Faytterro Bands Breakout📌 Faytterro Bands Breakout 📌
This indicator was created as a strategy showcase for another script: Faytterro Bands
It’s meant to demonstrate a simple breakout strategy based on Faytterro Bands logic and includes performance tracking.
❓ What Is It?
This script is a visual breakout strategy based on a custom moving average and dynamic deviation bands, similar in concept to Bollinger Bands but with unique smoothing (centered regression) and performance features.
🔍 What Does It Do?
Detects breakouts above or below the Faytterro Band.
Plots visual trade entries and exits.
Labels each trade with percentage return.
Draws profit/loss lines for every trade.
Shows cumulative performance (compounded return).
Displays key metrics in the top-right corner:
Total Return
Win Rate
Total Trades
Number of Wins / Losses
🛠 How Does It Work?
Bullish Breakout: When price crosses above the upper band and stays above the midline.
Bearish Breakout: When price crosses below the lower band and stays below the midline.
Each trade is held until breakout invalidation, not a fixed TP/SL.
Trades are compounded, i.e., profits stack up realistically over time.
📈 Best Use Cases:
For traders who want to experiment with breakout strategies.
For visual learners who want to study past breakouts with performance metrics.
As a template to develop your own logic on top of Faytterro Bands.
⚠ Notes:
This is a strategy-like visual indicator, not an automated backtest.
It doesn't use strategy.* commands, so you can still use alerts and visuals.
You can tweak the logic to create your own backtest-ready strategy.
Unlike the original Faytterro Bands, this script does not repaint and is fully stable on closed candles.
ความผันผวน
Frahm Factor Position Size CalculatorThe Frahm Factor Position Size Calculator is a powerful evolution of the original Frahm Factor script, leveraging its volatility analysis to dynamically adjust trading risk. This Pine Script for TradingView uses the Frahm Factor’s volatility score (1-10) to set risk percentages (1.75% to 5%) for both Margin-Based and Equity-Based position sizing. A compact table on the main chart displays Risk per Trade, Frahm Factor, and Average Candle Size, making it an essential tool for traders aligning risk with market conditions.
Calculates a volatility score (1-10) using true range percentile rank over a customizable look-back window (default 24 hours).
Dynamically sets risk percentage based on volatility:
Low volatility (score ≤ 3): 5% risk for bolder trades.
High volatility (score ≥ 8): 1.75% risk for caution.
Medium volatility (score 4-7): Smoothly interpolated (e.g., 4 → 4.3%, 5 → 3.6%).
Adjustable sensitivity via Frahm Scale Multiplier (default 9) for tailored volatility response.
Position Sizing:
Margin-Based: Risk as a percentage of total margin (e.g., $175 for 1.75% of $10,000 at high volatility).
Equity-Based: Risk as a percentage of (equity - minimum balance) (e.g., $175 for 1.75% of ($15,000 - $5,000)).
Compact 1-3 row table shows:
Risk per Trade with Frahm score (e.g., “$175.00 (Frahm: 8)”).
Frahm Factor (e.g., “Frahm Factor: 8”).
Average Candle Size (e.g., “Avg Candle: 50 t”).
Toggles to show/hide Frahm Factor and Average Candle Size rows, with no empty backgrounds.
Four sizes: XL (18x7, large text), L (13x6, normal), M (9x5, small, default), S (8x4, tiny).
Repositionable (9 positions, default: top-right).
Customizable cell color, text color, and transparency.
Set Frahm Factor:
Frahm Window (hrs): Pick how far back to measure volatility (e.g., 24 hours). Shorter for fast markets, longer for chill ones.
Frahm Scale Multiplier: Set sensitivity (1-10, default 9). Higher makes the score jumpier; lower smooths it out.
Set Margin-Based:
Total Margin: Enter your account balance (e.g., $10,000). Risk auto-adjusts via Frahm Factor.
Set Equity-Based:
Total Equity: Enter your total account balance (e.g., $15,000).
Minimum Balance: Set to the lowest your account can go before liquidation (e.g., $5,000). Risk is based on the difference, auto-adjusted by Frahm Factor.
Customize Display:
Calculation Method: Pick Margin-Based or Equity-Based.
Table Position: Choose where the table sits (e.g., top_right).
Table Size: Select XL, L, M, or S (default M, small text).
Table Cell Color: Set background color (default blue).
Table Text Color: Set text color (default white).
Table Cell Transparency: Adjust transparency (0 = solid, 100 = invisible, default 80).
Show Frahm Factor & Show Avg Candle Size: Check to show these rows, uncheck to hide (default on).
Machine Learning Key Levels [AlgoAlpha]🟠 OVERVIEW
This script plots Machine Learning Key Levels on your chart by detecting historical pivot points and grouping them using agglomerative clustering to highlight price levels with the most past reactions. It combines a pivot detection, hierarchical clustering logic, and an optional silhouette method to automatically select the optimal number of key levels, giving you an adaptive way to visualize price zones where activity concentrated over time.
🟠 CONCEPTS
Agglomerative clustering is a bottom-up method that starts by treating each pivot as its own cluster, then repeatedly merges the two closest clusters based on the average distance between their members until only the desired number of clusters remain. This process creates a hierarchy of groupings that can flexibly describe patterns in how price reacts around certain levels. This offers an advantage over K-means clustering, since the number of clusters does not need to be predefined. In this script, it uses an average linkage approach, where distance between clusters is computed as the average pairwise distance of all contained points.
The script finds pivot highs and lows over a set lookback period and saves them in a buffer controlled by the Pivot Memory setting. When there are at least two pivots, it groups them using agglomerative clustering: it starts with each pivot as its own group and keeps merging the closest pairs based on their average distance until the desired number of clusters is left. This number can be fixed or chosen automatically with the silhouette method, which checks how well each point fits in its cluster compared to others (higher scores mean cleaner separation). Once clustering finishes, the script takes the average price of each cluster to create key levels, sorts them, and draws horizontal lines with labels and colors showing their strength. A metrics table can also display details about the clusters to help you understand how the levels were calculated.
🟠 FEATURES
Agglomerative clustering engine with average linkage to merge pivots into level groups.
Dynamic lines showing each cluster’s price level for clarity.
Labels indicating level strength either as percent of all pivots or raw counts.
A metrics table displaying pivot count, cluster count, silhouette score, and cluster size data.
Optional silhouette-based auto-selection of cluster count to adaptively find the best fit.
🟠 USAGE
Add the indicator to any chart. Choose how far back to detect pivots using Pivot Length and set Pivot Memory to control how many are kept for clustering (more pivots give smoother levels but can slow performance). If you want the script to pick the number of levels automatically, enable Auto No. Levels ; otherwise, set Number of Levels . The colored horizontal lines represent the calculated key levels, and circles show where pivots occurred colored by which cluster they belong to. The labels beside each level indicate its strength, so you can see which levels are supported by more pivots. If Show Metrics Table is enabled, you will see statistics about the clustering in the corner you selected. Use this tool to spot areas where price often reacts and to plan entries or exits around levels that have been significant over time. Adjust settings to better match volatility and history depth of your instrument.
Alpha Trader University - London Continuation StrategyAlpha Trader University - London Continuation Strategy Indicator
OVERVIEW:
This educational indicator implements the London Continuation Strategy, a session-based trading methodology that capitalizes on price continuation patterns between the Asia and London trading sessions. Designed to teach traders about session timing, market structure, and continuation strategies.
STRATEGY METHODOLOGY:
The London Continuation Strategy is based on the market principle that directional movements established during the Asia session often continue during the early London session, creating high-probability trading opportunities.
SESSION ANALYSIS FRAMEWORK:
1. ASIA SESSION (4:00-9:00 Dubai Time):
- Establishes initial market direction and sentiment
- Creates key support and resistance levels
- Provides the foundation for continuation bias
- Blue box visualization with range tracking
2. PRE-LONDON SESSION (9:00-11:00 Dubai Time):
- Transition period between major sessions
- Setup and preparation phase for London entries
- Confirmation or negation of Asia session bias
- Teal box visualization for monitoring
3. LONDON SESSION (11:00-12:00 Dubai Time):
- Primary entry window for continuation trades
- Highest probability period for strategy execution
- Green box labeled "Entry Window" for clear identification
- Optimal timing for trade execution
EDUCATIONAL VALUE:
- Learn session-based trading concepts and timing
- Understand market flow between major trading centers
- Develop skills in identifying continuation patterns
- Practice using session ranges for risk management
- Build foundation for advanced session strategies
TRADING APPLICATIONS:
- Entry Timing: Use London session start for optimal entry points
- Direction Bias: Follow Asia session directional momentum
- Risk Management: Utilize session ranges for stop-loss placement
- Target Setting: Project targets based on session volatility patterns
- Market Structure: Respect key session levels and range breaks
UNIQUE FEATURES:
- Dubai timezone optimization for Middle East traders
- Three-session comprehensive analysis framework
- Real-time session range tracking and visualization
- Customizable visual elements and colors
- Educational labels and clear entry window identification
TECHNICAL IMPLEMENTATION:
- Accurate timezone conversion (UTC to Dubai time)
- Dynamic session detection and range calculation
- Real-time box and label updates during active sessions
- Clean visual design with professional color coding
- Efficient memory management for optimal performance
CUSTOMIZATION OPTIONS:
- Session colors for personal preference
- Box border width adjustment
- Label size customization
- Visual element toggle capabilities
RISK MANAGEMENT INTEGRATION:
- Session range-based stop-loss guidance
- Volatility assessment through range analysis
- Clear entry and exit timing signals
- Structure-based risk parameter definition
This indicator transforms complex session analysis into a systematic, visual trading approach, helping traders understand market timing and develop disciplined continuation strategies.
EDUCATIONAL DISCLAIMER: This indicator is designed for educational purposes and strategy development. It should be used as part of a comprehensive trading plan with proper risk management. Past performance of any strategy does not guarantee future results. Always practice proper risk management and consider market conditions before trading.
Volume & Distance IndicatorA comprehensive multi-metric indicator that combines volume analysis, volatility measurement, and momentum positioning to provide crucial trading insights in a clean, customizable table format.
📊 Key Metrics:
52WH (52-Week High Distance) - Shows percentage distance from 52-week high, helping identify momentum and potential reversal zones.
Vol Val (Volume Value) - Calculates current close × SMA of volume, providing dollar-weighted volume analysis for institutional activity insights.
ADR (Average Daily Range) - Measures average volatility using SMA of High/Low ratios, essential for position sizing and risk management.
⚙️ Features: • Customizable periods (20 or 50 days) for Volume and ADR calculations • Enable/disable individual metrics • Fully customizable colors for labels and values • Adjustable text size (Tiny/Small/Normal/Large) • 9 table position options • Smart alert system with color-coded warnings
🚨 Alert System: • Red background when ADR < 3% (low volatility warning) • Red background when 52WH < -25% (oversold condition) • Customizable thresholds for personalized risk management
💡 Use Cases:
Identify low-volatility breakout setups
Monitor institutional volume participation
Track momentum relative to recent highs
Set position sizing based on volatility metrics
Settings are fully customizable - choose your preferred periods, colors, and alert levels. Perfect for swing traders, day traders, and investors who rely on volume and volatility analysis.
Works on all timeframes and asset classes.
This description highlights the indicator's professional features while explaining its practical trading applications for TradingView users.
Alpha Trader University - Average Session VolatilityAlpha Trader University - Average Session Volatility Indicator
OVERVIEW:
This educational indicator calculates and displays the average volatility (price range) of the New York trading session over a customizable lookback period. Designed to help traders understand typical market movement patterns and make informed risk management decisions.
METHODOLOGY:
The indicator employs a systematic approach to volatility measurement:
1. SESSION IDENTIFICATION:
- Automatically detects New York trading session boundaries
- Default timing: 13:30-20:30 UTC (19:00-02:00 IST)
- Customizable session times for different markets or preferences
- Accurate timezone handling for global trading
2. RANGE CALCULATION:
- Records high-low range for each completed session
- Maintains rolling database of recent session ranges
- Calculates statistical average over specified lookback period
- Real-time tracking of current session development
3. VOLATILITY ANALYSIS:
- Orange line: Average session volatility over past sessions
- Blue dots: Current session range development
- Comparative analysis between current and historical volatility
EDUCATIONAL VALUE:
- Learn to assess market volatility objectively
- Understand the importance of volatility in trading decisions
- Develop skills in risk management and position sizing
- Build foundation for volatility-based trading strategies
TRADING APPLICATIONS:
- Position Sizing: Adjust trade size based on expected volatility
- Risk Management: Set appropriate stop-loss levels using average range
- Profit Targets: Align target expectations with typical session movement
- Market Timing: Identify high/low volatility periods for strategy selection
- Session Analysis: Compare different trading sessions' characteristics
UNIQUE FEATURES:
- Customizable session times and lookback periods
- Real-time current session tracking
- Statistical approach using rolling averages
- Clean visual representation with dual-line display
- Educational tooltips explaining each parameter
SETTINGS:
- Session Times: Fully customizable start/end hours and minutes
- Lookback Period: Adjustable number of sessions for average calculation (1-50)
- Visual Options: Toggle between different display modes
- Timezone Support: UTC-based calculations for global accuracy
PRACTICAL APPLICATIONS:
- Forex Trading: Optimize for major session overlaps
- Stock Trading: Adapt for market hours in different regions
- Cryptocurrency: 24/7 market session analysis
- Risk Assessment: Quantify expected price movement ranges
This indicator transforms complex volatility concepts into actionable trading intelligence, helping traders make more informed decisions based on statistical market behavior patterns.
EDUCATIONAL DISCLAIMER: This indicator is designed for educational purposes and volatility analysis. It should be used as part of a comprehensive trading strategy with proper risk management. Historical volatility patterns do not guarantee future market behavior.
Unified ATR LevelsThis is a unified ATR-based band plotting indicator.
It allows you to display:
Default ATR (on current timeframe)
Preset ATR (mapped to higher timeframe logic)
User-defined ATR (on any custom timeframe)
✳️ Features:
Configurable multipliers, colors, and line widths
Smart label positioning (left, middle, right)
Clean visuals with adjustable label size
Ideal for multi-timeframe analysis and volatility zones
📌 All feedback welcome!
Tags:
volatility, ATR, multi-timeframe, support-and-resistance, custom-indicator
Price Extension from 8 EMAOverview
This indicator can be used to see how far away the price is from the 8 EMA. It compares this to the Average Daily Range % to see if the stock may be overextended. The "Extension Multiplier" represents how far the stock is extended away from the 8 EMA.
Core Concept
This indicator is best used for breakout trades that are trying to make sure they are not chasing the stock.
How to Use This Indicator
This tool is primarily intended for analyzing daily charts of individual stocks and is often used by breakout traders to evaluate potential entry areas.
If the stock is far away from the 8 EMA, it is likely not ready to break out. If it is close to the 8ema, it could be ready to move higher.
This indicator can also be used in the opposite way. For example, shorting or puts.
Understanding the colors
Green (Not Extended): Indicates the price is close to the 8 EMA. This often corresponds to periods of consolidation.
Yellow (Slightly Extended): The price is beginning to move away from the 8 EMA.
Orange (Extended): The price has moved a considerable distance from the 8 EMA.
Red (Very Extended): The price is at an extreme distance from the 8 EMA, historically increasing the likelihood of a pullback or consolidation.
Settings
Info Row Position: Adjusts the vertical position of the display table on the chart. Useful when using other indicators.
ADR Length: Sets the lookback period for calculating the Average Daily Range. Or the average range % for different timeframes.
Timeframe: Determines the timeframe for the EMA and ADR calculation (the default is Daily).
Adaptive Squeeze Momentum +OVERVIEW
Adaptive Squeeze Momentum+ is an enhanced, auto-adaptive momentum indicator inspired by the classic Squeeze Momentum concept. This script dynamically adjusts its parameters to any timeframe without requiring manual inputs, making it a versatile tool for intraday traders and long-term investors alike.
CONCEPTS
The indicator combines Bollinger Bands (BB) and Keltner Channels (KC) to identify volatility compression ("squeeze") and expansion phases. When BB contracts within KC, a squeeze is detected, signaling reduced volatility and potential for a breakout. Additionally, a linear regression momentum calculation helps assess the strength and direction of price moves.
FEATURES
Auto-Adaptation:
Automatically adjusts BB/KC lengths and multipliers based on the chart timeframe (from 1 minute to 1 month).
Dynamic Squeeze Detection:
Clear visual encoding of squeeze status:
- Gray cross: neutral
- Blue cross: squeeze active
- Yellow cross: squeeze released
Momentum Histogram:
Colored area chart shows positive and negative momentum with slope-based coloring.
Clean Visualization:
Minimalist plots focused on actionable signals.
USAGE
Identify Squeeze Phases:
When the blue cross appears, the market is in a volatility squeeze, potentially preceding a breakout.
Monitor Momentum Direction:
The area plot shows the magnitude and direction of price momentum.
Confirm Entries and Exits:
Combine squeeze releases (yellow) with positive momentum for potential long entries or negative momentum for shorts.
Adaptable to Any Market:
Works seamlessly across cryptocurrencies, stocks, forex, and indices on all timeframes.
Volatility Stop — Screener & AlertsVstop Screener
🔔 Alerts Included
You can create TradingView alerts using:
"Bullish VSTOP crossover" — when price closes above the stop.
"Bearish VSTOP cross-under" — when price closes below the stop.
🧪 Use Cases
Trend Confirmation: VSTOP is used as a trend-following confirmation tool.
Exit Management: As a dynamic trailing stop-loss, it helps you stay in a trend until volatility-based reversal.
Breakout Trading: BUY signal = potential entry; SELL = early exit or short trigger.
🧑💻 Extension Ideas
Add multi-timeframe inputs (e.g., daily VSTOP on intraday chart).
Create dashboards or tables that screen VSTOP status for multiple symbols.
Combine with RSI/MACD for multi-indicator confluence.
+ ATR Table and BracketsHi, all. I'm back with a new indicator—one I firmly believe could be one of the most valuable indicators you keep in your indicator toolshed—based around true range.
This is a simple, streamlined indicator utilizing true range and average true range that will help any trader with stoploss, trailing stoploss, and take-profit placement—things that I know many traders use average true range for. It could also be useful for trade entries as well, depending on the trader's style.
Typically, most traders (or at least what I've seen recommended across websites, video tutorials on YouTube, etc.) are taught to simply take the ATR number and use that, and possibly some sort of multiplier, as your stoploss and take-profit. This is fine, but I thought that it might be possible to dive a bit deeper into these values. Because an average is a combination of values, some higher, some lower, and we often see ATR spikes during periods of high volatility, I thought wouldn't it be useful to know what value those ATR spikes are, and how do they relate to the ATR? Then I thought to myself, well, what about the most volatile candle within that ATR (the candle with the greatest true range)? Couldn't knowing that value be useful to a trader? So then the idea of a table displaying these values, along with the ATR and the ATR times some multiplier number, would be a useful, simple way to display this information. That's what we have here.
The table is made up of two columns, one with the name of the metric being measured, and the other with its value. That's it. Simple.
As nice as this was, I thought an additional, great, and perhaps better, way to visualize this information would be in the form of brackets extending from the current bar. These are simply lines/labels plotted at the price values of the ATR, ATR times X, highest ATR, highest ATR times X, and highest TR value. These labels supply the actual values of the ATR, etc., but may also display the price if you should choose (both of these values are toggleable in the 'Inputs' section of the indicator.). Additionally, you can choose to display none of these labels, or all five if you wish (leaves the chart a bit cluttered, as shown in the image below), though I suspect you'll determine your preferences for which information you'd like to see and which not.
Chart with all five lines/labels displayed. I adjusted the ATRX value to 3 just to make the screenshot as legible as possible. Default is set to 1.5. As you can see, the label doesn't show the multiplier number, but the table does.
Here's a screenshot of the labels showing the price in addition to the value of the ATR, set to "Previous Closing Price," (see next paragraph for what that means) and highest TR. Personally, I don't see the value in the displaying the price, but I thought some people might want that. It's not available in the table as of now, but perhaps if I get enough requests for it I will add it.
That's basically it, but one last detail I need to go over is the dropdown box labeled "Bar Value ATR Levels are Oriented To." Firstly, this has no effect on Highest ATR, Highest ATRX, and Highest TR levels. Those are based on the ATR up to the last closed candle, meaning they aren't including the value of the currently open candle (this would be useless). However, knowing that different traders trade different ways it seemed to me prudent to allow for traders to select which opening or closing value the trader wishes to have the ATR brackets based on. For example, as someone who has consumed much No Nonsense Forex content I know that traders are urged to enter their trades in the last fifteen minutes of the trading day because the ATR is unlikely to change significantly in that period (ATR being the centerpiece of NNFX money management), so one of three selections here is to plot the brackets based on the ATR's inclusion of this value (this of course means the brackets will move while the candle is still open). The other options are to set the brackets to the current opening price, or the previous closing price. Depending on what you're trading many times these prices are virtually identical, but sometimes price gaps (stocks in particular), so, wanting your brackets placed relative to the previous close as opposed to the current open might be preferable for some traders.
And that's it. I really hope you guys like this indicator. I haven't seen anything closely similar to it on TradingView, and I think it will be something you all will find incredibly handy.
Please enjoy!
Volume in Candle (Buy/Sell) - Clean & Spaced LabelsThis indicator shows per-candle buy and sell volume estimates, labeled directly on the chart and dynamically positioned to follow the price. It is ideal for traders who want to visually understand the volume balance inside each bar.
✅ Key Features:
🔁 Live updating labels for the current and previous candle only
📉 Labels are tied to the candle’s low price and move with chart scrolling
🧠 Smart spacing: labels are vertically separated so they never overlap
📦 Buy/Sell volume is estimated using candle body and total volume:
Buy Volume (B): Approximated bullish pressure
Sell Volume (S): Approximated bearish pressure
🛠 How it Works:
Volume is split using the candle's close vs open position relative to the total range.
Only two labels are shown at a time: the most recent bar and the one before it.
Labels are displayed below the candles, using a dynamic offset that auto-scales with candle size.
🧪 Use Case:
Spot volume pressure shifts in real time
Combine with price action to detect buy/sell imbalances
Use alongside trend tools or confirmation indicators
🔧 This script is lightweight, non-intrusive, and optimized for clarity.
📍 Best used on 1–15 minute charts, or any timeframe where candle volume analysis is helpful.
BB + RSI & Volume FilterThis script overlays three sets of technical filters on your price chart and generates signals when conditions align:
Bollinger Bands
Calculates upper, middle, and lower bands using either SMA or EMA.
Buy signal when price crosses up through the lower band.
Sell signal when price crosses down through the upper band.
Volume Filter
Computes a simple moving average of volume.
Ensures breakout moves have sufficient volume by requiring current volume > SMA(volume) × multiplier.
RSI Filter
Computes RSI on the chosen source.
Buy when RSI crosses above the oversold threshold.
Sell when RSI crosses below the overbought threshold.
Only plots RSI signals that pass the volume filter.
You get:
Bollinger entry/exit shapes (labeled “BB ↑/↓”).
RSI entry/exit shapes (labeled “RSI”) only when volume confirms the move.
Alerts for each signal type.
This combination reduces false breakouts by requiring both volatility (Bollinger) or momentum (RSI) and volume confirmation
Momentum Regression [BackQuant]Momentum Regression
The Momentum Regression is an advanced statistical indicator built to empower quants, strategists, and technically inclined traders with a robust visual and quantitative framework for analyzing momentum effects in financial markets. Unlike traditional momentum indicators that rely on raw price movements or moving averages, this tool leverages a volatility-adjusted linear regression model (y ~ x) to uncover and validate momentum behavior over a user-defined lookback window.
Purpose & Design Philosophy
Momentum is a core anomaly in quantitative finance — an effect where assets that have performed well (or poorly) continue to do so over short to medium-term horizons. However, this effect can be noisy, regime-dependent, and sometimes spurious.
The Momentum Regression is designed as a pre-strategy analytical tool to help you filter and verify whether statistically meaningful and tradable momentum exists in a given asset. Its architecture includes:
Volatility normalization to account for differences in scale and distribution.
Regression analysis to model the relationship between past and present standardized returns.
Deviation bands to highlight overbought/oversold zones around the predicted trendline.
Statistical summary tables to assess the reliability of the detected momentum.
Core Concepts and Calculations
The model uses the following:
Independent variable (x): The volatility-adjusted return over the chosen momentum period.
Dependent variable (y): The 1-bar lagged log return, also adjusted for volatility.
A simple linear regression is performed over a large lookback window (default: 1000 bars), which reveals the slope and intercept of the momentum line. These values are then used to construct:
A predicted momentum trendline across time.
Upper and lower deviation bands , representing ±n standard deviations of the regression residuals (errors).
These visual elements help traders judge how far current returns deviate from the modeled momentum trend, similar to Bollinger Bands but derived from a regression model rather than a moving average.
Key Metrics Provided
On each update, the indicator dynamically displays:
Momentum Slope (β₁): Indicates trend direction and strength. A higher absolute value implies a stronger effect.
Intercept (β₀): The predicted return when x = 0.
Pearson’s R: Correlation coefficient between x and y.
R² (Coefficient of Determination): Indicates how well the regression line explains the variance in y.
Standard Error of Residuals: Measures dispersion around the trendline.
t-Statistic of β₁: Used to evaluate statistical significance of the momentum slope.
These statistics are presented in a top-right summary table for immediate interpretation. A bottom-right signal table also summarizes key takeaways with visual indicators.
Features and Inputs
✅ Volatility-Adjusted Momentum : Reduces distortions from noisy price spikes.
✅ Custom Lookback Control : Set the number of bars to analyze regression.
✅ Extendable Trendlines : For continuous visualization into the future.
✅ Deviation Bands : Optional ±σ multipliers to detect abnormal price action.
✅ Contextual Tables : Help determine strength, direction, and significance of momentum.
✅ Separate Pane Design : Cleanly isolates statistical momentum from price chart.
How It Helps Traders
📉 Quantitative Strategy Validation:
Use the regression results to confirm whether a momentum-based strategy is worth pursuing on a specific asset or timeframe.
🔍 Regime Detection:
Track when momentum breaks down or reverses. Slope changes, drops in R², or weak t-stats can signal regime shifts.
📊 Trade Filtering:
Avoid false positives by entering trades only when momentum is both statistically significant and directionally favorable.
📈 Backtest Preparation:
Before running costly simulations, use this tool to pre-screen assets for exploitable return structures.
When to Use It
Before building or deploying a momentum strategy : Test if momentum exists and is statistically reliable.
During market transitions : Detect early signs of fading strength or reversal.
As part of an edge-stacking framework : Combine with other filters such as volatility compression, volume surges, or macro filters.
Conclusion
The Momentum Regression indicator offers a powerful fusion of statistical analysis and visual interpretation. By combining volatility-adjusted returns with real-time linear regression modeling, it helps quantify and qualify one of the most studied and traded anomalies in finance: momentum.
Omori Law Recovery PhasesWhat is the Omori Law?
Originally a seismological model, the Omori Law describes how earthquake aftershocks decay over time. It follows a power law relationship: the frequency of aftershocks decreases roughly proportionally to 1/(t+c)^p, where:
t = time since the main shock
c = time offset constant
p = power law exponent (typically around 1.0)
Application to the markets
Financial markets experience "aftershocks" similar to earthquakes:
Market Crashes as Main Shocks: Major market declines (crashes) represent the initial shock event.
Volatility Decay: After a crash, market volatility typically declines following a power law pattern rather than a linear or exponential one.
Behavioral Components: The decay pattern reflects collective market psychology - initial panic gives way to uncertainty, then stabilization, and finally normalization.
The Four Recovery Phases
The Omori decay pattern in markets can be divided into distinct phases:
Acute Phase: Immediately after the crash, characterized by extreme volatility, panic selling, and sharp reversals. Trading is hazardous.
Reaction Phase: Volatility begins decreasing, but markets test previous levels. False rallies and retests of lows are common.
Repair Phase: Structure returns to the market. Volatility approaches normal levels, and traditional technical analysis becomes more reliable.
Recovery Phase: The final stage where market behavior normalizes completely. The impact of the original shock has fully decayed.
Why It Matters for Traders
Understanding where the market stands in this recovery cycle provides valuable context:
Risk Management: Adjust position sizing based on the current phase
Strategy Selection: Different strategies work in different phases
Psychological Preparation: Know what to expect based on the phase
Time Horizon Guidance: Each phase suggests appropriate time frames for trading
ATR Stop-Loss with Fibonacci Take-Profit [jpkxyz]ATR Stop-Loss with Fibonacci Take-Profit Indicator
This comprehensive indicator combines Average True Range (ATR) volatility analysis with Fibonacci extensions to create dynamic stop-loss and take-profit levels. It's designed to help traders set precise risk management levels and profit targets based on market volatility and mathematical ratios.
Two Operating Modes
Default Mode (Rolling Levels)
In default mode, the indicator continuously plots evolving stop-loss and take-profit levels based on real-time price action. These levels update dynamically as new bars form, creating rolling horizontal lines across the chart. I use this mode primarily to plot the rolling ATR-Level which I use to trail my Stop-Loss into profit.
Characteristics:
Levels recalculate with each new bar
All selected Fibonacci levels display simultaneously
Uses plot() functions with trackprice=true for price tracking
Custom Anchor Mode (Fixed Levels)
This is the primary mode for precision trading. You select a specific timestamp (typically your entry bar), and the indicator locks all calculations to that exact moment, creating fixed horizontal lines that represent your actual trade levels.
Characteristics:
Entry line (blue) marks your anchor point
Stop-loss calculated using ATR from the anchor bar
Fibonacci levels projected from entry-to-stop distance
Lines terminate when price breaks through them
Includes comprehensive alert system
Core Calculation Logic
ATR Stop-Loss Calculation:
Stop Loss = Entry Price ± (ATR × Multiplier)
Long positions: SL = Entry - (ATR × Multiplier)
Short positions: SL = Entry + (ATR × Multiplier)
ATR uses your chosen smoothing method (RMA, SMA, EMA, or WMA)
Default multiplier is 1.5, adjustable to your risk tolerance
Fibonacci Take-Profit Projection:
The distance from entry to stop-loss becomes the base unit (1.0) for Fibonacci extensions:
TP Level = Entry + (Entry-to-SL Distance × Fibonacci Ratio)
Available Fibonacci Levels:
Conservative: 0.618, 1.0, 1.618
Extended: 2.618, 3.618, 4.618
Complete range: 0.0 to 4.764 (23 levels total)
Multi-Timeframe Functionality
One of the indicator's most powerful features is timeframe flexibility. You can analyze on one timeframe while using stop-loss and take-profit calculations from another.
Best Practices:
Identify your entry point on execution timeframe
Enable "Custom Anchor" mode
Set anchor timestamp to your entry bar
Select appropriate analysis timeframe
Choose relevant Fibonacci levels
Enable alerts for automated notifications
Example Scenario:
Analyse trend on 4-hour chart
Execute entry on 5-minute chart for precision
Set custom anchor to your 5-minute entry bar
Configure timeframe setting to "4h" for swing-level targets
Select appropriate Fibonacci Extension levels
Result: Precise entry with larger timeframe risk management
Visual Intelligence System
Line Behaviour in Custom Anchor Mode:
Active levels: Lines extend to the right edge
Hit levels: Lines terminate at the breaking bar
Entry line: Always visible in blue
Stop-loss: Red line, terminates when hit
Take-profits: Green lines (1.618 level in gold for emphasis)
Customisation Options:
Line width (1-4 pixels)
Show/hide individual Fibonacci levels
ATR length and smoothing method
ATR multiplier for stop-loss distance
Rolling Log Returns [BackQuant]Rolling Log Returns
The Rolling Log Returns indicator is a versatile tool designed to help traders, quants, and data-driven analysts evaluate the dynamics of price changes using logarithmic return analysis. Widely adopted in quantitative finance, log returns offer several mathematical and statistical advantages over simple returns, making them ideal for backtesting, portfolio optimization, volatility modeling, and risk management.
What Are Log Returns?
In quantitative finance, logarithmic returns are defined as:
ln(Pₜ / Pₜ₋₁)
or for rolling periods:
ln(Pₜ / Pₜ₋ₙ)
where P represents price and n is the rolling lookback window.
Log returns are preferred because:
They are time additive : returns over multiple periods can be summed.
They allow for easier statistical modeling , especially when assuming normally distributed returns.
They behave symmetrically for gains and losses, unlike arithmetic returns.
They normalize percentage changes, making cross-asset or cross-timeframe comparisons more consistent.
Indicator Overview
The Rolling Log Returns indicator computes log returns either on a standard (1-period) basis or using a rolling lookback period , allowing users to adapt it to short-term trading or long-term trend analysis.
It also supports a comparison series , enabling traders to compare the return structure of the main charted asset to another instrument (e.g., SPY, BTC, etc.).
Core Features
✅ Return Modes :
Normal Log Returns : Measures ln(price / price ), ideal for day-to-day return analysis.
Rolling Log Returns : Measures ln(price / price ), highlighting price drift over longer horizons.
✅ Comparison Support :
Compare log returns of the primary instrument to another symbol (like an index or ETF).
Useful for relative performance and market regime analysis .
✅ Moving Averages of Returns :
Smooth noisy return series with customizable MA types: SMA, EMA, WMA, RMA, and Linear Regression.
Applicable to both primary and comparison series.
✅ Conditional Coloring :
Returns > 0 are colored green ; returns < 0 are red .
Comparison series gets its own unique color scheme.
✅ Extreme Return Detection :
Highlight unusually large price moves using upper/lower thresholds.
Visually flags abnormal volatility events such as earnings surprises or macroeconomic shocks.
Quantitative Use Cases
🔍 Return Distribution Analysis :
Gain insight into the statistical properties of asset returns (e.g., skewness, kurtosis, tail behavior).
📉 Risk Management :
Use historical return outliers to define drawdown expectations, stress tests, or VaR simulations.
🔁 Strategy Backtesting :
Apply rolling log returns to momentum or mean-reversion models where compounding and consistent scaling matter.
📊 Market Regime Detection :
Identify periods of consistent overperformance/underperformance relative to a benchmark asset.
📈 Signal Engineering :
Incorporate return deltas, moving average crossover of returns, or threshold-based triggers into machine learning pipelines or rule-based systems.
Recommended Settings
Use Normal mode for high-frequency trading signals.
Use Rolling mode for swing or trend-following strategies.
Compare vs. a broad market index (e.g., SPY or QQQ ) to extract relative strength insights.
Set upper and lower thresholds around ±5% for spotting major volatility days.
Conclusion
The Rolling Log Returns indicator transforms raw price action into a statistically sound return series—equipping traders with a professional-grade lens into market behavior. Whether you're conducting exploratory data analysis, building factor models, or visually scanning for outliers, this indicator integrates seamlessly into a modern quant's toolbox.
Session Volume Breakout by aDiLHow to Use the Combined Session Breakout?
Session Breakout indicator is designed to assist traders in identifying key breakout levels and Fibonacci retracement levels during the London and New York trading sessions. It plots the session high, session low, and the 50% Fibonacci retracement level for each session directly on your TradingView chart. This tool is particularly useful for breakout trading strategies or for spotting potential support and resistance zones.
Recommended: Use PepperStone Chart for Perfect Use
What the Indicator Does
Session Breakout Levels: The indicator calculates the highest high (session high) and lowest low (session low) during the specified London and New York breakout sessions.
Fibonacci 50% Retracement: For each session, it computes the 50% retracement level between the session high and low, a level often considered significant by traders for potential reversals or consolidations.
Visual Representation: The session high, low, and 50% Fib levels are displayed as horizontal lines on the chart. Additionally, tiny labels mark the "High" and "Low" levels at the start of each session for quick reference.
ZF RSI PLOT1. How RSI Is Calculated
RSI is typically computed over 14 periods (days, hours, etc.) using the formula:
RSI=100−1001+RS
RSI=100−1+RS100
where
RS=Average Gain over N periodsAverage Loss over N periods
RS=Average Loss over N periodsAverage Gain over N periods
2. Overbought (> 70)
Definition: An RSI reading above 70 suggests that the instrument has experienced relatively large gains and may be “overbought.”
Interpretation:
Potential Reversal: Prices may have risen too far, too fast, and could be due for a pullback or consolidation.
Exit/Take Profits: Traders often trim long positions or tighten stops as RSI climbs above 70.
Confirmation Needed:
Bearish “RSI divergence” (price makes a higher high while RSI makes a lower high).
Price action signals (e.g., bearish candlestick patterns).
Volume drying up on advances.
3. Oversold (< 30)
Definition: An RSI reading below 30 suggests that the instrument has experienced relatively large losses and may be “oversold.”
Interpretation:
Potential Bounce: Prices may have fallen too far, too fast, and could be due for a rebound or consolidation.
Buying Opportunity: Traders often look to initiate or add to long positions as RSI drops below 30.
Confirmation Needed:
Bullish “RSI divergence” (price makes a lower low while RSI makes a higher low).
Price action signals (e.g., hammer candlesticks, support levels).
Volume picking up on declines.
4. Divergences
Bullish Divergence: Price ↓ makes a lower low, RSI ↑ makes a higher low ⇒ possible trend change to the upside.
Bearish Divergence: Price ↑ makes a higher high, RSI ↓ makes a lower high ⇒ possible trend change to the downside.
5. Adjustments & Variations
Stronger Trends: Use 80/20 thresholds to avoid early signals in very strong up- or down-trends.
Shorter/Longer Periods: Adjust the look-back period (e.g., 9 for more sensitivity, 21 for smoother signals) depending on your time frame.
6. Limitations & Best Practices
Can Stay Extreme: In strong trends, RSI may remain overbought/oversold for extended periods—don’t trade it in isolation.
Combine with Other Tools: Use trend filters (moving averages, ADX), support/resistance, and volume to confirm entries.
Risk Management: Always set stops and manage position size; RSI signals can fail.
7. Putting It All Together
Identify Trend: Is the market in an uptrend, downtrend, or range?
Watch RSI Extremes: Note when RSI crosses above 70 or below 30.
Seek Confirmation: Look for divergences, candlestick/pricing signals, and supporting volume.
Execute & Manage: Enter with clear stop-loss levels, consider scaling, and lock in profits appropriately.
By understanding both the raw threshold signals and the nuances—like divergences and trend-context—you can harness RSI’s simplicity while mitigating its pitfalls.
New London Breakout StructureThe London Breakout Structure Pro is a fully mechanical trading indicator designed to capture high-probability breakout moves during the London session. It automatically identifies valid trade setups based on time-defined zones, price structure, and breakout confirmation. With a built-in risk-reward ratio of 1:2 and session filters, it helps traders maintain consistency and discipline. Ideal for intraday traders looking to systematize their strategy during the most volatile hours of the Forex market.
Shavarie's Sniper LineShavarie’s Sniper Line is a precision confirmation tool built for high-quality entries — not noisy signals.
It activates only when all 3 conditions agree:
🔁 Momentum bend detection
💧 Money Flow Index (MFI) pressure
🔺 Delta volume strength (emulated from price/volume flow)
When all conditions align, the Sniper Line shifts to:
+1 for potential buy zone
-1 for potential sell zone
0 when neutral — no action
Best used in combination with supply/demand zones, Heikin Ashi, or larger trend structures. Built for traders who value patience, precision, and massive R:R setups.
Volatility & Market Regimes [AlgoXcalibur]Analyze Market Conditions Like a Pro.
Volatility & Market Regimes is a specialized, institution-inspired indicator designed to help traders instantly identify the current conditions of the market with clarity and confidence.
By combining a real-time Volatility Histogram and Strength Line with a compact Regime Table, this tool reveals four essential market dimensions—Volatility, Strength, Participation, and Noise—in a clean and intuitive format. Whether you’re confirming trade setups or managing risk, knowing the current regimes enhances awareness across all assets and timeframes.
🧠 Algorithm Logic
This sophisticated tool continuously monitors four independent regimes, each reflecting a distinct dimension of market behavior:
• Volatility – Gauges how active or dormant the market is by comparing current price action movement to historical averages. A dynamic, color-gradient Volatility Histogram transitions from Low (ice blue/white) to Medium (green/yellow) to High (orange/red), giving you an immediate assessment of volatility and risk.
• Strength – Measures directional intensity by assessing trend momentum, pressure, and persistence. A color-gradient Strength Line ranges from weak (red) to strong (green), helping traders determine if directional strength is trending, weakening, or consolidating.
• Participation – Analyzes relative volume to assess the level of trader engagement. Higher volume indicates stronger participation and conviction, while low volume may signal uncertainty, fading momentum, or even liquidity traps.
• Noise – Evaluates structural stability by measuring how orderly or chaotic the price action is. High noise suggests choppy, unstable conditions, while low noise reflects clean, stable moves.
Each regime includes a High / Medium / Low classification and a color-coded directional arrow to indicate whether condition parameters are increasing or decreasing. Together, these components deliver real-time market context—helping you stay grounded in logic, not emotion.
⚙️ User-Selectable Features
Each component of the indicator—the Volatility Histogram, Strength Line, and Regime Table—can be independently made visible or hidden to match your preference. This flexibility allows you to display only the Regime Table and move it directly to your main chart, where it auto-positions to the center-right and integrates seamlessly with other AlgoXcalibur indicators that also use data tables for a cohesive and refined experience.
📊 Clarity, Not Guesswork
Volatility & Market Regimes is a unique, institution-inspired algorithm rarely seen in retail trading. Not only does it clearly display volatility—it translates complex market behavior into a clear context to reveal what’s happening behind the candles. By decoding core regimes in real-time, this tool transforms uncertainty into structured insight—empowering traders to act with clarity, not guesswork.
🔐 To get access or learn more, visit the Author’s Instructions section.
Mean Amplitude (300 candles)Displays the average candle amplitude (volatility) as % over a selected period. Useful for gauging market activity compression or expansion.
Intra-bar Close/Open Gap [YuL]Just checking one idea: look at gaps between close and open bars on lower timeframe to try to estimate how much slippage exists there that may be a result of buying or selling pressure.
Perhaps it only useful in real time to see if situation of the current bar is changing.
Open to ideas and suggestions.
