Stochastic Momentum Index of Volume Oscillator (VO)
15.Stochastic Momentum Index of Positive Volume Index (PVI)
16.Stochastic Momentum Index of Negative Volume Index (NVI)
## Relative Strength Index:
1. RSI for Volume
2. RSI for Moving Average
rsi(source, length)
RSI (Relative Strengh Index). Measures the relative strength of recent price gains to recent price losses of an asset.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of RSI
roc(source, length)
ROC (Rate of Change). Measures the percentage change in price of an asset over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of ROC
stoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Stochastic Oscillator. Compares the current price of an asset to its price range over a specified time period.
Parameters:
kLength
kSmoothing : (int) Period for smoothig stochastic
dSmoothing : (int) Period for signal (moving average of stochastic)
maTypeK : (int) Type of Moving Average for Stochastic Oscillator
maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal
almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Oscillator and Signal
almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Oscillator and Signal
lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Oscillator and Signal
Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator
stoch(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Stochastic Oscillator. Customized source. Compares the current price of an asset to its price range over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
kLength : (int) Period of loopback to calculate the stochastic
kSmoothing : (int) Period for smoothig stochastic
dSmoothing : (int) Period for signal (moving average of stochastic)
maTypeK : (int) Type of Moving Average for Stochastic Oscillator
maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal
almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Stoch and Signal
almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Stoch and Signal
lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Stoch and Signal
Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator
tsi(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet)
TSI (True Strengh Index). Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the absolute price change.
The values of both are smoothed twice to reduce noise, and the final result is normalized in a range between 100 and -100.
Parameters:
source : (float) Source of series (close, high, low, etc.)
shortLength : (int) Short length
longLength : (int) Long length
maType : (int) Type of Moving Average for TSI
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: (float) TSI
smi(sourceTSI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
SMI (Stochastic Momentum Index). A TSI (True Strengh Index) plus a signal line.
Parameters:
sourceTSI : (float) Source of series for TSI (close, high, low, etc.)
shortLengthTSI : (int) Short length for TSI
longLengthTSI : (int) Long length for TSI
maTypeTSI : (int) Type of Moving Average for Signal of TSI
almaOffsetTSI : (float) Offset for Arnaud Legoux Moving Average
almaSigmaTSI : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSetTSI : (int) Offset for Least Squares Moving Average
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
Returns: A tuple with TSI, signal of TSI and histogram of difference
wpr(source, length)
Williams R% (Williams Percent Range). Compares the current price of an asset to its highest high and lowest low over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of Williams R%
cci(source, length, maType, almaOffset, almaSigma, lsmaOffSet)
CCI (Commodity Channel Index). Measures the relationship between an asset's current price and its moving average.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
maType : (int) Type of Moving Average
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: (float) Series of CCI
ultimateOscillator(fastLength, middleLength, slowLength)
UO (Ultimate Oscilator). Combines three different time periods to help identify possible reversal points.
Parameters:
fastLength : (int) Fast period of loopback
middleLength : (int) Middle period of loopback
slowLength : (int) Slow period of loopback
Returns: (float) Series of Ultimate Oscilator
ultimateOscillator(source, fastLength, middleLength, slowLength)
UO (Ultimate Oscilator). Customized source. Combines three different time periods to help identify possible reversal points.
Parameters:
source : (float) Source of series (close, high, low, etc.)
fastLength : (int) Fast period of loopback
middleLength : (int) Middle period of loopback
slowLength : (int) Slow period of loopback
Returns: (float) Series of Ultimate Oscilator
macd(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet)
MACD (Moving Average Convergence/Divergence). Shows the difference between short-term and long-term exponential moving averages.
Parameters:
source : (float) Source of series (close, high, low, etc.)
fastLength : (int) Period for fast moving average
slowLength : (int) Period for slow moving average
signalLength : (int) Signal length
maTypeFast : (int) Type of fast moving average
maTypeSlow : (int) Type of slow moving average
maTypeMACD : (int) Type of MACD moving average
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: A tuple with MACD, Signal, and Histgram
fisher(length)
Fisher Transform. Normalize prices into a Gaussian normal distribution.
Parameters:
length
Returns: A tuple with Fisher Transform and signal
fisher(source, length)
Fisher Transform. Customized source. Normalize prices into a Gaussian normal distribution.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length
Returns: A tuple with Fisher Transform and signal
inverseFisher(source, length, subtrahend, denominator)
Inverse Fisher Transform.
Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is
through the application of an inverse transformation to the hyperbolic tangent function.
This transformation takes the values of the FT, which range from -infinity to +infinity,
to a scale limited between -1 and +1, allowing them to be more easily visualized and compared.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period for loopback
subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.
denominator
Returns: (float) Series of Inverse Fisher Transform
premierStoch(length, smoothlen)
Premier Stochastic Oscillator (PSO).
Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing
average of the %K value, resulting in a symmetric scale of 1 to -1.
Parameters:
length : (int) Period for loopback
smoothlen : (int) Period for smoothing
Returns: (float) Series of PSO
premierStoch(source, smoothlen, subtrahend, denominator)
Premier Stochastic Oscillator (PSO) of custom source.
Normalizes the source by applying a five-period double exponential smoothing average.
Parameters:
source : (float) Source of series (close, high, low, etc.)
smoothlen : (int) Period for smoothing
subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.
denominator
Returns: (float) Series of PSO
stochRsi(sourceRSI, lengthRSI, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
sourceRSI
lengthRSI
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochRoc(sourceROC, lengthROC, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
sourceROC
lengthROC
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochUO(fastLength, middleLength, slowLength, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
fastLength
middleLength
slowLength
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
shortLength
longLength
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochWPR(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochFT(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVolume(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochMFI(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochOBV(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochPVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochNVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochPVT(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVROC(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
iftRSI(sourceRSI, lengthRSI, lengthIFT)
Parameters:
sourceRSI
lengthRSI
lengthIFT
iftROC(sourceROC, lengthROC, lengthIFT)
Parameters:
sourceROC
lengthROC
lengthIFT
iftUO(fastLength, middleLength, slowLength, lengthIFT)
Parameters:
fastLength
middleLength
slowLength
lengthIFT
iftStoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD, lengthIFT)
Parameters:
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
lengthIFT
iftTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
shortLength
longLength
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
length
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftFisher(length, lengthIFT)
Parameters:
length
lengthIFT
iftMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftWPR(source, length, lengthIFT)
Parameters:
source
length
lengthIFT
iftMFI(source, length, lengthIFT)
Parameters:
source
length
lengthIFT
iftCMF(length, lengthIFT)
Parameters:
length
lengthIFT
iftVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftVROC(length, lengthIFT)
Parameters:
length
lengthIFT
smiRSI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiROC(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVROC(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiWPR(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiFT(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiFT(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiCCI(source, length, maTypeCCI, almaOffsetCCI, almaSigmaCCI, lsmaOffSetCCI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
maTypeCCI
almaOffsetCCI
almaSigmaCCI
lsmaOffSetCCI
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiUO(fastLength, middleLength, slowLength, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
fastLength
middleLength
slowLength
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVol(shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiMFI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiCMF(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiOBV(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiPVT(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiPVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiNVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
rsiVolume(length)
Parameters:
length
rsiMA(sourceMA, lengthMA, maType, almaOffset, almaSigma, lsmaOffSet, lengthRSI)
Parameters:
sourceMA
lengthMA
maType
almaOffset
almaSigma
lsmaOffSet
lengthRSI
TRADING MADE SIMPLEThis indicator shows market structure. The standard method of using Williams Highs and Lows as pivots, is something of an approximation.
What's original here is that we follow rules to confirm Local Highs and Local Lows, and strictly enforce that a Low can only follow a confirmed High and vice-versa.
-- Highs and Lows
To confirm a candle as a Local High, you need a later candle to Close below its Low. To confirm a Local Low, you need a Close above its High.
A Low can only follow a High (after it's been confirmed). You can't go e.g High, High, Low, Low, only High, Low, High, Low.
When price makes Higher Highs and Higher Lows, market structure is said to be bullish. When price makes Lower Lows and Lower Highs, it's bearish.
I've defined the in-between Highs and Lows as "Ranging", meaning, neutral. They could be trend continuation or reversal.
-- Bullish/Bearish Breaks
A Bullish break in market structure is when the Close of the current candle goes higher than the previous confirmed Local High.
A Bearish Break is when the Close of the current candle goes lower than the most recent confirmed Local Low.
I chose to use Close rather than High to reduce edge case weirdness. The breaking candle often ends up being a big one, thus the close of that candle can be a poor entry.
You can get live warnings by setting the alert to Options: Only Once, because during a candle, the current price is taken as the Close.
Breaks are like early warnings of a change in market bias, because you're not waiting for a High or Low to be formed and confirmed.
Buy The Dip / Sell The Rally
Buy The Dip is a label I gave to the first Higher Low in a bullish market structure. Sell The Rally is the first Lower High in a bearish market structure.
These *might* be good buying/selling opportunities, but you still need to do your own analysis to confirm that.
== USAGE ==
The point of knowing market structure is so you don't make bullish bets in a bearish market and vice versa -
or if you do at least you're aware that that's what you're doing, and hopefully have some overwhelmingly good reason to do so.
These are not signals to be traded on their own. You still need a trade thesis. Use with support & resistance and your other favourite indicators.
Works on any market on any timeframe. Be aware that market structure will be different on different timeframes.
IMPORTANT: If you're not seeing what you expect, check your settings and re-read this entire description carefully. Confirming Highs and Lows can get deceptively complex.
Dekidaka-Ashi - Candles And Volume Teaming Up (Again)The introduction of candlestick methods for market price data visualization might be one of the most important events in the history of technical analysis, as it totally changed the way to see a trading chart. Candlestick charts are extremely efficient, as they allow the trader to visualize the opening, high, low and closing price (OHLC) each at the same time, something impossible with a traditional line chart. Candlesticks are also cleaner than bars charts and make a more efficient use of space. Japanese peoples are always better than everyone at an incredible amount of stuff, look at what they made, the candlesticks/renko/kagi/heikin-ashi charts, the Ichimoku, manga, ecchi...
However classical candlesticks only include historical market price data, and won't include other type of data such as volume, which is considered by many investors a key information toward effective financial forecasting as volume is an indicator of trading activity. In order to tackle to this problem solutions where proposed, the most common one being to adapt the width of the candle based on the amount of volume, this method is the most commonly accepted one when it comes to visualizing both volume and OHLC data using candlesticks.
Now why proposing an additional tool for volume data visualization ? Because the classical width approach don't provide usable data regarding volume (as the width is directly related to the volume data). Therefore a new trading tool based on candlesticks that allow the trader to gain access to information about the volume is proposed. The approach is based on rescaling the volume directly to the price without the direct use of user settings. We will also see that this tool allow to create support and resistances as well as providing signals based on a breakout methodology.
Dekidaka-Ashi - Kakatte Koi Yo!
"Dekidaka" (出来高) mean "Volume" in a financial context, while "Ashi" (足) mean "leg" or "bar". In general methods based on candlesticks will have "Ashi" in their name.
Now that the name of the indicator has been explained lets see how it works, the indicator should be overlayed directly to a candlestick chart. The proposed method don't alter the shape of the candlesticks and allow to visualize any information given by the candles. As you can see on the figure below the candle body of the proposed tool only return the border of the candle, this allow to show the high/low wick of the candle.
The body size of the candle is based on two things : the absolute close/open difference, and the volume, if the absolute close/open difference is high and the volume is high then the body of the candle will be clearly visible, if the volume is high but the absolute close/open difference is low, then the body will be less visible. This approach is used because of the rescaling method used, the volume is divided by the sum between the current volume value and the precedent volume value, this rescale the volume in a (0,1) range, this result is multiplied by the absolute close/open difference and added/subtracted to the high/low price. The original approach was based on normalization using the rolling maximum, but this approach would have led to repainting.
You have access to certain settings that can help you obtain a better visualization, the first one being the body size setting, with higher values increasing the body amplitude.
In green body with size 2, in red with size 1. The smooth parameter will smooth the volume data before being used, this allow to create more visible bodies.
Here smooth = 100.
Making Bands From The Dekidaka-Ashi
This tool is made so it output two rescaled volume values, with the highest value being denoted as "Dekidaka-high" and the lowest one as "Dekidaka-low". In order to get bands we must use two moving averages, one using the Dekidaka-high as input and the other one using Dekidaka-low, the body size parameter should be fairly high, therefore i will hide the tool as it could cause trouble visualizing the bands.
Bands with both MA's of period 20 and the body size equal to 20. Larger periods of the MA's will require a larger amount of body size.
Breakout Signals
There is a wide variety of signals that can be made from candles, ones i personally like comes from the HA candles. The proposed tool is no exception and can produce a wide variety of signals. The signals generated are basic ones based on a breakout methodology, here is each signal with their associated label :
Strong Bullish signal "⇈" : The high price cross the Dekidaka-high and the closing price is greater than the opening price
Strong Bearish signal "⇊" : The low price cross the Dekidaka-low and the closing price is lower than the opening price
Weak Bullish signal "↑" : The high price cross the Dekidaka-high and the closing price is lower than the opening price
Weak Bearish signal "↓" : The low price cross the Dekidaka-low and the closing price is greater than the opening price
Uncertain "↕" : The high price cross the Dekidaka-high and the low price cross the the Dekidaka-low
In order to see the signals on the chart check the "Show signals" option. Note that such signals are not based on an advanced study, and even if they are based on a breakout methodology we can see that volatile movement rarely produce signals, therefore signals mostly occur during low volume/volatility periods, which isn't necessarily a great thing.
Conclusion
A trading tool based on candlesticks that aim to include volume information has been presented and a brief methodology has been introduced. A study of the signals generated is required, however i'am not confident at all on their accuracy, i could work on that in the future. We have also seen how to make bands from the tool.
Candlesticks remain a beautiful charting technique that can provide an enormous amount of information to the trader, and even if the accuracy of patterns based on candlesticks is subject to debates, we can all agree that candlesticks will remain the most widely used type of financial chart.
On a side note i mostly use a dark color for a bullish candle, and a light gray for a bearish candle, with the border color being of the same color as the bullish candle. This is in my opinion the best setup for a candlestick chart, as candles using the traditional green/red can kill the eyes and because this setup allow to apply a wide variety of colors to the plot of overlayed indicators without the fear of causing conflict with the candles color.
Thanks for reading ! :3 Nya
A Word
This morning i received some hateful messages on twitter, the users behind them certainly coming from tradingview, so lets be clear, i know i'am not the most liked person in this community, i know that perfectly, but no one merit to be receive hateful messages. I'am not responsible for the losses of peoples using my indicators, nor is tradingview, using technical indicators does not guarantee long term returns, your ability to be profitable will mostly be based on the quality and quantity of knowledge you have.
cd_VWAP_mtg_CxCd_VWAP_mtg_Cx
Overview
The most important condition for being successful and profitable in the market is to consistently follow the same rules without compromise, while the price constantly moves in countless different ways.
Regardless of the concept or trading school, those who have rules win.
In this indicator, we will define and use three main sections to set and apply our rules.
The indicator uses the VWAP (Volume Weighted Average Price) — price weighted by volume.
Two VWAPs can be displayed either by manually entering date and time, or by selecting from the menu.
From the menu, you can select the following reference levels:
• HTF Open: Opening candle of the higher timeframe
• ATH / ATL: All-Time High / All-Time Low candles
• PMH / PML, PWH / PWL, PDH / PDL, PH4H / PH4L: Previous Month, Week, Day, or H4 Highs/Lows
• MH / ML, WH / WL, DH / DL, H4H / H4L: Current Month, Week, Day, or H4 Highs/Lows
Additionally, it includes:
• Mitigation / Order Block zones (local buyer-seller balance) across two timeframes.
• Buy/Sell Side Liquidity levels (BSL / SSL) from the aligned higher timeframe (target levels).
________________________________________
Components and Usage
1 – VWAP
Calculated using the classical method:
• High + Volume for the upper value
• Close + Volume for the middle value
• Low + Volume for the lower value
The VWAP is displayed as a colored band, where the coloring represents the bias.
Let’s call this band FVB (Fair Value Band) for ease of explanation.
The FVB represents the final line of defense, the buyer/seller boundary, and in technical terms, it can be viewed as premium/discount zones or support/resistance levels.
Within this critical area, the strong side continues its move, while the weaker side is forced to retreat.
But does the side that breaks beyond the band always keep going?
We all know that’s not always the case — in different pairs and timeframes, price often violates both the upper and lower edges multiple times.
To achieve more consistent analysis, we’ll define a new set of rules.
________________________________________
2 – Mitigation / Order Blocks
In trading literature, there are dozens of different definitions and uses of mitigation or order blocks.
Here, we will interpret the candlesticks to create our own definition, and we’ll use the zones defined by candles that fit this pattern.
For simplicity, let’s abbreviate mitigation as “mtg.”
For a candle to be selected as an mtg, it must clearly show strength from one side (buyers or sellers) — which can also be observed visually on the chart.
________________________________________
Bullish mtg criteria:
1. The first candle must be bullish (close > open) → buyers are strong.
2. The next candle makes a new high (buyers push higher) but fails to close above and pulls back to close inside the previous range → sellers react.
It also must not break the previous low → buyers defend.
3. In the following candle(s), as long as the first candle’s low is protected and the second candle’s high is broken, it indicates buyer strength → a bullish mtg is confirmed.
When price returns to this zone later (gets mitigated), the expectation is that the zone holds and price pushes upward again.
If the low is violated, the mtg becomes invalid.
In technical terms:
If the previous candle’s high is broken but no close occurs above it, the expectation is a reversal move that will retest its low.
Question:
What if the low is protected and in the next candle(s) a new high forms?
Answer: → Bullish mtg.
Bearish mtg (opposite)
3 – Buy/Sell Side Liquidity Levels
With the help of the aligned higher timeframe (swing points), we will define our market structure framework and set our liquidity targets accordingly.
Let’s put the pieces together.
If we continue explaining from a trade-focused perspective, our first priority should be our bias — our projection or expectation of the market’s potential movement.
We will determine this bias using the FVB.
Since we know the band often gets violated on both sides, we want the price action to convince us of its strength.
To do that, we’ll use the first candle that closes beyond the band.
The distance from that candle’s high to low will be our threshold range
Bullish level = high + (candle length × coefficient)
Bearish level = low - (candle length × coefficient)
When the price closes beyond this threshold, it demonstrates strength, and our bias will now align in that direction.
How long will this bias remain valid?
→ Until a closing candle appears on the opposite side of the band.
If a close occurs on the opposite side, then a new bias will only be confirmed once the new threshold level is broken.
During the period in between, we have no bias.
Let’s continue on the chart:
Now that our bias has been established, where and how do we look for trade opportunities?
There are two possible entry approaches:
• Aggressive entry: Enter immediately with the breakout.
• Conservative entry: Wait for a pullback and enter once a suitable structure forms.
(The choice depends on the user’s preference.)
At this stage, the user can apply their own entry model. Let’s give an example:
Let’s assume we’re looking for setups using HTF sweep + LTF CISD confirmation.
Once our bias turns bearish, we look for an HTF sweep forming on or near an FVB or mtg block, and then confirm the entry with a CISD signal.
In summary:
• FVB defines the bias, the entry zone, and the target zone.
• Mtg blocks represent entry zones.
• BSL / SSL levels suggest target zones.
Overlapping FVB and mtg blocks are expected to be more effective.
The indicator also provides an option for a second FVB.
A band attached to a lower timeframe can be used as confirmation.
• Main band: Bias + FVB
• Extra band: Entry trigger confirmed by a close beyond it.
Mtg blocks can provide trade entry opportunities, especially when the price is moving strongly in one direction (flow).
Consecutive or complementary mtg blocks indicate that the price is decisive in one direction, while sometimes also showing areas where we should wait before entering.
Mtg blocks that contain an FVG (Fair Value Gap) within their body are expected to be more effective.
Settings:
The default values are set to 1-3-5m, optimized for scalping trades.
VWAP settings:
Main VWAP (FVB):
• Can be set by selecting a start time, manually entering date and time, or choosing a predefined level.
Extra VWAP (FVB):
• Set from the menu. If not needed, select “none.”
• Visibility, color, and fill settings for VWAP are located here.
• Threshold levels visibility and color options are also in this section.
• The multiplier is used for calculating the threshold level.
Important:
• If the Extra VWAP is selected but not displayed, you need to increase the chart timeframe.
o Example: If the chart is on 3m and you select WH from the extra options, it will not display correctly.
• Upper limits for VWAP:
o 1m and 3m charts: daily High/Low
o 5m chart: weekly High/Low
________________________________________
Mtg Settings:
• Visibility and color settings for blocks are configured here.
• To display on a second timeframe, the box must be checked and the timeframe specified.
• Optional display modes: “only active blocks,” “only last violated mtg,” or “all.”
• For confirmation and removal criteria, choosing high/low or close determines the source used for mtg block formation and deletion conditions.
BSL/SSL Settings:
• Visibility, color, font size, and line style can be configured in this section.
When “Auto” is selected, the aligned timeframe is determined automatically by the indicator, while in manual mode, the user defines the timeframe.
Final Words:
Simply opening trades every time the price touches the VWAP or mtg blocks will not make you a profitable trader. Searching for setups with similar structures while maintaining proper risk management will yield better results in the long run.
I would be happy to hear your feedback and suggestions.
Happy trading!
Institutional Activity DetectorInstitutional Activity Detector - Complete Tutorial
Table of Contents
Installation
Understanding the Indicator
Signal Interpretation
Settings Configuration
Trading Strategies
Best Practices
Common Mistakes to Avoid
1. Installation {#installation}
Step-by-Step Setup:
Step 1: Access TradingView
Go to TradingView.com
Log in to your account (free account works fine)
Step 2: Open Pine Editor
Click on "Pine Editor" at the bottom of the chart
If you don't see it, go to the top menu and select "Pine Editor"
Step 3: Add the Script
Click "New" to create a new indicator
Delete any default code
Copy the entire Institutional Activity Detector code
Paste it into the editor
Step 4: Save and Apply
Click "Save" (give it a name like "Inst Detector")
Click "Add to Chart"
The indicator will now appear on your chart
2. Understanding the Indicator {#understanding}
What It Detects:
This indicator identifies institutional traders (banks, hedge funds, market makers) by analyzing:
Volume Analysis
Detects unusual volume spikes that indicate large players entering
Compares current volume to 20-period average
Institutional trades create volume 2-5x normal levels
Order Flow
Delta: Difference between buying and selling volume
Positive delta = More buying pressure
Negative delta = More selling pressure
Institutions leave "footprints" in order flow
Price Action Patterns
Bullish Rejection Wicks:
| <- Small upper wick
|
███ <- Small body
███
|
|
| <- Large lower wick (rejection)
Indicates institutions bought aggressively at lower prices
Bearish Rejection Wicks:
|
|
| <- Large upper wick (rejection)
|
███ <- Small body
███
| <- Small lower wick
Indicates institutions sold aggressively at higher prices
Liquidity Grabs
Institutions often:
Push price above resistance or below support
Trigger stop losses (grab liquidity)
Reverse direction and trade the other way
Dark Pool Activity
Large block trades executed off-exchange:
High volume with minimal price movement
Indicates institutional accumulation/distribution without moving price
3. Signal Interpretation {#signals}
Signal Types:
🟢 INSTITUTIONAL BUY Signal
Appears as green triangle below candle with strength number (2-5)
What it means:
Institutions are actively accumulating (buying)
Higher strength = More confirmation factors
Strength Levels:
2-3: Moderate confidence - Wait for confirmation
4: High confidence - Strong institutional interest
5: Maximum confidence - Multiple factors aligned
🔴 INSTITUTIONAL SELL Signal
Appears as red triangle above candle with strength number (2-5)
What it means:
Institutions are actively distributing (selling)
Higher strength = More confirmation factors
🟠 Dark Pool (DP) Marker
Small orange diamond
What it means:
Large block trade executed
Accumulation/distribution happening quietly
Often precedes significant moves
Liquidity Zones
Red boxes above price = Resistance/sell liquidity
Green boxes below price = Support/buy liquidity
Institutions target these zones to trigger stops
4. Settings Configuration {#settings}
Recommended Settings by Asset Type:
For Stocks (SPY, AAPL, TSLA):
Volume Spike Multiplier: 2.0
Volume Average Period: 20
Delta Threshold: 70%
Minimum Signal Strength: 3
Timeframe: 5m, 15m, 1H
For Forex (EUR/USD, GBP/USD):
Volume Spike Multiplier: 1.5
Volume Average Period: 30
Delta Threshold: 65%
Minimum Signal Strength: 3
Timeframe: 15m, 1H, 4H
For Crypto (BTC, ETH):
Volume Spike Multiplier: 2.5
Volume Average Period: 20
Delta Threshold: 70%
Minimum Signal Strength: 4
Timeframe: 15m, 1H, 4H
For Futures (ES, NQ):
Volume Spike Multiplier: 2.0
Volume Average Period: 20
Delta Threshold: 75%
Minimum Signal Strength: 3
Timeframe: 5m, 15m, 30m
Parameter Explanations:
Volume Spike Multiplier (1.0 - 10.0)
Lower = More sensitive (more signals, some false)
Higher = Less sensitive (fewer signals, more reliable)
Start with 2.0 and adjust based on your asset's volatility
Delta Threshold % (50 - 100)
Measures buying vs selling pressure
70% = Strong institutional bias required
Lower for ranging markets, higher for trending
Minimum Signal Strength (2 - 5)
Number of factors that must align for a signal
2 = Very sensitive (many signals)
5 = Very conservative (rare signals)
Recommended: 3-4 for balance
5. Trading Strategies {#strategies}
Strategy 1: Liquidity Grab Reversal
Setup:
Price approaches a liquidity zone (green/red box)
Price penetrates the zone briefly
Institutional BUY/SELL signal appears
Price reverses away from the zone
Entry:
Enter on the signal candle close
Or wait for next candle confirmation
Stop Loss:
Below the liquidity grab low (for buys)
Above the liquidity grab high (for sells)
Take Profit:
2:1 or 3:1 risk/reward ratio
Or next opposing liquidity zone
Example:
Price drops below support → Triggers stops →
Institutional BUY signal (4-5 strength) →
Enter LONG → Price rallies
Strategy 2: Trend Continuation
Setup:
Identify the trend (higher highs/higher lows for uptrend)
Wait for pullback to support in uptrend
Institutional BUY signal appears during pullback
Confirms institutions are adding to positions
Entry:
Enter on signal with strength ≥ 4
Or next candle after signal
Stop Loss:
Below the pullback low + small buffer
Take Profit:
Previous swing high
Or trailing stop using ATR
Strategy 3: Dark Pool Accumulation
Setup:
Dark Pool (DP) markers appear multiple times
Price consolidates in tight range
Institutional BUY signal with high strength appears
Breakout occurs
Entry:
Enter on breakout candle after signal
Or on retest of breakout level
Stop Loss:
Below consolidation range
Take Profit:
Measured move (height of consolidation projected)
Strategy 4: Divergence Play
Setup:
Price makes lower low
MFI/RSI makes higher low (bullish divergence)
Institutional BUY signal appears
Volume confirms with spike
Entry:
Enter on signal candle or next
Stop Loss:
Below the divergence low
Take Profit:
Previous swing high or resistance
6. Best Practices {#best-practices}
✅ DO's:
1. Use Multiple Timeframes
Check higher timeframe for trend direction
Trade signals that align with higher timeframe
Example: 15m signals in direction of 1H trend
2. Combine with Key Levels
Support/resistance
Supply/demand zones
Previous day high/low
Round numbers (psychological levels)
3. Wait for Confirmation
Don't rush into trades
Let the signal candle close
Watch next candle for follow-through
4. Check the Metrics Table
Look at Relative Volume (should be >2.0)
Check Delta % (should be strong positive/negative)
Verify Order Flow aligns with signal
5. Consider Market Context
News events can override signals
Low liquidity times (lunch, overnight) less reliable
Major economic releases need caution
6. Paper Trade First
Test the indicator for 2-4 weeks
Learn how it behaves on your chosen assets
Develop confidence before using real money
Best Times to Trade:
Stock Market Hours:
9:30-11:30 AM EST (high volume, strong moves)
2:00-4:00 PM EST (institutional positioning)
Avoid: 11:30 AM-2:00 PM (lunch, low volume)
Forex:
London Open: 3:00-6:00 AM EST
New York Open: 8:00-11:00 AM EST
London/NY Overlap: 8:00 AM-12:00 PM EST
Crypto:
24/7 market, but highest volume during US/European hours
Watch for weekend low liquidity
7. Common Mistakes to Avoid {#mistakes}
❌ DON'T:
1. Trade Every Signal
Not all signals are equal
Focus on strength 4-5 signals
Wait for optimal setups
2. Ignore Market Structure
Don't buy into strong downtrends (catch falling knife)
Don't sell into strong uptrends (fight the tape)
Respect major support/resistance
3. Use Too Small Timeframes
1m and 2m charts are too noisy
Minimum recommended: 5m for scalping
Better: 15m, 30m, 1H for reliability
4. Overtrade
Quality over quantity
2-5 good trades per day is excellent
Forcing trades leads to losses
5. Ignore Risk Management
Always use stop losses
Risk only 1-2% per trade
Don't revenge trade after losses
6. Trade During Low Volume
Signals less reliable with low volume
Check Relative Volume metric (should be >1.5)
Avoid pre-market/after-hours for stocks
7. Misread Liquidity Grabs
Not every wick is a liquidity grab
Need volume confirmation
Must have institutional signal
Advanced Tips:
Filtering False Signals:
Use Signal Strength Filter:
Minimum strength 3 = Balanced
Minimum strength 4 = Conservative (recommended)
Minimum strength 5 = Ultra conservative
Confluence Checklist:
Signal strength ≥ 4
Relative volume > 2.0
At key support/resistance
Aligns with higher timeframe trend
Delta % strongly positive/negative
Clean price action setup
If 4+ boxes checked = High probability trade
Setting Up Alerts:
Click the three dots on the indicator
Select "Create Alert"
Choose condition:
"Institutional Buy Signal"
"Institutional Sell Signal"
"Dark Pool Activity"
Set up notification (email, SMS, app)
Save alert
Alert Strategy:
Set minimum strength to 4 for fewer, better alerts
Use for assets you can't watch constantly
Don't rely solely on alerts - check chart context
Practice Exercise:
Week 1-2: Observation
Add indicator to your favorite assets
Watch how signals develop
Note which ones lead to profitable moves
Don't trade yet - just observe
Week 3-4: Paper Trading
Use TradingView's paper trading
Trade only strength 4-5 signals
Record results in a journal
Note: entry, exit, profit/loss, what worked/didn't
Week 5+: Small Live Positions
Start with smallest position size
Trade only your best setups
Gradually increase size as you gain confidence
Keep detailed journal
Quick Reference Card:
Signal Quality Ranking:
🔥 Best Setups (Take These):
Strength 5 + Liquidity grab + Key level
Strength 4-5 + Volume >3.0 + Trend alignment
Dark Pool markers + Strength 4+ signal
✅ Good Setups:
Strength 4 at support/resistance
Strength 3-4 with strong delta
Liquidity grab + Strength 3+
⚠️ Caution (Wait for More):
Strength 2-3 in middle of nowhere
Against higher timeframe trend
Low volume (Rel Vol <1.5)
❌ Avoid:
Strength 2 only
During major news
Low liquidity hours
Against strong trend
Troubleshooting:
"Too many signals"
→ Increase Minimum Signal Strength to 4
→ Increase Volume Spike Multiplier to 2.5-3.0
"Too few signals"
→ Decrease Minimum Signal Strength to 2-3
→ Decrease Volume Spike Multiplier to 1.5
"Signals not working"
→ Check if you're trading during low volume hours
→ Verify you're using recommended timeframes
→ Make sure signals align with market structure
"Can't see liquidity zones"
→ Enable "Show Liquidity Zones" in settings
→ Adjust Swing Detection Length (try 7-15)
Resources for Further Learning:
Concepts to Study:
Order Flow Trading
Market Profile / Volume Profile
Smart Money Concepts (SMC)
Liquidity Sweeps and Stop Hunts
Institutional Order Flow
Wyckoff Method
Volume Spread Analysis (VSA)
Recommended Practice:
Study past signals on chart
Replay market using TradingView's bar replay feature
Join trading communities to share setups
Keep a detailed trading journal
Final Thoughts:
This indicator is a tool, not a crystal ball. It identifies high-probability setups where institutions are active, but still requires:
Proper risk management
Market context understanding
Patience and discipline
Continuous learning
Success Formula:
Right Tool + Proper Training + Risk Management + Discipline = Consistent Profits
Start slow, master the basics, and gradually increase complexity as you gain experience.
Good luck and trade smart! 📊📈
Key Levels: Daily, Weekly, Monthly [BackQuant]Key Levels: Daily, Weekly, Monthly
Map the market’s “memory” in one glance—yesterday’s range, this week’s chosen day high/low, and D/W/M opens—then auto-clean levels once they break.
What it does
This tool plots three families of high-signal reference lines and keeps them tidy as price evolves:
Chosen Day High/Low (per week) — Pick a weekday (e.g., Monday). For each past week, the script records that day’s session high and low and projects them forward for a configurable number of bars. These act like “memory levels” that price often revisits.
Daily / Weekly / Monthly Opens — Plots the opening price of each new day, week, and month with separate styling. These opens frequently behave like magnets/flip lines intraday and anchors for regime on higher timeframes.
Auto-pruning — When price breaks a stored level, the script can automatically remove it to reduce clutter and refocus you on still-active lines. See: (broken levels removed).
Why these levels matter
Liquidity pockets — Prior day’s high/low and the daily open concentrate stops and pending orders. Mapping them quickly reveals likely sweep or fade zones. Example: previous day highs + daily open highlighting liquidity:
Context & regime — Monthly opens frame macro bias; trading above a rising cluster of monthly opens vs. below gives a clean top-down read. Example: monthly-only “macro outlook” view:
Cleaner charts — Auto-remove broken lines so you focus on what still matters right now.
What it plots (at a glance)
Past Chosen Day High/Low for up to N prior weeks (your choice), extended right.
Current Daily Open , Weekly Open , and Monthly Open , each with its own color, label, and forward extension.
Optional short labels (e.g., “Mon High”) or full labels (with week/month info).
How breaks are detected & cleaned
You control both the evidence and the timing of a “break”:
Break uses — Choose Close (more conservative) or Wick (more sensitive).
Inclusive? — If enabled, equality counts (≥ high or ≤ low). If disabled, you need a strict cross.
Allow intraday breaks? — If on, a level can break during the tracked day; if off, the script only counts breaks after the session completes.
Remove Broken Levels — When a break is confirmed, the line/label is deleted automatically. (See the demo: )
Quick start
Pick a Day of Week to Track (e.g., Monday).
Set how many weeks back to show (e.g., 8–10).
Choose how far to extend each family (bars to the right for chosen-day H/L and D/W/M opens).
Decide if a break uses Close or Wick , and whether equality counts.
Toggle Remove Broken Levels to keep the chart clean automatically.
Tips by use-case
Intraday bias — Watch the Daily Open as a magnet/flip. If price gaps above and holds, pullbacks to the daily open often decide direction. Pair with last day’s high/low for sweep→reversal or true breakout cues. See:
Weekly structure — Track the week’s chosen day (e.g., Monday) high/low across prior weeks. If price stalls near a cluster of old “Monday Highs,” look for sweep/reject patterns or continuation on reclaim.
Macro regime — Hide daily/weekly lines and keep only Monthly Opens to read bigger cycles at a glance (BTC/crypto especially). Example:
Customization
Use wicks or bodies for highs/lows (wicks capture extremes; bodies are stricter).
Line style & thickness — solid/dashed/dotted, width 1–5, plus global transparency.
Labels — Abbreviated (“Mon High”, “D Open”) or full (month/week/day info).
Color scheme — Separate colors for highs, lows, and each of D/W/M opens.
Capacity controls — Set how many daily/weekly/monthly opens and how many weeks of chosen-day H/L to keep visible.
What’s under the hood
On your selected weekday, the script records that session’s true high and true low (using wicks or body-based extremes—your choice), then projects a horizontal line forward for the next bars.
At each new day/week/month , it records the opening price and projects that line forward as well.
Each bar, the script checks your “break” rules; once broken, lines/labels are removed if auto-cleaning is on.
Everything updates in real time; past levels don’t repaint after the session finishes.
Recommended presets
Day trading — Weeks back: 6–10; extend D/W opens: 50–100 bars; Break uses: Close ; Inclusive: off; Auto-remove: on.
Swing — Fewer daily opens, more weekly opens (2–6), and 8–12 weeks of chosen-day H/L.
Macro — Show only Monthly Opens (1–6 months), dashed style, thicker lines for clarity.
Reading the examples
Broken lines disappear — decluttering in action:
Macro outlook — monthly opens as cycle rails:
Liquidity map — previous day highs + daily open:
Final note
These are not “signals”—they’re reference points that many participants watch. By standardising how you draw them and automatically clearing the ones that no longer matter, you turn a noisy chart into a focused map: where liquidity likely sits, where price memory lives, and which lines are still in play.
Multi-Timeframe SMTSummery
The Multi-Timeframe SMT indicator is designed to identify and visualize Higher Timeframe (HTF) data on a Lower Timeframe (LTF) chart, allowing traders to see the broader market context without changing their current chart's resolution. It accurately draws pivots and SMT divergences from higher timeframes on the corresponding candles of your current lower timeframe chart.
Its core features include:
Multi-Timeframe Analysis: Configure and monitor pivots on up to four independent timeframes, from intraday to monthly.
Customizable Pivot Detection: Define the strength of pivots by adjusting the number of bars to the left and right.
SMT Divergence: Automatically identifies bullish and bearish SMT divergences by comparing the price action of the main chart symbol with a chosen correlated asset.
Early SMT Detection: A unique feature that monitors a lower "detection timeframe" to provide early warnings of potential SMT setups before they're confirmed on the main timeframe. Note that this early detection is only shown on timeframes equal to or lower than the "Detection timeframe" you have set.
Visual Cues & Alerts: Clear on-chart labels, lines, and fully customizable alerts notify you of confirmed pivots and SMT divergences, ensuring you don't miss key opportunities.
Important Nuance Regarding Pivot Label Display
Due to a self-imposed limit within this script's drawing management logic, the indicator might quickly reach its drawing capacity if you enable pivot crosses for multiple timeframes simultaneously. When this internal drawing limit is exceeded, the script is designed to automatically remove the oldest drawings to make space for new ones.
Therefore, to ensure optimal performance and visibility of the most recent and relevant pivots, it's highly recommended to only enable the "Show Pivot Crosses" option for one timeframe at a time. If you wish to view pivots for a different timeframe, simply disable the pivot crosses for the currently active timeframe and then enable them for your desired one. This approach prevents the rapid cycling and disappearance of pivot labels, providing a clearer and more stable visual experience.
In-Depth Explanation of the Logic
This script is built on two primary concepts: pivot points and Smart Money Technique (SMT) divergence. It systematically collects historical data on multiple timeframes, identifies pivots, and then compares them between two assets to find divergences.
Pivot Point Identification
A pivot is a turning point in the market. A pivot high is a candle that has a higher high than the candles to its immediate left and right. Conversely, a pivot low is a candle with a lower low than its neighbors.
How it Works in the Script:
The script tracks the highest high and lowest low for each period of the selected timeframe (e.g., for each 4-hour candle). When a new high-timeframe candle closes, it stores that high/low value and its bar index in an array. The checkForPivot() function then checks if a recently stored high or low qualifies as a pivot.
Key Inputs:
Left Strength (leftBars1): The number of candles to the left that must have a lower high (for a pivot high) or higher low (for a pivot low).
Right Strength (rightBars1): The number of candles to the right that must meet the same criteria.
For example, with Left Strength and Right Strength both set to 3, a pivot high is only confirmed when its high is greater than the highs of the 3 previous high-timeframe candles and the 3 subsequent high-timeframe candles. Increasing these values will identify more significant, longer-term pivots.
Smart Money Technique (SMT) Divergence
SMT Divergence is a concept popularized by The Inner Circle Trader (ICT). It occurs when two closely correlated assets fail to move in sync. For instance, if Asset A makes a higher high but Asset B fails to do so and instead makes a lower high, this creates a bearish SMT divergence. It suggests that the "smart money" may not be supporting the move in Asset A, signaling a potential reversal.
Bearish SMT: Main asset makes a higher high, while the correlated asset makes a lower high. This is a potential sell signal.
Bullish SMT: Main asset makes a lower low, while the correlated asset makes a higher low. This is a potential buy signal.
How it Works in the Script:
Data Request: For each timeframe, the script uses the request.security() function to fetch the high and low data for both the main chart symbol (syminfo.tickerid) and the chosen Comparison Asset.
Pivot Comparison: When a new pivot is confirmed on the main asset, the script checks if a corresponding pivot also formed on the comparison asset at the same time.
Divergence Check: It then compares the direction of the pivots. For a bearish SMT, it checks if the main asset's new pivot high is higher than its previous pivot high, while the comparison asset's new pivot high is lower than its previous one. The logic is reversed for bullish SMT.
Visualization: If a divergence is found, the script draws a red (bearish) or green (bullish) line connecting the two pivots on your chart and places an "SMT" label.
Early SMT Detection
This is a proactive feature designed to give you a heads-up. Waiting for a 4-hour or daily pivot to form can take a long time. The early detection system looks for SMT divergences on a much smaller, user-defined Detection timeframe (e.g., 15-minute).
How it Works in the Script:
Awaiting Setup: After a primary pivot (Pivot A) is formed on the main timeframe (e.g., a Daily pivot high), the script begins monitoring.
Intraday Monitoring: It then watches the Detection timeframe (e.g., 15-minute) for smaller intraday pivots.
Potential Divergence: It looks for an intraday pivot that forms a divergence against the primary Pivot A.
Watchline & Alert: When this "potential" divergence occurs, the script draws a dashed white line and triggers a "Potential SMT" alert. This isn't a confirmed SMT on the main timeframe yet, but it's a powerful early warning that one may be forming.
Drawing & Object Management
To keep the chart clean and prevent performance issues, the script manages its drawings (lines and labels) efficiently. It stores them in arrays and uses a drawing limit to automatically delete the oldest drawings as new ones are created, ensuring your TradingView remains responsive.
How to Use the Indicator
Configuration
Enable Timeframes: Use the checkboxes (Enable Timeframe 1, Enable Timeframe 2, etc.) to activate the timeframes you want to monitor. It's often best to start with one or two to keep the chart clean.
Select Timeframes: Choose the higher timeframes you want to analyze (e.g., 240 for 4-hour, D for Daily, W for Weekly).
Set Pivot Strength: The default of 3 for Left/Right strength is a good starting point. Increase it to find more significant market structure points or decrease it for more frequent, shorter-term pivots.
Configure SMT:
Check Enable SMT for the timeframes where you want to detect divergence.
Enter a Comparison Asset . This is crucial. Ensure the assets are correlated.
To use the early warning system, check Enable early SMT detection and select an appropriate Detection timeframe (e.g., 15 or 60 minutes for a Daily analysis).
Swing High/Low with Liquidity Sweeps🧠 Overview
This indicator identifies swing highs and swing lows based on user-defined candle lengths and checks for liquidity sweeps—situations where the price breaks a previous swing level but then closes back inside, indicating a potential false breakout or stop hunt. It also supports visual labeling and alerts for these events.
⚙️ Inputs
Swing Length (must be odd number ≥ 3):
Determines how many candles are used to identify swing highs/lows. The central candle must be higher or lower than all neighbors within the range.
Example: If swingLength = 5, the central candle must be higher/lower than the 2 candles on both sides.
Sweep Lookback (bars):
Defines how many bars to look back for possible liquidity sweeps.
Show Swing Labels (checkbox):
Optionally display labels on the chart when a swing high or low is detected.
Show Sweep Labels (checkbox):
Optionally display labels on the chart when a liquidity sweep occurs.
🕯️ Swing Detection Logic
A Swing High is detected when the high of the central candle is greater than the highs of all candles around it (as per the defined length).
A Swing Low is detected when the low of the central candle is lower than the lows of surrounding candles.
Swing labels are placed slightly above (for highs) or below (for lows) the candle.
💧 Liquidity Sweep Logic
A Sweep High is triggered if:
The current high breaks above a previously detected swing high,
And then the candle closes below that swing high,
Within the configured lookback window.
A Sweep Low is triggered if:
The current low breaks below a previous swing low,
And then closes above it,
Within the lookback window.
These are often seen as stop hunts or fake breakouts.
🔔 Alerts
Sweep High Alert: Triggered when a sweep above a swing high occurs.
Sweep Low Alert: Triggered when a sweep below a swing low occurs.
You can use these to set up TradingView alerts to notify you of potential liquidity grabs.
📊 Use Cases
Identifying market structure shifts.
Spotting fake breakouts and potential reversals.
Assisting in smart money concepts and liquidity-based trading.
Supporting entry timing in trend continuation or reversal strategies.
Initial balance - weeklyWeekly Initial Balance (IB) — Indicator Description
The Weekly Initial Balance (IB) is the price range (High–Low) established during the week’s first trading session (most commonly Monday). You can measure it over the entire day or just the first X hours (e.g. 60 or 120 minutes). Once that session ends, the IB High and IB Low define the key levels where the initial weekly range formed.
Why Measure the Weekly IB?
Week-Opening Sentiment:
Monday’s range often sets the tone for the rest of the week. Trading above the IB High signals bullish control; trading below the IB Low signals bearish control.
Key Liquidity Zones:
Large institutions tend to place orders around these extremes, so you’ll frequently see tests, breakouts, or rejections at these levels.
Support & Resistance:
The IB High and IB Low become natural barriers. Price will often return to them, bounce off them, or break through them—ideal spots for entries and exits.
Volatility Forecast:
The width of the IB (High minus Low) indicates whether to expect a volatile week (wide IB) or a quieter one (narrow IB).
Significance of IB Levels
Breakout:
A clear break above the IB High (for longs) or below the IB Low (for shorts) can ignite a strong trending move.
Fade:
A rejection off the IB High/Low during low momentum (e.g. low volume or pin-bar formations) offers a high-probability reversal trade.
Mid-Point:
The 50% level of the IB range often “magnetizes” price back to it, providing entry points for continuation or reversal strategies.
Three Core Monday IB Strategies
A. Breakout (Open-Range Breakout)
Entry: Wait for 1–2 candles (e.g. 5-minute) to close above IB High (long) or below IB Low (short).
Stop-Loss: A few pips below IB High (long) or above IB Low (short).
Profit-Target: 2–3× your risk (Reward:Risk ≥ 2:1).
Best When: You spot a clear impulse—such as a strong pre-open volume spike or news-driven move.
B. Fade (Reversal at Extremes)
Entry: When price tests IB High but shows weakening momentum (shrinking volume, upper-wick candles), enter short; vice versa for IB Low and longs.
Stop-Loss: Just beyond the IB extreme you’re fading.
Profit-Target: Back toward the IB mid-point (50% level) or all the way to the opposite IB extreme.
Best When: Monday’s action is range-bound and lacks a clear directional trend.
C. Mid-Point Trading
Entry: When price returns to the 50% level of the IB range.
In an up-trend: buy if it bounces off mid-point back toward IB High.
In a down-trend: sell if it reverses off mid-point back toward IB Low.
Stop-Loss: Just below the nearest swing-low (for longs) or above the nearest swing-high (for shorts).
Profit-Target: To the corresponding IB extreme (High or Low).
Best When: You see a strong initial move away from the IB, followed by a pullback to the mid-point.
Usage Steps
Configure your session: Measure IB over your chosen Monday timeframe (whole day or first X hours).
Choose your strategy: Align Breakout, Fade, or Mid-Point entries with the current market context (trend vs. range).
Manage risk: Keep risk per trade ≤ 1% of account and maintain at least a 2:1 Reward:Risk ratio.
Backtest & forward-test: Verify performance over multiple Mondays and in a paper-trading environment before going live.
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
Timeframe Resistance Evaluation And Detection - CoffeeKillerTREAD - Timeframe Resistance Evaluation And Detection Guide
🔔 Important Technical Limitation 🔔
**This indicator does NOT fetch true higher timeframe data.** Instead, it simulates higher timeframe levels by aggregating data from your current chart timeframe. This means:
- Results will vary depending on what chart timeframe you're viewing
- Levels may not match actual higher timeframe candle highs/lows
- You might miss important wicks or gaps that occurred between chart timeframe bars
- **Always verify levels against actual higher timeframe charts before trading**
Welcome traders! This guide will walk you through the TREAD (Timeframe Resistance Evaluation And Detection) indicator, a multi-timeframe analysis tool developed by CoffeeKiller that identifies support and resistance confluence across different time periods.(I am 50+ year old trader and always thought I was bad a teaching and explaining so you get a AI guide. I personally use this on the 5 minute chart with the default settings, but to each there own and if you can improve the trend detection methods please DM me. I would like to see the code. Thanks)
Core Components
1. Dual Timeframe Level Tracking
- Short Timeframe Levels: Tracks opening price extremes within shorter periods
- Long Timeframe Levels: Tracks actual high/low extremes within longer periods
- Dynamic Reset Mechanism: Levels reset at the start of each new timeframe period
- Momentum Detection: Identifies when levels change mid-period, indicating active price movement
2. Visual Zone System
- High Zones: Areas between long timeframe highs and short timeframe highs
- Low Zones: Areas between long timeframe lows and short timeframe lows
- Fill Coloring: Dynamic colors based on whether levels are static or actively changing
- Momentum Highlighting: Special colors when levels break during active periods
3. Customizable Display Options
- Multiple Plot Styles: Line, circles, or cross markers
- Flexible Timeframe Selection: Wide range of short and long timeframe combinations
- Color Customization: Separate colors for each level type and momentum state
- Toggle Controls: Show/hide different elements based on trading preference
Main Features
Timeframe Settings
- Short Timeframe Options: 15m, 30m, 1h, 2h, 4h
- Long Timeframe Options: 1h, 2h, 4h, 8h, 12h, 1D, 1W
- Recommended Combinations:
- Scalping: 15m/1h or 30m/2h
- Day Trading: 30m/4h or 1h/4h
- Swing Trading: 4h/1D or 1D/1W
Display Configuration
- Level Visibility: Toggle short/long timeframe levels independently
- Fill Zone Control: Enable/disable colored zones between levels
- Momentum Fills: Special highlighting for actively changing levels
- Line Customization: Width, style, and color options for all elements
Color System
- Short TF High: Default red for resistance levels
- Short TF Low: Default green for support levels
- Long TF High: Transparent red for broader resistance context
- Long TF Low: Transparent green for broader support context
- Momentum Colors: Brighter colors when levels are actively changing
Technical Implementation Details
How Level Tracking Works
The indicator uses a custom tracking function that:
1. Detects Timeframe Periods: Uses `time()` function to identify when new periods begin
2. Tracks Extremes: Monitors highest/lowest values within each period
3. Resets on New Periods: Clears tracking when timeframe periods change
4. Updates Mid-Period: Continues tracking if new extremes are reached
The Timeframe Limitation Explained
`pinescript
// What the indicator does:
short_tf_start = ta.change(time(short_timeframe)) != 0 // Detects 30m period start
= track_highest(open, short_tf_start) // BUT uses chart TF opens!
// What true multi-timeframe would be:
// short_tf_high = request.security(syminfo.tickerid, short_timeframe, high)
`
This means:
- On a 5m chart with 30m/4h settings: Tracks 5m bar opens during 30m and 4h windows
- On a 1m chart with same settings: Tracks 1m bar opens during 30m and 4h windows
- Results will be different between chart timeframes
- May miss important price action that occurred between your chart's bars
Visual Elements
1. Level Lines
- Short TF High: Upper resistance line from shorter timeframe analysis
- Short TF Low: Lower support line from shorter timeframe analysis
- Long TF High: Broader resistance context from longer timeframe
- Long TF Low: Broader support context from longer timeframe
2. Zone Fills
- High Zone: Area between long TF high and short TF high (potential resistance cluster)
- Low Zone: Area between long TF low and short TF low (potential support cluster)
- Regular Fill: Standard transparency when levels are static
- Momentum Fill: Enhanced visibility when levels are actively changing
3. Dynamic Coloring
- Static Periods: Normal colors when levels haven't changed recently
- Active Periods: Momentum colors when levels are being tested/broken
- Confluence Zones: Different intensities based on timeframe alignment
Trading Applications
1. Support/Resistance Trading
- Entry Points: Trade bounces from zone boundaries
- Confluence Areas: Focus on areas where short and long TF levels cluster
- Zone Breaks: Enter on confirmed breaks through entire zones
- Multiple Timeframe Confirmation: Stronger signals when both timeframes align
2. Range Trading
- Zone Boundaries: Use fill zones as range extremes
- Mean Reversion: Trade back toward opposite zone when price reaches extremes
- Breakout Preparation: Watch for momentum color changes indicating potential breakouts
- Risk Management: Place stops outside the opposite zone
3. Trend Following
- Direction Bias: Trade in direction of zone breaks
- Pullback Entries: Enter on pullbacks to broken zones (now support/resistance)
- Momentum Confirmation: Use momentum coloring to confirm trend strength
- Multiple Timeframe Alignment: Strongest trends when both timeframes agree
4. Scalping Applications
- Quick Bounces: Trade rapid moves between zone boundaries
- Momentum Signals: Enter when momentum colors appear
- Short-Term Targets: Use opposite zone as profit target
- Tight Stops: Place stops just outside current zone
Optimization Guide
1. Timeframe Selection
For Different Trading Styles:
- Scalping: 15m/1h - Quick levels, frequent updates
- Day Trading: 30m/4h - Balanced view, good for intraday moves
- Swing Trading: 4h/1D - Longer-term perspective, fewer false signals
- Position Trading: 1D/1W - Major structural levels
2. Chart Timeframe Considerations
**Important**: Your chart timeframe affects results
- Lower Chart TF: More granular level tracking, but may be noisy
- Higher Chart TF: Smoother levels, but may miss important price action
- Recommended: Use chart timeframe 2-4x smaller than short indicator timeframe
3. Display Settings
- Busy Charts: Disable fills, show only key levels
- Clean Analysis: Enable all fills and momentum coloring
- Multi-Monitor Setup: Use different color schemes for easy identification
- Mobile Trading: Increase line width for visibility
Best Practices
1. Level Verification
- Always Cross-Check: Verify levels against actual higher timeframe charts
- Multiple Timeframes: Check 2-3 different chart timeframes for consistency
- Price Action Confirmation: Wait for candlestick confirmation at levels
- Volume Analysis: Combine with volume for stronger confirmation
2. Risk Management
- Stop Placement: Use zones rather than exact prices for stops
- Position Sizing: Reduce size when zones are narrow (higher risk)
- Multiple Targets: Scale out at different zone boundaries
- False Break Protection: Allow for minor zone penetrations
3. Signal Quality Assessment
- Momentum Colors: Higher probability when momentum coloring appears
- Zone Width: Wider zones often provide stronger support/resistance
- Historical Testing: Backtest on your preferred timeframe combinations
- Market Conditions: Adjust sensitivity based on volatility
Advanced Features
1. Momentum Detection System
The indicator tracks when levels change mid-period:
`pinescript
short_high_changed = short_high != short_high and not short_tf_start
`
This identifies:
- Active level testing
- Potential breakout situations
- Increased market volatility
- Trend acceleration points
2. Dynamic Color System
Complex conditional logic determines fill colors:
- Static Zones: Regular transparency for stable levels
- Active Zones: Enhanced colors for changing levels
- Mixed States: Different combinations based on user preferences
- Custom Overrides: User can prioritize certain color schemes
3. Zone Interaction Analysis
- Convergence: When short and long TF levels approach each other
- Divergence: When timeframes show conflicting levels
- Alignment: When both timeframes agree on direction
- Transition: When one timeframe changes while other remains static
Common Issues and Solutions
1. Inconsistent Levels
Problem: Levels look different on various chart timeframes
Solution: Always verify against actual higher timeframe charts
2. Missing Price Action
Problem: Important wicks or gaps not reflected in levels
Solution: Use chart timeframe closer to indicator's short timeframe setting
3. Too Many Signals
Problem: Excessive level changes and momentum alerts
Solution: Increase timeframe settings or reduce chart timeframe granularity
4. Lagging Signals
Problem: Levels seem to update too slowly
Solution: Decrease chart timeframe or use more sensitive timeframe combinations
Recommended Setups
Conservative Approach
- Timeframes: 4h/1D
- Chart: 1h
- Display: Show fills only, no momentum coloring
- Use: Swing trading, position management
Aggressive Approach
- Timeframes: 15m/1h
- Chart: 5m
- Display: All features enabled, momentum highlighting
- Use: Scalping, quick reversal trades
Balanced Approach
- Timeframes: 30m/4h
- Chart: 15m
- Display: Selective fills, momentum on key levels
- Use: Day trading, multi-session analysis
Final Notes
**Remember**: This indicator provides a synthetic view of multi-timeframe levels, not true higher timeframe data. While useful for identifying potential confluence areas, always verify important levels by checking actual higher timeframe charts.
**Best Results When**:
- Combined with actual multi-timeframe analysis
- Used for confluence confirmation rather than primary signals
- Applied with proper risk management
- Verified against price action and volume
**DISCLAIMER**: This indicator and its signals are intended solely for educational and informational purposes. The timeframe limitation means results may not reflect true higher timeframe levels. Always conduct your own analysis and verify levels independently before making trading decisions. Trading involves significant risk of loss.
Sessions [Plug&Play]This indicator automatically highlights the three major FX trading sessions—Asia, London, and New York—on your chart and, at the close of each session, draws right-extended horizontal rays at that session’s high and low. It’s designed to help you visually identify when price is trading within each session’s range and to quickly see where the highest and lowest prices occurred before the next major session begins.
Key Features:
Session Boxes
Draws a semi-transparent box around each session’s timeframe (Asia, London, New York) based on your local UTC offset.
Each box dynamically expands in real time: as new candles form during the session, the box’s top and bottom edges update to match the highest high and lowest low seen so far in that session.
When the session ends, the box remains on your chart, anchored to the exact candles that formed its boundaries.
High/Low Rays
As soon as a session closes (e.g., London session ends at 17:00 UTC+0 by default), two horizontal rays are drawn at that session’s final high and low.
These rays are “pinned” to the exact candles where the high/low occurred, so they stay in place when you scroll or zoom.
Each ray extends indefinitely to the right, providing a clear reference of the key supply/demand levels created during that session.
Session Labels
Optionally places a small “London,” “New York,” or “Asia” label at the top edge of each completed session’s box.
Labels are horizontally centered within the session’s box and use a contrasting, easy-to-read font color.
Customizable Appearance
Show/Hide Each Session: Toggle display of London, New York, and Asia sessions separately.
Time Ranges: By default, London is 08:00–17:00 (UTC), New York is 13:00–22:00 (UTC), and Asia is 00:00–07:00 (UTC). You can override each session’s start/end times using the “Time Range” picker.
Color & Opacity: Assign custom colors to each session. Choose a global “Dark,” “Medium,” or “Light” opacity preset to adjust box fill transparency and border shading.
Show/Hide Labels & Outlines: Turn the text labels and the box borders on or off independently.
UTC Offset Support
If your local broker feed or price data is not in UTC, simply adjust the “UTC Offset (+/–)” input. The indicator will recalculate session start/end times relative to your chosen offset.
How to Use:
Add the Indicator:
Open TradingView’s Pine Editor, paste in this script, and click “Add to Chart.”
By default, you’ll see three translucent boxes appear once each session begins (Asia, London, New York).
Watch in Real Time:
As soon as a session starts, its box will appear anchored to the first candle. The top and bottom of the box expand if new extremes occur.
When the session closes, the final box remains visible and two horizontal rays mark that session’s high and low.
Analyze Key Levels:
Use the high- and low-level rays to gauge session liquidity zones—areas where stop orders, breakouts, or reversals often occur.
For example, if London’s high is significantly above current price, it may act as resistance in the New York session.
Customize to Your Needs:
Toggle specific sessions on/off (e.g., if you only care about London and New York).
Change each session’s color to match your chart theme.
Adjust the “UTC Offset” so sessions align with your local time.
Disable labels or box borders if you prefer a cleaner look.
Inputs Overview:
Show London/New York/Asia Session (bool): Show or hide each session’s box and its high/low rays.
Time Range (session): Defines the start/end of each session in “HHMM–HHMM” (24h) format.
Colour (color): Custom color for each session’s box fill, border, and high/low rays.
Show Session Labels (bool): Toggle the “London,” “New York,” “Asia” text that appears at the top of each completed box.
Show Range Outline (bool): Toggle the box border (if off, only a translucent fill is drawn).
Opacity Preset (Dark/Medium/Light): Controls transparency of box fill and border.
UTC Offset (+/–) (int): Adjusts session times for different time zones (e.g., +1 for UTC+1).
Why It’s Useful:
Quickly Identify Session Activity: Visually distinguish when each major trading session is active, then compare price action across sessions.
Pinpoint High/Low Liquidity Levels: Drawn rays highlight where the market hit its extremes—critical zones for stop orders or breakout entries.
Multi-Timeframe Context: By seeing historical session boxes and rays, you can locate recurring supply/demand areas, overlap zones, or session re-tests.
Fully Automated Workflow: Once added to your chart, the script does all the work of tracking session boundaries and drawing high/low lines—no manual box or line drawing necessary.
Example Use Cases:
London Breakout Traders: See where London’s high/low formed, then wait for price to revisit those levels during the New York session.
Range Breakout Strategies: If price consolidates inside the London box, use the boxed extremes as immediate targets for breakout entries.
Intraday Liquidity Swings: During quieter hours, watch Asia’s high/low to identify potential support/resistance before London’s opening.
Overlap Zones: Compare London’s range with Asia’s range to find areas of confluence—high-probability reversal or continuation zones.
CYCLE BY RiotWolftradingDescription of the "CYCLE" Indicator
The "CYCLE" indicator is a custom Pine Script v5 script for TradingView that visualizes cyclic patterns in price action, dividing the trading day into specific sessions and 90-minute quarters (Q1-Q4). It is designed to identify and display market phases (Accumulation, Manipulation, Distribution, and Continuation/Reversal) along with key support and resistance levels within those sessions. Additionally, it allows customization of boxes, lines, labels, and colors to suit user preferences.
Main Features
Cycle Phases:
Accumulation (1900-0100): Represents the phase where large operators accumulate positions.
Manipulation (0100-0700): Identifies potential manipulative moves to mislead retail traders.
Distribution (0700-1300): The phase where large operators distribute their positions.
Continuation/Reversal (1300-1900): Indicates whether the price continues the trend or reverses.
90-Minute Quarters (Q1-Q4):
Divides each 6-hour cycle (360 minutes) into four 90-minute quarters (Q1: 00:00-01:30, Q2: 01:30-03:00, Q3: 03:00-04:30, Q4: 04:30-06:00 UTC).
Each quarter is displayed with a colored box (Q1: light purple, Q2: light blue, Q3: light gray, Q4: light pink) and labels (defaulted to black).
Support and Resistance Visualization:
Draws boxes or lines (based on settings) showing the high and low levels of each session.
Optionally displays accumulated volume at the highs and lows within the boxes.
Daily Lines and Last 3 Boxes:
How to Use the Indicator
Step 1: Add the Indicator to TradingView
Open TradingView and select the chart where you want to apply the indicator (e.g., UMG9OOR on a 5-minute timeframe, as shown in the screenshot).
Go to the Pine Editor (at the bottom of the TradingView interface).
Copy and paste the provided code.
Click Compile and then Add to Chart.
Step 2: Configure the Indicator
Click on the indicator name on the chart ("CYCLE") and select Settings (or double-click the name).
Adjust the options based on your needs:
Cycle Phases: Enable/disable phases (Accumulation, Manipulation, Distribution, Continuation/Reversal) and adjust their time slots if needed.
90-Minute Quarters: Enable/disable quarters (Q1-Q4).
Step 3: Interpret the Indicator
Identify Cycle Phases:
Observe the red boxes indicating the phases (Accumulation, Manipulation, etc.).
The high and low levels within each phase are potential support/resistance zones.
If volume is enabled, pay attention to the accumulated volume at highs and lows, as it may indicate the strength of those levels.
Use the 90-Minute Quarters (Q1-Q4):
The colored boxes (Q1-Q4) divide the day into 90-minute segments.
Each quarter shows the price range (high and low) during that period.
Use these boxes to identify price patterns within each quarter, such as breakouts or consolidations.
The labels (Q1, Q2, etc.) help you track time and anticipate potential moves in the next quarter.
Analyze Support and Resistance:
The high and low levels of each phase/quarter act as support and resistance.
Daily lines (if enabled) show key levels from the previous day, useful for planning entries/exits.
The "last 3 boxes below price" (if enabled) highlight potential support levels the price might target.
Avoid Manipulation:
During the Manipulation phase (0100-0700), be cautious of sharp moves or false breakouts.
Use the high/low levels of this phase to identify potential traps (as explained in your first question about manipulation candles).
Step 4: Trading Strategy
Entries and Exits:
Support/Resistance: Use the high/low levels of phases and quarters to set entry or exit points.
For example, if the price bounces off a Q1 support level, consider a buy.
Breakouts: If the price breaks a high/low of a quarter (e.g., Q2), wait for confirmation to enter in the direction of the breakout.
Volume: If accumulated volume is high near a key level, that level may be more significant.
Risk Management:
Place stop-loss orders below lows (for buys) or above highs (for sells) identified by the indicator.
Avoid trading during the Manipulation phase unless you have a specific strategy to handle false breakouts.
Time Context:
Use the quarters (Q1-Q4) to plan your trades based on time. For example, if Q3 is typically volatile in your market, prepare for larger moves between 03:00-04:30 UTC.
Step 5: Adjustments and Testing
Test on Different Timeframes: The indicator is set for a 5-minute timeframe (as in the screenshot), but you can test it on other timeframes (e.g., 1-minute, 15-minute) by adjusting the time slots if needed.
Adjust Colors and Styles: If the default colors are not visible on your chart, change them for better clarity.
---
📌 1. **Accumulation: Strong Institutional Activity**
- During the **accumulation phase, we see **high volume: 82.773K, which suggests strong buying interest**, likely from institutional players.
- This sets the base for the following upward move in price.
---
📌 2. **Manipulation: False Breakout with Lower Volume**
- Later, there's a manipulation phase where price breaks above previous highs, but the volume (71.814K) is **lower than during accumulation**.
- This implies that buyers are not as aggressive as before—no real demandbehind the breakout.
- It’s likely a bull trap, where smart money is selling into the breakout to exit their positions.
---
### 📌 3. Distribution: Weakness and Lack of Demand
- The market enters a distribution phase, and volume drops even further (only 7.914K).
- Price struggles to go higher, and you start seeing rejections at the top.
- This shows that demand is drying up, and smart money is offloading positions**—not accumulating anymore.
---
### 💡 Why Take the Short Here?
- Volume is not increasing with new highs—showing weak demand**.
- The manipulation volume is weaker than the accumulation volume, confirming the breakout was likely false.
- Structure starts to break down (Q levels falling), which confirms weakness.
- This creates a high-probability short setup:
- **Entry:** after confirmation of distribution and structural breakdown.
- **Stop loss:** above the manipulation high.
- **Target:** down toward previous lows or value zones.
---
### ✅ Conclusion
Since the manipulation volume failed to exceed the accumulation volume, the breakout lacked real strength. Combined with decreasing volume in the distribution phase, this indicates fading demand and supply taking control—which justifies entering a short position.
Highs & Lows - Multi TimeFrame### **📌 HL-MWD (Highs & Lows - Multi Timeframe Indicator) – Community Release**
#### **🔹 Overview**
The **HL-MWD Indicator** is a **multi-timeframe support & resistance tool** that plots **historical highs and lows** from **daily, weekly, and monthly timeframes** onto an intraday chart. It helps traders **identify key levels of support and resistance** that have influenced price action over different timeframes.
This indicator is useful for **day traders, swing traders, and position traders** who rely on **multi-timeframe analysis** to spot critical price levels.
---
### **🔥 Key Features**
✅ **Plots Highs & Lows for Daily, Weekly, and Monthly Timeframes**
✅ **Customizable Lookback Periods for Each Timeframe**
✅ **Adjustable Line Colors, Styles (Solid, Dotted, Dashed), and Widths**
✅ **Extend Lines into the Future to Identify Key Price Levels**
✅ **Option to Display Price Labels for Each Level**
✅ **Gradient Option to Highlight Recent Highs & Lows (Disabled by Default)**
✅ **Compatible with Intraday, Daily, and Weekly Charts**
---
### **📈 How It Works**
- **Daily Highs & Lows:** Captures the **highest and lowest prices** within the selected lookback period (default: **14 bars**).
- **Weekly Highs & Lows:** Marks the **highest and lowest prices** within the chosen weekly lookback (default: **52 bars**).
- **Monthly Highs & Lows:** Displays the **high and low points** from the monthly timeframe (default: **36 bars**).
- **Extended Lines:** Project past highs and lows **into the future** to help identify **potential support & resistance zones**.
---
### **⚠️ TradingView Lookback Limitations**
🔹 **TradingView has a limit on how many historical bars can be accessed per timeframe**, which affects how far back the indicator can retrieve data.
🔹 **Intraday charts (e.g., 5m, 15m) have a limited number of past bars**, meaning:
- **You won’t be able to view 36 months' worth of monthly levels** on a **5-minute chart**, because TradingView doesn’t store that much data in lower timeframes.
- **If multiple timeframes (e.g., weekly + monthly) are enabled at the same time**, some historical data may **not be available on shorter timeframes**.
🔹 **Recommendation:**
- If using **monthly lookbacks (36 months+), view them on a daily or higher timeframe**.
- If using **weekly lookbacks (52 weeks+), higher intraday timeframes (e.g., 1-hour, 4-hour) are better suited**.
- **Lower timeframes (1m, 5m, 15m) may miss some levels** if TradingView's bar limit is exceeded.
---
### **⚙️ Customization Options**
| **Setting** | **Default Value** | **Description** |
|------------------|----------------|----------------|
| **Daily Lookback** | `14` | Number of bars used to calculate daily highs/lows. |
| **Weekly Lookback** | `52` | Number of bars used to calculate weekly highs/lows. |
| **Monthly Lookback** | `36` | Number of bars used to calculate monthly highs/lows. |
| **Line Colors** | Daily: `Blue` Weekly: `Green` Monthly: `Red` | Customizable colors for each timeframe. |
| **Line Style** | `Solid` | Options: Solid, Dashed, Dotted. |
| **Line Width** | `1` | Thickness of the plotted lines. |
| **Extend Line** | `1` | Controls how far the highs/lows extend into the future. |
| **Display Price Labels** | `Enabled` | Shows price labels on each level. |
---
### **🛠️ How to Use It**
- **Enable/disable different timeframes** based on your strategy.
- **Customize colors, line styles, and widths** to match your charting style.
- **Use extended lines to identify support & resistance zones.**
- **Watch price reactions at these levels** for potential entries, exits, and stop-loss placements.
---
### **🚀 Final Thoughts**
The **HL-MWD Indicator** is a **powerful multi-timeframe tool** that helps traders **visualize key support & resistance levels** from higher timeframes on an intraday chart.
⚠️ **However, TradingView’s lookback limits apply—so for longer-term levels, higher timeframes are recommended.**
📌 **Now published for the community!** Let me know if you need any last-minute tweaks! 🔥
CandleCandle: A Comprehensive Pine Script™ Library for Candlestick Analysis
Overview
The Candle library, developed in Pine Script™, provides traders and developers with a robust toolkit for analyzing candlestick data. By offering easy access to fundamental candlestick components like open, high, low, and close prices, along with advanced derived metrics such as body-to-wick ratios, percentage calculations, and volatility analysis, this library enables detailed insights into market behavior.
This library is ideal for creating custom indicators, trading strategies, and backtesting frameworks, making it a powerful resource for any Pine Script™ developer.
Key Features
1. Core Candlestick Data
• Open : Access the opening price of the current candle.
• High : Retrieve the highest price.
• Low : Retrieve the lowest price.
• Close : Access the closing price.
2. Candle Metrics
• Full Size : Calculates the total range of the candle (high - low).
• Body Size : Computes the size of the candle’s body (open - close).
• Wick Size : Provides the combined size of the upper and lower wicks.
3. Wick and Body Ratios
• Upper Wick Size and Lower Wick Size .
• Body-to-Wick Ratio and Wick-to-Body Ratio .
4. Percentage Calculations
• Upper Wick Percentage : The proportion of the upper wick size relative to the full candle size.
• Lower Wick Percentage : The proportion of the lower wick size relative to the full candle size.
• Body Percentage and Wick Percentage relative to the candle’s range.
5. Candle Direction Analysis
• Determines if a candle is "Bullish" or "Bearish" based on its closing and opening prices.
6. Price Metrics
• Average Price : The mean of the open, high, low, and close prices.
• Midpoint Price : The midpoint between the high and low prices.
7. Volatility Measurement
• Calculates the standard deviation of the OHLC prices, providing a volatility metric for the current candle.
Code Architecture
Example Functionality
The library employs a modular structure, exporting various functions that can be used independently or in combination. For instance:
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © DevArjun
//@version=6
indicator("Candle Data", overlay = true)
import DevArjun/Candle/1 as Candle
// Body Size %
bodySize = Candle.BodySize()
// Determining the candle direction
candleDirection = Candle.CandleDirection()
// Calculating the volatility of the current candle
volatility = Candle.Volatility()
// Plotting the metrics (for demonstration)
plot(bodySize, title="Body Size", color=color.blue)
label.new(bar_index, high, candleDirection, style=label.style_circle)
Scalability
The modularity of the Candle library allows seamless integration into more extensive trading systems. Functions can be mixed and matched to suit specific analytical or strategic needs.
Use Cases
Trading Strategies
Developers can use the library to create strategies based on candle properties such as:
• Identifying long-bodied candles (momentum signals).
• Detecting wicks as potential reversal zones.
• Filtering trades based on candle ratios.
Visualization
Plotting components like body size, wick size, and directional labels helps visualize market behavior and identify patterns.
Backtesting
By incorporating volatility and ratio metrics, traders can design and test strategies on historical data, ensuring robust performance before live trading.
Education
This library is a great tool for teaching candlestick analysis and how each component contributes to market behavior.
Portfolio Highlights
Project Objective
To create a Pine Script™ library that simplifies candlestick analysis by providing comprehensive metrics and insights, empowering traders and developers with advanced tools for market analysis.
Development Challenges and Solutions
• Challenge : Achieving high precision in calculating ratios and percentages.
• Solution : Implemented robust mathematical operations and safeguarded against division-by-zero errors.
• Challenge : Ensuring modularity and scalability.
• Solution : Designed functions as independent modules, allowing flexible integration.
Impact
• Efficiency : The library reduces the time required to calculate complex candlestick metrics.
• Versatility : Supports various trading styles, from scalping to swing trading.
• Clarity : Clean code and detailed documentation ensure usability for developers of all levels.
Conclusion
The Candle library exemplifies the power of Pine Script™ in simplifying and enhancing candlestick analysis. By including this project in your portfolio, you showcase your expertise in:
• Financial data analysis.
• Pine Script™ development.
• Creating tools that solve real-world trading challenges.
This project demonstrates both technical proficiency and a keen understanding of market analysis, making it an excellent addition to your professional portfolio.
Library "Candle"
A comprehensive library to access and analyze the basic components of a candlestick, including open, high, low, close prices, and various derived metrics such as full size, body size, wick sizes, ratios, percentages, and additional analysis metrics.
Open()
Open
@description Returns the opening price of the current candle.
Returns: float - The opening price of the current candle.
High()
High
@description Returns the highest price of the current candle.
Returns: float - The highest price of the current candle.
Low()
Low
@description Returns the lowest price of the current candle.
Returns: float - The lowest price of the current candle.
Close()
Close
@description Returns the closing price of the current candle.
Returns: float - The closing price of the current candle.
FullSize()
FullSize
@description Returns the full size (range) of the current candle (high - low).
Returns: float - The full size of the current candle.
BodySize()
BodySize
@description Returns the body size of the current candle (open - close).
Returns: float - The body size of the current candle.
WickSize()
WickSize
@description Returns the size of the wicks of the current candle (full size - body size).
Returns: float - The size of the wicks of the current candle.
UpperWickSize()
UpperWickSize
@description Returns the size of the upper wick of the current candle.
Returns: float - The size of the upper wick of the current candle.
LowerWickSize()
LowerWickSize
@description Returns the size of the lower wick of the current candle.
Returns: float - The size of the lower wick of the current candle.
BodyToWickRatio()
BodyToWickRatio
@description Returns the ratio of the body size to the wick size of the current candle.
Returns: float - The body to wick ratio of the current candle.
UpperWickPercentage()
UpperWickPercentage
@description Returns the percentage of the upper wick size relative to the full size of the current candle.
Returns: float - The percentage of the upper wick size relative to the full size of the current candle.
LowerWickPercentage()
LowerWickPercentage
@description Returns the percentage of the lower wick size relative to the full size of the current candle.
Returns: float - The percentage of the lower wick size relative to the full size of the current candle.
WickToBodyRatio()
WickToBodyRatio
@description Returns the ratio of the wick size to the body size of the current candle.
Returns: float - The wick to body ratio of the current candle.
BodyPercentage()
BodyPercentage
@description Returns the percentage of the body size relative to the full size of the current candle.
Returns: float - The percentage of the body size relative to the full size of the current candle.
WickPercentage()
WickPercentage
@description Returns the percentage of the wick size relative to the full size of the current candle.
Returns: float - The percentage of the wick size relative to the full size of the current candle.
CandleDirection()
CandleDirection
@description Returns the direction of the current candle.
Returns: string - "Bullish" if the candle is bullish, "Bearish" if the candle is bearish.
AveragePrice()
AveragePrice
@description Returns the average price of the current candle (mean of open, high, low, and close).
Returns: float - The average price of the current candle.
MidpointPrice()
MidpointPrice
@description Returns the midpoint price of the current candle (mean of high and low).
Returns: float - The midpoint price of the current candle.
Volatility()
Volatility
@description Returns the standard deviation of the OHLC prices of the current candle.
Returns: float - The volatility of the current candle.
Previous Day High and Low Count with Probabilities
Indicator Explanation
This indicator displays the number of days on which the previous day's high or low prices were not reached and calculates probabilities for future price movements based on this information. It stores the high and low values of the last 45 days and checks daily whether these levels were touched. Based on the number of days without touching either the high or the low, the indicator calculates the probability of future price movements in either direction (Up or Down).
The indicator offers customization options for label placement and color on the chart. The counts for the high and low touches, along with the calculated probabilities (in percentages), are displayed as labels on the chart. These labels can be shifted along the X-axis by up to 50 bars and can be customized in color and size. Additionally, the text for the labels can be freely chosen, giving the user improved flexibility and overview.
In summary, this indicator helps to:
- Track how often previous day's high and low levels were not reached.
- Estimate probabilities for future price movements based on this information.
- Customize the chart display for easier interpretation.
Strategy Concept
Probability and Touch Conditions:
A long position is entered only if:
The probability of reaching the high is at least 60%.
The price has not touched the previous day’s high in the last three days.
Similarly, for short positions:
The probability of reaching the low is at least 60%.
The price has not touched the previous day’s low in the last three days.
Incremental Position Size Increase:
On the 3rd consecutive day without a high/low touch and with the probability condition met, an initial position of 0.01 lots is opened.
On the 4th day, an additional position of 0.01 lots is added.
On the 5th day, an extra position of 0.02 lots is opened.
After a two-day pause, the situation is re-evaluated, and if conditions are still met, a 0.04-lot position is considered.
Trend Reversal Detection:
The strategy also includes a simple trend reversal check. If the market shows clear reversal signals, no new positions will be opened.
Adjustments and Risk Management
This strategy can be adjusted by modifying the probability values, the number of days without a high/low touch, and the lot sizes. Additionally, stop-loss and take-profit levels can be added to further control the risk and secure profits.
Strategy Concept
Probability and Touch Conditions:
A long position is entered only if:
The probability of reaching the high is at least 60%.
The price has not touched the previous day’s high in the last three days.
Similarly, for short positions:
The probability of reaching the low is at least 60%.
The price has not touched the previous day’s low in the last three days.
Incremental Position Size Increase:
On the 3rd consecutive day without a high/low touch and with the probability condition met, an initial position of 0.01 lots is opened.
On the 4th day, an additional position of 0.01 lots is added.
On the 5th day, an extra position of 0.02 lots is opened.
After a two-day pause, the situation is re-evaluated, and if conditions are still met, a 0.04-lot position is considered.
Trend Reversal Detection:
The strategy also includes a simple trend reversal check. If the market shows clear reversal signals, no new positions will be opened.
Risk Disclaimer
The author of this strategy does not assume any liability for potential losses or gains that may arise from the use of this strategy. Trading involves significant risk, and it is important to only trade with capital that you can afford to lose. The strategy presented is for educational purposes only and should not be considered as financial advice. Always conduct your own research and consider seeking advice from a professional financial advisor before making any trading decisions.
