Mean Reversion and TrendfollowingTitle: Mean Reversion and Trendfollowing
Introduction:
This script presents a hybrid trading strategy that combines mean reversion and trend following techniques. The strategy aims to capitalize on short-term price corrections during a downtrend (mean reversion) as well as ride the momentum of a trending market (trend following). It uses a 200-period Simple Moving Average (SMA) and a 2-period Relative Strength Index (RSI) to generate buy and sell signals.
Key Features:
Combines mean reversion and trend following techniques
Utilizes 200-period SMA and 2-period RSI
Customizable starting date
Allows for enabling/disabling mean reversion or trend following modes
Adjustable position sizing for trend following and mean reversion
Script Description:
The script implements a trading strategy that combines mean reversion and trend following techniques. Users can enable or disable either of these techniques through the input options. The strategy uses a 200-period Simple Moving Average (SMA) and a 2-period Relative Strength Index (RSI) to generate buy and sell signals.
The mean reversion mode is active when the price is below the SMA200, while the trend following mode is active when the price is above the SMA200. The script generates buy signals when the RSI is below 20 (oversold) in mean reversion mode or when the price is above the SMA200 in trend following mode. The script generates sell signals when the RSI is above 80 (overbought) in mean reversion mode or when the price falls below 95% of the SMA200 in trend following mode.
Users can adjust the position sizing for both trend following and mean reversion modes using the input options.
To use this script on TradingView, follow these steps:
Open TradingView and load your preferred chart.
Click on the 'Pine Editor' tab located at the bottom of the screen.
Paste the provided script into the Pine Editor.
Click 'Add to Chart' to apply the strategy to your chart.
Please note that the past performance of any trading system or methodology is not necessarily indicative of future results. Always use proper risk management and consult a financial advisor before making any investment decisions.
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The following is a summary of the underlying whitepaper (onlinelibrary.wiley.com) for this strategy:
This paper proposes a theory of securities market under- and overreactions based on two psychological biases: investor overconfidence about the precision of private information and biased self-attribution, which causes asymmetric shifts in investors' confidence as a function of their investment outcomes. The authors show that overconfidence implies negative long-lag autocorrelations, excess volatility, and public-event-based return predictability. Biased self-attribution adds positive short-lag autocorrelations (momentum), short-run earnings "drift," and negative correlation between future returns and long-term past stock market and accounting performance.
The paper explains that there is empirical evidence challenging the traditional view that securities are rationally priced to reflect all publicly available information. Some of these anomalies include event-based return predictability, short-term momentum, long-term reversal, high volatility of asset prices relative to fundamentals, and short-run post-earnings announcement stock price "drift."
The authors argue that investor overconfidence can lead to stock prices overreacting to private information signals and underreacting to public signals. This overreaction-correction pattern is consistent with long-run negative autocorrelation in stock returns, excess volatility, and further implications for volatility conditional on the type of signal. The market's tendency to over- or underreact to different types of information allows the authors to address the pattern that average announcement date returns in virtually all event studies are of the same sign as the average post-event abnormal returns.
Biased self-attribution implies short-run momentum and long-term reversals in security prices. The dynamic analysis based on biased self-attribution can also lead to a lag-dependent response to corporate events. Cash flow or earnings surprises at first tend to reinforce confidence, causing a same-direction average stock price trend. Later reversal of overreaction can lead to an opposing stock price trend.
The paper concludes by summarizing the findings, relating the analysis to the literature on exogenous noise trading, and discussing issues related to the survival of overconfident traders in financial markets.
חפש סקריפטים עבור "Relative"
[Hoss] OBV RSIThe OBV ( On Balance Volume ) RSI ( Relative Strength Index ) indicator is an innovative tool that combines the power of OBV and RSI to provide traders with a comprehensive view of the market's momentum and volume dynamics. This combination enables users to make better-informed trading decisions by analyzing the relationship between price, volume , and relative strength .
The script starts by calculating the On Balance Volume , which is a cumulative volume-based indicator that measures buying and selling pressure. The OBV increases when the closing price is higher than the previous closing price and decreases when the closing price is lower than the previous closing price. This helps traders identify potential price trend reversals based on volume accumulation or distribution.
Next, the script computes the Relative Strength Index ( RSI ) based on the OBV values, offering a unique perspective on the market's momentum through the lens of volume . The RSI is a popular momentum indicator that ranges from 0 to 100 and helps traders identify overbought and oversold conditions. In this script, the user can define the RSI length and the higher and lower levels (default values are 70 and 30, respectively).
A distinctive feature of this OBV RSI indicator is the addition of a monitor that counts the number of times the RSI crosses above the higher level and below the lower level within a user-defined lookback period. This monitor is displayed as a table in the bottom right corner of the chart and can be enabled or disabled through an input option.
The cross count monitor provides valuable insights into the historical frequency of RSI crossings, helping traders to identify potential trading opportunities based on historical price behavior around these levels.
"The Stocashi" - Stochastic RSI + Heikin-AshiWhat up guys and welcome to the coffee shop. I have a special little tool for you today to throw in your toolbox. This one is a freebie.
This is the Stochastic RS-Heiken-Ashi "The Stocashi"
This is the stochastic RSI built to look like Heikin-Ashi candles.
a lot of people have trouble using the stochastic indicator because of its ability to look very choppy at its edges instead of having nice curves or arcs to its form when you use it on scalping time frames it ends up being very pointed and you can't really tell when the bands turn over if you're using a stochastic Ribbon or you can't tell when it's actually moving in a particular direction if you're just using the K and the D line.
This new format of Presentation seeks to get you to have a better visual representation of what the stochastic is actually doing.
It's long been noted that Heikin-Ashi do a very good job of representing momentum in a price so using it on something that is erratic as the stochastic indicator seems like a plausible idea.
The strategy is simple because you use it exactly the same way you've always used the stochastic indicator except now you can look for the full color of the candle.
this one uses a gradient color setup for the candle so when the candle is fully red then you have a confirmed downtrend and when the candle is fully green you have a confirmed up trend of the stochastic however if, you a combination of the two colors inside of one candle then you do not have a confirmed direction of the stochastic.
the strategy is simple for the stochastic and that you need to know your overall trend. if you are in an uptrend you are waiting for the stochastic to reach bottom and start curving up.
if you are in a downtrend you are waiting for the stochastic to reach its top or its peak and curve down.
In an uptrend you want to make sure that the stochastic is making consistently higher lows just like price should be. if at any moment it makes a lower low then you know you have a problem with your Trend and you should consider exiting.
The opposite is true for a downtrend. In a downtrend you want to make sure you have lower highs. if at any given moment you end up with a higher high than you know you have a problem with your Trend and it's probably ending so you should consider exiting.
The stochastic indicator done as he can actually candles also does a very good job of telling you when there is a change of character. In that moment when the change of character shows up you simply wait until your trend and your price start to match up.
You can also use the stochastic indicator in this format to find divergences the same way you would on the relative strength index against your price highs and price lows so Divergence trading is visually a little bit easier with this tool.
The settings for the K percent D percent RSI length and stochastic length can be adjusted at will so be sure to study the history of the stochastic and find the good settings for your trading strategy.
Dynamo
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Overview
Dynamo is built to be the Swiss-knife for price-movement & strength detection, it aims to provide a holistic view of the current price across multiple dimensions. This is achieved by combining 3 very specific indicators(RSI, Stochastic & ADX) into a single view. Each of which serve a different purpose, and collectively provide a simple, yet powerful tool to gauge the true nature of price-action.
Background
Dynamo uses 3 technical analysis tools in conjunction to provide better insights into price movement, they are briefly explained below:
Relative Strength Index(RSI)
RSI is a popular indicator that is often used to measure the velocity of price change & the intensity of directional moves. RSI computes the relative strength of the current price by comparing the security’s bullish strength versus bearish strength for a given period, i.e. by comparing average gain to average loss.
It is a range bound(0-100) variable that generates a bullish reading if average gain is higher, and a bullish reading if average loss is higher. Values over 50 are generally considered bullish & values less than 50 indicate a bearish market. Values over 70 indicate an overbought condition, and values below 30 indicate oversold condition.
Stochastic
Stochastic is an indicator that aims to measure the momentum in the market, by comparing most recent closing price of the security to its price range for a given period. It is based on the assumption that price tends to close near the recent high in an up trend, and it closes near the recent low during a down trend.
It is also range bound(0-100), values over 80 indicate overbought condition and values below 20 indicate oversold condition.
Average Directional Index(ADX)
ADX is an indicator that can quantify trend strength, it is derived from two underlying indices, known as Directional Movement Index(DMI). +DMI represents strength of the up trend, and -DMI represents strength of the down trend, and ADX is the average of the two.
ADX is non-directional or trend-neutral, which means, it does not follow the direction of the price, instead ADX will rise only when there is a strong trend, it does not matter if it’s an up trend or a down trend. Typical ranges of ADX are 25-50 for a strong trend, anything below 25 is considered as no trend or weak trend. ADX can frequently shoot upto higher values, but it generally finds exhaustion levels around the 60-75 range.
About the script
All these indicators are very powerful tools, but just like any other indicator they have their limitations. Stochastic & ADX can generate false signals in volatile markets, meaning price wouldn’t always follow through with what’s being indicated. ADX may even fail to generate a signal in less volatile markets, simply because it is based on moving averages, it tends to react slower to price changes. RSI can also lose it’s effectiveness when markets are trending strong, as it can stay in the overbought or oversold ranges for an extended period of time.
Dynamo aims to provide the trader with a much broader perspective by bringing together these contrasting indicators into a single simplified view. When Stochastic becomes less reliable in highly volatile conditions, one can cross validate their deduction by looking at RSI patterns. When RSI gets stuck in overbought or oversold range, one can refer to ADX to get better picture about the current trend. Similarly, various combinations of rules & setups can be formulated to get a more deterministic view, when working with either of these indicators.
There many possible use cases for a tool like this, and it totally depends on how you want to use it. An obvious option is to use it to trigger signals only after it has been confirmed by two or more indicators, for example, RSI & Stochastic make a great combination for cross-over or cross-under strategies. Some of the other options include trend detection, strength detection, reversals or price rejection points, possible duration of a trend, and all of these can very easily be translated into effective entry and exit points for trades.
How to use it
Dynamo is an easy-to-use tool, just add it to your chart and you’re good to start with your market analysis. Output consists of three overlapping plots, each of which tackle price movement from a slightly different angle.
Stochastic: A momentum indicator that plots the current closing price in relation to the price-range over a given period of time.
Can be used to detect the direction of the price movement, potential reversals, or duration of an up/down move.
Plotted as grey coloured histograms in the background.
Relative Strength Index(RSI): RSI is also a momentum indicator that measures the velocity with which the price changes.
Can be used to detect the speed of the price movement, RSI divergences can be a nice way to detect directional changes.
Plotted as an aqua coloured line.
Average Directional Index(ADX): ADX is an indicator that is used to measure the strength of the current trend.
Can be used to measure how strong the price movement is, both up and down, or to establish long terms trends.
Plotted as an orange coloured line.
Features
Provides a well-rounded view of the market movement by amalgamating some of the best strength indicators, helping traders make better informed decisions with minimal effort.
Simplistic plots that aim to convey clean signals, as a result, reducing clutter on the chart, and hopefully in the trader's head too.
Combines different types of indicators into a single view, which leads to an optimised use of the precious screen real-estate.
Final Note
Dynamo is designed to be minimalistic in functionality and in appearance, as it is being built to be a general purpose tool that is not only beginner friendly, but can also be highly-configurable to meet the needs of pro traders.
Thresholds & default values for the indicators are only suggestions based on industry standards, they may not be an exact match for all markets & conditions. Hence, it is advisable for the user to test & adjust these values according their securities and trading styles.
The chart highlights one of many possible setups using this tool, and it can used to create various types of setups & strategies, but it is also worth noting that the usability & the effectiveness of this tool also depends on the user’s understanding & interpretation of the underlying indicators.
Lastly, this tool is only an indicator and should only be perceived that way. It does not guarantee anything, and the user should do their own research before committing to trades based on any indicator.
AII - Average indicator of indicatorsThis Pine Script for TradingView is a technical analysis tool that visualizes the average of several popular indicators in the trading world. The indicators included are the RSI (Relative Strength Index), RVI (Relative Vigor Index), Stochastic RSI, Williams %R, relative MACD (ranging from 0 to 100), and Bollinger Bands price distance from 0 to 100. The script uses the "input" function to customize the length of the indicators and the "plot" function to display the results on the chart. In addition, options are included to turn off certain indicators and change the line colors if the user desires. All indicators can also be activated independently, allowing the user to see only the indicators they want. It is also mentioned that the script will be improved in the future to offer a better user experience. The calculated values are calculated with the default EMA of 14. Overall, this script is an excellent option for those looking for a combined view of several important indicators for making trading decisions.
Stable Coin Dominance RSIThe Stable Coin Dominance RSI evaluates the relative dominance of stable coins within the crypto ecosystem as compared to the total market cap. As stable coin dominance rises, it suggests that market participants are exiting out of crypto assets and into dollar pegged stable coins. The opposite is true inversely; as stable coin dominance diminishes, it suggests that market participants are divesting out of stable coins and into crypto assets.
Stable coin dominance can be expressed as a percentage of the total market cap as follows: Stable Coins / Total Crypto. The Stable Coin Dominance RSI indicator uses this percentage and converts it into an oscillator using the formula for the relative strength index.
The calculation for the indicator is: RSI
The users can select from USDT and USDC, two most dominant stable tokens by market cap, and compare their relative dominance against Bitcoin and the alt market.
The Stable Coin Dominance RSI may be useful on larger timeframes when attempting to identify the market’s appetite for risk along with oversold and undersold readings which may indicate pivots or turn arounds along market extremes.
The limitation of the indicator lies in the fact that stable coins continue to make up a growing percentage of the total market cap over time and thus comparisons to earlier cycles will not be a perfect apples-to-apples evaluation. This being said, the smoothing function of the RSI’s look back helps to moderate these comparative differences.
Banknifty Volume - IN
This simple indicator computes the average Relative Strength Index of each Banknifty stock and displays the volume on the chart with color schemes while the average line indicates the average RSI of all Bank Stocks. This indicator works on Banknifty and its stocks.
It works on all time frames
How You can use this?
You can use this indicator for Volume analysis if the average RSI line is above the 0 line, the stock is moving upside and vice versa for Downside .
KINSKI Multi Trend OscillatorThe Multi Trend Oscillator is a tool that combines the ratings of several indicators to facilitate the search for profitable trades. I was inspired by the excellent indicator "Technical Ratings" from Team TradingView to create an alternative with a technically new approach. Therefore, it is not a modified copy of the original, but newly conceived and implemented.
The recommendations of the indicator are based on the calculated ratings from the different indicators included in it. The special thing here is that all settings for the individual indicators can be changed according to your own needs and displayed as a histogram and MA line. This provides an excellent visual control of your own settings. Alarms are also triggered.
Criteria for determining the rating
Relative Strength Index (RSI)
Buy - Crossover oversold level and indicator < oversold level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Relative Strength Index (RSI) Laguerre
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Noise free Relative Strength Index (RSX)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Money Flow Index (MFI)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Commodity Channel Index (CCI)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Moving Average Convergence/Divergence (MACD)
Buy - values of the main line > values of the signal line and rising
Sell - values of the main line < values of the signal line and falling
Neutral - neither Buy nor Sell
Klinger
Buy - indicator >= 0 and rising
Sell - indicator < 0 and falling
Neutral - neither Buy nor Sell
Average Directional Index (ADX)
Buy - indicator > 20 and +DI line crosses over the -DI line and rising
Sell - indicator > 20 and +DI line crosses below the -DI line and falling
Neutral - neither Buy nor Sell
Awesome Oscillator
Buy - Crossover 0 and values are greater than 0, or exceed the zero line
Sell - Crossunder 0 and values are lower than 0, or fall below the zero line
Neutral - neither Buy nor Sell
Ultimate Oscillator
Buy - Crossover oversold level and indicator < oversold level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Williams Percent Range
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder Oversold Level and Indicator >= Oversold Level and falling
Neutral - neither Buy nor Sell
Momentum
Buy - Crossover 0 and indicator levels rising
Sell - Crossunder 0 and indicator values falling
Neutral - neither Buy nor Sell
Total Ratings
The numerical value of the rating "Sell" is 0, "Neutral" is 0 and "Buy" is 1. The total rating is calculated as the average of the ratings of the individual indicators and are determined according to the following criteria:
MaxCount = 12 (depending on whether other oscillators are added).
CompareSellStrong = MaxCount * 0.3
CompareMid = MaxCount * 0.5
CompareBuyStrong = MaxCount * 0.7
value <= CompareSellStrong - Strong Sell
value < CompareMid and value > CompareSellStrong - Sell
value == 6 - Neutral
value > CompareMid and value < CompareBuyStrong - Buy
value >= CompareBuyStrong - Strong Buy
Understanding the results
The Multi Trend Oscillator is designed so that its values fluctuate between 0 and currently 12 (maximum number of integrated indicators). Its values are displayed as a histogram with green, red and gray bars. The bars are gray when the value of the indicator is at half of the number of indicators used, currently 12. Increasingly saturated green bars indicate increasing values above 6, and increasingly saturated red bars indicate increasingly decreasing values below 6.
The table at the end of the histogram shows details (can be activated in the settings) about the overall rating and the individual indicators. Its color is determined by the rating value: gray for neutral, green for buy or strong buy, red for sell or strong sell.
The following alarms are triggered:
Multi Trend Oscillator: Sell
Multi Trend Oscillator: Strong Sell
Multi Trend Oscillator: Buy
Multi Trend Oscillator: Strong Buy
Volatility Adapted Relative StrengthVARS uses a stock's ALPHA in comparison to the SPX to determine whether there is RS on an volatility adjusted basis.
ETF Trends//@Devendra Akolkar - @dakolkar - This indicator will compare and show relative performance of 3 symbols.
// It'll compare those 3 symbols on 3 different Timeframe (Weekly - 5 sessions , BiWeekly - 10 sessions and Monthly - 20 sessions) and display performance in %
TRIX RSI - Tripple Exponetial Relative Strength (TRSI) This indicator applies the RSI formula over the TRIX indicator to get the TRIX RSI.
The EMA and the TRIX RSA cross gives you an indication for a trend change
Strength Relative to BTCShows strength of the currently charted alt compared to BTCUSD. If BTC is going down or sideways and the alt is going up, then you'll see green and vice-versa for red. Good for quick at-a-glance strength evaluation when flying through a watchlist. The output uses a normalised moving average to reduce signal noise.
[RS]Volume Relative Strength IndexEXPERIMENTAL:
A different take at the RSI weighted by volume , supposedly it should give a clearer picture of the underlying action.
RSI Distribution [Kodexius]RSI Distribution is a statistics driven visualization companion for the classic RSI oscillator. In addition to plotting RSI itself, it continuously builds a rolling sample of recent RSI values and projects their distribution as a forward drawn histogram, so you can see where RSI has spent most of its time over the selected lookback window.
The indicator is designed to add context to oscillator readings. Instead of only treating RSI as a single point estimate that is either “high” or “low”, you can evaluate the current RSI level relative to its own recent history. This makes it easier to recognize when the market is operating inside a familiar regime, and when RSI is pushing into rarer tail conditions that tend to appear during momentum bursts, exhaustion, or volatility expansion.
To complement the histogram, the script can optionally overlay a Gaussian curve fitted to the sample mean and standard deviation. It also runs a Jarque Bera normality check, based on skewness and excess kurtosis, and surfaces the result both visually and in a compact dashboard. On the oscillator panel itself, RSI is presented with a clean gradient line and standard overbought and oversold references, with fills that become more visible when RSI meaningfully extends beyond key thresholds.
🔹 Features
1. Distribution Histogram of Recent RSI Values
The script stores the last N RSI values in an internal sample and uses that rolling window to compute a frequency distribution across a user selected number of bins. The histogram is drawn into the future by a configurable width in bars, which keeps it readable and prevents it from colliding with the active RSI plot. The result is a compact visual summary of where RSI clusters most often, whether it is spending more time near the center, or shifting toward higher or lower regimes.
2. Gaussian Overlay for Shape Intuition
If enabled, a fitted bell curve is drawn on top of the histogram using the sample mean and standard deviation. This overlay is not intended as a direct trading signal. Its purpose is to provide a fast visual comparator between the empirical RSI distribution and a theoretical normal shape. When the histogram diverges strongly from the curve, you can quickly spot skew, heavy tails, or regime changes that often occur when market structure or volatility conditions shift.
3. Jarque Bera Normality Check With Clear PASS/FAIL Feedback
The script computes skewness and excess kurtosis from the RSI sample, then forms the Jarque Bera statistic and compares it to a fixed 95% critical value. When the distribution is closer to normal under this test, the status is marked as PASS, otherwise it is marked as FAIL. This result is displayed in the dashboard and can also influence the histogram styling, giving immediate feedback about whether the recent RSI behavior resembles a bell shaped distribution or a more distorted, regime driven profile.
Jarque Bera is a goodness of fit test that evaluates whether a dataset looks consistent with a normal distribution by checking two shape properties: skewness (asymmetry) and kurtosis (tail heaviness, expressed here as excess kurtosis where a perfect normal has 0). Under the null hypothesis of normality, skewness should be near 0 and excess kurtosis should be near 0. The test combines deviations in both into a single statistic, which is then compared to a chi square threshold. A PASS in this script means the sample does not show strong evidence against normality at the chosen threshold, while a FAIL means the sample is meaningfully skewed, heavy tailed, or both. In practical trading terms, a FAIL often suggests RSI is behaving in a regime where extremes and asymmetry are more common, which is typical during strong trends, volatility expansions, or one sided market pressure. It is still a statistical diagnostic, not a prediction tool, and results can vary with lookback length and market conditions.
4. Integrated Stats Dashboard
A compact table in the top right summarizes key distribution moments and the normality result: Mean, StdDev, Skewness, Kurtosis, and the JB statistic with PASS/FAIL text. Skewness is color coded by sign to quickly distinguish right skew (more time at higher RSI) versus left skew (more time at lower RSI), which can be helpful when diagnosing trend bias and momentum persistence.
5. RSI Visual Quality and Context Zones
RSI is plotted with a gradient color scheme and standard overbought and oversold reference lines. The overbought and oversold areas are filled with a smart gradient so visual emphasis increases when RSI meaningfully extends beyond the 70 and 30 regions, improving readability without overwhelming the panel.
🔹 Calculations
This section summarizes the main calculations and transformations used internally.
1. RSI Series
RSI is computed from the selected source and length using the standard RSI function:
rsi_val = ta.rsi(rsi_src, rsi_len)
2. Rolling Sample Collection
A float array stores recent RSI values. Each bar appends the newest RSI, and if the array exceeds the configured lookback, the oldest value is removed. Conceptually:
rsi_history.push(rsi_val)
if rsi_history.size() > lookback
rsi_history.shift()
This maintains a fixed size window that represents the most recent RSI behavior.
3. Mean, Variance, and Standard Deviation
The script computes the sample mean across the array. Variance is computed as sample variance using (n - 1) in the denominator, and standard deviation is the square root of that variance. These values serve both the dashboard display and the Gaussian overlay parameters.
4. Skewness and Excess Kurtosis
Skewness is calculated from the standardized third central moment with a small sample correction. Kurtosis is computed as excess kurtosis (kurtosis minus 3), so the normal baseline is 0. These two metrics summarize asymmetry and tail heaviness, which are the core ingredients for the Jarque Bera statistic.
5. Jarque Bera Statistic and Decision Rule
Using skewness S and excess kurtosis K, the Jarque Bera statistic is computed as:
JB = (n / 6.0) * (S^2 + 0.25 * K^2)
Normality is flagged using a fixed critical value:
is_normal = JB < 5.991
This produces a simple PASS/FAIL classification suitable for fast chart interpretation.
6. Histogram Binning and Scaling
The RSI domain is treated as 0 to 100 and divided into a configurable number of bins. Bin size is:
bin_size = 100.0 / bins
Each RSI sample maps to a bin index via floor(rsi / bin_size), with clamping to ensure the index stays within valid bounds. The script counts occurrences per bin, tracks the maximum frequency, and normalizes each bar height by freq/max_freq so the histogram remains visually stable and comparable as the window updates.
7. Gaussian Curve Overlay (Optional)
The Gaussian overlay uses the normal probability density function with mu as the sample mean and sigma as the sample standard deviation:
normal_pdf(x) = (1 / (sigma * sqrt(2*pi))) * exp(-0.5 * ((x - mu)/sigma)^2)
For drawing, the script samples x across the histogram width, evaluates the PDF, and normalizes it relative to its peak so the curve fits within the same visual height scale as the histogram.
Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]Impulse Reactor RSI-SMA Trend Indicator
Introduction and Theoretical Background
Design Rationale
Standard indicators frequently generate binary 'BUY' or 'SELL' signals without accounting for the broader market context. This often results in erratic "Flip-Flop" behavior, where signals are triggered indiscriminately regardless of the prevailing volatility regime.
Impulse Reactor was engineered to address this limitation by unifying two critical requirements: Quantitative Rigor and Execution Flexibility.
The Solution
Composite Analytical Framework This script is not a simple visual overlay of existing indicators. It is an algorithmic synthesis designed to function as a unified decision-making engine. The primary objective was to implement rigorous quantitative analysis (Volatility Normalization, Structural Filtering) directly within an alert-enabled framework. This architecture is designed to process signals through strict, multi-factor validation protocols before generating real-time notifications, allowing users to focus on structurally validated setups without manual monitoring.
How It Works
This is not a simple visual mashup. It utilizes a cross-validation algorithm where the Trend Structure acts as a gatekeeper for Momentum signals:
Logic over Lag: Unlike simple moving average crossovers, this script uses a 15-layer Gradient Ribbon to detect "Laminar Flow." If the ribbon is knotted (Compression), the system mathematically suppresses all signals.
Volatility Normalization: The core calculation adapts to ATR (Average True Range). This means the indicator automatically expands in volatile markets and contracts in quiet ones, maintaining accuracy without constant manual tweaking.
Adaptive Signal Thresholding: It incorporates an 'Anti-Greed' algorithm (Dynamic Thresholding) that automatically adjusts entry criteria based on trend duration. This logic aims to mitigate the risk of entering positions during periods of statistical trend exhaustion.
Why Use It?
Market State Decoding: The gradient Ribbon visualizes the underlying trend phase in real-time.
◦ Cyan/Blue Flow: Strong Bullish Trend (Laminar Flow).
◦ Magenta/Pink Flow: Strong Bearish Trend.
◦ Compressed/Knotted: When the ribbon lines are tightly squeezed or overlapping, it signals Consolidation. The system filters signals here to avoid chop.
Noise Reduction: The goal is not to catch every pivot, but to isolate high-confidence setups. The logic explicitly filters out minor fluctuations to help maintain position alignment with the broader trend.
⚖️ Chapter 1: System Architecture
Introduction: Composite Analytical Framework
System Overview
Impulse Reactor serves as a comprehensive technical analysis engine designed to synthesize three distinct market dimensions—Momentum, Volatility, and Trend Structure—into a unified decision-making framework. Unlike traditional methods that analyze these metrics in isolation, this system functions as a central processing unit that integrates disparate data streams to construct a coherent model of market behavior.
Operational Objective
The primary objective is to transition from single-dimensional signal generation to a multi-factor assessment model. By fusing data from the Impulse Core (Volatility), Gradient Oscillator (Momentum), and Structural Baseline (Trend), the system aims to filter out stochastic noise and identify high-probability trade setups grounded in quantitative confluence.
Market Microstructure Analysis: Limitations of Conventional Models
Extensive backtesting and quantitative analysis have identified three critical inefficiencies in standard oscillator-based strategies:
• Bounded Oscillator Limitations (The "Oscillation Trap"): Traditional indicators such as RSI or Stochastics are mathematically constrained between fixed values (0 to 100). In strong trending environments, these metrics often saturate in "overbought" or "oversold" zones. Consequently, traders relying on static thresholds frequently exit structurally valid positions prematurely or initiate counter-trend trades against prevailing momentum, resulting in suboptimal performance.
• Quantitative Blindness to Quality: Standard moving averages and trend indicators often fail to distinguish the qualitative nature of price movement. They treat low-volume drift and high-velocity expansion identically. This inability to account for "Volatility Quality" leads to delayed responsiveness during critical market events.
• Fractal Dissonance (Timeframe Disconnect): Financial markets exhibit fractal characteristics where trends on lower timeframes may contradict higher timeframe structures. Manual integration of multi-timeframe analysis increases cognitive load and susceptibility to human error, often resulting in conflicting biases at the point of execution.
Core Design Principles
To mitigate the aforementioned systemic inefficiencies, Impulse Reactor employs a modular architecture governed by three foundational principles:
Principle A:
Volatility Precursor Analysis Market mechanics demonstrate that volatility expansion often functions as a leading indicator for directional price movement. The system is engineered to detect "Volatility Deviation" — specifically, the divergence between short-term and long-term volatility baselines—prior to its manifestation in price action. This allows for entry timing aligned with the expansion phase of market volatility.
Principle B:
Momentum Density Visualization The system replaces singular momentum lines with a "Momentum Density" model utilizing a 15-layer Simple Moving Average (SMA) Ribbon.
• Concept: This visualization represents the aggregate strength and consistency of the trend.
• Application: A fully aligned and expanded ribbon indicates a robust trend structure ("Laminar Flow") capable of withstanding minor counter-trend noise, whereas a compressed ribbon signals consolidation or structural weakness.
Principle C:
Adaptive Confluence Protocols Signal validity is strictly governed by a multi-dimensional confluence logic. The system suppresses signal generation unless there is synchronized confirmation across all three analytical vectors:
1. Volatility: Confirmed expansion via the Impulse Core.
2. Momentum: Directional alignment via the Hybrid Oscillator.
3. Structure: Trend validation via the Baseline. This strict filtering mechanism significantly reduces false positives in non-trending (choppy) environments while maintaining sensitivity to genuine breakouts.
🔍 Chapter 2: Core Modules & Algorithmic Logic
Module A: Impulse Core (Normalized Volatility Deviation)
Operational Logic The Impulse Core functions as a volatility-normalized momentum gauge rather than a standard oscillator. It is designed to identify "Volatility Contraction" (Squeeze) and "Volatility Expansion" phases by quantifying the divergence between short-term and long-term volatility states.
Volatility Z-Score Normalization
The formula implements a custom normalization algorithm. Unlike standard oscillators that rely on absolute price changes, this logic calculates the Z-Score of the Volatility Spread.
◦ Numerator: (atr_f - atr_s) captures the raw momentum of volatility expansion.
◦ Denominator: (std_f + 1e-6) standardizes this value against historical variance.
◦ Result: This allows the indicator scales consistently across assets (e.g., Bitcoin vs. Euro) without manual recalibration.
f_impulse() =>
atr_f = ta.atr(fastLen) // Fast Volatility Baseline
atr_s = ta.atr(slowLen) // Slow Volatility Baseline
std_f = ta.stdev(atr_f, devLen) // Volatility Standard Deviation
(atr_f - atr_s) / (std_f + 1e-6) // Normalized Differential Calculation
Algorithmic Framework
• Differential Calculation: The system computes the spread between a Fast Volatility Baseline (ATR-10) and a Slow Volatility Baseline (ATR-30).
• Normalization Protocol: To standardize consistency across diverse asset classes (e.g., Forex vs. Crypto), the raw differential is divided by the standard deviation of the volatility itself over a 30-period lookback.
• Signal Generation:
◦ Contraction (Squeeze): When the Fast ATR compresses below the Slow ATR, it registers a potential volatility buildup phase.
◦ Expansion (Release): A rapid divergence of the Fast ATR above the Slow ATR signals a confirmed volatility expansion, validating the strength of the move.
Module B: Gradient Oscillator (RSI-SMA Hybrid)
Design Rationale To mitigate the "noise" and "false reversal" signals common in single-line oscillators (like standard RSI), this module utilizes a 15-Layer Gradient Ribbon to visualize momentum density and persistence.
Technical Architecture
• Ribbon Array: The system generates 15 sequential Simple Moving Averages (SMA) applied to a volatility-adjusted RSI source. The length of each layer increases incrementally.
• State Analysis:
Momentum Alignment (Laminar Flow): When all 15 layers are expanded and parallel, it indicates a robust trend where buying/selling pressure is distributed evenly across multiple timeframes. This state helps filter out premature "overbought/oversold" signals.
• Consolidation (Compression): When the distance between the fastest layer (Layer 1) and the slowest layer (Layer 15) approaches zero or the layers intersect, the system identifies a "Non-Tradable Zone," preventing entries during choppy market conditions.
// Laminar Flow Validation
f_validate_trend() =>
// Calculate spread between Ribbon layers
ribbon_spread = ta.stdev(ribbon_array, 15)
// Only allow signals if Ribbon is expanded (Laminar Flow)
is_flowing = ribbon_spread > min_expansion_threshold
// If compressed (Knotted), force signal to false
is_flowing ? signal : na
Module C: Adaptive Signal Filtering (Behavioral Bias Mitigation)
This subsystem, operating as an algorithmic "Anti-Greed" Mechanism, addresses the statistical tendency for signal degradation following prolonged trends.
Dynamic Threshold Adjustment
• Win Streak Detection: The algorithm internally tracks the outcome of closed trade cycles.
• Sensitivity Multiplier: Upon detecting consecutive successful signals in the same direction, a Penalty_Factor is applied to the entry logic.
• Operational Impact: This effectively raises the Required_Slope threshold for subsequent signals. For example, after three consecutive bullish signals, the system requires a 30% steeper trend angle to validate a fourth entry. This enforces stricter discipline during extended trends to reduce the probability of entering at the point of trend exhaustion.
Anti-Greed Logic: Dynamic Threshold Calculation
f_adjust_threshold(base_slope, win_streak) =>
// Adds a 10% penalty to the difficulty for every consecutive win
penalty_factor = 0.10
risk_scaler = 1 + (win_streak * penalty_factor)
// Returns the new, harder-to-reach threshold
base_slope * risk_scaler
Module D: Trend Baseline (Triple-Smoothed Structure)
The Trend Baseline serves as the structural filter for all signals. It employs a Triple-Smoothed Hybrid Algorithm designed to balance lag reduction with noise filtration.
Smoothing Stages
1. Volatility Banding: Utilizes a SuperTrend-based calculation to establish the upper and lower boundaries of price action.
2. Weighted Filter: Applies a Weighted Moving Average (WMA) to prioritize recent price data.
3. Exponential Smoothing: A final Exponential Moving Average (EMA) pass is applied to create a seamless baseline curve.
Functionality
This "Heavy" baseline resists minor intraday volatility spikes while remaining responsive to sustained structural shifts. A signal is only considered valid if the price action maintains structural integrity relative to this baseline
🚦 Chapter 3: Risk Management & Exit Protocols
Quantitative Risk Management (TP/SL & Trailing)
Foundational Architecture: Volatility-Adjusted Geometry Unlike strategies relying on static nominal values, Impulse Reactor establishes dynamic risk boundaries derived from quantitative volatility metrics. This design aligns trade invalidation levels mathematically with the current market regime.
• ATR-Based Dynamic Bracketing:
The protocol calculates Stop-Loss and Take-Profit levels by applying Fibonacci coefficients (Default: 0.786 for SL / 1.618 for TP) to the Average True Range (ATR).
◦ High Volatility Environments: The risk bands automatically expand to accommodate wider variance, preventing premature exits caused by standard market noise.
◦ Low Volatility Environments: The bands contract to tighten risk parameters, thereby dynamically adjusting the Risk-to-Reward (R:R) geometry.
• Close-Validation Protocol ("Soft Stop"):
Institutional algorithms frequently execute liquidity sweeps—driving prices briefly below key support levels to accumulate inventory.
◦ Mechanism: When the "Soft Stop" feature is enabled, the system filters out intraday volatility spikes. The stop-loss is conditional; execution is triggered only if the candle closes beyond the invalidation threshold.
◦ Strategic Advantage: This logic distinguishes between momentary price wicks and genuine structural breakdowns, preserving positions during transient volatility.
• Step-Function Trailing Mechanism:
To protect unrealized PnL while allowing for normal price breathing, a two-phase trailing methodology is employed:
◦ Phase 1 (Activation): The trailing function remains dormant until the price advances by a pre-defined percentage threshold.
◦ Phase 2 (Dynamic Floor): Once armed, the stop level creates a moving floor, adjusting relative to price action while maintaining a volatility-based (ATR) buffer to systematically protect unrealized PnL.
• Algorithmic Exit Protocols (Dynamic Liquidity Analysis)
◦ Rationale: Inefficiencies of Static Targets Static "Take Profit" levels often result in suboptimal exits. They compel traders to close positions based on arbitrary figures rather than evolving market structure, potentially capping upside during significant trends or retaining positions while the underlying trend structure deteriorates.
◦ Solution: Structural Integrity Assessment The system utilizes a Dynamic Liquidity Engine to continuously audit the validity of the position. Instead of targeting a specific price point, the algorithm evaluates whether the trend remains statistically robust.
Multi-Factor Exit Logic (The Tri-Vector System)
The Smart Exit protocol executes only when specific algorithmic invalidation criteria are met:
• 1. Momentum Exhaustion (Confluence Decay): The system monitors a 168-hour rolling average of the Confluence Score. A significant deviation below this historical baseline indicates momentum exhaustion, signaling that the driving force behind the trend has dissipated prior to a price reversal. This enables preemptive exits before a potential drawdown.
• 2. Statistical Over-Extension (Mean Reversion): Utilizing the core volatility logic, the system identifies instances where price deviates beyond 2.0 standard deviations from the mean. While the trend may be technically bullish, this statistical anomaly suggests a high probability of mean reversion (elastic snap-back), triggering a defensive exit to capitalize on peak valuation.
• 3. Oscillator Rejection (Immediate Pivot): To manage sudden V-shaped volatility, the system monitors RSI pivots. If a sharp "Pivot High" or divergence is detected, the protocol triggers an immediate "Peak Exit," bypassing standard trend filters to secure liquidity during high-velocity reversals.
🎨 Chapter 4: Visualization Guide
Gradient Oscillator Ribbon
The 15-layer SMA ribbon visualized via plot(r1...r15) represents the "Momentum Density" of the market.
• Visuals:
◦ Cyan/Blue Ribbon: Indicates Bullish Momentum.
◦ Pink/Magenta Ribbon: Indicates Bearish Momentum.
• Interpretation:
◦ Laminar Flow: When the ribbon expands widely and flows in parallel, it signifies a robust trend where momentum is distributed evenly across timeframes. This is the ideal state for trend-following.
◦ Compression (Consolidation): If the ribbon becomes narrow, twisted, or knotted, it indicates a "Non-Tradable Zone" where the market lacks a unified direction. Traders are advised to wait for clarity.
◦ Over-Extension: If the top layer crosses the Overbought (85) or Oversold (15) lines, it visually warns of potential market overheating.
Trend Baseline
The thick, color-changing line plotted via plot(baseline) represents the Structural Backbone of the market.
• Visuals: Changes color based on the trend direction (Blue for Bullish, Pink for Bearish).
• Interpretation:
Structural Filter: Long positions are statistically favored only when price action sustains above this baseline, while short positions are favored below it.
Dynamic Support/Resistance: The baseline acts as a dynamic support level during uptrends and resistance during downtrends.
Entry Signals & Labels
Text labels ("Long Entry", "Short Entry") appear when the system detects high-probability setups grounded in quantitative confluence.
• Visuals: Labeled signals appear above/below specific candles.
• Interpretation:
These signals represent moments where Volatility (Expansion), Momentum (Alignment), and Structure (Trend) are synchronized.
Smart Exit: Labels such as "Smart Exit" or "Peak Exit" appear when the system detects momentum exhaustion or structural decay, prompting a defensive exit to preserve capital.
Dynamic TP/SL Boxes
The semi-transparent colored zones drawn via fill() represent the risk management geometry.
• Visuals: Colored boxes extending from the entry point to the Take Profit (TP) and Stop Loss (SL) levels.
• Function:
Volatility-Adjusted Geometry: Unlike static price targets, these boxes expand during high volatility (to prevent wicks from stopping you out) and contract during low volatility (to optimize Risk-to-Reward ratios).
SAR + MACD Glow
Small glowing shapes appearing above or below candles.
• Visuals: Triangle or circle glows near the price bars.
• Interpretation:
This visual indicates a secondary confirmation where Parabolic SAR and MACD align with the main trend direction. It serves as an additional confluence factor to increase confidence in the trade setup.
Support/Resistance Table
A small table located at the bottom-right of the chart.
• Function: Automatically identifies and displays recent Pivot Highs (Resistance) and Pivot Lows (Support).
• Interpretation: These levels can be used as potential targets for Take Profit or invalidation points for manual Stop Loss adjustments.
🖥️ Chapter 5: Dashboard & Operational Guide
Integrated Analytics Panel (Dashboard Overview)
To facilitate rapid decision-making without manual calculation, the system aggregates critical market dimensions into a unified "Heads-Up Display" (HUD). This panel monitors real-time metrics across multiple timeframes and analytical vectors.
A. Intermediate Structure (12H Trend)
• Function: Anchors the intraday analysis to the broader market structure using a 12-hour rolling window.
• Interpretation:
◦ Bullish (> +0.5%): Indicates a positive structural bias. Long setups align with the macro flow.
◦ Bearish (< -0.5%): Indicates structural weakness. Short setups are statistically favored.
◦ Neutral: Represents a ranging environment where the Confluence Score becomes the primary weighting factor.
B. Composite Confluence Score (Signal Confidence)
• Definition: A probability metric derived from the synchronization of Volatility (Impulse Core), Momentum (Ribbon), and Trend (Baseline).
• Grading Scale:
Strong Buy/Sell (> 7.0 / < 3.0): Indicates full alignment across all three vectors. Represents a "Prime Setup" eligible for standard position sizing.
Buy/Sell (5.0–7.0 / 3.0–5.0): Indicates a valid trend but with moderate volatility confirmation.
Neutral: Signals conflicting data (e.g., Bullish Momentum vs. Bearish Structure). Trading is not recommended ("No-Trade Zone").
C. Statistical Deviation Status (Mean Reversion)
• Logic: Utilizes Bollinger Band deviation principles to quantify how far price has stretched from the statistical mean (20 SMA).
• Alert States:
Over-Extended (> 2.0 SD): Warning that price is statistically likely to revert to the mean (Elastic Snap-back), even if the trend remains technically valid. New entries are discouraged in this zone.
Normal: Price is within standard distribution limits, suitable for trend-following entries.
D. Volatility Regime Classification
• Metric: Compares current ATR against a 100-period historical baseline to categorize the market state.
• Regimes:
Low Volatility (Lvl < 1.0): Market Compression. Often precedes volatility expansion events.
Mid Volatility (Lvl 1.0 - 1.5): Standard operating environment.
High Volatility (Lvl > 1.5): Elevated market stress. Risk parameters should be adjusted (e.g., reduced position size) to account for increased variance.
E. Performance Telemetry
• Function: Displays the historical reliability of the Trend Baseline for the current asset and timeframe.
• Operational Threshold: If the displayed Win Rate falls below 40%, it suggests the current market behavior is incoherent (choppy) and does not respect trend logic. In such cases, switching assets or timeframes is recommended.
Operational Protocols & Signal Decoding
Visual Interpretation Standards
• Laminar Flow (Trade Confirmation): A valid trend is visually confirmed when the 15-layer SMA Ribbon is fully expanded and parallel. This indicates distributed momentum across timeframes.
• Consolidation (No-Trade): If the ribbon appears twisted, knotted, or compressed, the market lacks a unified directional vector.
• Baseline Interaction: The Triple-Smoothed Baseline acts as a dynamic support/resistance filter. Long positions remain valid only while price sustains above this structure.
System Calibration (Settings)
• Adaptive Signal Filtering (Prev. Anti-Greed): Enabled by default. This logic automatically raises the required trend slope threshold following consecutive wins to mitigate behavioral bias.
• Impulse Sensitivity: Controls the reactivity of the Volatility Core. Higher settings capture faster moves but may introduce more noise.
⚙️ Chapter 6: System Configuration & Alert Guide
This section provides a complete breakdown of every adjustable setting within Impulse Reactor to assist you in tailoring the engine to your specific needs.
🌐 LANGUAGE SETTINGS (Localization)
◦ Select Language (Default: English):
Function: Instantly translates all chart labels, dashboard texts into your preferred language.
Supported: English, Korean, Chinese, Spanish
⚡ IMPULSE CORE SETTINGS (Volatility Engine)
◦ Deviation Lookback (Default: 30): The period used to calculate the standard deviation of volatility.
Role: Sets the baseline for normalizing momentum. Higher values make the core smoother but slower to react.
◦ Fast Pulse Length (Default: 10): The short-term ATR period.
Role: Detects rapid volatility expansion.
◦ Slow Pulse Length (Default: 30): The long-term ATR baseline.
Role: Establishes the background volatility level. The core signal is derived from the divergence between Fast and Slow pulses.
🎯 TP/SL SETTINGS (Risk Management)
◦ SL/TP Fibonacci (Default: 0.786 / 1.618): Selects the Fibonacci ratio used for risk calculation.
◦ SL/TP Multiplier (Default: 1.5 / 2): Applies a multiplier to the ATR-based bands.
Role: Expands or contracts the Take Profit and Stop Loss boxes. Increase these values for higher volatility assets (like Altcoins) to avoid premature stop-outs.
◦ ATR Length (Default: 14): The lookback period for calculating the Average True Range used in risk geometry.
◦ Use Soft Stop (Close Basis):
Role: If enabled, Stop Loss alerts only trigger if a candle closes beyond the invalidation level. This prevents being stopped out by wick manipulations.
🔊 RIBBON SETTINGS (Momentum Visualization)
◦ Show SMA Ribbon: Toggles the visibility of the 15-layer gradient ribbon.
◦ Ribbon Line Count (Default: 15): The number of SMA lines in the ribbon array.
◦ Ribbon Start Length (Default: 2) & Step (Default: 1): Defines the spread of the ribbon.
Role: Controls the "thickness" of the momentum density visualization. A wider step creates a broader ribbon, useful for higher timeframes.
📎 DISPLAY OPTIONS
◦ Show Entry Lines / TP/SL Box / Position Labels / S/R Levels / Dashboard: Toggles individual visual elements on the chart to reduce clutter.
◦ Show SAR+MACD Glow: Enables the secondary confirmation shapes (triangles/circles) above/below candles.
📈 TREND BASELINE (Structural Filter)
◦ Supertrend Factor (Default: 12) & ATR Period (Default: 90): Controls the sensitivity of the underlying Supertrend algorithm used for the baseline calculation.
◦ WMA Length (40) & EMA Length (14): The smoothing periods for the Triple-Smoothed Baseline.
◦ Min Trend Duration (Default: 10): The minimum number of bars the trend must be established before a signal is considered valid.
🧠 SMART EXIT (Dynamic Liquidity)
◦ Use Smart Exit: Enables the momentum exhaustion logic.
◦ Exit Threshold Score (Default: 3): The sensitivity level for triggering a Smart Exit. Lower values trigger earlier exits.
◦ Average Period (168) & Min Hold Bars (5): Defines the rolling window for momentum decay analysis and the minimum duration a trade must be held before Smart Exit logic activates.
🛡️ TRAILING STOP (Step)
◦ Use Trailing Stop: Activates the step-function trailing mechanism.
◦ Step 1 Activation % (0.5) & Offset % (0.5): The price must move 0.5% in your favor to arm the first trail level, which sets a stop 0.5% behind price.
◦ Step 2 Activation % (1) & Offset % (0.2): Once price moves 1%, the trail tightens to 0.2%, securing the position.
🌀 SAR & MACD SETTINGS (Secondary Confirmation)
◦ SAR Start/Increment/Max: Standard Parabolic SAR parameters.
◦ SAR Score Scaling (ATR): Adjusts how much weight the SAR signal has in the overall confluence score.
◦ MACD Fast/Slow/Signal: Standard MACD parameters used for the "Glow" signals.
🔄 ANTI-GREED LOGIC (Behavioral Bias)
◦ Strict Entry after Win: Enables the negative feedback loop.
◦ Strict Multiplier (Default: 1.1): Increases the entry difficulty by 10% after each win.
Role: Prevents overtrading and entering at the top of an extended trend.
🌍 HTF FILTER (Multi-Timeframe)
◦ Use Auto-Adaptive HTF Filter: Automatically selects a higher timeframe (e.g., 1H -> 4H) to filter signals.
◦ Bypass HTF on Steep Trigger: Allows an entry even against the HTF trend if the local momentum slope is exceptionally steep (catch powerful reversals).
📉 RSI PEAK & CHOPPINESS
◦ RSI Peak Exit (Instant): Triggers an immediate exit if a sharp RSI pivot (V-shape) is detected.
◦ Choppiness Filter: Suppresses signals if the Choppiness Index is above the threshold (Default: 60), indicating a flat market.
📐 SLOPE TRIGGER LOGIC
◦ Force Entry on Steep Slope: Overrides other filters if the price angle is extremely vertical (high velocity).
◦ Slope Sensitivity (1.5): The angle required to trigger this override.
⛔ FLAT MARKET FILTER (ADX & ATR)
◦ Use ADX Filter: Blocks signals if ADX is below the threshold (Default: 20), indicating no trend.
◦ Use ATR Flat Filter: Blocks signals if volatility drops below a critical level (dead market).
🔔 Alert Configuration Guide
Impulse Reactor is designed with a comprehensive suite of alert conditions, allowing you to automate your trading or receive real-time notifications for specific market events.
How to Set Up:
Click the "Alert" (Clock) icon in the TradingView toolbar.
Select "Impulse Reactor " from the Condition dropdown.
Choose one of the specific trigger conditions below:
🚀 Entry Signals (Trend Initiation)
Long Entry:
Trigger: Fires when a confirmed Bullish Setup is detected (Momentum + Volatility + Structure align).
Usage: Use this to enter new Long positions.
Short Entry:
Trigger: Fires when a confirmed Bearish Setup is detected.
Usage: Use this to enter new Short positions.
🎯 Profit Taking (Target Levels)
Long TP:
Trigger: Fires when price hits the calculated Take Profit level for a Long trade.
Usage: Automate partial or full profit taking.
Short TP:
Trigger: Fires when price hits the calculated Take Profit level for a Short trade.
Usage: Automate partial or full profit taking.
🛡️ Defensive Exits (Risk Management)
Smart Exit:
Trigger: Fires when the system detects momentum decay or statistical exhaustion (even if the trend hasn't fully reversed).
Usage: Recommended for tightening stops or closing positions early to preserve gains.
Overbought / Oversold:
Trigger: Fires when the ribbon extends into extreme zones.
Usage: Warning signal to prepare for a potential reversal or pullback.
💡 Secondary Confirmation (Confluence)
SAR+MACD Bullish:
Trigger: Fires when Parabolic SAR and MACD align bullishly with the main trend.
Usage: Ideal for Pyramiding (adding to an existing winning position).
SAR+MACD Bearish:
Trigger: Fires when Parabolic SAR and MACD align bearishly.
Usage: Ideal for adding to short positions.
⚠️ Chapter 7: Conclusion & Risk Disclosure
Methodological Synthesis
Impulse Reactor represents a shift from reactive price tracking to proactive energy analysis. By decomposing market activity into its atomic components — Volatility, Momentum, and Structure — and reconstructing them into a coherent decision model, the system aims to provide a quantitative framework for market engagement. It is designed not to predict the future, but to identify high-probability conditions where kinetic energy and trend structure align.
Disclaimer & Risk Warnings
◦ Educational Purpose Only
This indicator, including all associated code, documentation, and visual outputs, is provided strictly for educational and informational purposes. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments.
◦ No Guarantee of Performance
Past performance is not indicative of future results. All metrics displayed on the dashboard (including "Win Rate" and "P&L") are theoretical calculations based on historical data. These figures do not account for real-world trading factors such as slippage, liquidity gaps, spread costs, or broker commissions.
◦ High-Risk Warning
Trading cryptocurrencies, futures, and leveraged financial products involves a substantial risk of loss. The use of leverage can amplify both gains and losses. Users acknowledge that they are solely responsible for their trading decisions and should conduct independent due diligence before executing any trades.
◦ Software Limitations
The software is provided "as is" without warranty. Users should be aware that market data feeds on analysis platforms may experience latency or outages, which can affect signal generation accuracy.
Hyper Strength Index | QuantLapse🧠 Hyper Strength Index (HSI) | QuantLapse
Overview:
The Hyper Strength Index (HSI) is a composite momentum oscillator designed to unify multiple strength measures into a single, adaptive framework. It combines the Relative Strength Index (RSI), Chande Momentum Oscillator (CMO), Money Flow Index (MFI), and Stochastic RSI to deliver a refined, multidimensional view of market momentum and overbought/oversold conditions.
Unlike traditional oscillators that rely on a single formula, the HSI averages four distinct momentum perspectives — price velocity, directional conviction, volume participation, and stochastic behavior — offering traders a more balanced and noise-resistant reading of market strength.
⚙️ Calculation Logic:
The Hyper Strength Index is computed as the normalized average of:
📈 RSI — classic measure of relative momentum.
💪 CMO — captures directional bias and intensity of moves.
💵 MFI — integrates volume and money flow pressure.
🔄 Stochastic RSI (K-line) — identifies momentum extremes and short-term turning points.
This fusion creates a smoother, more comprehensive signal, mitigating the weaknesses of any single oscillator.
🎯 Interpretation:
Overbought Zone (Default: > 75):
Indicates potential exhaustion of bullish momentum — a cooling phase or reversal may follow.
Oversold Zone (Default: < 7):
Suggests bearish exhaustion — a rebound or accumulation phase may emerge.
Neutral Zone (Between 7 and 75):
Represents balanced market conditions or trend continuation phases.
Visual cues highlight key conditions:
🔺 Red Highlights — Overbought regions or downward inflection points.
🔻 Green Highlights — Oversold regions or upward inflection points.
Neutral zones are shaded with subtle gray backgrounds for clarity.
💡 Key Features:
🔹 Multi-factor strength analysis (RSI + CMO + MFI + StochRSI).
🔹 Adaptive overbought/oversold detection.
🔹 Visual alerts via colored backgrounds and bar markers.
🔹 Customizable smoothing and length parameters for fine-tuning sensitivity.
🔹 Intuitive visualization ideal for both short-term scalping and swing trading setups.
🧭 Usage Notes:
Works best as a momentum confirmation tool — pair with trend filters like EMA, SuperTrend, or ADX.
In trending markets, use crossovers from extreme zones as potential continuation or exhaustion signals.
In ranging markets, exploit overbought/oversold reversals for high-probability mean reversion trades.
📘 Summary:
The Hyper Strength Index | QuantLapse distills multiple dimensions of market strength into a single, cohesive oscillator. By merging price, volume, and directional momentum, it provides traders with a more robust, responsive, and context-aware perspective on market dynamics — a next-generation evolution beyond the limitations of RSI or CMO alone.
Advanced Speedometer Gauge [PhenLabs]Advanced Speedometer Gauge
Version: PineScript™v6
📌 Description
The Advanced Speedometer Gauge is a revolutionary multi-metric visualization tool that consolidates 13 distinct trading indicators into a single, intuitive speedometer display. Instead of cluttering your workspace with multiple oscillators and panels, this gauge provides a unified interface where you can switch between different metrics while maintaining consistent visual interpretation.
Built on PineScript™ v6, the indicator transforms complex technical calculations into an easy-to-read semi-circular gauge with color-coded zones and a precision needle indicator. Each of the 13 available metrics has been carefully normalized to a 0-100 scale, ensuring that whether you’re analyzing RSI, volume trends, or volatility extremes, the visual interpretation remains consistent and intuitive.
The gauge is designed for traders who value efficiency and clarity. By consolidating multiple analytical perspectives into one compact display, you can quickly assess market conditions without the visual noise of traditional multi-indicator setups. All metrics are non-overlapping, meaning each provides unique insights into different aspects of market behavior.
🚀 Points of Innovation
13 selectable metrics covering momentum, volume, volatility, trend, and statistical analysis, all accessible through a single dropdown menu
Universal 0-100 normalization system that standardizes different indicator scales for consistent visual interpretation across all metrics
Semi-circular gauge design with 21 arc segments providing smooth precision and clear visual feedback through color-coded zones
Non-redundant metric selection ensuring each indicator provides unique market insights without analytical overlap
Advanced metrics including MFI (volume-weighted momentum), CCI (statistical deviation), Volatility Rank (extended lookback), Trend Strength (ADX-style), Choppiness Index, Volume Trend, and Price Distance from MA
Flexible positioning system with 5 chart locations, 3 size options, and fully customizable color schemes for optimal workspace integration
🔧 Core Components
Metric Selection Engine: Dropdown interface allowing instant switching between 13 different technical indicators, each with independent parameter controls
Normalization System: All metrics converted to 0-100 scale using indicator-specific algorithms that preserve the statistical significance of each measurement
Semi-Circular Gauge: Visual display using 21 arc segments arranged in curved formation with two-row thickness for enhanced visibility
Color Zone System: Three distinct zones (0-40 green, 40-70 yellow, 70-100 red) providing instant visual feedback on metric extremes
Needle Indicator: Dynamic pointer that positions across the gauge arc based on precise current metric value
Table Implementation: Professional table structure ensuring consistent positioning and rendering across different chart configurations
🔥 Key Features
RSI (Relative Strength Index): Classic momentum oscillator measuring overbought/oversold conditions with adjustable period length (default 14)
Stochastic Oscillator: Compares closing price to price range over specified period with smoothing, ideal for identifying momentum shifts
MFI (Money Flow Index): Volume-weighted RSI that combines price movement with volume to measure buying and selling pressure intensity
CCI (Commodity Channel Index): Measures statistical deviation from average price, normalized from typical -200 to +200 range to 0-100 scale
Williams %R: Alternative overbought/oversold indicator using high-low range analysis, inverted to match 0-100 scale conventions
Volume %: Current volume relative to moving average expressed as percentage, capped at 100 for extreme spikes
Volume Trend: Cumulative directional volume flow showing whether volume is flowing into up moves or down moves over specified period
ATR Percentile: Current Average True Range position within historical range using specified lookback period (default 100 bars)
Volatility Rank: Close-to-close volatility measured against extended historical range (default 252 days), differs from ATR in calculation method
Momentum: Rate of change calculation showing price movement speed, centered at 50 and normalized to 0-100 range
Trend Strength: ADX-style calculation using directional movement to quantify trend intensity regardless of direction
Choppiness Index: Measures market choppiness versus trending behavior, where high values indicate ranging markets and low values indicate strong trends
Price Distance from MA: Measures current price over-extension from moving average using standard deviation calculations
🎨 Visualization
Semi-Circular Arc Display: Curved gauge spanning from 0 (left) to 100 (right) with smooth progression and two-row thickness for visibility
Color-Coded Zones: Green zone (0-40) for low/oversold conditions, yellow zone (40-70) for neutral readings, red zone (70-100) for high/overbought conditions
Needle Indicator: Downward-pointing triangle (▼) positioned precisely at current metric value along the gauge arc
Scale Markers: Vertical line markers at 0, 25, 50, 75, and 100 positions with corresponding numerical labels below
Title Display: Merged cell showing “𓄀 PhenLabs” branding plus currently selected metric name in monospace font
Large Value Display: Current metric value shown with two decimal precision in large text directly below title
Table Structure: Professional table with customizable background color, text color, and transparency for minimal chart obstruction
📖 Usage Guidelines
Metric Selection
Select Metric: Default: RSI | Options: RSI, Stochastic, Volume %, ATR Percentile, Momentum, MFI (Money Flow), CCI (Commodity Channel), Williams %R, Volatility Rank, Trend Strength, Choppiness Index, Volume Trend, Price Distance | Choose the technical indicator you want to display on the gauge based on your current analytical needs
RSI Settings
RSI Length: Default: 14 | Range: 1+ | Controls the lookback period for RSI calculation, shorter periods increase sensitivity to recent price changes
Stochastic Settings
Stochastic Length: Default: 14 | Range: 1+ | Lookback period for stochastic calculation comparing close to high-low range
Stochastic Smooth: Default: 3 | Range: 1+ | Smoothing period applied to raw stochastic value to reduce noise and false signals
Volume Settings
Volume MA Length: Default: 20 | Range: 1+ | Moving average period used to calculate average volume for comparison with current volume
Volume Trend Length: Default: 20 | Range: 5+ | Period for calculating cumulative directional volume flow trend
ATR and Volatility Settings
ATR Length: Default: 14 | Range: 1+ | Period for Average True Range calculation used in ATR Percentile metric
ATR Percentile Lookback: Default: 100 | Range: 20+ | Historical range used to determine current ATR position as percentile
Volatility Rank Lookback (Days): Default: 252 | Range: 50+ | Extended lookback period for Volatility Rank metric using close-to-close volatility
Momentum and Trend Settings
Momentum Length: Default: 10 | Range: 1+ | Lookback period for rate of change calculation in Momentum metric
Trend Strength Length: Default: 20 | Range: 5+ | Period for directional movement calculations in ADX-style Trend Strength metric
Advanced Metric Settings
MFI Length: Default: 14 | Range: 1+ | Lookback period for Money Flow Index calculation combining price and volume
CCI Length: Default: 20 | Range: 1+ | Period for Commodity Channel Index statistical deviation calculation
Williams %R Length: Default: 14 | Range: 1+ | Lookback period for Williams %R high-low range analysis
Choppiness Index Length: Default: 14 | Range: 5+ | Period for calculating market choppiness versus trending behavior
Price Distance MA Length: Default: 50 | Range: 10+ | Moving average period used for Price Distance standard deviation calculation
Visual Customization
Position: Default: Top Right | Options: Top Left, Top Right, Bottom Left, Bottom Right, Middle Right | Controls gauge placement on chart for optimal workspace organization
Size: Default: Normal | Options: Small, Normal, Large | Adjusts overall gauge dimensions and text size for different monitor resolutions and preferences
Low Zone Color (0-40): Default: Green (#00FF00) | Customize color for low/oversold zone of gauge arc
Medium Zone Color (40-70): Default: Yellow (#FFFF00) | Customize color for neutral/medium zone of gauge arc
High Zone Color (70-100): Default: Red (#FF0000) | Customize color for high/overbought zone of gauge arc
Background Color: Default: Semi-transparent dark gray | Customize gauge background for contrast and chart integration
Text Color: Default: White (#FFFFFF) | Customize all text elements including title, value, and scale labels
✅ Best Use Cases
Quick visual assessment of market conditions when you need instant feedback on whether an asset is in extreme territory across multiple analytical dimensions
Workspace organization for traders who monitor multiple indicators but want to reduce chart clutter and visual complexity
Metric comparison by switching between different indicators while maintaining consistent visual interpretation through the 0-100 normalization
Overbought/oversold identification using RSI, Stochastic, Williams %R, or MFI depending on whether you prefer price-only or volume-weighted analysis
Volume analysis through Volume %, Volume Trend, or MFI to confirm price movements with corresponding volume characteristics
Volatility monitoring using ATR Percentile or Volatility Rank to identify expansion/contraction cycles and adjust position sizing
Trend vs range identification by comparing Trend Strength (high values = trending) against Choppiness Index (high values = ranging)
Statistical over-extension detection using CCI or Price Distance to identify when price has deviated significantly from normal behavior
Multi-timeframe analysis by duplicating the gauge on different timeframe charts to compare metric readings across time horizons
Educational purposes for new traders learning to interpret technical indicators through consistent visual representation
⚠️ Limitations
The gauge displays only one metric at a time, requiring manual switching to compare different indicators rather than simultaneous multi-metric viewing
The 0-100 normalization, while providing consistency, may obscure the raw values and specific nuances of each underlying indicator
Table-based visualization cannot be exported or saved as an image separately from the full chart screenshot
Optimal parameter settings vary by asset type, timeframe, and market conditions, requiring user experimentation for best results
💡 What Makes This Unique
Unified Multi-Metric Interface: The only gauge-style indicator offering 13 distinct metrics through a single interface, eliminating the need for multiple oscillator panels
Non-Overlapping Analytics: Each metric provides genuinely unique insights—MFI combines volume with price, CCI measures statistical deviation, Volatility Rank uses extended lookback, Trend Strength quantifies directional movement, and Choppiness Index measures ranging behavior
Universal Normalization System: All metrics standardized to 0-100 scale using indicator-appropriate algorithms that preserve statistical meaning while enabling consistent visual interpretation
Professional Visual Design: Semi-circular gauge with 21 arc segments, precision needle positioning, color-coded zones, and clean table implementation that maintains clarity across all chart configurations
Extensive Customization: Independent parameter controls for each metric, five position options, three size presets, and full color customization for seamless workspace integration
🔬 How It Works
1. Metric Calculation Phase:
All 13 metrics are calculated simultaneously on every bar using their respective algorithms with user-defined parameters
Each metric applies its own specific calculation method—RSI uses average gains vs losses, Stochastic compares close to high-low range, MFI incorporates typical price and volume, CCI measures deviation from statistical mean, ATR calculates true range, directional indicators measure up/down movement, and statistical metrics analyze price relationships
2. Normalization Process:
Each calculated metric is converted to a standardized 0-100 scale using indicator-appropriate transformations
Some metrics are naturally 0-100 (RSI, Stochastic, MFI, Williams %R), while others require scaling—CCI transforms from ±200 range, Momentum centers around 50, Volume ratio caps at 2x for 100, ATR and Volatility Rank calculate percentile positions, and Price Distance scales by standard deviations
3. Gauge Rendering:
The selected metric’s normalized value determines the needle position across 21 arc segments spanning 0-100
Each arc segment receives its color based on position—segments 0-8 are green zone, segments 9-14 are yellow zone, segments 15-20 are red zone
The needle indicator (▼) appears in row 5 at the column corresponding to the current metric value, providing precise visual feedback
4. Table Construction:
The gauge uses TradingView’s table system with merged cells for title and value display, ensuring consistent positioning regardless of chart configuration
Rows are allocated as follows: Row 0 merged for title, Row 1 merged for large value display, Row 2 for spacing, Rows 3-4 for the semi-circular arc with curved shaping, Row 5 for needle indicator, Row 6 for scale markers, Row 7 for numerical labels at 0/25/50/75/100
All visual elements update on every bar when barstate.islast is true, ensuring real-time accuracy without performance impact
💡 Note:
This indicator is designed for visual analysis and market condition assessment, not as a standalone trading system. For best results, combine gauge readings with price action analysis, support and resistance levels, and broader market context. Parameter optimization is recommended based on your specific trading timeframe and asset class. The gauge works on all timeframes but may require different parameter settings for intraday versus daily/weekly analysis. Consider using multiple instances of the gauge set to different metrics for comprehensive market analysis without switching between settings.
Adaptive Convergence Divergence### Adaptive Convergence Divergence (ACD)
By Gurjit Singh
The Adaptive Convergence Divergence (ACD) reimagines the classic MACD by replacing fixed moving averages with adaptive moving averages. Instead of a static smoothing factor, it dynamically adjusts sensitivity based on price momentum, relative strength, volatility, fractal roughness, or volume pressure. This makes the oscillator more responsive in trending markets while filtering noise in choppy ranges.
#### 📌 Key Features
1. Dual Adaptive Structure: The oscillator uses two adaptive moving averages to form its convergence-divergence line, with EMA/RMA as signal line:
* Primary Adaptive (MA): Fast line, reacts quickly to changes.
* Following Adaptive (FAMA): Slow line, with half-alpha smoothing for confirmation.
2. Adaptive MA Types
* ACMO: Adaptive CMO (momentum)
* ARSI: Adaptive RSI (relative strength)
* FRMA: Fractal Roughness (volatility + fractal dimension)
* VOLA: Volume adaptive (volume pressure)
3. PPO Option: Switch between classic MACD or Percentage Price Oscillator (PPO) style calculation.
4. Signal Smoothing: Choose between EMA or Wilder’s RMA.
5. Visuals: Colored oscillator, signal line, histogram with adaptive transparency.
6. Alerts: Bullish/Bearish crossovers built-in.
#### 🔑 How to Use
1. Add to chart: Works on any timeframe and asset.
2. Choose MA Type: Experiment with ACMO, ARSI, FRMA, or VOLA depending on market regime.
3. Crossovers:
* Bullish (🐂): Oscillator crosses above signal → potential long entry.
* Bearish (🐻): Oscillator crosses below signal → potential short entry.
4. Histogram: expansion = strengthening trend; contraction = weakening trend.
5. Divergences:
* Bullish (hidden strength): Price pushes lower, but ACD turns higher = potential upward reversal.
* Bearish (hidden weakness): Price pushes higher, but ACD turns lower = potential downward reversal.
6. Customize: Adjust lengths, smoothing type, and PPO/MACD mode to match your style.
7. Set Alerts:
* Enable Bullish or Bearish crossover alerts to catch momentum shifts in real time.
#### 💡 Tips
* PPO mode normalizes values across assets, useful for cross-asset analysis.
* Wilder’s smoothing is gentler than EMA, reducing whipsaws in sideways conditions.
* Adaptive smoothing helps reduce false divergence signals by filtering noise in choppy ranges.
Inside Candle DivergenceStudy Material: Inside Candle Divergence Indicator (aiTrendview)
1. Introduction
The Inside Candle Divergence Indicator is a custom tool built on TradingView using Pine Script. It is designed to help traders identify potential reversal points or trend continuations using a mix of candlestick analysis, RSI (Relative Strength Index), VWAP (Volume Weighted Average Price), Pivot Points, and Volume analytics. The tool also provides a dashboard table on the chart, summarizing all key values in a single glance for traders and analysts.
This indicator is not just a signal generator but also an educational framework—explaining how different concepts in technical analysis combine to build a systematic approach for market entries and exits.
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2. Core Concepts Behind the Tool
A. Inside Candle Pattern
An Inside Candle forms when the current candle’s high is lower than or equal to the previous candle’s high, and the low is higher than or equal to the previous candle’s low.
• This means the entire price action of the current candle is "inside" the range of the previous candle.
• A bullish inside candle occurs when the close is higher than the open.
• A bearish inside candle occurs when the close is lower than the open.
This pattern shows market indecision but also sets up potential breakouts or trend reversals.
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B. RSI (Relative Strength Index)
The indicator calculates RSI using the formula from the ta.rsi() function in TradingView. RSI helps measure momentum in the market.
• A low RSI (below 25) signals an oversold zone → possible buy.
• A high RSI (above 75) signals an overbought zone → possible sell.
By combining RSI with the Inside Candle, the indicator ensures that signals are triggered only when momentum and price patterns confirm each other.
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C. Buy & Sell Signals
• Buy Signal: Triggered when RSI < Buy Level (default 25) and a bullish inside candle forms.
• Sell Signal: Triggered when RSI > Sell Level (default 75) and a bearish inside candle forms.
When triggered, the chart displays a BUY (green label below candle) or SELL (red label above candle) marker. The indicator also saves the entry price and signal bar for future reference inside the dashboard.
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D. VWAP (Volume Weighted Average Price)
VWAP is calculated using the typical price (H+L+C)/3 and weighting it by volume.
• VWAP shows the average trading price weighted by volume, widely used by institutions.
• The tool calculates the distance of price from VWAP in % terms.
• If price is far above VWAP, the market may be overheated (overbought). If far below, it may be undervalued (oversold).
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E. Volume Analysis
The tool splits volume into Buy Volume and Sell Volume:
• Buy Volume: If close > open.
• Sell Volume: If close ≤ open.
• Cumulative totals are maintained, and percentages are calculated to show what proportion of total market volume is bullish vs bearish.
• A progress bar style visual (using blocks █) shows the dominance of buyers or sellers.
This allows traders to quickly measure whether buyers or sellers are controlling the market trend.
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F. Daily Pivot Points
Pivot Points are calculated using the previous day’s high, low, and close:
• Pivot = (High + Low + Close) / 3
• R1, S1, R2, S2, R3, S3 levels are derived from this pivot.
• These levels act as support and resistance zones.
The script plots Pivot, R1, and S1 lines on the chart for easy reference.
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G. Trend Direction
The indicator checks where the price is compared to R1 and S1:
• If price > R1 → Bullish Trend
• If price < S1 → Bearish Trend
• Otherwise → Neutral Trend
The trend direction is displayed in the dashboard with arrows (↑, ↓, →).
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H. Price Change Calculation
The tool calculates:
• Price Change = Current Close – Previous Close
• Percentage Change = (Change / Previous Close) × 100
• Displays ▲ (green upward) or ▼ (red downward) with the exact percentage.
This gives traders a quick snapshot of intraday price movement.
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I. Dashboard Table
One of the most powerful features is the real-time dashboard table shown on the chart. It contains:
1. Symbol & Price Info (Current ticker, price, change %)
2. RSI Reading (with color coding: green for oversold, red for overbought)
3. VWAP and Distance from VWAP
4. Volume Analysis with Progress Bar (Buy vs Sell %)
5. Pivot Levels (Pivot, R1, S1)
6. Trend Direction (Bullish, Bearish, Neutral)
7. Signal Status (Last Buy/Sell signal with entry price)
This reduces the need for multiple indicators and gives traders a command-center view directly on the chart.
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J. Alerts
The tool generates alerts whenever a Buy or Sell condition is met. Traders can set up TradingView alerts to be notified instantly when:
• Buy Signal Alert → RSI oversold + Bullish inside candle
• Sell Signal Alert → RSI overbought + Bearish inside candle
This ensures no opportunity is missed even if you’re not actively monitoring the chart.
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K. Background Highlights
The chart background also changes faintly (light green or light red) when a Buy or Sell condition is triggered. This gives traders visual confirmation along with signals and alerts.
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3. Practical Use of This Tool
• Scalpers & Intraday Traders can use it for quick momentum-based entries.
• Swing Traders can use the RSI + Inside Candle + Pivot Points to find medium-term reversals.
• Analysts can use the dashboard for real-time summaries in reports.
• Volume Analysis helps understand institutional activity.
Remember: This is not a standalone holy grail. It must be used with proper risk management and confirmation from higher timeframes.
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4. Strict Disclaimer (aiTrendview)
⚠️ Disclaimer from aiTrendview:
This indicator is designed for educational and analytical purposes only. It is not financial advice or a guaranteed trading strategy. Markets are inherently risky and unpredictable; past performance of indicators does not ensure future results. Trading involves risk of financial loss, and traders must use proper risk management, stop-loss, and independent judgment.
aiTrendview strictly follows TradingView.com rules and compliance guidelines.
Any misuse of this tool, its code, or analytical features for unauthorized commercial purposes, false promises, or misleading activities is strictly discouraged. The creators of this script and aiTrendview will not be responsible for any losses, damages, or misuse arising from its application. Always trade responsibly and only with money you can afford to lose.
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Consecutive Candles Above/Below EMADescription:
This indicator identifies and highlights periods where the price remains consistently above or below an Exponential Moving Average (EMA) for a user-defined number of consecutive candles. It visually marks these sustained trends with background colors and labels, helping traders spot strong bullish or bearish market conditions. Ideal for trend-following strategies or identifying potential trend exhaustion points, this tool provides clear visual cues for price behavior relative to the EMA.
How It Works:
EMA Calculation: The indicator calculates an EMA based on the user-specified period (default: 100). The EMA is plotted as a blue line on the chart for reference.
Consecutive Candle Tracking: It counts how many consecutive candles close above or below the EMA:
If a candle closes below the EMA, the "below" counter increments; any candle closing above resets it to zero.
If a candle closes above the EMA, the "above" counter increments; any candle closing below resets it to zero.
Highlighting Trends: When the number of consecutive candles above or below the EMA meets or exceeds the user-defined threshold (default: 200 candles):
A translucent red background highlights periods where the price has been below the EMA.
A translucent green background highlights periods where the price has been above the EMA.
Labeling: When the required number of consecutive candles is first reached:
A red downward arrow label with the text "↓ Below" appears for below-EMA streaks.
A green upward arrow label with the text "↑ Above" appears for above-EMA streaks.
Usage:
Trend Confirmation: Use the highlights and labels to confirm strong trends. For example, 200 candles above the EMA may indicate a robust uptrend.
Reversal Signals: Prolonged streaks (e.g., 200+ candles) might suggest overextension, potentially signaling reversals.
Customization: Adjust the EMA period to make it faster or slower, and modify the candle count to make the indicator more or less sensitive to trends.
Settings:
EMA Length: Set the period for the EMA calculation (default: 100).
Candles Count: Define the minimum number of consecutive candles required to trigger highlights and labels (default: 200).
Visuals:
Blue EMA line for tracking the moving average.
Red background for sustained below-EMA periods.
Green background for sustained above-EMA periods.
Labeled arrows to mark when the streak threshold is met.
This indicator is a powerful tool for traders looking to visualize and capitalize on persistent price trends relative to the EMA, with clear, customizable signals for market analysis.
Explain EMA calculation
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C&B Auto MK5C&B Auto MK5.2ema BullBear
Overview
The C&B Auto MK5.2ema BullBear is a versatile Pine Script indicator designed to help traders identify bullish and bearish market conditions across various timeframes. It combines Exponential Moving Averages (EMAs), Relative Strength Index (RSI), Average True Range (ATR), and customizable time filters to generate actionable signals. The indicator overlays on the price chart, displaying EMAs, a dynamic cloud, scaled RSI levels, bull/bear signals, and market condition labels, making it suitable for swing trading, day trading, or scalping in trending or volatile markets.
What It Does
This indicator generates bull and bear signals based on the interaction of two EMAs, filtered by RSI thresholds, ATR-based volatility, a 50/200 EMA trend filter, and user-defined time windows. It adapts to market volatility by adjusting EMA lengths and RSI thresholds. A dynamic cloud highlights trend direction or neutral zones, with candlestick coloring in neutral conditions. Market condition labels (current and historical) provide real-time trend and volatility context, displayed above the chart.
How It Works
The indicator uses the following components:
EMAs: Two EMAs (short and long) are calculated on a user-selected timeframe (1, 5, 15, 30, or 60 minutes). Their crossover or crossunder triggers potential bull/bear signals. EMA lengths adjust based on volatility (e.g., 10/20 for volatile markets, 5/10 for non-volatile).
Dynamic Cloud: The area between the EMAs forms a cloud, colored green for bullish trends, red for bearish trends, or a user-defined color (default yellow) for neutral zones (when EMAs are close, determined by an ATR-based threshold). Users can widen the cloud for visibility.
RSI Filter: RSI is scaled to price levels and plotted on the chart (optional). Signals are filtered to ensure RSI is within volatility-adjusted bull/bear thresholds and not in overbought/oversold zones.
ATR Volatility Filter: An optional filter ensures signals occur during sufficient volatility (ATR(14) > SMA(ATR, 20)).
50/200 EMA Trend Filter: An optional filter restricts bull signals to bullish trends (50 EMA > 200 EMA) and bear signals to bearish trends (50 EMA < 200 EMA).
Time Filter: Signals are restricted to a user-defined UTC time window (default 9:00–15:00), aligning with active trading sessions.
Market Condition Labels: Labels above the chart display the current trend (Bullish, Bearish, Neutral) and optionally volatility (e.g., “Bullish Volatile”). Up to two historical labels persist for a user-defined number of bars (default 5) to show recent trend changes.
Visual Aids: Bull signals appear as green triangles/labels below the bar, bear signals as red triangles/labels above. Candlesticks in neutral zones are colored (default yellow).
The indicator ensures compatibility with standard chart types (e.g., candlestick or bar charts) to produce realistic signals, avoiding non-standard types like Heikin Ashi or Renko.
How to Use It
Add to Chart: Apply the indicator to a candlestick or bar chart on TradingView.
Configure Settings:
Timeframe: Choose a timeframe (1, 5, 15, 30, or 60 minutes) to match your trading style.
Filters:
Enable/disable the ATR volatility filter to focus on high-volatility periods.
Enable/disable the 50/200 EMA trend filter to align signals with the broader trend.
Enable the time filter and set custom UTC hours/minutes (default 9:00–15:00).
Cloud Settings: Adjust the cloud width, neutral zone threshold, color, and transparency.
EMA Colors: Use default trend-based colors or set custom colors for short/long EMAs.
RSI Display: Toggle the scaled RSI and its thresholds, with customizable colors.
Signal Settings: Toggle bull/bear labels and set signal colors.
Market Condition Labels: Toggle current/historical labels, include/exclude volatility, and adjust decay period.
Interpret Signals:
Bull Signal: A green triangle or “Bull” label below the bar indicates potential bullish momentum (EMA crossover, RSI above bull threshold, within time window, passing filters).
Bear Signal: A red triangle or “Bear” label above the bar indicates potential bearish momentum (EMA crossunder, RSI below bear threshold, within time window, passing filters).
Neutral Zone: Yellow candlesticks and cloud (if enabled) suggest a lack of clear trend; consider range-bound strategies or avoid trading.
Market Condition Labels: Check labels above the chart for real-time trend (Bullish, Bearish, Neutral) and volatility status to confirm market context.
Monitor Context: Use the cloud, RSI, and labels to assess trend strength and volatility before acting on signals.
Unique Features
Volatility-Adaptive EMAs: Automatically adjusts EMA lengths based on ATR to suit volatile or non-volatile markets, reducing manual configuration.
Neutral Zone Detection: Uses an ATR-based threshold to identify low-trend periods, helping traders avoid choppy markets.
Scaled RSI Visualization: Plots RSI and thresholds directly on the price chart, simplifying momentum analysis relative to price.
Flexible Time Filtering: Supports precise UTC-based trading windows, ideal for day traders targeting specific sessions.
Historical Market Labels: Displays recent trend changes (up to two) with a decay period, providing context for market shifts.
50/200 EMA Trend Filter: Aligns signals with the broader market trend, enhancing signal reliability.
Notes
Use on standard candlestick or bar charts to ensure accurate signals.
Test the indicator on a demo account to optimize settings for your market and timeframe.
Combine with other analysis (e.g., support/resistance, volume) for better decision-making.
The indicator is not a standalone system; use it as part of a broader trading strategy.
Limitations
Signals may lag in fast-moving markets due to EMA-based calculations.
Neutral zone detection may vary in extremely volatile or illiquid markets.
Time filters are UTC-based; ensure your platform’s timezone settings align.
This indicator is designed for traders seeking a customizable, trend-following tool that adapts to volatility and provides clear visual cues with robust filtering for bullish and bearish market conditions.
Log Regression Oscillator Channel [BigBeluga]
This unique overlay tool blends logarithmic trend analysis with dynamic oscillator behavior. It projects RSI, MFI, or Stochastic lines directly into a log regression channel on the price chart — offering an intuitive way to detect overbought/oversold momentum within the broader price structure.
🔵Key Features:
Logarithmic Regression Channel:
➣ Draws a trend-based channel using logarithmic regression, adapting to price growth curvature over time.
➣ Features upper, lower, and optional midline boundaries to visualize trend flow and range extremes.
Oscillator Overlay (RSI / MFI / Stochastic):
➣ Projects your chosen oscillator inside the channel using dynamic polylines.
➣ Allows switching between RSI, Money Flow Index, or Stochastic for versatile momentum insight.
Threshold-Based Scaling:
➣ The top and bottom of the channel represent traditional oscillator thresholds (e.g., RSI 70/30).
➣ Users can modify the scale in settings to customize what "overbought" or "oversold" means visually.
Signal Line Integration:
➣ Adds a yellow moving average (signal line) for smoother confirmation of oscillator turns.
➣ Helps identify divergence, momentum shifts, and fakeouts with better clarity.
Live Oscillator Readout:
➣ Displays the real-time oscillator value at the right edge of the chart.
➣ Ensures traders stay aware of current momentum levels without switching panels.
🔵Usage:
Momentum Context:
➣ When the oscillator touches the upper regression band, it may signal local overbought pressure.
➣ Touching the lower band may indicate oversold conditions within the current log trend.
Divergence Detection:
➣ Use the oscillator’s behavior relative to the channel slope to spot divergence from price.
➣ For example, RSI rising inside a falling channel can flag early trend shifts.
Trend-Sensitive Entries:
➣ Combine oscillator signals with log channel direction to filter trades in trend alignment.
➣ Signal line crossovers inside the channel act as early warning for momentum turns.
The Log Regression Oscillator Channel transforms how traders view classic momentum tools. By embedding oscillators into a logarithmic trend structure, it offers unmatched clarity on momentum positioning relative to price expansion. Ideal for swing traders, mean-reverters, or trend followers looking to sharpen entries and exits with style.
Volume Weighted RSI (VW RSI)The Volume Weighted RSI (VW RSI) is a momentum oscillator designed for TradingView, implemented in Pine Script v6, that enhances the traditional Relative Strength Index (RSI) by incorporating trading volume into its calculation. Unlike the standard RSI, which measures the speed and change of price movements based solely on price data, the VW RSI weights its analysis by volume, emphasizing price movements backed by significant trading activity. This makes the VW RSI particularly effective for identifying bullish or bearish momentum, overbought/oversold conditions, and potential trend reversals in markets where volume plays a critical role, such as stocks, forex, and cryptocurrencies.
Key Features
Volume-Weighted Momentum Calculation:
The VW RSI calculates momentum by comparing the volume associated with upward price movements (up-volume) to the volume associated with downward price movements (down-volume).
Up-volume is the volume on bars where the closing price is higher than the previous close, while down-volume is the volume on bars where the closing price is lower than the previous close.
These volumes are smoothed over a user-defined period (default: 14 bars) using a Running Moving Average (RMA), and the VW RSI is computed using the formula:
\text{VW RSI} = 100 - \frac{100}{1 + \text{VoRS}}
where
\text{VoRS} = \frac{\text{Average Up-Volume}}{\text{Average Down-Volume}}
.
Oscillator Range and Interpretation:
The VW RSI oscillates between 0 and 100, with a centerline at 50.
Above 50: Indicates bullish volume momentum, suggesting that volume on up bars dominates, which may signal buying pressure and a potential uptrend.
Below 50: Indicates bearish volume momentum, suggesting that volume on down bars dominates, which may signal selling pressure and a potential downtrend.
Overbought/Oversold Levels: User-defined thresholds (default: 70 for overbought, 30 for oversold) help identify potential reversal points:
VW RSI > 70: Overbought, indicating a possible pullback or reversal.
VW RSI < 30: Oversold, indicating a possible bounce or reversal.
Visual Elements:
VW RSI Line: Plotted in a separate pane below the price chart, colored dynamically based on its value:
Green when above 50 (bullish momentum).
Red when below 50 (bearish momentum).
Gray when at 50 (neutral).
Centerline: A dashed line at 50, optionally displayed, serving as the neutral threshold between bullish and bearish momentum.
Overbought/Oversold Lines: Dashed lines at the user-defined overbought (default: 70) and oversold (default: 30) levels, optionally displayed, to highlight extreme conditions.
Background Coloring: The background of the VW RSI pane is shaded red when the indicator is in overbought territory and green when in oversold territory, providing a quick visual cue of potential reversal zones.
Alerts:
Built-in alerts for key events:
Bullish Momentum: Triggered when the VW RSI crosses above 50, indicating a shift to bullish volume momentum.
Bearish Momentum: Triggered when the VW RSI crosses below 50, indicating a shift to bearish volume momentum.
Overbought Condition: Triggered when the VW RSI crosses above the overbought threshold (default: 70), signaling a potential pullback.
Oversold Condition: Triggered when the VW RSI crosses below the oversold threshold (default: 30), signaling a potential bounce.
Input Parameters
VW RSI Length (default: 14): The period over which the up-volume and down-volume are smoothed to calculate the VW RSI. A longer period results in smoother signals, while a shorter period increases sensitivity.
Overbought Level (default: 70): The threshold above which the VW RSI is considered overbought, indicating a potential reversal or pullback.
Oversold Level (default: 30): The threshold below which the VW RSI is considered oversold, indicating a potential reversal or bounce.
Show Centerline (default: true): Toggles the display of the 50 centerline, which separates bullish and bearish momentum zones.
Show Overbought/Oversold Lines (default: true): Toggles the display of the overbought and oversold threshold lines.
How It Works
Volume Classification:
For each bar, the indicator determines whether the price movement is upward or downward:
If the current close is higher than the previous close, the bar’s volume is classified as up-volume.
If the current close is lower than the previous close, the bar’s volume is classified as down-volume.
If the close is unchanged, both up-volume and down-volume are set to 0 for that bar.
Smoothing:
The up-volume and down-volume are smoothed using a Running Moving Average (RMA) over the specified period (default: 14 bars) to reduce noise and provide a more stable measure of volume momentum.
VW RSI Calculation:
The Volume Relative Strength (VoRS) is calculated as the ratio of smoothed up-volume to smoothed down-volume.
The VW RSI is then computed using the standard RSI formula, but with volume data instead of price changes, resulting in a value between 0 and 100.
Visualization and Alerts:
The VW RSI is plotted with dynamic coloring to reflect its momentum direction, and optional lines are drawn for the centerline and overbought/oversold levels.
Background coloring highlights overbought and oversold conditions, and alerts notify the trader of significant crossings.
Usage
Timeframe: The VW RSI can be used on any timeframe, but it is particularly effective on intraday charts (e.g., 1-hour, 4-hour) or daily charts where volume data is reliable. Shorter timeframes may require a shorter length for increased sensitivity, while longer timeframes may benefit from a longer length for smoother signals.
Markets: Best suited for markets with significant and reliable volume data, such as stocks, forex, and cryptocurrencies. It may be less effective in markets with low or inconsistent volume, such as certain futures contracts.
Trading Strategies:
Trend Confirmation:
Use the VW RSI to confirm the direction of a trend. For example, in an uptrend, look for the VW RSI to remain above 50, indicating sustained bullish volume momentum, and consider buying on pullbacks when the VW RSI dips but stays above 50.
In a downtrend, look for the VW RSI to remain below 50, indicating sustained bearish volume momentum, and consider selling on rallies when the VW RSI rises but stays below 50.
Overbought/Oversold Conditions:
When the VW RSI crosses above 70, the market may be overbought, suggesting a potential pullback or reversal. Consider taking profits on long positions or preparing for a short entry, but confirm with price action or other indicators.
When the VW RSI crosses below 30, the market may be oversold, suggesting a potential bounce or reversal. Consider entering long positions or covering shorts, but confirm with additional signals.
Divergences:
Look for divergences between the VW RSI and price to spot potential reversals. For example, if the price makes a higher high but the VW RSI makes a lower high, this bearish divergence may signal an impending downtrend.
Conversely, if the price makes a lower low but the VW RSI makes a higher low, this bullish divergence may signal an impending uptrend.
Momentum Shifts:
A crossover above 50 can signal the start of bullish momentum, making it a potential entry point for long trades.
A crossunder below 50 can signal the start of bearish momentum, making it a potential entry point for short trades or an exit for long positions.
Example
On a 4-hour SOLUSDT chart:
During an uptrend, the VW RSI might rise above 50 and stay there, confirming bullish volume momentum. If it approaches 70, it may indicate overbought conditions, as seen near a price peak of 145.08, suggesting a potential pullback.
During a downtrend, the VW RSI might fall below 50, confirming bearish volume momentum. If it drops below 30 near a price low of 141.82, it may indicate oversold conditions, suggesting a potential bounce, as seen in a slight recovery afterward.
A bullish divergence might occur if the price makes a lower low during the downtrend, but the VW RSI makes a higher low, signaling a potential reversal.
Limitations
Lagging Nature: Like the traditional RSI, the VW RSI is a lagging indicator because it relies on smoothed data (RMA). It may not react quickly to sudden price reversals, potentially missing the start of new trends.
False Signals in Ranging Markets: In choppy or ranging markets, the VW RSI may oscillate around 50, generating frequent crossovers that lead to false signals. Combining it with a trend filter (e.g., ADX) can help mitigate this.
Volume Data Dependency: The VW RSI relies on accurate volume data, which may be inconsistent or unavailable in some markets (e.g., certain forex pairs or futures contracts). In such cases, the indicator’s effectiveness may be reduced.
Overbought/Oversold in Strong Trends: During strong trends, the VW RSI can remain in overbought or oversold territory for extended periods, leading to premature exit signals. Use additional confirmation to avoid exiting too early.
Potential Improvements
Smoothing Options: Add options to use different smoothing methods (e.g., EMA, SMA) instead of RMA for the up/down volume calculations, allowing users to adjust the indicator’s responsiveness.
Divergence Detection: Include logic to detect and plot bullish/bearish divergences between the VW RSI and price, providing visual cues for potential reversals.
Customizable Colors: Allow users to customize the colors of the VW RSI line, centerline, overbought/oversold lines, and background shading.
Trend Filter: Integrate a trend strength filter (e.g., ADX > 25) to ensure signals are generated only during strong trends, reducing false signals in ranging markets.
The Volume Weighted RSI (VW RSI) is a powerful tool for traders seeking to incorporate volume into their momentum analysis, offering a unique perspective on market dynamics by emphasizing price movements backed by significant trading activity. It is best used in conjunction with other indicators and price action analysis to confirm signals and improve trading decisions.
