Scientific Correlation Testing FrameworkScientific Correlation Testing Framework - Comprehensive Guide
Introduction to Correlation Analysis
What is Correlation?
Correlation is a statistical measure that describes the degree to which two assets move in relation to each other. Think of it like measuring how closely two dancers move together on a dance floor.
Perfect Positive Correlation (+1.0): Both dancers move in perfect sync, same direction, same speed
Perfect Negative Correlation (-1.0): Both dancers move in perfect sync but in opposite directions
Zero Correlation (0): The dancers move completely independently of each other
In financial markets, correlation helps us understand relationships between different assets, which is crucial for:
Portfolio diversification
Risk management
Pairs trading strategies
Hedging positions
Market analysis
Why This Script is Special
This script goes beyond simple correlation calculations by providing:
Two different correlation methods (Pearson and Spearman)
Statistical significance testing to ensure results are meaningful
Rolling correlation analysis to track how relationships change over time
Visual representation for easy interpretation
Comprehensive statistics table with detailed metrics
Deep Dive into the Script's Components
1. Input Parameters Explained-
Symbol Selection:
This allows you to select the second asset to compare with the chart's primary asset
Default is Apple (NASDAQ:AAPL), but you can change this to any symbol
Example: If you're viewing a Bitcoin chart, you might set this to "NASDAQ:TSLA" to see if Bitcoin and Tesla are correlated
Correlation Window (60): This is the number of periods used to calculate the main correlation
Larger values (e.g., 100-500) provide more stable, long-term correlation measures
Smaller values (e.g., 10-50) are more responsive to recent price movements
60 is a good balance for most daily charts (about 3 months of trading days)
Rolling Correlation Window (20): A shorter window to detect recent changes in correlation
This helps identify when the relationship between assets is strengthening or weakening
Default of 20 is roughly one month of trading days
Return Type: This determines how price changes are calculated
Simple Returns: (Today's Price - Yesterday's Price) / Yesterday's Price
Easy to understand: "The asset went up 2% today"
Log Returns: Natural logarithm of (Today's Price / Yesterday's Price)
More mathematically elegant for statistical analysis
Better for time-additive properties (returns over multiple periods)
Less sensitive to extreme values.
Confidence Level (95%): This determines how certain we want to be about our results
95% confidence means we accept a 5% chance of being wrong (false positive)
Higher confidence (e.g., 99%) makes the test more strict
Lower confidence (e.g., 90%) makes the test more lenient
95% is the standard in most scientific research
Show Statistical Significance: When enabled, the script will test if the correlation is statistically significant or just due to random chance.
Display options control what you see on the chart:
Show Pearson/Spearman/Rolling Correlation: Toggle each correlation type on/off
Show Scatter Plot: Displays a scatter plot of returns (limited to recent points to avoid performance issues)
Show Statistical Tests: Enables the detailed statistics table
Table Text Size: Adjusts the size of text in the statistics table
2.Functions explained-
calcReturns():
This function calculates price returns based on your selected method:
Log Returns:
Formula: ln(Price_t / Price_t-1)
Example: If a stock goes from $100 to $101, the log return is ln(101/100) = ln(1.01) ≈ 0.00995 or 0.995%
Benefits: More symmetric, time-additive, and better for statistical modeling
Simple Returns:
Formula: (Price_t - Price_t-1) / Price_t-1
Example: If a stock goes from $100 to $101, the simple return is (101-100)/100 = 0.01 or 1%
Benefits: More intuitive and easier to understand
rankArray():
This function calculates the rank of each value in an array, which is used for Spearman correlation:
How ranking works:
The smallest value gets rank 1
The second smallest gets rank 2, and so on
For ties (equal values), they get the average of their ranks
Example: For values
Sorted:
Ranks: (the two 2s tie for ranks 1 and 2, so they both get 1.5)
Why this matters: Spearman correlation uses ranks instead of actual values, making it less sensitive to outliers and non-linear relationships.
pearsonCorr():
This function calculates the Pearson correlation coefficient:
Mathematical Formula:
r = (nΣxy - ΣxΣy) / √
Where x and y are the two variables, and n is the sample size
What it measures:
The strength and direction of the linear relationship between two variables
Values range from -1 (perfect negative linear relationship) to +1 (perfect positive linear relationship)
0 indicates no linear relationship
Example:
If two stocks have a Pearson correlation of 0.8, they have a strong positive linear relationship
When one stock goes up, the other tends to go up in a fairly consistent proportion
spearmanCorr():
This function calculates the Spearman rank correlation:
How it works:
Convert each value in both datasets to its rank
Calculate the Pearson correlation on the ranks instead of the original values
What it measures:
The strength and direction of the monotonic relationship between two variables
A monotonic relationship is one where as one variable increases, the other either consistently increases or decreases
It doesn't require the relationship to be linear
When to use it instead of Pearson:
When the relationship is monotonic but not linear
When there are significant outliers in the data
When the data is ordinal (ranked) rather than interval/ratio
Example:
If two stocks have a Spearman correlation of 0.7, they have a strong positive monotonic relationship
When one stock goes up, the other tends to go up, but not necessarily in a straight-line relationship
tStatistic():
This function calculates the t-statistic for correlation:
Mathematical Formula: t = r × √((n-2)/(1-r²))
Where r is the correlation coefficient and n is the sample size
What it measures:
How many standard errors the correlation is away from zero
Used to test the null hypothesis that the true correlation is zero
Interpretation:
Larger absolute t-values indicate stronger evidence against the null hypothesis
Generally, a t-value greater than 2 (in absolute terms) is considered statistically significant at the 95% confidence level
criticalT() and pValue():
These functions provide approximations for statistical significance testing:
criticalT():
Returns the critical t-value for a given degrees of freedom (df) and significance level
The critical value is the threshold that the t-statistic must exceed to be considered statistically significant
Uses approximations since Pine Script doesn't have built-in statistical distribution functions
pValue():
Estimates the p-value for a given t-statistic and degrees of freedom
The p-value is the probability of observing a correlation as strong as the one calculated, assuming the true correlation is zero
Smaller p-values indicate stronger evidence against the null hypothesis
Standard interpretation:
p < 0.01: Very strong evidence (marked with **)
p < 0.05: Strong evidence (marked with *)
p ≥ 0.05: Weak evidence, not statistically significant
stdev():
This function calculates the standard deviation of a dataset:
Mathematical Formula: σ = √(Σ(x-μ)²/(n-1))
Where x is each value, μ is the mean, and n is the sample size
What it measures:
The amount of variation or dispersion in a set of values
A low standard deviation indicates that the values tend to be close to the mean
A high standard deviation indicates that the values are spread out over a wider range
Why it matters for correlation:
Standard deviation is used in calculating the correlation coefficient
It also provides information about the volatility of each asset's returns
Comparing standard deviations helps understand the relative riskiness of the two assets.
3.Getting Price Data-
price1: The closing price of the primary asset (the chart you're viewing)
price2: The closing price of the secondary asset (the one you selected in the input parameters)
Returns are used instead of raw prices because:
Returns are typically stationary (mean and variance stay constant over time)
Returns normalize for price levels, allowing comparison between assets of different values
Returns represent what investors actually care about: percentage changes in value
4.Information Table-
Creates a table to display statistics
Only shows on the last bar to avoid performance issues
Positioned in the top right of the chart
Has 2 columns and 15 rows
Populating the Table
The script then populates the table with various statistics:
Header Row: "Metric" and "Value"
Sample Information: Sample size and return type
Pearson Correlation: Value, t-statistic, p-value, and significance
Spearman Correlation: Value, t-statistic, p-value, and significance
Rolling Correlation: Current value
Standard Deviations: For both assets
Interpretation: Text description of the correlation strength
The table uses color coding to highlight important information:
Green for significant positive results
Red for significant negative results
Yellow for borderline significance
Color-coded headers for each section
=> Practical Applications and Interpretation
How to Interpret the Results
Correlation Strength
0.0 to 0.3 (or 0.0 to -0.3): Weak or no correlation
The assets move mostly independently of each other
Good for diversification purposes
0.3 to 0.7 (or -0.3 to -0.7): Moderate correlation
The assets show some tendency to move together (or in opposite directions)
May be useful for certain trading strategies but not extremely reliable
0.7 to 1.0 (or -0.7 to -1.0): Strong correlation
The assets show a strong tendency to move together (or in opposite directions)
Can be useful for pairs trading, hedging, or as a market indicator
Statistical Significance
p < 0.01: Very strong evidence that the correlation is real
Marked with ** in the table
Very unlikely to be due to random chance
p < 0.05: Strong evidence that the correlation is real
Marked with * in the table
Unlikely to be due to random chance
p ≥ 0.05: Weak evidence that the correlation is real
Not marked in the table
Could easily be due to random chance
Rolling Correlation
The rolling correlation shows how the relationship between assets changes over time
If the rolling correlation is much different from the long-term correlation, it suggests the relationship is changing
This can indicate:
A shift in market regime
Changing fundamentals of one or both assets
Temporary market dislocations that might present trading opportunities
Trading Applications
1. Portfolio Diversification
Goal: Reduce overall portfolio risk by combining assets that don't move together
Strategy: Look for assets with low or negative correlations
Example: If you hold tech stocks, you might add some utilities or bonds that have low correlation with tech
2. Pairs Trading
Goal: Profit from the relative price movements of two correlated assets
Strategy:
Find two assets with strong historical correlation
When their prices diverge (one goes up while the other goes down)
Buy the underperforming asset and short the outperforming asset
Close the positions when they converge back to their normal relationship
Example: If Coca-Cola and Pepsi are highly correlated but Coca-Cola drops while Pepsi rises, you might buy Coca-Cola and short Pepsi
3. Hedging
Goal: Reduce risk by taking an offsetting position in a negatively correlated asset
Strategy: Find assets that tend to move in opposite directions
Example: If you hold a portfolio of stocks, you might buy some gold or government bonds that tend to rise when stocks fall
4. Market Analysis
Goal: Understand market dynamics and interrelationships
Strategy: Analyze correlations between different sectors or asset classes
Example:
If tech stocks and semiconductor stocks are highly correlated, movements in one might predict movements in the other
If the correlation between stocks and bonds changes, it might signal a shift in market expectations
5. Risk Management
Goal: Understand and manage portfolio risk
Strategy: Monitor correlations to identify when diversification benefits might be breaking down
Example: During market crises, many assets that normally have low correlations can become highly correlated (correlation convergence), reducing diversification benefits
Advanced Interpretation and Caveats
Correlation vs. Causation
Important Note: Correlation does not imply causation
Example: Ice cream sales and drowning incidents are correlated (both increase in summer), but one doesn't cause the other
Implication: Just because two assets move together doesn't mean one causes the other to move
Solution: Look for fundamental economic reasons why assets might be correlated
Non-Stationary Correlations
Problem: Correlations between assets can change over time
Causes:
Changing market conditions
Shifts in monetary policy
Structural changes in the economy
Changes in the underlying businesses
Solution: Use rolling correlations to monitor how relationships change over time
Outliers and Extreme Events
Problem: Extreme market events can distort correlation measurements
Example: During a market crash, many assets may move in the same direction regardless of their normal relationship
Solution:
Use Spearman correlation, which is less sensitive to outliers
Be cautious when interpreting correlations during extreme market conditions
Sample Size Considerations
Problem: Small sample sizes can produce unreliable correlation estimates
Rule of Thumb: Use at least 30 data points for a rough estimate, 60+ for more reliable results
Solution:
Use the default correlation length of 60 or higher
Be skeptical of correlations calculated with small samples
Timeframe Considerations
Problem: Correlations can vary across different timeframes
Example: Two assets might be positively correlated on a daily basis but negatively correlated on a weekly basis
Solution:
Test correlations on multiple timeframes
Use the timeframe that matches your trading horizon
Look-Ahead Bias
Problem: Using information that wouldn't have been available at the time of trading
Example: Calculating correlation using future data
Solution: This script avoids look-ahead bias by using only historical data
Best Practices for Using This Script
1. Appropriate Parameter Selection
Correlation Window:
For short-term trading: 20-50 periods
For medium-term analysis: 50-100 periods
For long-term analysis: 100-500 periods
Rolling Window:
Should be shorter than the main correlation window
Typically 1/3 to 1/2 of the main window
Return Type:
For most applications: Log Returns (better statistical properties)
For simplicity: Simple Returns (easier to interpret)
2. Validation and Testing
Out-of-Sample Testing:
Calculate correlations on one time period
Test if they hold in a different time period
Multiple Timeframes:
Check if correlations are consistent across different timeframes
Economic Rationale:
Ensure there's a logical reason why assets should be correlated
3. Monitoring and Maintenance
Regular Review:
Correlations can change, so review them regularly
Alerts:
Set up alerts for significant correlation changes
Documentation:
Keep notes on why certain assets are correlated and what might change that relationship
4. Integration with Other Analysis
Fundamental Analysis:
Combine correlation analysis with fundamental factors
Technical Analysis:
Use correlation analysis alongside technical indicators
Market Context:
Consider how market conditions might affect correlations
Conclusion
This Scientific Correlation Testing Framework provides a comprehensive tool for analyzing relationships between financial assets. By offering both Pearson and Spearman correlation methods, statistical significance testing, and rolling correlation analysis, it goes beyond simple correlation measures to provide deeper insights.
For beginners, this script might seem complex, but it's built on fundamental statistical concepts that become clearer with use. Start with the default settings and focus on interpreting the main correlation lines and the statistics table. As you become more comfortable, you can adjust the parameters and explore more advanced applications.
Remember that correlation analysis is just one tool in a trader's toolkit. It should be used in conjunction with other forms of analysis and with a clear understanding of its limitations. When used properly, it can provide valuable insights for portfolio construction, risk management, and pair trading strategy development.
Pesquisar nos scripts por "如何用wind搜索股票的发行价和份数"
Halt-Risk Guard (5-min / 10%) — TTP Safe🛑 Halt-Risk Guard (5-min / 10%) — TTP Safe
Stay clear of halts, invalidations, and over-extended moves.
🔍 Overview
The Halt-Risk Guard helps traders avoid sudden invalidations by monitoring price velocity over the past X minutes (default: 5 min) and flagging when moves exceed a configurable threshold (default: 10%).
Originally built to meet Trade The Pool (TTP) risk-management rules — where even non-halted 10% moves can void trades — this tool provides a clear, visual warning system and optional entry blocker.
⚙️ Key Features
✅ Halt-Risk Detection – Calculates both reference-based and swing-based (high↔low) percentage change over the chosen lookback period.
✅ TTP Safe Mode – “Swing mode” captures extreme volatility spikes that may invalidate trades even when the market stays open.
✅ Entry Blocker (optional) – Automatically greys candles and dims the background during risky conditions to prevent impulsive entries.
✅ Customisable Positioning – Move the on-chart info box to any corner of your chart (Top Left / Top Right / Bottom Left / Bottom Right).
✅ Clean Alerts –
⚠️ At/Above Threshold
✅ Back to Safe
⛔ Entry Blocker Active
✅ Visual Table Display – Compact dashboard shows current % move, lookback window, and threshold with intuitive green/red status.
✅ Strategy-Ready Output – A hidden 0/1 plot lets you block or filter trades in automated systems.
⚡ How It Works
Monitors the selected symbol using your chosen computation timeframe (recommended 1-minute).
Evaluates either:
REF mode: Close-to-close change over the lookback window.
SWING mode: High-to-low range within the same window.
If the move ≥ Threshold %, the script highlights a halt-risk condition and optionally activates the entry blocker.
🎨 Recommended Settings
Lookback: 5 minutes
Threshold: 10 %
Swing mode: ON (TTP-safe)
Computation timeframe: 1 minute
Entry blocker: ON
Dim background: ON
🧠 Use Cases
TTP and other prop-firm evaluations enforcing price-movement limits.
Volatility-based scalping systems to avoid chasing extended candles.
Strategy filters for algorithmic entries (e.g. pause trading during halt-risk windows).
⚠️ Disclaimer
This tool provides visual and alert-based guidance only. It does not guarantee compliance with any specific firm’s rules or eliminate trading risk. Always verify thresholds and rules with your broker or evaluation provider.
BTC/USD Breakout Hours – IST (Hyderabad)This indicator highlights the most volatile BTC/USD trading hours based on Hyderabad (IST) time.
It marks three key breakout windows:
London–US Overlap (17:30–20:30 IST) – Highest liquidity & volatility
US Market Open Momentum (19:00–23:30 IST) – Strong trend moves
Early London Session (12:30–15:30 IST) – Pre-US setup moves
The script automatically converts chart time to IST, shades each breakout window, and includes optional alerts for:
Window start
15 minutes before start
Ideal for traders who want to align entries with high-probability market moves while avoiding low-volume hours.
Closed Market / Back-Test Filter x 'Bull_Trap_9'Hello TradingView Traders!
This is a very valuable tool that I believe all traders will find useful.
This indicator / filter is '1 of 2'. I prefer it as a filter because it is not meant for live trade analysis. It is designed to make a trader aware of their individual trade sessions and to help aid in static chart candlestick back-testing.
Also, look for my indicator / filter, '2 of 2': 'Red Report Filter'
There are two functions to this filter.
Primary use: It allows a trader to set a session window: Open / Close.
During a trade session, like YM, I only trade 9:30 - 15:00. Without the filter, many times I have traded past my cutoff because I was focused on the chart and not the time.
With this filter on as close nears with an open trade and the filter starts to apply, I know I am at session close with no more trades upon exit. Otherwise, I know the session is done with no further trades.
It is also nice to have the filter on during the session open as a demarcation boundary.
Secondary use: It is used as a chart back-test tool.
When applied to a traders back-test chart, the trader can control their trade session envelopes for easier and more precise evaluation. The filter will allow only the candles per session that the trader wants to focus on and will filter all other non-session candles.
I can easily compare a whole week of 30m session data, concentrating solely on the filtered trade windows.
Please Note: The filter will be active as far back as the historic data prints.
Thanks for viewing!
Hurst Exponent Oscillator [PhenLabs]📊 Hurst Exponent Oscillator -
Version: PineScript™ v5
📌 Description
The Hurst Exponent Oscillator (HEO) by PhenLabs is a powerful tool developed for traders who want to distinguish between trending, mean-reverting, and random market behaviors with clarity and precision. By estimating the Hurst Exponent—a statistical measure of long-term memory in financial time series—this indicator helps users make sense of underlying market dynamics that are often not visible through traditional moving averages or oscillators.
Traders can quickly know if the market is likely to continue its current direction (trending), revert to the mean, or behave randomly, allowing for more strategic timing of entries and exits. With customizable smoothing and clear visual cues, the HEO enhances decision-making in a wide range of trading environments.
🚀 Points of Innovation
Integrates advanced Hurst Exponent calculation via Rescaled Range (R/S) analysis, providing unique market character insights.
Offers real-time visual cues for trending, mean-reverting, or random price action zones.
User-controllable EMA smoothing reduces noise for clearer interpretation.
Dynamic coloring and fill for immediate visual categorization of market regime.
Configurable visual thresholds for critical Hurst levels (e.g., 0.4, 0.5, 0.6).
Fully customizable appearance settings to fit different charting preferences.
🔧 Core Components
Log Returns Calculation: Computes log returns of the selected price source to feed into the Hurst calculation, ensuring robust and scale-independent analysis.
Rescaled Range (R/S) Analysis: Assesses the dispersion and cumulative deviation over a rolling window, forming the core statistical basis for the Hurst exponent estimate.
Smoothing Engine: Applies Exponential Moving Average (EMA) smoothing to the raw Hurst value for enhanced clarity.
Dynamic Rolling Windows: Utilizes arrays to maintain efficient, real-time calculations over user-defined lengths.
Adaptive Color Logic: Assigns different highlight and fill colors based on the current Hurst value zone.
🔥 Key Features
Visually differentiates between trending, mean-reverting, and random market modes.
User-adjustable lookback and smoothing periods for tailored sensitivity.
Distinct fill and line styles for each regime to avoid ambiguity.
On-chart reference lines for strong trending and mean-reverting thresholds.
Works with any price series (close, open, HL2, etc.) for versatile application.
🎨 Visualization
Hurst Exponent Curve: Primary plotted line (smoothed if EMA is used) reflects the ongoing estimate of the Hurst exponent.
Colored Zone Filling: The area between the Hurst line and the 0.5 reference line is filled, with color and opacity dynamically indicating the current market regime.
Reference Lines: Dash/dot lines mark standard Hurst thresholds (0.4, 0.5, 0.6) to contextualize the current regime.
All visual elements can be customized for thickness, color intensity, and opacity for user preference.
📖 Usage Guidelines
Data Settings
Hurst Calculation Length
Default: 100
Range: 10-300
Description: Number of bars used in Hurst calculation; higher values mean longer-term analysis, lower values for quicker reaction.
Data Source
Default: close
Description: Select which data series to analyze (e.g., Close, Open, HL2).
Smoothing Length (EMA)
Default: 5
Range: 1-50
Description: Length for smoothing the Hurst value; higher settings yield smoother but less responsive results.
Style Settings
Trending Color (Hurst > 0.5)
Default: Blue tone
Description: Color used when trending regime is detected.
Mean-Reverting Color (Hurst < 0.5)
Default: Orange tone
Description: Color used when mean-reverting regime is detected.
Neutral/Random Color
Default: Soft blue
Description: Color when market behavior is indeterminate or shifting.
Fill Opacity
Default: 70-80
Range: 0-100
Description: Transparency of area fills—higher opacity for stronger visual effect.
Line Width
Default: 2
Range: 1-5
Description: Thickness of the main indicator curve.
✅ Best Use Cases
Identifying if a market is regime-shifting from trending to mean-reverting (or vice versa).
Filtering signals in automated or systematic trading strategies.
Spotting periods of randomness where trading signals should be deprioritized.
Enhancing mean-reversion or trend-following models with regime-awareness.
⚠️ Limitations
Not predictive: Reflects current and recent market state, not future direction.
Sensitive to input parameters—overfitting may occur if settings are changed too frequently.
Smoothing can introduce lag in regime recognition.
May not work optimally in markets with structural breaks or extreme volatility.
💡 What Makes This Unique
Employs advanced statistical market analysis (Hurst exponent) rarely found in standard toolkits.
Offers immediate regime visualization through smart dynamic coloring and zone fills.
🔬 How It Works
Rolling Log Return Calculation:
Each new price creates a log return, forming the basis for robust, non-linear analysis. This ensures all price differences are treated proportionally.
Rescaled Range Analysis:
A rolling window maintains cumulative deviations and computes the statistical “range” (max-min of deviations). This is compared against the standard deviation to estimate “memory”.
Exponent Calculation & Smoothing:
The raw Hurst value is translated from the log of the rescaled range ratio, and then optionally smoothed via EMA to dampen noise and false signals.
Regime Detection Logic:
The smoothed value is checked against 0.5. Values above = trending; below = mean-reverting; near 0.5 = random. These control plot/fill color and zone display.
💡 Note:
Use longer calculation lengths for major market character study, and shorter ones for tactical, short-term adaptation. Smoothing balances noise vs. lag—find a best fit for your trading style. Always combine regime awareness with broader technical/fundamental context for best results.
MACD by Take and TradeImproved version of MACD with asymmetrical BUY and SELL approaches.
This indicator is based on popular MACD one, but with some "tricks" designed to make it more applicable to the rapidly changing crypto market.
Key benefits:
Dynamic auto-adjusted threshold to filter out weak signals
Highlighted BUY/SELL signals with divergence (if a signal is accompanied by divergence, for example, price makes a new high while macd has a second high below the first, this signal is considered stronger and will be highlighted in a darker color)
Boost BUY signals on very slow market in accumulation phase
Not symmetric! It uses 2 different signal lines, which allows to obtain SELL signals earlier comparing to classic MACD approach
Classic concept of MACD
Classic MACD, in its simplest case, consists of two lines - macd line and signal line. Macd line is a difference between so-called "fast" and "slow" EMA lines (there are just a Exponential Moving Average lines with different windows: "12" for fast and "26" for slow). Signal line is just a smoothed "macd" line.
When macd line crosses signal line from bottom to up and intersection point < 0, this is "BUY" signal. And vise versa, when macd line crosses signal line from top to bottom, and intersection point > 0, this is "SELL" signal.
Parameters used in default configuration of classic MACD indicator:
Fast line: EMA-12
Slow line: EMA-26
Signal line: EMA-9
Problem of classic concept
Classic MACD indicator usually gives not bad "BUY" signals, especially if using them not for operational trading but for "investment" strategy. But "SELL" signalls usually generated too late. Simply because the market tends to fall much faster than it rises.
Possible solution (the main feature of our version of MACD)
To make indicator react faster on SELL condition, while still keeping it reliable for BUY signals, we decided to use two signal lines . Faster than default signal line (with window=6) for BUY signals and much faster than default (with window=2) for SELL signals.
This approach allowed us to receive sell signals earlier and exit deals on more favorable prices. Trade off of this change - is the number of SELL signals - there were more of them. However, this does not matter, since we receive the very first sell signal with a "very fast signal line" much earlier than with classic indicator settings.
Parameters we use in our improved MACD indicator:
Fast line: EMA-12
Slow line: EMA-24
Faster signal line: EMA-6
Much faster signal line: EMA-2
Removing noise (false triggerings)
Other drawback of classic MACD - it generates a lot of "weak" (false) signals. This signals are generated when macd crosses signal line much close to zero-line. And usually there are a lot of such intersections.
To remove this kind of noise, we added a trigger threshold, which by default is equal to 2.5% of the average asset price over a long period of time. Due to the link to the average price, this threshold automatically takes a specific value for each trading pair. Threshold 2.5% works perfect for all trading pairs for 1D timeframe. For other timeframes user can (and maybe will want) change it.
Boost weak BUY signals in a prolonged bear market
Signals on bearish stage are usually very weak, because there is no volatility, and no price impulse. And such signals will be filtered out as "noise" - see above. But this time is perfect time to buy! Therefore, we further boost the buy signals in a prolonged bear market so that they can pass through the filter and appear on the chart. Bearish period is the best time to invest!
Developed by Take and Trade. Enjoy using it!
The Echo Forecast [LuxAlgo]This indicator uses a simple time series forecasting method derived from the similarity between recent prices and similar/dissimilar historical prices. We named this method "ECHO".
This method originally assumes that future prices can be estimated from a historical series of observations that are most similar to the most recent price variations. This similarity is quantified using the correlation coefficient. Such an assumption can prove to be relatively effective with the forecasting of a periodic time series. We later introduced the ability to select dissimilar series of observations for further experimentation.
This forecasting technique is closely inspired by the analogue method introduced by Lorenz for the prediction of atmospheric data.
1. Settings
Evaluation Window: Window size used for finding historical observations similar/dissimilar to recent observations. The total evaluation window is equal to "Forecast Window" + "Evaluation Window"
Forecast Window: Determines the forecasting horizon.
Forecast Mode: Determines whether to choose historical series similar or dissimilar to the recent price observations.
Forecast Construction: Determines how the forecast is constructed. See "Usage" below.
Src: Source input of the forecast
Other style settings are self-explanatory.
2. Usage
This tool can be used to forecast future trends but also to indicate which historical variations have the highest degree of similarity/dissimilarity between the observations in the orange zone.
The forecasting window determines the prices segment (in orange) to be used as a reference for the search of the most similar/dissimilar historical price segment (in green) within the gray area.
Most forecasting techniques highly benefit from a detrended series. Due to the nature of this method, we highly recommend applying it to a detrended and periodic series.
You can see above the method is applied on a smooth periodic oscillator and a momentum oscillator.
The construction of the forecast is made from the price changes obtained in the green area, denoted as w(t) . Using the "Cumulative" options we construct the forecast from the cumulative sum of w(t) . Finally, we add the most recent price value to this cumulated series.
Using the "Mean" options will add the series w(t) with the mean of the prices within the orange segment.
Finally the "Linreg" will add the series w(t) to an extrapolated linear regression fit to the prices within the orange segment.
PM Range Breaker [CHE] PM Range Breaker — Premarket bias with first-five range breaks, optional SWDEMA regime latch, and simple two-times-range targets
Summary
This indicator sets a once-per-day directional bias during New York premarket and then tracks a strict first-five-minutes range from the session open. After the first five complete, it marks clean breakouts and can project targets at two times the measured range. A second mode latches an EMA-based regime to inform the bias and optional background tinting. A compact panel reports live state, first-five levels, and rolling hit rates of both bias modes using a user-defined midday close for statistics.
Motivation: Why this design?
Intraday traders often get whipsawed by early noise or by fast flips in trend filters. This script commits to a bias at a single premarket minute and then waits for the market to present an objective structure: the first-five range. Breaks after that window are clearer and easier to manage. The alternative SWDEMA regime gives a slower, latched context for users who prefer a trend scaffold rather than a midpoint reference.
What’s different vs. standard approaches?
Baseline: Typical open-range-breakout lines or a single moving-average filter without daily commitment.
Architecture differences:
Bias decision at a fixed New York time using either a midpoint lookback (“Classic”) or a two-EMA regime latch (“SWDEMA”).
Strict five-minute window from session open; breakout shapes print only after that window.
Single-shot breakout direction per session (debounce) and optional two-times-range targets.
On-chart panel with hit rates using a configurable midday close for statistics.
Practical effect: Cleaner visuals, fewer repeated signals, and a traceable daily decision that can be evaluated over time.
How it works (technical)
Time handling uses New York session times for premarket decision, open, first-five end, and a midday statistics checkpoint.
Classic bias: A midpoint is computed from the highest and lowest over a user period; at the premarket minute, the bias is set long when the close is above the midpoint, short otherwise.
SWDEMA bias: Two EMAs define a regime score that requires price and trend agreement; when both agree on a confirmed bar, the regime latches. At the premarket minute, the daily bias is set from the current regime.
The first-five range captures high and low from open until the end minute, then freezes. Breakouts are detected after that window using close-based cross logic.
The script draws range lines and optional targets at two times the frozen range. A session break direction latch prevents duplicate break markers.
Statistics compare daily open and a configurable midday close to record if the chosen bias aligned with the move.
Optional elements include EMA lines, midpoint line, latched-regime background, and regime switch markers.
Data aggregation for day logic and the first-five window is sampled on one-minute data with explicit lookahead off. On charts above one minute, values update intra-bar until the underlying minute closes.
Parameter Guide
Premarket Start (NY) — Minute when the bias is decided — Default: 08:30 — Move earlier for more stability; later for recency.
Market Open (NY) — Session start used for the first-five window — Default: 09:30 — Align to instrument’s RTH if different.
First-5 End (NY) — End of the first-five window — Default: 09:35 — Extend slightly to capture wider opening ranges.
Day End (NY) for Stats — Midday checkpoint for hit rate — Default: 12:00 — Use a later time for a longer evaluation window.
Show First-5 Lines — Draw the frozen range lines — Default: On — Turn off if your chart is crowded.
Show Bias Background (Session) — Tint by daily bias during session — Default: On — Useful for directional context.
Show Break Shapes — Print breakout triangles — Default: On — Disable if you only want lines and alerts.
Show 2R Targets (Optional) — Plot targets at two times the range — Default: On — Switch off if you manage exits differently.
Line Length Right — Extension length of drawn lines — Default: 20 (bars) — Increase for slower timeframes.
High/Low Line Colors — Visual colors for range levels — Defaults: Green/Red — Adjust to your theme.
Long/Short Bias Colors — Background tints — Defaults: Green/Red with high transparency — Lower transparency for stronger emphasis.
Show Corner Panel — Enable the info panel — Default: On — Centralizes status and numbers.
Show Hit Rates in Panel — Include success rates — Default: On — Turn off to reduce panel rows.
Panel Position — Anchor on chart — Default: Top right — Move to avoid overlap.
Panel Size — Text size in panel — Default: Small — Increase on high-resolution displays.
Dark Panel — Dark theme for the panel — Default: On — Match your chart background.
Show EMA Lines — Plot blue and red EMAs — Default: Off — Enable for SWDEMA context.
Show Midpoint Line — Plot the midpoint — Default: Off — Useful for Classic mode visualization.
Midpoint Lookback Period — Bars for high-low midpoint — Default: 300 — Larger values stabilize; smaller values respond faster.
Midpoint Line Color — Color for midpoint — Default: Gray — A neutral line works best.
SWDEMA Lengths (Blue/Red) — Periods for the two EMAs — Defaults: 144 and 312 — Longer values reduce flips.
Sources (Blue/Red) — Price sources — Defaults: Close and HLC3 — Adjust if you prefer consistency.
Offsets (Blue/Red) — Pixel offsets for EMA plots — Defaults: zero — Use only for visual shift.
Show Latched Regime Background — Background by SWDEMA regime — Default: Off — Separate from session bias.
Latched Background Transparency — Opacity of regime background — Default: eighty-eight — Lower value for stronger tint.
Show Latch Switch Markers — Plot regime change markers — Default: Off — For auditing regime changes.
Bias Mode — Classic midpoint or SWDEMA latch — Default: Classic — Choose per your style.
Background Mode — Session bias or SWDEMA regime — Default: Session — Decide which background narrative you want.
Reading & Interpretation
Panel: Shows the active bias, first-five high and low, and a state that reads Building during the window, Ready once frozen, and Break arrows when a breakout occurs. Hit rates show the percentage of days where each bias mode aligned with the midday move.
Colors and shapes: Green background implies long bias; red implies short bias. Triangle markers denote the first valid breakout after the first-five window. Optional regime markers flag regime changes.
Lines: First-five high and low form the core structure. Optional targets mark a level at two times the frozen range from the breakout side.
Practical Workflows & Combinations
Trend following: Choose a bias mode. Wait for the first clean breakout after the first-five window in the direction of the bias. Confirm with structure such as higher highs and higher lows or lower highs and lower lows.
Exits and risk: Conservative users can trail behind the opposite side of the first-five range. Aggressive users can scale near the two-times-range target.
Multi-asset and multi-TF: Works well on intraday timeframes from one minute upward. For non-US sessions, adjust the time inputs to the instrument’s regular trading hours.
Behavior, Constraints & Performance
Repaint and confirmation: Bias and regime decisions use confirmed bars. Breakout signals evaluate on bar close at the chart timeframe. On higher timeframes, minute-based sources update within the live bar until the minute closes.
security and HTF: The script samples one-minute data. Lookahead is off. Values stabilize once the source minute closes.
Resources: `max_bars_back` is five thousand. Drawing objects and the panel update efficiently, with position extensions handled on the last bar.
Known limits: Midday statistics use the configured time, not the official daily close. Session logic assumes New York session timing. Targets are simple multiples of the first-five range and do not adapt to volatility beyond that structure.
Sensible Defaults & Quick Tuning
Start with Classic bias, midpoint lookback at three hundred, and all visuals on.
Too many flips in context → switch to SWDEMA mode or increase EMA lengths.
Breakouts feel noisy → extend the first-five end by a minute or two, or wait for a retest by your own rules.
Too sluggish → reduce midpoint lookback or shorten EMA lengths.
Chart cluttered → hide EMA or midpoint lines and keep only range levels and breakout shapes.
What this indicator is—and isn’t
This is a visualization and signal layer for session bias and first-five structure. It does not manage orders, position sizing, or risk. It is not predictive. Use it alongside market structure, execution rules, and independent risk controls.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Many thanks to LonesomeTheBlue
for the original work. I adapted the midpoint calculation for this script. www.tradingview.com
Rolling Midpoint of Price & VWAP with ATR BandsThe Rolling Midpoint of Price & VWAP with ATR Bands indicator is a dual-equilibrium concept that fuses price-range structure and traded-volume flow into one continuously updating hybrid model. Traditional VWAPs reset each session and reflect where trading occurred by volume, while midpoints used here reveal where price has structurally balanced between extremes. This script merges both ideas into a cohesive, dynamic system. The Rolling Price Midpoint (50 % of range) represents the structural fair-value line, calculated as the average of the highest high and lowest low over a selected window. The Rolling VWAP (Volume-Weighted Window) tracks the flow-based fair-value line by weighting each bar’s typical price by its volume. Together, these components form the Hybrid Equilibrium — the adaptive center of gravity that shifts as price and volume evolve. Surrounding this equilibrium, ATR Bands at ± 2.226 ATR and ± 5.382 ATR define volatility envelopes that expand and contract with market energy. The result is a living cloud that breathes with the market: compressing during phases of balance and widening during impulsive movements, offering traders a clear visual framework for understanding equilibrium, volatility, and directional bias in real time.
➖
⚙️ Auto-Preset System
The Auto-Preset System intelligently adjusts lookback windows for both the Price Midpoint and VWAP calculations according to the active chart timeframe.
This ensures that the indicator automatically adapts to any trading style — from scalping on 1-minute charts to swing trading on daily or weekly charts — without manual tuning.
🔹 How It Works
When Auto-Preset mode is enabled, the script dynamically selects the most effective lookback lengths for each timeframe.
These presets are optimized to balance responsiveness and stability, maintaining consistent real-world coverage (e.g., the same approximate duration of price data) across all intervals.
📊 Preset Mapping Table
| Chart Timeframe | Price Midpoint Lookback | VWAP Lookback |
|:----------------:|:-----------------------:|:--------------:|
| 1–3m | 13 bars | 21 bars
| 5–10m | 21 bars | 34 bars
| 15–30m | 34 bars | 55 bars
| 1–2 hr | 55 bars | 89 bars
| 4 hr-1D | 89 bars | 144 bars
| 1W | 144 bars | 233 bars
| 1M | 233 bars | 377 bars
⚡ Notes & Customization
- Manual Override: Turn off Auto-Preset Mode to specify your own custom lookback lengths.
- Consistency Across Scales: These adaptive values keep the indicator visually coherent when switching between timeframes — avoiding distortions that can occur with static lengths.
- Practical Benefit: Traders can maintain a single chart layout that self-tunes seamlessly, removing the need to manually recalibrate settings when shifting from short-term to long-term analysis.
In short, the Auto-Preset System is designed to make this hybrid equilibrium tool timeframe-aware — automatically scaling its logic so that the cloud behaves consistently, regardless of chart resolution.
➖
🌐 Hybrid Equilibrium Envelope
The core hybrid midpoint acts as the mean of structural (price) and volumetric (VWAP) balance.
ATR-based bands project natural expansion zones:
🔸+2.226 / –2.226 ATR → inner equilibrium (controlled trend)
*🔸+5.382 / –5.382 ATR → outer volatility extension (over-stretch / reversion zones)
Color-coded fills show regime strength:
* 🟧 Upper Outer (+5.382) – strong bullish expansion
* 🟩 Upper Inner (+2.226) – trending equilibrium
* 🔴 Lower Inner (–2.226) – mild bearish control
* 🟣 Lower Outer (–5.382) – volatility exhaustion
➖
🧭 Higher-Timeframe Framework
Two macro anchors — Price length of 144 and VWAP length of 233 — outline higher-timeframe bias zones. These help confirm when local momentum aligns with (or fades against) long-term structure.
Labels on the right show active lookback values for quick readout:
`$(13) V(21)` → current rolling pair
`$144 / V233` → macro anchors
➖
🧩 Chart Examples
**AMD 15m (Equilibrium Expansion)**
Price steadily rides above the hybrid midpoint as teal and orange (bullish) ATR zones widen, confirming a phase of controlled bullish volatility and healthy trend expansion.
BTCUSD 1m (Volatility Compression)
Bitcoin coils tightly inside the teal-to-maroon equilibrium bands before breaking out.
The hybrid midpoint flattens and ATR envelopes contract, signaling a state of balance before volatility expansion.
ETHUSD 15m (Transition from Compression → Impulse)
Ethereum transitions from purple-zone compression into a clear upper-band expansion.
The hybrid midpoint breaks above the macro VWAP 233, confirming the shift from equilibrium to directional momentum.
SOFI 1m (Micro Bias Reversal)
SOFI’s intraday structure flips as price reclaims the hybrid midpoint.
The macro VWAP 233 flattens, signaling a transition from oversold lower bands back toward equilibrium and early trend recovery.
➖
🎯 How to Use
1. Bias Detection – Price > Hybrid Midpoint → bullish; < → bearish.
2. Volatility Gauge – Watch band spacing for compression / expansion cycles.
3. Confluence Checks – Align Hybrid Midpoint with HTF 233 VWAP for strong continuation signals.
4. Mean Reversion Zones – Outer bands highlight areas where probability of snap-back increases.
➖
🔧 Inputs & Customization
Auto Presets toggle
🔸Manual Lookback Overrides** for fine-tuning
🔸Plot Window Length** (show recent vs full history)
🔸ATR Sensitivity & Fill Opacity** controls
🔸Label Padding / Font Size** for cleaner overlay visuals
➖
🧮 Formula Highlights
➖Rolling Midpoint = (highest(high,N) + lowest(low,N)) / 2
➖Rolling VWAP = Σ(Typical Price×Vol) / Σ(Vol)
➖Hybrid = (PriceMid + VWAP) / 2
➖Upper₂ = Hybrid + ATR×2.226
➖Lower₂ = Hybrid − ATR×2.226
➖Upper₅ = Hybrid + ATR×5.382
➖Lower₅ = Hybrid − ATR×5.382
➖
🎯 Ideal For
➡️ Traders who want adaptive fair-value zones that evolve with both price and volume.
➡️ Analysts who shift between scalping, swing, and position timeframes, and need a tool that self-adjusts.
➡️ Those who rely on visual structure clarity to confirm setups across changing volatility conditions.
➡️ Anyone seeking a hybrid model that unites structural range logic (midpoint) and flow-based balance (VWAP).
➖
🏁 Final Word
This script is more than a visual overlay — it’s a complete trend and structure framework built to adapt with market rhythm. It helps traders visualize equilibrium, momentum, and volatility as one cohesive system. Whether you’re seeking clean trend alignment, dynamic support/resistance, or early warning signs of reversals, this indicator is tuned to help you react with confidence — not hindsight.
➖
Remember — no single indicator should ever stand alone. For best results, pair it with price action context, higher-timeframe structure, and complementary tools such as moving averages or trendlines. Use it to confirm setups, not define them in isolation.
💡 Turn logic into clarity, structure into trades, and uncertainty into confidence.
Breakouts with timefilter [LuciTech]Here's the updated description with "colors" replaced by "colours" throughout, maintaining the original structure and content:
Breaking Point 2.0
This is a technical analysis overlay indicator designed to identify breakout levels based on pivot highs and lows, with a focus on price action during customizable time windows using London time (UK). It draws horizontal lines at pivot points and plots signals when price breaks above or below these levels, offering traders a tool to monitor potential bullish or bearish movements. The indicator includes options for time filtering and displaying only the most recent breakout.
Features
The Pivot Breakout Lines display horizontal lines at detected pivot highs (bullish) and pivot lows (bearish), coloured green and red by default. These lines extend from the pivot point to the breakout bar and can be set to show only the latest breakout.
The Breakout Signals mark bullish breakouts with an upward triangle below the bar and bearish breakouts with a downward triangle above the bar, using customizable colours.
The Time Filter restricts signals and lines to a specific window (default: 14:30–15:00 UK), which can be toggled on or off. A shaded background highlights this period when enabled.
How It Works
The indicator calculates pivot highs and lows using a user-defined lookback period (default: 5 bars). When price closes above a pivot high, it triggers a bullish signal and draws a line from the pivot to the breakout bar. When price closes below a pivot low, it triggers a bearish signal with a corresponding line.
If the time filter is active, signals and lines only appear within the specified window. Outside this period—or if the filter is disabled—they appear based solely on price action. The indicator maintains up to three recent pivots in memory, removing older ones as new pivots form.
Alerts are available for both bullish and bearish breakouts, triggered when signals occur.
Settings
Length controls the lookback period for pivot detection (default: 5).
Colours Bull/Bear sets the colours for bullish (default: green) and bearish (default: red) lines and signals.
Show Last Breakout toggles whether only the most recent breakout line and signal are displayed (default: false).
Time Filter enables or disables the time restriction (default: true).
Fill Background toggles a shaded area during the time window (default: true), with a customizable colour.
Time Settings define the start hour/minute and end hour/minute for the filter (default: 14:30–15:00).
Interpretation
The Pivot Breakout Lines highlight levels where price has previously reversed, potentially acting as support or resistance. A breakout above a pivot high may suggest bullish momentum, while a breakout below a pivot low may indicate bearish pressure.
The Breakout Signals provide visual cues for these events, useful for timing entries or exits. When "Show Last Breakout" is enabled, the chart focuses on the most recent signal, reducing clutter.
The Time Filter and background shading help traders concentrate on specific trading sessions, such as high-volatility periods. When disabled, the indicator tracks breakouts across all times.
Backtesting & Trading Engine [PineCoders]The PineCoders Backtesting and Trading Engine is a sophisticated framework with hybrid code that can run as a study to generate alerts for automated or discretionary trading while simultaneously providing backtest results. It can also easily be converted to a TradingView strategy in order to run TV backtesting. The Engine comes with many built-in strats for entries, filters, stops and exits, but you can also add you own.
If, like any self-respecting strategy modeler should, you spend a reasonable amount of time constantly researching new strategies and tinkering, our hope is that the Engine will become your inseparable go-to tool to test the validity of your creations, as once your tests are conclusive, you will be able to run this code as a study to generate the alerts required to put it in real-world use, whether for discretionary trading or to interface with an execution bot/app. You may also find the backtesting results the Engine produces in study mode enough for your needs and spend most of your time there, only occasionally converting to strategy mode in order to backtest using TV backtesting.
As you will quickly grasp when you bring up this script’s Settings, this is a complex tool. While you will be able to see results very quickly by just putting it on a chart and using its built-in strategies, in order to reap the full benefits of the PineCoders Engine, you will need to invest the time required to understand the subtleties involved in putting all its potential into play.
Disclaimer: use the Engine at your own risk.
Before we delve in more detail, here’s a bird’s eye view of the Engine’s features:
More than 40 built-in strategies,
Customizable components,
Coupling with your own external indicator,
Simple conversion from Study to Strategy modes,
Post-Exit analysis to search for alternate trade outcomes,
Use of the Data Window to show detailed bar by bar trade information and global statistics, including some not provided by TV backtesting,
Plotting of reminders and generation of alerts on in-trade events.
By combining your own strats to the built-in strats supplied with the Engine, and then tuning the numerous options and parameters in the Inputs dialog box, you will be able to play what-if scenarios from an infinite number of permutations.
USE CASES
You have written an indicator that provides an entry strat but it’s missing other components like a filter and a stop strategy. You add a plot in your indicator that respects the Engine’s External Signal Protocol, connect it to the Engine by simply selecting your indicator’s plot name in the Engine’s Settings/Inputs and then run tests on different combinations of entry stops, in-trade stops and profit taking strats to find out which one produces the best results with your entry strat.
You are building a complex strategy that you will want to run as an indicator generating alerts to be sent to a third-party execution bot. You insert your code in the Engine’s modules and leverage its trade management code to quickly move your strategy into production.
You have many different filters and want to explore results using them separately or in combination. Integrate the filter code in the Engine and run through different permutations or hook up your filtering through the external input and control your filter combos from your indicator.
You are tweaking the parameters of your entry, filter or stop strat. You integrate it in the Engine and evaluate its performance using the Engine’s statistics.
You always wondered what results a random entry strat would yield on your markets. You use the Engine’s built-in random entry strat and test it using different combinations of filters, stop and exit strats.
You want to evaluate the impact of fees and slippage on your strategy. You use the Engine’s inputs to play with different values and get immediate feedback in the detailed numbers provided in the Data Window.
You just want to inspect the individual trades your strategy generates. You include it in the Engine and then inspect trades visually on your charts, looking at the numbers in the Data Window as you move your cursor around.
You have never written a production-grade strategy and you want to learn how. Inspect the code in the Engine; you will find essential components typical of what is being used in actual trading systems.
You have run your system for a while and have compiled actual slippage information and your broker/exchange has updated his fees schedule. You enter the information in the Engine and run it on your markets to see the impact this has on your results.
FEATURES
Before going into the detail of the Inputs and the Data Window numbers, here’s a more detailed overview of the Engine’s features.
Built-in strats
The engine comes with more than 40 pre-coded strategies for the following standard system components:
Entries,
Filters,
Entry stops,
2 stage in-trade stops with kick-in rules,
Pyramiding rules,
Hard exits.
While some of the filter and stop strats provided may be useful in production-quality systems, you will not devise crazy profit-generating systems using only the entry strats supplied; that part is still up to you, as will be finding the elusive combination of components that makes winning systems. The Engine will, however, provide you with a solid foundation where all the trade management nitty-gritty is handled for you. By binding your custom strats to the Engine, you will be able to build reliable systems of the best quality currently allowed on the TV platform.
On-chart trade information
As you move over the bars in a trade, you will see trade numbers in the Data Window change at each bar. The engine calculates the P&L at every bar, including slippage and fees that would be incurred were the trade exited at that bar’s close. If the trade includes pyramided entries, those will be taken into account as well, although for those, final fees and slippage are only calculated at the trade’s exit.
You can also see on-chart markers for the entry level, stop positions, in-trade special events and entries/exits (you will want to disable these when using the Engine in strategy mode to see TV backtesting results).
Customization
You can couple your own strats to the Engine in two ways:
1. By inserting your own code in the Engine’s different modules. The modular design should enable you to do so with minimal effort by following the instructions in the code.
2. By linking an external indicator to the engine. After making the proper selections in the engine’s Settings and providing values respecting the engine’s protocol, your external indicator can, when the Engine is used in Indicator mode only:
Tell the engine when to enter long or short trades, but let the engine’s in-trade stop and exit strats manage the exits,
Signal both entries and exits,
Provide an entry stop along with your entry signal,
Filter other entry signals generated by any of the engine’s entry strats.
Conversion from strategy to study
TradingView strategies are required to backtest using the TradingView backtesting feature, but if you want to generate alerts with your script, whether for automated trading or just to trigger alerts that you will use in discretionary trading, your code has to run as a study since, for the time being, strategies can’t generate alerts. From hereon we will use indicator as a synonym for study.
Unless you want to maintain two code bases, you will need hybrid code that easily flips between strategy and indicator modes, and your code will need to restrict its use of strategy() calls and their arguments if it’s going to be able to run both as an indicator and a strategy using the same trade logic. That’s one of the benefits of using this Engine. Once you will have entered your own strats in the Engine, it will be a matter of commenting/uncommenting only four lines of code to flip between indicator and strategy modes in a matter of seconds.
Additionally, even when running in Indicator mode, the Engine will still provide you with precious numbers on your individual trades and global results, some of which are not available with normal TradingView backtesting.
Post-Exit Analysis for alternate outcomes (PEA)
While typical backtesting shows results of trade outcomes, PEA focuses on what could have happened after the exit. The intention is to help traders get an idea of the opportunity/risk in the bars following the trade in order to evaluate if their exit strategies are too aggressive or conservative.
After a trade is exited, the Engine’s PEA module continues analyzing outcomes for a user-defined quantity of bars. It identifies the maximum opportunity and risk available in that space, and calculates the drawdown required to reach the highest opportunity level post-exit, while recording the number of bars to that point.
Typically, if you can’t find opportunity greater than 1X past your trade using a few different reasonable lengths of PEA, your strategy is doing pretty good at capturing opportunity. Remember that 100% of opportunity is never capturable. If, however, PEA was finding post-trade maximum opportunity of 3 or 4X with average drawdowns of 0.3 to those areas, this could be a clue revealing your system is exiting trades prematurely. To analyze PEA numbers, you can uncomment complete sets of plots in the Plot module to reveal detailed global and individual PEA numbers.
Statistics
The Engine provides stats on your trades that TV backtesting does not provide, such as:
Average Profitability Per Trade (APPT), aka statistical expectancy, a crucial value.
APPT per bar,
Average stop size,
Traded volume .
It also shows you on a trade-by-trade basis, on-going individual trade results and data.
In-trade events
In-trade events can plot reminders and trigger alerts when they occur. The built-in events are:
Price approaching stop,
Possible tops/bottoms,
Large stop movement (for discretionary trading where stop is moved manually),
Large price movements.
Slippage and Fees
Even when running in indicator mode, the Engine allows for slippage and fees to be included in the logic and test results.
Alerts
The alert creation mechanism allows you to configure alerts on any combination of the normal or pyramided entries, exits and in-trade events.
Backtesting results
A few words on the numbers calculated in the Engine. Priority is given to numbers not shown in TV backtesting, as you can readily convert the script to a strategy if you need them.
We have chosen to focus on numbers expressing results relative to X (the trade’s risk) rather than in absolute currency numbers or in other more conventional but less useful ways. For example, most of the individual trade results are not shown in percentages, as this unit of measure is often less meaningful than those expressed in units of risk (X). A trade that closes with a +25% result, for example, is a poor outcome if it was entered with a -50% stop. Expressed in X, this trade’s P&L becomes 0.5, which provides much better insight into the trade’s outcome. A trade that closes with a P&L of +2X has earned twice the risk incurred upon entry, which would represent a pre-trade risk:reward ratio of 2.
The way to go about it when you think in X’s and that you adopt the sound risk management policy to risk a fixed percentage of your account on each trade is to equate a currency value to a unit of X. E.g. your account is 10K USD and you decide you will risk a maximum of 1% of it on each trade. That means your unit of X for each trade is worth 100 USD. If your APPT is 2X, this means every time you risk 100 USD in a trade, you can expect to make, on average, 200 USD.
By presenting results this way, we hope that the Engine’s statistics will appeal to those cognisant of sound risk management strategies, while gently leading traders who aren’t, towards them.
We trade to turn in tangible profits of course, so at some point currency must come into play. Accordingly, some values such as equity, P&L, slippage and fees are expressed in currency.
Many of the usual numbers shown in TV backtests are nonetheless available, but they have been commented out in the Engine’s Plot module.
Position sizing and risk management
All good system designers understand that optimal risk management is at the very heart of all winning strategies. The risk in a trade is defined by the fraction of current equity represented by the amplitude of the stop, so in order to manage risk optimally on each trade, position size should adjust to the stop’s amplitude. Systems that enter trades with a fixed stop amplitude can get away with calculating position size as a fixed percentage of current equity. In the context of a test run where equity varies, what represents a fixed amount of risk translates into different currency values.
Dynamically adjusting position size throughout a system’s life is optimal in many ways. First, as position sizing will vary with current equity, it reproduces a behavioral pattern common to experienced traders, who will dial down risk when confronted to poor performance and increase it when performance improves. Second, limiting risk confers more predictability to statistical test results. Third, position sizing isn’t just about managing risk, it’s also about maximizing opportunity. By using the maximum leverage (no reference to trading on margin here) into the trade that your risk management strategy allows, a dynamic position size allows you to capture maximal opportunity.
To calculate position sizes using the fixed risk method, we use the following formula: Position = Account * MaxRisk% / Stop% [, which calculates a position size taking into account the trade’s entry stop so that if the trade is stopped out, 100 USD will be lost. For someone who manages risk this way, common instructions to invest a certain percentage of your account in a position are simply worthless, as they do not take into account the risk incurred in the trade.
The Engine lets you select either the fixed risk or fixed percentage of equity position sizing methods. The closest thing to dynamic position sizing that can currently be done with alerts is to use a bot that allows syntax to specify position size as a percentage of equity which, while being dynamic in the sense that it will adapt to current equity when the trade is entered, does not allow us to modulate position size using the stop’s amplitude. Changes to alerts are on the way which should solve this problem.
In order for you to simulate performance with the constraint of fixed position sizing, the Engine also offers a third, less preferable option, where position size is defined as a fixed percentage of initial capital so that it is constant throughout the test and will thus represent a varying proportion of current equity.
Let’s recap. The three position sizing methods the Engine offers are:
1. By specifying the maximum percentage of risk to incur on your remaining equity, so the Engine will dynamically adjust position size for each trade so that, combining the stop’s amplitude with position size will yield a fixed percentage of risk incurred on current equity,
2. By specifying a fixed percentage of remaining equity. Note that unless your system has a fixed stop at entry, this method will not provide maximal risk control, as risk will vary with the amplitude of the stop for every trade. This method, as the first, does however have the advantage of automatically adjusting position size to equity. It is the Engine’s default method because it has an equivalent in TV backtesting, so when flipping between indicator and strategy mode, test results will more or less correspond.
3. By specifying a fixed percentage of the Initial Capital. While this is the least preferable method, it nonetheless reflects the reality confronted by most system designers on TradingView today. In this case, risk varies both because the fixed position size in initial capital currency represents a varying percentage of remaining equity, and because the trade’s stop amplitude may vary, adding another variability vector to risk.
Note that the Engine cannot display equity results for strategies entering trades for a fixed amount of shares/contracts at a variable price.
SETTINGS/INPUTS
Because the initial text first published with a script cannot be edited later and because there are just too many options, the Engine’s Inputs will not be covered in minute detail, as they will most certainly evolve. We will go over them with broad strokes; you should be able to figure the rest out. If you have questions, just ask them here or in the PineCoders Telegram group.
Display
The display header’s checkbox does nothing.
For the moment, only one exit strategy uses a take profit level, so only that one will show information when checking “Show Take Profit Level”.
Entries
You can activate two simultaneous entry strats, each selected from the same set of strats contained in the Engine. If you select two and they fire simultaneously, the main strat’s signal will be used.
The random strat in each list uses a different seed, so you will get different results from each.
The “Filter transitions” and “Filter states” strats delegate signal generation to the selected filter(s). “Filter transitions” signals will only fire when the filter transitions into bull/bear state, so after a trade is stopped out, the next entry may take some time to trigger if the filter’s state does not change quickly. When you choose “Filter states”, then a new trade will be entered immediately after an exit in the direction the filter allows.
If you select “External Indicator”, your indicator will need to generate a +2/-2 (or a positive/negative stop value) to enter a long/short position, providing the selected filters allow for it. If you wish to use the Engine’s capacity to also derive the entry stop level from your indicator’s signal, then you must explicitly choose this option in the Entry Stops section.
Filters
You can activate as many filters as you wish; they are additive. The “Maximum stop allowed on entry” is an important component of proper risk management. If your system has an average 3% stop size and you need to trade using fixed position sizes because of alert/execution bot limitations, you must use this filter because if your system was to enter a trade with a 15% stop, that trade would incur 5 times the normal risk, and its result would account for an abnormally high proportion in your system’s performance.
Remember that any filter can also be used as an entry signal, either when it changes states, or whenever no trade is active and the filter is in a bull or bear mode.
Entry Stops
An entry stop must be selected in the Engine, as it requires a stop level before the in-trade stop is calculated. Until the selected in-trade stop strat generates a stop that comes closer to price than the entry stop (or respects another one of the in-trade stops kick in strats), the entry stop level is used.
It is here that you must select “External Indicator” if your indicator supplies a +price/-price value to be used as the entry stop. A +price is expected for a long entry and a -price value will enter a short with a stop at price. Note that the price is the absolute price, not an offset to the current price level.
In-Trade Stops
The Engine comes with many built-in in-trade stop strats. Note that some of them share the “Length” and “Multiple” field, so when you swap between them, be sure that the length and multiple in use correspond to what you want for that stop strat. Suggested defaults appear with the name of each strat in the dropdown.
In addition to the strat you wish to use, you must also determine when it kicks in to replace the initial entry’s stop, which is determined using different strats. For strats where you can define a positive or negative multiple of X, percentage or fixed value for a kick-in strat, a positive value is above the trade’s entry fill and a negative one below. A value of zero represents breakeven.
Pyramiding
What you specify in this section are the rules that allow pyramiding to happen. By themselves, these rules will not generate pyramiding entries. For those to happen, entry signals must be issued by one of the active entry strats, and conform to the pyramiding rules which act as a filter for them. The “Filter must allow entry” selection must be chosen if you want the usual system’s filters to act as additional filtering criteria for your pyramided entries.
Hard Exits
You can choose from a variety of hard exit strats. Hard exits are exit strategies which signal trade exits on specific events, as opposed to price breaching a stop level in In-Trade Stops strategies. They are self-explanatory. The last one labelled When Take Profit Level (multiple of X) is reached is the only one that uses a level, but contrary to stops, it is above price and while it is relative because it is expressed as a multiple of X, it does not move during the trade. This is the level called Take Profit that is show when the “Show Take Profit Level” checkbox is checked in the Display section.
While stops focus on managing risk, hard exit strategies try to put the emphasis on capturing opportunity.
Slippage
You can define it as a percentage or a fixed value, with different settings for entries and exits. The entry and exit markers on the chart show the impact of slippage on the entry price (the fill).
Fees
Fees, whether expressed as a percentage of position size in and out of the trade or as a fixed value per in and out, are in the same units of currency as the capital defined in the Position Sizing section. Fees being deducted from your Capital, they do not have an impact on the chart marker positions.
In-Trade Events
These events will only trigger during trades. They can be helpful to act as reminders for traders using the Engine as assistance to discretionary trading.
Post-Exit Analysis
It is normally on. Some of its results will show in the Global Numbers section of the Data Window. Only a few of the statistics generated are shown; many more are available, but commented out in the Plot module.
Date Range Filtering
Note that you don’t have to change the dates to enable/diable filtering. When you are done with a specific date range, just uncheck “Date Range Filtering” to disable date filtering.
Alert Triggers
Each selection corresponds to one condition. Conditions can be combined into a single alert as you please. Just be sure you have selected the ones you want to trigger the alert before you create the alert. For example, if you trade in both directions and you want a single alert to trigger on both types of exits, you must select both “Long Exit” and “Short Exit” before creating your alert.
Once the alert is triggered, these settings no longer have relevance as they have been saved with the alert.
When viewing charts where an alert has just triggered, if your alert triggers on more than one condition, you will need the appropriate markers active on your chart to figure out which condition triggered the alert, since plotting of markers is independent of alert management.
Position sizing
You have 3 options to determine position size:
1. Proportional to Stop -> Variable, with a cap on size.
2. Percentage of equity -> Variable.
3. Percentage of Initial Capital -> Fixed.
External Indicator
This is where you connect your indicator’s plot that will generate the signals the Engine will act upon. Remember this only works in Indicator mode.
DATA WINDOW INFORMATION
The top part of the window contains global numbers while the individual trade information appears in the bottom part. The different types of units used to express values are:
curr: denotes the currency used in the Position Sizing section of Inputs for the Initial Capital value.
quote: denotes quote currency, i.e. the value the instrument is expressed in, or the right side of the market pair (USD in EURUSD ).
X: the stop’s amplitude, itself expressed in quote currency, which we use to express a trade’s P&L, so that a trade with P&L=2X has made twice the stop’s amplitude in profit. This is sometimes referred to as R, since it represents one unit of risk. It is also the unit of measure used in the APPT, which denotes expected reward per unit of risk.
X%: is also the stop’s amplitude, but expressed as a percentage of the Entry Fill.
The numbers appearing in the Data Window are all prefixed:
“ALL:” the number is the average for all first entries and pyramided entries.
”1ST:” the number is for first entries only.
”PYR:” the number is for pyramided entries only.
”PEA:” the number is for Post-Exit Analyses
Global Numbers
Numbers in this section represent the results of all trades up to the cursor on the chart.
Average Profitability Per Trade (X): This value is the most important gauge of your strat’s worthiness. It represents the returns that can be expected from your strat for each unit of risk incurred. E.g.: your APPT is 2.0, thus for every unit of currency you invest in a trade, you can on average expect to obtain 2 after the trade. APPT is also referred to as “statistical expectancy”. If it is negative, your strategy is losing, even if your win rate is very good (it means your winning trades aren’t winning enough, or your losing trades lose too much, or both). Its counterpart in currency is also shown, as is the APPT/bar, which can be a useful gauge in deciding between rivalling systems.
Profit Factor: Gross of winning trades/Gross of losing trades. Strategy is profitable when >1. Not as useful as the APPT because it doesn’t take into account the win rate and the average win/loss per trade. It is calculated from the total winning/losing results of this particular backtest and has less predictive value than the APPT. A good profit factor together with a poor APPT means you just found a chart where your system outperformed. Relying too much on the profit factor is a bit like a poker player who would think going all in with two’s against aces is optimal because he just won a hand that way.
Win Rate: Percentage of winning trades out of all trades. Taken alone, it doesn’t have much to do with strategy profitability. You can have a win rate of 99% but if that one trade in 100 ruins you because of poor risk management, 99% doesn’t look so good anymore. This number speaks more of the system’s profile than its worthiness. Still, it can be useful to gauge if the system fits your personality. It can also be useful to traders intending to sell their systems, as low win rate systems are more difficult to sell and require more handholding of worried customers.
Equity (curr): This the sum of initial capital and the P&L of your system’s trades, including fees and slippage.
Return on Capital is the equivalent of TV’s Net Profit figure, i.e. the variation on your initial capital.
Maximum drawdown is the maximal drawdown from the highest equity point until the drop . There is also a close to close (meaning it doesn’t take into account in-trade variations) maximum drawdown value commented out in the code.
The next values are self-explanatory, until:
PYR: Avg Profitability Per Entry (X): this is the APPT for all pyramided entries.
PEA: Avg Max Opp . Available (X): the average maximal opportunity found in the Post-Exit Analyses.
PEA: Avg Drawdown to Max Opp . (X): this represents the maximum drawdown (incurred from the close at the beginning of the PEA analysis) required to reach the maximal opportunity point.
Trade Information
Numbers in this section concern only the current trade under the cursor. Most of them are self-explanatory. Use the description’s prefix to determine what the values applies to.
PYR: Avg Profitability Per Entry (X): While this value includes the impact of all current pyramided entries (and only those) and updates when you move your cursor around, P&L only reflects fees at the trade’s last bar.
PEA: Max Opp . Available (X): It’s the most profitable close reached post-trade, measured from the trade’s Exit Fill, expressed in the X value of the trade the PEA follows.
PEA: Drawdown to Max Opp . (X): This is the maximum drawdown from the trade’s Exit Fill that needs to be sustained in order to reach the maximum opportunity point, also expressed in X. Note that PEA numbers do not include slippage and fees.
EXTERNAL SIGNAL PROTOCOL
Only one external indicator can be connected to a script; in order to leverage its use to the fullest, the engine provides options to use it as either an entry signal, an entry/exit signal or a filter. When used as an entry signal, you can also use the signal to provide the entry’s stop. Here’s how this works:
For filter state: supply +1 for bull (long entries allowed), -1 for bear (short entries allowed).
For entry signals: supply +2 for long, -2 for short.
For exit signals: supply +3 for exit from long, -3 for exit from short.
To send an entry stop level with an entry signal: Send positive stop level for long entry (e.g. 103.33 to enter a long with a stop at 103.33), negative stop level for short entry (e.g. -103.33 to enter a short with a stop at 103.33). If you use this feature, your indicator will have to check for exact stop levels of 1.0, 2.0 or 3.0 and their negative counterparts, and fudge them with a tick in order to avoid confusion with other signals in the protocol.
Remember that mere generation of the values by your indicator will have no effect until you explicitly allow their use in the appropriate sections of the Engine’s Settings/Inputs.
An example of a script issuing a signal for the Engine is published by PineCoders.
RECOMMENDATIONS TO ASPIRING SYSTEM DESIGNERS
Stick to higher timeframes. On progressively lower timeframes, margins decrease and fees and slippage take a proportionally larger portion of profits, to the point where they can very easily turn a profitable strategy into a losing one. Additionally, your margin for error shrinks as the equilibrium of your system’s profitability becomes more fragile with the tight numbers involved in the shorter time frames. Avoid <1H time frames.
Know and calculate fees and slippage. To avoid market shock, backtest using conservative fees and slippage parameters. Systems rarely show unexpectedly good returns when they are confronted to the markets, so put all chances on your side by being outrageously conservative—or a the very least, realistic. Test results that do not include fees and slippage are worthless. Slippage is there for a reason, and that’s because our interventions in the market change the market. It is easier to find alpha in illiquid markets such as cryptos because not many large players participate in them. If your backtesting results are based on moving large positions and you don’t also add the inevitable slippage that will occur when you enter/exit thin markets, your backtesting will produce unrealistic results. Even if you do include large slippage in your settings, the Engine can only do so much as it will not let slippage push fills past the high or low of the entry bar, but the gap may be much larger in illiquid markets.
Never test and optimize your system on the same dataset , as that is the perfect recipe for overfitting or data dredging, which is trying to find one precise set of rules/parameters that works only on one dataset. These setups are the most fragile and often get destroyed when they meet the real world.
Try to find datasets yielding more than 100 trades. Less than that and results are not as reliable.
Consider all backtesting results with suspicion. If you never entertained sceptic tendencies, now is the time to begin. If your backtest results look really good, assume they are flawed, either because of your methodology, the data you’re using or the software doing the testing. Always assume the worse and learn proper backtesting techniques such as monte carlo simulations and walk forward analysis to avoid the traps and biases that unchecked greed will set for you. If you are not familiar with concepts such as survivor bias, lookahead bias and confirmation bias, learn about them.
Stick to simple bars or candles when designing systems. Other types of bars often do not yield reliable results, whether by design (Heikin Ashi) or because of the way they are implemented on TV (Renko bars).
Know that you don’t know and use that knowledge to learn more about systems and how to properly test them, about your biases, and about yourself.
Manage risk first , then capture opportunity.
Respect the inherent uncertainty of the future. Cleanse yourself of the sad arrogance and unchecked greed common to newcomers to trading. Strive for rationality. Respect the fact that while backtest results may look promising, there is no guarantee they will repeat in the future (there is actually a high probability they won’t!), because the future is fundamentally unknowable. If you develop a system that looks promising, don’t oversell it to others whose greed may lead them to entertain unreasonable expectations.
Have a plan. Understand what king of trading system you are trying to build. Have a clear picture or where entries, exits and other important levels will be in the sort of trade you are trying to create with your system. This stated direction will help you discard more efficiently many of the inevitably useless ideas that will pop up during system design.
Be wary of complexity. Experienced systems engineers understand how rapidly complexity builds when you assemble components together—however simple each one may be. The more complex your system, the more difficult it will be to manage.
Play! . Allow yourself time to play around when you design your systems. While much comes about from working with a purpose, great ideas sometimes come out of just trying things with no set goal, when you are stuck and don’t know how to move ahead. Have fun!
@LucF
NOTES
While the engine’s code can supply multiple consecutive entries of longs or shorts in order to scale positions (pyramid), all exits currently assume the execution bot will exit the totality of the position. No partial exits are currently possible with the Engine.
Because the Engine is literally crippled by the limitations on the number of plots a script can output on TV; it can only show a fraction of all the information it calculates in the Data Window. You will find in the Plot Module vast amounts of commented out lines that you can activate if you also disable an equivalent number of other plots. This may be useful to explore certain characteristics of your system in more detail.
When backtesting using the TV backtesting feature, you will need to provide the strategy parameters you wish to use through either Settings/Properties or by changing the default values in the code’s header. These values are defined in variables and used not only in the strategy() statement, but also as defaults in the Engine’s relevant Inputs.
If you want to test using pyramiding, then both the strategy’s Setting/Properties and the Engine’s Settings/Inputs need to allow pyramiding.
If you find any bugs in the Engine, please let us know.
THANKS
To @glaz for allowing the use of his unpublished MA Squize in the filters.
To @everget for his Chandelier stop code, which is also used as a filter in the Engine.
To @RicardoSantos for his pseudo-random generator, and because it’s from him that I first read in the Pine chat about the idea of using an external indicator as input into another. In the PineCoders group, @theheirophant then mentioned the idea of using it as a buy/sell signal and @simpelyfe showed a piece of code implementing the idea. That’s the tortuous story behind the use of the external indicator in the Engine.
To @admin for the Volatility stop’s original code and for the donchian function lifted from Ichimoku .
To @BobHoward21 for the v3 version of Volatility Stop .
To @scarf and @midtownsk8rguy for the color tuning.
To many other scripters who provided encouragement and suggestions for improvement during the long process of writing and testing this piece of code.
To J. Welles Wilder Jr. for ATR, used extensively throughout the Engine.
To TradingView for graciously making an account available to PineCoders.
And finally, to all fellow PineCoders for the constant intellectual stimulation; it is a privilege to share ideas with you all. The Engine is for all TradingView PineCoders, of course—but especially for you.
Look first. Then leap.
SMART RSISimilar to RSI in concept, but with a few enhancements!
Improvements over the standard RSI indicator?
1. Adaptive Decision Boundaries:
Who says 70-30 are the best decision boundaries to use for trading off of the RSI indicator? Why not 80-20, or another combination? Is 70-30 still the best when you shorten or lengthen the RSI indicator's look-back window? What about when you change the time frame? I wondered this for a while too, and thats what inspired me to create this indicator! Instead of using fixed lines for the boundaries, the boundaries are calculated based off of a user specified percentile. What this means is that the reference lines are calculated by looking at the values the RSI indicator took over some look back window, and calculating an upper and lower bound where the RSI actually stayed n% of the time over that look-back window. The default parameter given for this argument is 90. What that means is over the last n days, the RSI indicator spent 90% of it's time between the upper and lower bound.
2. Smoothing The RSI Indicator:
The RSI indicator on smaller time windows tends to be very noisy. However a simple linear regression over a short time period on the RSI indicator helps to cancel out this noise without losing too much information. This makes cross-overs more meaningful as they are less likely to happen due to small deviations. In addition, it also paints a smoothed picture of the price momentum that is easy and pleasant to read. The reference lines are also smoothed.
3. Color Coding Crosses When They Happen!
Wouldn't it be great if your software highlights cross overs when they happen for you so you would not have to go back over your chart and identify it for yourself? Well this software does! It paints red behind the indicator when the RSI indicator goes above the upper reference line, and paints blue when the RSI goes below the lower reference line.
The default parameters were selected based on what I feel is useful for daily candles on BTCUSD. However you are free to change the parameters as you see fit for different securities and time frames.
[SM-021] Gaussian Trend System [Optimized]This script is a comprehensive trend-following strategy centered around a Gaussian Channel. It is designed to capture significant market movements while filtering out noise during consolidation phases. This version (v2) introduces code optimizations using Pine Script v6 Arrays and a new Intraday Time Control feature.
1. Core Methodology & Math
The foundation of this strategy is the Gaussian Filter, originally conceptualized by @DonovanWall.
Gaussian Poles: Unlike standard moving averages (SMA/EMA), this filter uses "poles" (referencing signal processing logic) to reduce lag while maintaining smoothness.
Array Optimization: In this specific iteration, the f_pole function has been refactored to utilize Pine Script Arrays. This improves calculation efficiency and rendering speed compared to recursive variable calls, especially when calculating deep historical data.
Channel Logic: The strategy calculates a "Filtered True Range" to create High and Low bands around the main Gaussian line.
Long Entry: Price closes above the High Band.
Short Entry: Price closes below the Low Band.
2. Signal Filtering (Confluence)
To reduce false signals common in trend-following systems, the strategy employs a "confluence" approach using three additional layers:
Baseline Filter: A 200-period (customizable) EMA or SMA acts as a regime filter. Longs are only taken above the baseline; Shorts only below.
ADX Filter (Volatility): The Average Directional Index (ADX) is used to measure trend strength. If the ADX is below a user-defined threshold (default: 20), the market is considered "choppy," and new entries are blocked.
Momentum Check: A Stochastic RSI check ensures that momentum aligns with the breakout direction.
3. NEW: Intraday Session Filter
Per user requests, a time-based filter has been added to restrict trading activity to specific market sessions (e.g., the New York Open).
How it works: Users can toggle a checkbox to enable/disable the filter.
Configuration: You can define a specific time range (Default: 09:30 - 16:00) and a specific Timezone (Default: New York).
Logic: The strategy longCondition and shortCondition now check if the current bar's timestamp falls within this window. If outside the window, no new entries are generated, though existing trades are managed normally.
4. Risk Management
The strategy relies on volatility-based exits rather than fixed percentage stops:
ATR Stop Loss: A multiple of the Average True Range (ATR) is calculated at the moment of entry to set a dynamic Stop Loss.
ATR Take Profit: An optional Reward-to-Risk (RR) ratio can be set to place a Take Profit target relative to the Stop Loss distance.
Band Exit: If the trend reverses and price crosses the opposite band, the trade is closed immediately to prevent large drawdowns.
Credits & Attribution
Original Gaussian Logic: Developed by @DonovanWalll. This script utilizes his mathematical formula for the pole filters.
Strategy Wrapper & Array Refactor: Developed by @sebamarghella.
Community Request: The Intraday Session Filter was added to assist traders focusing on specific liquidity windows.
Disclaimer: This strategy is for educational purposes. Past performance is not indicative of future results. Please use the settings menu to adjust the Session Time and Risk parameters to fit your specific asset class.
Momentum Gamma StraddleExact definition of what that script does
1) Purpose
The script is a decision aid for intraday expiry-day ATM straddle trades. It detects intraday structure breakouts and signals candidate long straddle entries for Nifty or Sensex using price structure, volume, RSI momentum, and a user-supplied combined ATM premium value (CE + PE). It draws support/resistance, shows an info box, and raises alerts.
2) Inputs the user can change
Trading time window: startHour, startMin, endHour, endMin.
Structure lookback: res_lookback (how many candles to use to compute resistance/support).
Minimum candle body as fraction of candle range: min_body_pct.
Volume multiplier threshold: vol_mult (breakout candle volume must exceed vol_mult * sma5).
RSI length and thresholds: rsi_len, rsi_bull_thresh, rsi_bear_thresh.
Combined premium source: choose Manual or Symbol. If Manual, set manual_combined. If Symbol, provide a TradingView symbol that returns CE+PE combined ATM premium.
Combined premium acceptable band: min_combined_ok and max_combined_ok.
Profit target percent and SL percent (target_pct and sl_pct).
Misc pattern heuristics: min_res_hits (min tests of resistance inside lookback), low_slope_min (used to detect rising lows).
Micro-confirmation toggle, micro timeframe, nonrepaint option, show_entry_label toggle (in the later fixed versions some of these were added, but the earlier fixed script had basic combined_symbol options and a lookahead fallback).
3) Data calculated on each bar
Safety check hasEnough: true when bar_index >= res_lookback.
resistance: the highest high over res_lookback bars.
support: the lowest low over res_lookback bars.
res_hits: count of bars within lookback whose high is within a tolerance of resistance. Tolerance is 10 percent of the range between resistance and support.
low_slope: simple slope of lows over res_lookback bars.
body_pct: the candle body as a fraction of its high-low range. strong_body true when body_pct >= min_body_pct.
bull_breakout: true if hasEnough and current close > resistance and strong_body and res_hits >= min_res_hits.
bear_breakout: true if hasEnough and current close < support and strong_body and res_hits >= min_res_hits.
vol_sma5 and vol_ok: vol_ok true when current volume > vol_mult * vol_sma5.
rsi and rsi checks: rsi_bull_ok true if rsi >= rsi_bull_thresh; rsi_bear_ok true if rsi <= rsi_bear_thresh.
combined_premium: either the manual_combined input or the value read from combined_symbol via request.security. The script attempted a fallback to manual when the symbol was not valid.
combined_ok: true if combined_premium lies between min_combined_ok and max_combined_ok.
final signals: bull_signal when in_time_window and bull_breakout and vol_ok and rsi_bull_ok and combined_ok. bear_signal similar for bearish breakout.
4) Visual output and alerts
Plots resistance and support lines on the chart.
Plots a label shape "STRADDLE BUY" below the bar for bull_signal and above the bar for bear_signal.
Creates an info label (on last bar) that shows TimeOK, VolOK and vol ratio, RSI, Combined premium and whether it is OK, ResHits and LowSlope.
Sets two alertcondition events: "Bull Straddle BUY" and "Bear Straddle BUY" with a short candidate message. The alerts fire when the corresponding signal is true.
5) Execution assumptions you must follow manually
The script does not place any orders or compute option strike-level prices or greeks. It only flags candidate entry bars.
When combined_source is Manual you must type CE+PE yourself. The indicator will only accept the manual number and treat it as the combined premium.
When combined_source is Symbol the script uses request.security to read that symbol. For historical bars the indicator may repaint depending on lookahead settings. The earlier fixed script attempted to use request.security inside a conditional which leads to runtime or compile errors. You experienced that exact error.
6) Known implementation caveats and bugs you encountered
Pine typing issue with low_slope. The earlier version set low_slope = na without explicit type. That triggers the Pine error: "Value with NA type cannot be assigned to a variable that was defined without type keyword". This required changing to float low_slope = na.
The earlier version attempted to call request.security() inside an if block or conditional. Pine prohibits request.security in conditional blocks unless allowed patterns are followed. That produced the error you saw: "Cannot use request.* call within loops or conditional structures" or similar. The correct pattern is to call request.security at top-level and decide later which value to use.
If combined_symbol is invalid or not available on your TradingView subscription, request.security can return na and the script must fall back to manual value. The earlier fixed script attempted fallback but compiled errors prevented reliable behavior.
The earlier script did not include micro-confirmation or advanced nonrepaint controls. Those were added in later versions. Because of that, the earlier script may have given signals that appear to repaint on historical bars or may have thrown errors when using combined_symbol.
7) Decision logic summary (exact)
Only operate if current chart time is inside user set time window.
Only consider trade candidates when enough history exists for res_lookback.
Identify a resistance level as the highest high in the lookback. Count how many times that resistance was tested. Ensure the breakout candle has a strong body and volume spike. Ensure RSI is aligned with breakout direction.
Require combined ATM premium to be inside a user preferred band. If combined_symbol is used the script tries to read that value and use it; otherwise it uses manual_combined input.
If all the above conditions are true on a confirmed bar, the script plots a STRADDLE BUY label and triggers an alertcondition.
8) What the script does not do
It does not calculate CE and PE prices by strike. It only consumes or accepts combined premium number.
It does not compute greeks, IV, or OI. OI and IV checks must be done manually.
It does not manage positions. No SL management or automatic exits are executed by the script.
It does not simulate fills or account for bid/ask spreads or slippage.
It cannot detect off-exchange block trades or read exchange-level auction states beyond raw volume bars.
It may repaint historical labels if the combined_symbol was read with lookahead_on or the script used request.security in a way that repainted. The corrected final version uses nonrepaint options.
9) Manual checks you must always perform even when the script signals BUY
Confirm the live combined ATM premium and the bid/ask for CE and PE.
Check ATM IV and recent IV movement for a potential IV crush risk.
Check option OI distribution and recent OI changes for strike pinning or large player exposure.
Confirm CE and PE liquidity and depth. Wide spreads make fills unrealistic.
Confirm there is no scheduled news or auction within the next few minutes.
Confirm margin and position sizing fits your risk plan.
10) Quick testing checklist you can run now
Add the script to a 5-minute chart with combined_source = Manual.
Enter manual_combined equal to the real CE+PE at the moment you test.
Set startHour and endHour so the in_time_window is true for current time.
Look for STRADDLE BUY label on confirmed bars. Inspect the info box to see why it did or did not signal.
If you set combined_source = Symbol, verify the symbol exists and that TradingView returns values for it. If you previously saw the request.security error, that was caused by placing the request inside a conditional. The correct behavior is to call request.security unconditionally at top-level like in the final fixed version.
Momentum Reversal / Dip Buyer [Score Based]Strategy Overview
Momentum Reversal / Dip Buyer is a quantitative reversal engine designed to fade stretched moves and buy dips / sell rallies when multiple momentum and context factors line up. It’s built for liquid instruments especially for ticker CME_MINI:ES1! and works best on intraday timeframes like the 5-minute or 1-minute chart.
Core Logic
This strategy builds a composite Momentum Score by combining:
Price Location: Relative to 100 SMA, 1000 EMA, and VWAP (trend / regime filter).
RSI: Overbought/oversold and mid-zone strength.
VWMO (Volume-Weighted Momentum): Direction and strength of volume-weighted price drift.
ADX: Trend strength filter (high vs low trend environment).
Full Stoch (%K): Short-term exhaustion and mean-reversion context.
CCI: Overbought/oversold turns (key trigger).
MFI: Volume-confirmed buying/selling pressure.
ATR Regime: High vs low volatility environment.
Cumulative Delta: Whether net aggressor flow is rising or falling.
From this, a single Momentum Score is computed each bar:
Longs: Taken when the score is depressed (scoreLow) and CCI crosses up from oversold.
Shorts: Taken when the score is elevated (scoreHigh) and CCI crosses down from overbought.
Risk Management & Trade Logic
Max Daily Trades: Hard cap on entries per day.
Hard Stop: Fixed % stop based on entry price.
Profit Target: Target ATR Multiplier × main ATR from entry.
Breakeven Logic: Optional; moves stop to breakeven (plus optional offset) after price moves a configurable multiple of the main ATR in your favor.
Trailing Stop (Separate ATR): Optional; uses its own ATR length and ATR-based trigger and distance. This lets you run slower ATR for targets while using a tighter, more reactive ATR for the trail.
Session Control
Trading Window: Optional session filter (e.g., 09:30–16:00). Entries are only allowed inside the defined window.
Force Flat at Session End: Option to automatically close all open positions when the session ends.
Visuals
The script plots entry arrows and a compact dashboard displaying: current Momentum Score, daily trade usage, and CCI status.
Disclaimer:
This script is for educational and research purposes only and is not financial advice. Past performance does not guarantee future results. Always forward-test and adjust parameters to your own risk tolerance and market.
Shoutout and all credit goes to AuclairsCapital for building the base foundation of this strategy on ThinkScript
Analog Flow [KedArc Quant]Overview
AnalogFlow is an advanced analogue based market projection engine that reconstructs future price tendencies by matching current price behavior to historical analogues in the same instrument. Instead of using traditional indicators such as moving averages, RSI, or regression, AnalogFlow applies pattern vector similarity analysis - a data driven technique that identifies historically similar sequences and aggregates their subsequent movements into a smooth, forward looking curve.
Think of it as a market memory system:
If the current pattern looks like one we have seen before, how did price move afterward?
Why AnalogFlow Is Unique
1. Pattern centric - it does not rely on any standard indicator formula; it directly analyzes price movement vectors.
2. Adaptive - it learns from the same instrument's past behavior, making it self calibrating to volatility and regime shifts.
3. Non repainting - the projection is generated on the latest completed bar and remains fixed until new data is available.
4. Noise resistant - the EMA Blend engine smooths the projected trajectory, reducing random variance between analogues.
Inputs and Configuration
Pattern Bars
Number of bars in the reference pattern window: 40
Projection Bars
Number of bars forward to project: 30
Search Depth
Number of bars back to look for matching analogues: 600
Distance Metric
Comparison method: Euclidean, Manhattan, or Cosine (default Euclidean)
Matches
Number of top analogues to blend (1-5): Top 3
Build Mode
Projection type: Cumulative, MeanStep, or EMA Blend (default EMA Blend)
EMA Blend Length
Smoothness of the projected path: 15
Normalize Pattern
Enable Z score normalization for shape matching: true
Dissimilarity Mode
If true, finds inverse analogues for mean reversion analysis: false
Line Color and Width
Style settings for projection curve: Blue, width 2
How It Works with Past Data
1. The system builds a memory bank of patterns from the last N bars based on the scanDepth value.
2. It compares the latest Pattern Bars segment to each historical segment.
3. It selects the Top K most similar or dissimilar analogues.
4. For each analogue, it retrieves what happened after that pattern historically.
5. It averages or smooths those forward moves into a single composite forecast curve.
6. The forecast (blue line) is drawn ahead of the current candle using line.new with no repainting.
Output Explained
Blue Path
The weighted mean future trajectory based on historical analogues.
Smoother when EMA Blend mode is enabled.
Flat Section
Indicates low directional consensus or equilibrium across analogues.
Upward or Downward Slope
Represents historical tendency toward continuation or reversal following similar conditions.
Recommended Timeframes
Scalping / Short Term
1m - 5m : Short winLen (20-30), small ahead (10-15)
Swing Trading
15m - 1h : Balanced settings (winLen 40-60, ahead 20-30)
Positional / Multi Day
4h - 1D : Large windows (winLen 80-120, ahead 30-50)
Instrument Compatibility
Works seamlessly on:
Stocks and ETFs
Indices
Cryptocurrency
Commodities (Gold, Crude, etc.)
Futures and F&O (both intraday and positional)
Forex
No symbol specific calibration needed. It self adapts to volatility.
How Traders Can Use It
Forecast Context
Identify likely short term price path or drift direction.
Reversal Detection
Flip seekOpp to true for mean reversion pattern analysis.
Scenario Comparison
Observe whether the current regime tends to continue or stall.
Momentum Confirmation
Combine with trend tools such as EMA or MACD for directional bias.
Backtesting Support
Compare projected path versus realized price to evaluate reliability.
FAQ
Q1. Does AnalogFlow repaint?
No. It calculates only once per completed bar and projects forward. The future path remains static until a new bar closes.
Q2. Is it a neural network or AI model?
Not in the machine learning sense. It is a deterministic analogue matching engine using statistical distance metrics.
Q3. Why does the projection sometimes flatten?
That means similar historical setups had no clear consensus in direction (neutral expectation).
Q4. Can I use it for live trading signals?
AnalogFlow is not a signal generator. It provides probabilistic context for upcoming movement.
Q5. Does higher scanDepth improve accuracy?
Up to a point. More depth gives more analogues, but too much can dilute recency. Try 400 to 800.
Glossary
Analogue
A past pattern similar to the current price behavior.
Distance Metric
Mathematical formula for pattern similarity.
Step Vector
Difference between consecutive closing prices.
EMA Blend
Exponential smoothing of the projected path.
Cumulative Mode
Adds sequential historical deltas directly.
Z Score Normalization
Rescaling to mean 0 and variance 1 for shape comparison.
Summary
AnalogFlow converts the market's historical echoes into a structured, statistically weighted forward projection. It gives traders a contextual roadmap, not a signal, showing how similar past setups evolved and allowing better informed entries, exits, and scenario planning across all asset classes.
Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and proper risk management when applying this strategy.
Indian + Evening Session HighlighterThis indicator visually highlights two key trading windows for Indian instruments according to IST:
Indian Session: 9:00 AM to 11:30 PM IST is shaded light orange on the chart, representing the main domestic trading hours for stocks, indices, commodities, or derivatives.
Evening Session: 5:00 PM to 10:30 PM IST is shaded light red, marking the commonly followed evening window, which often captures the impact of US and European market movements.
The indicator automatically overlays these session backgrounds on your chart, helping you quickly identify when price action occurs during India’s core and evening trade windows. This allows traders to focus on strategies specific to these time intervals, identify session-based volatility, and avoid trading during less active periods. If the evening session overlaps with the Indian session, the colors are layered for visual clarity.
It is ideal for intraday traders, option strategists, and anyone monitoring Indian market rhythms or US-linked volatility impacts on Indian assets. No inputs are required; simply apply the script and view distinct session highlights for improved timing and decision making.
Hidden Impulse═══════════════════════════════════════════════════════════════════
HIDDEN IMPULSE - Multi-Timeframe Momentum Detection System
═══════════════════════════════════════════════════════════════════
OVERVIEW
Hidden Impulse is an advanced momentum oscillator that combines the Schaff Trend Cycle (STC) and Force Index into a comprehensive multi-timeframe trading system. Unlike standard implementations of these indicators, this script introduces three distinct trading setups with specific entry conditions, multi-timeframe confirmation, and trend filtering.
═══════════════════════════════════════════════════════════════════
ORIGINALITY & KEY FEATURES
This indicator is original in the following ways:
1. DUAL-TIMEFRAME STC ANALYSIS
Standard STC implementations work on a single timeframe. This script
simultaneously analyzes STC on both your trading timeframe and a higher
timeframe, providing trend context and filtering out low-probability signals.
2. FORCE INDEX INTEGRATION
The script combines STC with Force Index (volume-weighted price momentum)
to confirm the strength behind price moves. This combination helps identify
when momentum shifts are backed by genuine buying/selling pressure.
3. THREE DISTINCT TRADING SETUPS
Rather than generic overbought/oversold signals, the indicator provides
three specific, rule-based setups:
- Setup A: Classic trend-following entries with multi-timeframe confirmation
- Setup B: Divergence-based reversal entries (highest probability)
- Setup C: Mean-reversion bounce trades at extreme levels
4. INTELLIGENT FILTERING
All signals are filtered through:
- 50 EMA trend direction (prevents counter-trend trades)
- Higher timeframe STC alignment (ensures macro trend agreement)
- Force Index confirmation (validates volume support)
═══════════════════════════════════════════════════════════════════
HOW IT WORKS - TECHNICAL EXPLANATION
SCHAFF TREND CYCLE (STC) CALCULATION:
The STC is a cyclical oscillator that combines MACD concepts with stochastic
smoothing to create earlier and smoother trend signals.
Step 1: Calculate MACD
- Fast MA = EMA(close, Length1) — default 23
- Slow MA = EMA(close, Length2) — default 50
- MACD Line = Fast MA - Slow MA
Step 2: First Stochastic Smoothing
- Apply stochastic calculation to MACD
- Stoch1 = 100 × (MACD - Lowest(MACD, Smoothing)) / (Highest(MACD, Smoothing) - Lowest(MACD, Smoothing))
- Smooth result with EMA(Stoch1, Smoothing) — default 10
Step 3: Second Stochastic Smoothing
- Apply stochastic calculation again to the smoothed stochastic
- This creates the final STC value between 0-100
The dual stochastic smoothing makes STC more responsive than MACD while
being smoother than traditional stochastics.
FORCE INDEX CALCULATION:
Force Index measures the power behind price movements by incorporating volume:
Force Raw = (Close - Close ) × Volume
Force Index = EMA(Force Raw, Period) — default 13
Interpretation:
- Positive Force Index = Buying pressure (bulls in control)
- Negative Force Index = Selling pressure (bears in control)
- Force Index crossing zero = Momentum shift
- Divergences with price = Weakening momentum (reversal signal)
TREND FILTER:
A 50-period EMA serves as the trend filter:
- Price above EMA50 = Uptrend → Only LONG signals allowed
- Price below EMA50 = Downtrend → Only SHORT signals allowed
This prevents counter-trend trading which accounts for most losing trades.
═══════════════════════════════════════════════════════════════════
THE THREE TRADING SETUPS - DETAILED
SETUP A: CLASSIC MOMENTUM ENTRY
Concept: Enter when STC exits oversold/overbought zones with trend confirmation
LONG CONDITIONS:
1. Higher timeframe STC > 25 (macro trend is up)
2. Primary timeframe STC crosses above 25 (momentum turning up)
3. Force Index crosses above 0 OR already positive (volume confirms)
4. Price above 50 EMA (local trend is up)
SHORT CONDITIONS:
1. Higher timeframe STC < 75 (macro trend is down)
2. Primary timeframe STC crosses below 75 (momentum turning down)
3. Force Index crosses below 0 OR already negative (volume confirms)
4. Price below 50 EMA (local trend is down)
Best for: Trending markets, continuation trades
Win rate: Moderate (60-65%)
Risk/Reward: 1:2 to 1:3
───────────────────────────────────────────────────────────────────
SETUP B: DIVERGENCE REVERSAL (HIGHEST PROBABILITY)
Concept: Identify exhaustion points where price makes new extremes but
momentum (Force Index) fails to confirm
BULLISH DIVERGENCE:
1. Price makes a lower low (LL) over 10 bars
2. Force Index makes a higher low (HL) — refuses to follow price down
3. STC is below 25 (oversold condition)
Trigger: STC starts rising AND Force Index crosses above zero
BEARISH DIVERGENCE:
1. Price makes a higher high (HH) over 10 bars
2. Force Index makes a lower high (LH) — refuses to follow price up
3. STC is above 75 (overbought condition)
Trigger: STC starts falling AND Force Index crosses below zero
Why this works: Divergences signal that the current trend is losing steam.
When volume (Force Index) doesn't confirm new price extremes, a reversal
is likely.
Best for: Reversal trading, range-bound markets
Win rate: High (70-75%)
Risk/Reward: 1:3 to 1:5
───────────────────────────────────────────────────────────────────
SETUP C: QUICK BOUNCE AT EXTREMES
Concept: Catch rapid mean-reversion moves when price touches EMA50 in
extreme STC zones
LONG CONDITIONS:
1. Price touches 50 EMA from above (pullback in uptrend)
2. STC < 15 (extreme oversold)
3. Force Index > 0 (buyers stepping in)
SHORT CONDITIONS:
1. Price touches 50 EMA from below (pullback in downtrend)
2. STC > 85 (extreme overbought)
3. Force Index < 0 (sellers stepping in)
Best for: Scalping, quick mean-reversion trades
Win rate: Moderate (55-60%)
Risk/Reward: 1:1 to 1:2
Note: Use tighter stops and quick profit-taking
═══════════════════════════════════════════════════════════════════
HOW TO USE THE INDICATOR
STEP 1: CONFIGURE TIMEFRAMES
Primary Timeframe (STC - Primary Timeframe):
- Leave empty to use your current chart timeframe
- This is where you'll take trades
Higher Timeframe (STC - Higher Timeframe):
- Default: 30 minutes
- Recommended ratios:
* 5min chart → 30min higher TF
* 15min chart → 1H higher TF
* 1H chart → 4H higher TF
* Daily chart → Weekly higher TF
───────────────────────────────────────────────────────────────────
STEP 2: ADJUST STC PARAMETERS FOR YOUR MARKET
Default (23/50/10) works well for stocks and forex, but adjust for:
CRYPTO (volatile):
- Length 1: 15
- Length 2: 35
- Smoothing: 8
(Faster response for rapid price movements)
STOCKS (standard):
- Length 1: 23
- Length 2: 50
- Smoothing: 10
(Balanced settings)
FOREX MAJORS (slower):
- Length 1: 30
- Length 2: 60
- Smoothing: 12
(Filters out noise in 24/7 markets)
───────────────────────────────────────────────────────────────────
STEP 3: ENABLE YOUR PREFERRED SETUPS
Toggle setups based on your trading style:
Conservative Trader:
✓ Setup B (Divergence) — highest win rate
✗ Setup A (Classic) — only in strong trends
✗ Setup C (Bounce) — too aggressive
Trend Trader:
✓ Setup A (Classic) — primary signals
✓ Setup B (Divergence) — for entries on pullbacks
✗ Setup C (Bounce) — not suitable for trending
Scalper:
✓ Setup C (Bounce) — quick in-and-out
✓ Setup B (Divergence) — high probability scalps
✗ Setup A (Classic) — too slow
───────────────────────────────────────────────────────────────────
STEP 4: READ THE SIGNALS
ON THE CHART:
Labels appear when conditions are met:
Green labels:
- "LONG A" — Setup A long entry
- "LONG B DIV" — Setup B divergence long (best signal)
- "LONG C" — Setup C bounce long
Red labels:
- "SHORT A" — Setup A short entry
- "SHORT B DIV" — Setup B divergence short (best signal)
- "SHORT C" — Setup C bounce short
IN THE INDICATOR PANEL (bottom):
- Blue line = Primary timeframe STC
- Orange dots = Higher timeframe STC (optional)
- Green/Red bars = Force Index histogram
- Dashed lines at 25/75 = Entry/Exit zones
- Background shading = Oversold (green) / Overbought (red)
INFO TABLE (top-right corner):
Shows real-time status:
- STC values for both timeframes
- Force Index direction
- Price position vs EMA
- Current trend direction
- Active signal type
═══════════════════════════════════════════════════════════════════
TRADING STRATEGY & RISK MANAGEMENT
ENTRY RULES:
Priority ranking (best to worst):
1st: Setup B (Divergence) — wait for these
2nd: Setup A (Classic) — in confirmed trends only
3rd: Setup C (Bounce) — scalping only
Confirmation checklist before entry:
☑ Signal label appears on chart
☑ TREND in info table matches signal direction
☑ Higher timeframe STC aligned (check orange dots or table)
☑ Force Index confirming (check histogram color)
───────────────────────────────────────────────────────────────────
STOP LOSS PLACEMENT:
Setup A (Classic):
- LONG: Below recent swing low
- SHORT: Above recent swing high
- Typical: 1-2 ATR distance
Setup B (Divergence):
- LONG: Below the divergence low
- SHORT: Above the divergence high
- Typical: 0.5-1.5 ATR distance
Setup C (Bounce):
- LONG: 5-10 pips below EMA50
- SHORT: 5-10 pips above EMA50
- Typical: 0.3-0.8 ATR distance
───────────────────────────────────────────────────────────────────
TAKE PROFIT TARGETS:
Conservative approach:
- Exit when STC reaches opposite level
- LONG: Exit when STC > 75
- SHORT: Exit when STC < 25
Aggressive approach:
- Hold until opposite signal appears
- Trail stop as STC moves in your favor
Partial profits:
- Take 50% at 1:2 risk/reward
- Let remaining 50% run to target
───────────────────────────────────────────────────────────────────
WHAT TO AVOID:
❌ Trading Setup A in sideways/choppy markets
→ Wait for clear trend or use Setup B only
❌ Ignoring higher timeframe STC
→ Always check orange dots align with your direction
❌ Taking signals against the major trend
→ If weekly trend is down, be cautious with longs
❌ Overtrading Setup C
→ Maximum 2-3 bounce trades per session
❌ Trading during low volume periods
→ Force Index becomes unreliable
═══════════════════════════════════════════════════════════════════
ALERTS CONFIGURATION
The indicator includes 8 alert types:
Individual setup alerts:
- "Setup A - LONG" / "Setup A - SHORT"
- "Setup B - DIV LONG" / "Setup B - DIV SHORT" ⭐ recommended
- "Setup C - BOUNCE LONG" / "Setup C - BOUNCE SHORT"
Combined alerts:
- "ANY LONG" — fires on any long signal
- "ANY SHORT" — fires on any short signal
Recommended alert setup:
- Create "Setup B - DIV LONG" and "Setup B - DIV SHORT" alerts
- These are the highest probability signals
- Set "Once Per Bar Close" to avoid false alerts
═══════════════════════════════════════════════════════════════════
VISUALIZATION SETTINGS
Show Labels on Chart:
Toggle on/off the signal labels (green/red)
Disable for cleaner chart once you're familiar with the indicator
Show Higher TF STC:
Toggle the orange dots showing higher timeframe STC
Useful for visual confirmation of multi-timeframe alignment
Info Panel:
Cannot be disabled — always shows current status
Positioned top-right to avoid chart interference
═══════════════════════════════════════════════════════════════════
EXAMPLE TRADE WALKTHROUGH
SETUP B DIVERGENCE LONG EXAMPLE:
1. Market Context:
- Price in downtrend, below 50 EMA
- Multiple lower lows forming
- STC below 25 (oversold)
2. Divergence Formation:
- Price makes new low at $45.20
- Force Index refuses to make new low (higher low forms)
- This indicates selling pressure weakening
3. Signal Trigger:
- STC starts turning up
- Force Index crosses above zero
- Label appears: "LONG B DIV"
4. Trade Execution:
- Entry: $45.50 (current price at signal)
- Stop Loss: $44.80 (below divergence low)
- Target 1: $47.90 (STC reaches 75) — risk/reward 1:3.4
- Target 2: Opposite signal or trail stop
5. Trade Management:
- Price rallies to $47.20
- STC reaches 68 (approaching target zone)
- Take 50% profit, move stop to breakeven
- Exit remaining at $48.10 when STC crosses 75
Result: 3.7R gain
═══════════════════════════════════════════════════════════════════
ADVANCED TIPS
1. MULTI-TIMEFRAME CONFLUENCE
For highest probability trades, wait for:
- Primary TF signal
- Higher TF STC aligned (>25 for longs, <75 for shorts)
- Even higher TF trend in same direction (manual check)
2. VOLUME CONFIRMATION
Watch the Force Index histogram:
- Increasing bar size = Strengthening momentum
- Decreasing bar size = Weakening momentum
- Use this to gauge signal strength
3. AVOID THESE MARKET CONDITIONS
- Major news events (Force Index becomes erratic)
- Market open first 30 minutes (volatility spikes)
- Low liquidity instruments (Force Index unreliable)
- Extreme trending days (wait for pullbacks)
4. COMBINE WITH SUPPORT/RESISTANCE
Best signals occur near:
- Key horizontal levels
- Fibonacci retracements
- Previous day's high/low
- Psychological round numbers
5. SESSION AWARENESS
- Asia session: Use lower timeframes, Setup C works well
- London session: Setup A and B both effective
- New York session: All setups work, highest volume
═══════════════════════════════════════════════════════════════════
INDICATOR WINDOWS LAYOUT
MAIN CHART:
- Price action
- 50 EMA (green/red)
- Signal labels
- Info panel
INDICATOR WINDOW:
- STC oscillator (blue line, 0-100 scale)
- Higher TF STC (orange dots, optional)
- Force Index histogram (green/red bars)
- Reference levels (25, 50, 75)
- Background zones (green oversold, red overbought)
═══════════════════════════════════════════════════════════════════
PERFORMANCE OPTIMIZATION
For best results:
Backtesting:
- Test on your specific instrument and timeframe
- Adjust STC parameters if win rate < 55%
- Record which setup works best for your market
Position Sizing:
- Risk 1-2% per trade
- Setup B can use 2% risk (higher win rate)
- Setup C should use 1% risk (lower win rate)
Trade Frequency:
- Setup B: 2-5 signals per week (be patient)
- Setup A: 5-10 signals per week
- Setup C: 10+ signals per week (scalping)
═══════════════════════════════════════════════════════════════════
CREDITS & REFERENCES
This indicator builds upon established technical analysis concepts:
Schaff Trend Cycle:
- Developed by Doug Schaff (1996)
- Original concept published in Technical Analysis of Stocks & Commodities
- Implementation based on standard STC formula
Force Index:
- Developed by Dr. Alexander Elder
- Described in "Trading for a Living" (1993)
- Classic volume-momentum indicator
The multi-timeframe integration, three-setup system, and specific
entry conditions are original contributions of this indicator.
═══════════════════════════════════════════════════════════════════
DISCLAIMER
This indicator is a technical analysis tool and does not guarantee profits.
Past performance is not indicative of future results. Always:
- Use proper risk management
- Test on demo account first
- Combine with fundamental analysis
- Never risk more than you can afford to lose
═══════════════════════════════════════════════════════════════════
SUPPORT & QUESTIONS
If you find this indicator helpful, please:
- Leave a like and comment
- Share your feedback and results
- Report any bugs or issues
For questions about usage or optimization for specific markets,
feel free to comment below.
═════════════════════════════════════════════════════════════
Dynamic Volume Trace Profile [ChartPrime]⯁ OVERVIEW
Dynamic Volume Trace Profile is a reimagined take on volume profile analysis. Instead of plotting a static horizontal histogram on the side of your chart, this indicator projects dynamic volume trace lines directly onto the price action. Each bin is color-graded according to its relative strength, creating a living “volume skeleton” of the market. The orange trace highlights the current Point of Control (POC)—the price level with maximum historical traded volume within the lookback window. On the right side, the tool builds a mini profile, showing absolute volume per bin alongside its percentage share, where the POC always represents 100% strength .
⯁ KEY FEATURES
Dynamic On-Chart Bins:
The range between highest high and lowest low is split into 25 bins. Each bin is drawn as a horizontal trace line across the lookback chart period.
Gradient Color Encoding:
Trace lines fade from transparent to teal depending on relative volume size. The more intense the teal, the stronger the historical traded activity at that level.
Automatic POC Highlight:
The bin with the highest aggregated volume is flagged with an orange line . This POC adapts bar-by-bar as volume distribution shifts.
Right-Side Volume Profile:
At the chart’s right edge, the script prints a box-style profile. Each bin shows:
• Total volume (absolute units).
• Percentage of max volume, in parentheses (POC bin = 100%).
This gives both raw and normalized context at a glance.
Adjustable Lookback Window:
The lookback defines how many bars feed the profile. Increase for stable HTF zones or decrease for responsive intraday distributions.
POC Toggle & Styling:
Optionally toggle POC highlighting on/off, adjust colors, and set line thickness for better integration with your chart theme.
⯁ HOW IT WORKS (UNDER THE HOOD)
Step Sizing:
over last 100 bars is divided by to calculate bin height.
Volume Aggregation:
For each bar in the , the script checks which bin the close falls into, then adds that bar’s volume to the bin’s counter.
Gradient Mapping:
Bin volume is normalized against the max volume across all bins. That value is mapped onto a gradient from transparent → teal.
POC Logic:
The bin with highest volume is colored orange both on the dynamic trace and in the right-side profile.
Right-Hand Profile:
Boxes are drawn for each bin proportional to volume / maxVolume × 50 units, with text labels showing both absolute volume and normalized %.
⯁ USAGE
Use the orange trace as the dominant “magnet” level—price often gravitates to the POC.
Watch for clusters of strong teal traces as areas of high acceptance; thin or faint zones mark low-liquidity gaps prone to fast moves.
On intraday charts, tighten lookback to reveal session-based distributions . For swing or position trading, expand lookback to surface more durable volume shelves.
Compare the right-side profile % to judge how “top-heavy” or “bottom-heavy” the current distribution is.
Use bright, intense color traces as context for confluence with structure, OBs, or liquidity hunts.
⯁ CONCLUSION
Dynamic Volume Trace Profile takes the traditional volume profile and fuses it into the body of price itself. Instead of a fixed sidebar, you see gradient traces layered directly on the chart, giving real-time context of where volume concentrated and where price may be drawn. With built-in POC highlighting, normalized % readouts, and an adaptive right-side profile, it offers both precision levels and market structure awareness in a cleaner, more intuitive form.
Momentum Volume Analyzer [CHE] Momentum Volume Analyzer — Adaptive momentum with volume-gated signals and expressive visual cues
Summary
This indicator combines a normalized momentum oscillator with a volume Z-score gate and adaptive gradient visuals. The oscillator centers around a midline and scales between a lower and an upper bound. Intensity is derived from the distance to the midline and is normalized inside a rolling window, which helps keep contrast consistent across regimes. Volume pressure is compressed to a discrete level between one and ten and is used to qualify momentum flips and extremes. Layered “burst” markers and optional background gradients provide immediate visual emphasis without adding new data sources. Pine version is v6. The script runs in a separate pane.
Motivation: Why this design?
Common oscillators flip rapidly during noisy conditions or flatten during calm periods, which obscures actionable shifts. A rolling normalization keeps the visual intensity stable across different regimes, and a volume gate reduces reactions when participation is weak. The goal is clearer momentum shifts that are supported by measurable activity rather than cosmetic smoothing alone.
What’s different vs. standard approaches?
Baseline reference: Classical RSI-style oscillators or simple filtered momentum without volume gating.
Architecture differences:
Local window normalization with gamma control for contrast.
Volume converted to a Z-score and compressed into a discrete level between one and ten with a configurable cap.
Directional color gradients that intensify with distance from the midline.
Layered glow markers with optional trail and an internal label budget to avoid UI overload.
Practical effect: Signals are visually stronger only when both momentum and volume align; background and line colors convey regime strength at a glance.
How it works (technical)
Momentum core: A high-pass path with automatic gain control produces a bounded oscillator centered around a midline. A simple moving average smooths the result over a short window.
Normalization and contrast: The absolute distance from the midline is scaled inside a rolling window and limited between zero and one. Two gamma parameters separately shape contrast for the line and for labels.
Coloring: When the oscillator is above the midline, a green gradient is used; below the midline, a red gradient is used. Intensity increases with normalized distance. Optional area fill to the midline and a background gradient reinforce strength.
Volume levels: Volume is standardized over a lookback window, clipped by a user cap, and mapped to a level between one and ten. Only positive excursions are considered; non-positive values map to zero.
Event markers: When the oscillator reaches extreme zones and the volume level is positive, the script spawns layered circular labels at fixed y-positions. A small trail can extend behind the event. An internal queue discards the oldest labels when a user-defined maximum is exceeded.
Alerts: Alerts fire on overbought and oversold spikes, midline shifts with minimum intensity and volume, and continuation patterns inside strong zones.
Parameter Guide
TFRSI length (default six): Core momentum lookback. Shorter values react faster but are less stable.
Signal SMA (default two): Light smoothing of the oscillator. Larger values reduce jitter.
Gradient window (default one hundred): Normalization window for intensity. Longer values produce steadier contrast but slower adaptation.
Line/marker transparency (default zero): Visual prominence of drawings. Higher values reduce dominance.
Background on and BG transparency (defaults true and eighty-five): Enables and tunes the pane background gradient.
Area fill to fifty and Fill transparency (defaults true and eighty): Fills between the oscillator and the midline.
Gamma bars/labels and Gamma plot (defaults zero point seven and zero point eight): Contrast shapers for markers and line. Higher values compress low intensities.
Bottom marker and Show last N (defaults true and three hundred thirty-three): Optional compact heat markers with a display cap.
Up/Down colors: Dark and neon pairs for positive and negative regimes.
Lookback (default two hundred) and Z cap (default five): Volume standardization window and clipping level before scaling to one through ten.
Enable bursts, Layers, Trail, Trail transparency, Max live labels, Size scale: Control the layered glow effect, trail length, opacity, label budget, and size multiplier. Reducing the size scale lowers visual dominance.
Spike min level, Shift min level, Min intensity, Rise/Fall length: Gates for alerts; adjust to balance sensitivity and false positives.
Reading & Interpretation
Line color and intensity: Green shades above the midline indicate bullish pressure; red shades below indicate bearish pressure. Stronger color corresponds to stronger normalized distance.
Background and fill: Reinforce regime strength; consider reducing transparency when the pane feels too busy.
Bursts and trails: Emphasize volume-backed extremes. Larger bursts reflect stronger volume levels or scaling choices.
Volume level: Internal level between one and ten. Levels near the upper bound signal exceptional activity.
Practical Workflows & Combinations
Trend following: Use midline cross upward with minimum shift level and intensity as a trigger. Confirm with structure such as higher highs and higher lows. For shorts, reverse the conditions.
Exits and risk: Fade exposure when intensity weakens toward the midline or when volume level drops below the shift threshold. Consider disabling bursts when monitoring many symbols.
Multi-asset and multi-timeframe: Defaults are designed to travel across liquid futures, large-cap equities, and major crypto pairs. For higher timeframes, increase the lookback window and consider reducing the Z cap.
Behavior, Constraints & Performance
Repaint and confirmation: Signals are evaluated on the live bar. They can appear and withdraw before bar close. For confirmed signals, require closed-bar alerts or manual confirmation.
Higher-timeframe sources: Not used. No `security` calls.
Resources: `max_bars_back` is two thousand. The script uses arrays and label objects, including loops for trails. The label budget mitigates clutter.
Known limits: Very illiquid symbols with unstable volume can reduce the usefulness of the Z-score. Sharp regime changes can still produce brief flips.
Sensible Defaults & Quick Tuning
Starting point: TFRSI length six, Signal two, Gradient window one hundred, Z cap five, Spike level six, Shift level four, Min intensity zero point four, Rise length three, Size scale zero point five.
Too many flips: Increase Signal, increase Gradient window, or raise Shift level.
Too sluggish: Decrease TFRSI length or reduce Gradient window.
Bursts too dominant: Lower Size scale or reduce Layers; increase Trail transparency or set Trail length to zero.
What this indicator is—and isn’t
This is a visualization and signal layer that couples momentum with a volume gate and adaptive visuals. It is not a complete trading system, optimizer, or predictor. Use it together with market structure, risk controls, and position management.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino
ICT Silver Bullet Zones (All Sessions, Custom Labels)CT Silver Bullet Zones
This indicator is designed for traders who follow the ICT *Silver Bullet* concept.
It automatically marks the **Silver Bullet window** (10:00–11:00 by default) across the **London, New York AM, New York PM, and Asia sessions**, with customizable settings for each session.
### Features:
* Separate adjustable time windows for **London, NY AM, NY PM, and Asia Silver Bullet sessions**.
* Colored session boxes with individual **opacity controls**.
* **Session labels placed at the top** of each zone, with customizable text size, color, and background opacity.
* Works on all timeframes and highlights only the Silver Bullet trading windows.
This tool is meant to help traders quickly identify ICT Silver Bullet opportunities in all major sessions without manual plotting.
Bias + VWAP Pullback — v4 (PA + BOS/CHOCH)Simple idea: I identify the trend (bias) from the larger timeframe, and only trade pullbacks to the VWAP/EMA during liquidity (London/New York). When the trend is clear, gold moves strongly, and its pullbacks to the balance lines provide clear opportunities.
Timeframe and Sessions (Cairo Time)
Analysis: H1 to determine the trend.
Implementation: 5m (or 1m if professional).
Trading window:
London Opening: 10:00–12:30
New York Opening: 16:30–19:00
(avoid the rest of the day unless there is exceptional traffic).
Direction determination (BIAS)
On H1:
If the price is above the 200 EMA and the daily VWAP is bullish and the price is above it → uptrend (long-only).
If the price is below the 200 EMA and the daily VWAP is bearish and the price is below it → bearish trend (short-only).
Determine your levels: yesterday's high/low (PDH/PDL) + approximate Asia range (03:00–09:30).
Entry Rules (Setup A: Trend Continuation)
Asia range breakout towards Bias during liquidity window.
Wait for a withdrawal to:
Daily VWAP, or
EMA50 on 5m frame (best if both cross).
Confirmation: Confirmation low/high on 5m (HL buy/LH sell) + clear impulse candle (Body is greater than average of last 10 candles).
Entry:
Buy: When the price returns above VWAP/EMA50 with a confirmation candle close.
Sell: The exact opposite.
Stop Loss (SL): Below/above the last confirmation low/high or ATR(14, 5m) x 1.5 (largest).
Objectives:
TP1 = 1R (Close 50% and move the rest Break-even).
TP2 = 2.5R to 3R or at an important HTF level (PDH/PDL/Bid/Demand Zone).
Entry Rules (Setup B: Reversion to VWAP – “Mean Reversion”)
Use with extreme caution, once daily maximum:
Price deviation from VWAP by more than ~1.5 x ATR(14, 5m) with rejection candles appearing near PDH/PDL.
Reverse entry towards the return of VWAP.
SL small behind rejection top/bottom.
Main target: VWAP. (Don't get greedy — this scenario is for extended periods only.)
News Filtering and Risk Management
Avoid trading 15–30 minutes before/after strong US news (CPI, NFP, FOMC).
Maximum daily loss: 1.5–2% of account balance.
Risk per trade: 0.25–0.5% (if you are learning) or 0.5–1% (if you are experienced).
Do not exceed two consecutive losing trades per day.
Don't chase the market after the opportunity has passed — wait for the next pullback.
Smart Deal Management
After TP1: Move stop to entry point + trail the rest with EMA20 on 5m or ATR Trailing = ATR(14)×1.0.
If the price touches a strong daily level (PDH/PDL) and fails to break, consider taking additional profit.
If VWAP starts to flatten and breaks against the trend on H1, stop trading for the day.
Quick Checklist (Before Entry)
H1 trend is clear and consistent with 200EMA + VWAP.
Penetrating the Asia range towards Bias.
Clean pull to VWAP/EMA50 on 5m.
Confirmation candle and real push.
SL is logical (behind swing/ATR×1.5) and R :R ≥ 1:2.
No red news coming soon.
Example of "ready-made" settings
EMA: 20, 50, 200 on 5m, 200 only on H1.
VWAP: Daily (reset daily).
ATR: 14 on 5m.
Levels: PDH/PDL + Asia Band (03:00–09:30 Cairo).
Gold Notes
Gold is fast and sharp at the open; don't get in early — wait for the draw.
Fakeouts are common before news: it is best to call with the trend after the price returns above/below VWAP.
Don't expect 80% consistent wins every day — the advantage comes from discipline, filtering out bad days, and only withdrawing when you're on the right track.
تعتبر شركة الماسة الألمانية أحد المؤسسات العاملة بالمملكة العربية السعودية ولها تاريخ طويل من الخدمات الكثيرة والمتنوعة التى مازالت تقدمها للكثير من العملاء داخل جميع مدن وأحياء المملكة حيث نقدم أفضل ما لدينا من خلال مجموعة الشركات التالية والتي من خلالها ستتلقي كل ما تحتاج إلية في كل المجال المختلفة فنحن نعمل منذ عام 2015 ولنا سابقات اعمال فى مختلف المجالات الحيوية التى نخدم من خلالها عملائنا ونوفر لهم أرخص الأسعار وبأعلى جودة من الممكن توفرها فى المجالات التالية :-
خدمات تنظيف المنازل والفلل والشقق
خدمات عزل الخزانات تنظيف غسيل صيانة اصلاح
خدمات جلي البلاط والرخام والسيراميك
خدمات نقل العفش عمالة فلبينية مدربة
خدمات مكافحة الحشرات بجدة
كل هذة الخدمات وأكثر نوفرها لكل المتعاقدين بأفضل الطرق مع توفير خطط وبرامج متنوعة لأتمام العمل المسنود إلينا بأفضل وأحدث الطرق الحديثة والعصرية سواء فى شركات النظافة بجدة ومكة المكرمة أو شركات نقل العفش بجدة عمالة فلبينية وباقى الخدمات مثل جلي وتلميع الرخام بمكة وجدة ولا ننسي شركة مكافحة حشرات بجدة التى ساعدت آلاف المواطنين على تنظيف منازلهم من الحشرات بأفضل مبيدات حشرية.
Benford's Law Actual [Tagstrading]Benford’s Law Chart — First Digit Analysis of Percentage Price Drops
This script visualizes the distribution of the leading digit in the percentage change of price drops, and compares it to the theoretical distribution expected by Benford’s Law.
It helps traders, analysts, and quants to detect anomalies, unnatural behavior, or price manipulation in any asset or timeframe.
How to Use
Add to any chart or symbol (stocks, crypto, FX, etc.) and select the timeframe you wish to analyze.
Set the “Number of Bars to Analyze” input (default: 500) to control the length of the historical window.
The chart will display, for the latest window:
A blue line: the actual leading-digit distribution for percentage price changes between bars.
A red line: the expected distribution per Benford’s Law.
Labels below and above: digit markers and the expected (theoretical) percentages.
Summary panel on the right: frequency counts and actual vs. theoretical % for each digit.
Interpretation:
If your actual (blue) curve or digit counts are significantly different from the red Benford’s Law curve, it could indicate unnatural price action, fraud, bot activity, or structural anomalies.
Why is this useful for TradingView?
Financial forensics: Benford’s Law is a classic tool for detecting data manipulation and fraud in accounting. On charts, it can reveal if price movements are statistically “natural.”
Transparency and confidence: Helps communities audit markets, brokers, or exchanges for irregularities.
Adaptable: Works on any market, any timeframe.
What makes this script unique?
Focuses on % price changes, not raw prices.
This provides a fair comparison across assets, symbols, and timeframes.
Measures only the direction and magnitude of drops/rises — more suitable for detecting manipulation in active markets.
Clear and customizable visualization:
The Benford line, actual data, and summary are all visible and readable in one glance.
Optimized for speed and clarity (runs efficiently on all major charts).
How is it different from stg44’s Benford’s Law script?
This script analyzes the leading digit of percentage price changes (i.e., how much the price drops or rises in %),
while the original by stg44 analyzes the leading digit of price itself.
Results are less sensitive to price scale and more comparable across volatile and non-volatile assets.
The summary panel clearly shows ( ) for actual and for Benford theoretical values.
Full code is commented and open for the community.
Credits and Inspiration
This script was inspired by “Benford’s Law” by stg44:
Thanks to the TradingView community for sharing powerful visual ideas.
—
By tags trading
