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.
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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.
Adiyogi Trend🟢🔴 “Adiyogi” Trend — Market Alignment Visualizer
“Adiyogi” Trend is a powerful, non-intrusive trend detection system built for traders who seek clarity, discipline, and alignment with true market flow. Inspired by the meditative stillness of Adiyogi and the need for mindful, high-probability decisions, this tool offers a clean and intuitive visual guide to trending environments — without cluttering the chart or pushing forced trades.
This is not a buy/sell signal generator. Instead, it is designed as a background confirmation engine that helps you stay on the right side of the market by identifying moments of true directional strength.
🧠 Core Logic
The “Adiyogi” Trend indicator highlights the background of your chart in green or red when multiple layers of strength and structure align — including momentum, market positioning, and relative force. Only when these internal components agree does the system activate a directional state.
It’s built on three foundational energies of trend confirmation:
Strength of movement
Structure in price action
Conviction in momentum
By combining these into one visual background, the indicator filters out indecision and helps you stay focused during real trend phases — whether you're day trading, swing trading, or holding longer-term positions.
📌 Core Concepts Behind the Tool
The indicator integrates three essential market filters—each confirming a different dimension of trend strength:
ADX (Average Directional Index) – Measures trend momentum.
You’ve chosen a very responsive setting (ADX Length = 2), which helps catch the earliest possible signs of momentum emergence.
The threshold is ADX ≥ 22, ensuring that weak or sideways markets are filtered out.
SuperTrend (10,1) – Captures short-term trend direction.
This setup follows price closely and reacts quickly to reversals, making it ideal for fast-moving assets or intraday strategies.
SuperTrend acts as the structural confirmation of directional bias.
RSI (Relative Strength Index) – Measures strength based on recent price closes.
You’ve configured RSI > 50 for bullish zones and < 50 for bearish—a neutral midpoint standard often used by professional traders.
This ensures that only trades in sync with momentum and recent strength are highlighted.
🌈 How It Visually Works
Background turns GREEN when:
ADX ≥ 22, indicating strong momentum
Price is above the 20 EMA and above SuperTrend (10,1)
RSI > 50, confirming recent strength
Background turns RED when:
ADX ≥ 22, indicating strong momentum
Price is below the 20 EMA and below SuperTrend (10,1)
RSI < 50, confirming recent weakness
The background remains neutral (transparent) when trend conditions are not clearly aligned—this is the tool's way of keeping you out of indecisive markets.
A label (BULL / BEAR) appears only when the bias flips from the previous one. This helps avoid repeated or redundant alerts, focusing your attention only when something changes.
📊 Practical Uses & Benefits
✅ Stay with the trend: Perfectly filters out choppy or sideways markets by only activating when conditions align across momentum, structure, and strength.
✅ Pre-trade confirmation: Use this tool to confirm trade setups from other indicators or price action patterns.
✅ Avoid noise: Prevent overtrading by focusing only on high-quality trend conditions.
✅ Visual clarity: Unlike arrows or plots that clutter the chart, this tool subtly highlights trend conditions in the background, preserving your price action view.
📍 Important Notes
This is not a buy/sell signal generator. It is a trend-confirmation system.
Use it in conjunction with your existing entry setups—such as breakouts, order blocks, retests, or candlestick patterns.
The tool helps you stay in sync with the dominant direction, especially when combining multiple timeframes.
Can be used on any market (stocks, forex, crypto, indices) and on any timeframe.
Institutional Momentum Scanner [IMS]Institutional Momentum Scanner - Professional Momentum Detection System
Hunt explosive price movements like the professionals. IMS identifies maximum momentum displacement within 10-bar windows, revealing where institutional money commits to directional moves.
KEY FEATURES:
▪ Scans for strongest momentum in rolling 10-bar windows (institutional accumulation period)
▪ Adaptive filtering reduces false signals using efficiency ratio technology
▪ Three clear states: LONG (green), SHORT (red), WAIT (gray)
▪ Dynamic volatility-adjusted thresholds (8% ATR-scaled)
▪ Visual momentum flow with glow effects for signal strength
BASED ON:
- Pocket Pivot concept (O'Neil/Morales) applied to price momentum
- Adaptive Moving Average principles (Kaufman KAMA)
- Market Wizards momentum philosophy
- Institutional order flow patterns (5-day verification window)
HOW IT WORKS:
The scanner finds the maximum price displacement in each 10-bar window - where the market showed its hand. An adaptive filter (5-bar regression) separates real moves from noise. When momentum exceeds the volatility-adjusted threshold, states change.
IDEAL FOR:
- Momentum traders seeking explosive moves
- Swing traders (especially 4H timeframe)
- Position traders wanting institutional footprints
- Anyone tired of false breakout signals
Default parameters (10,5) optimized for 4H charts but adaptable to any timeframe. Remember: The market rewards patience and punishes heroes. Wait for clear signals.
"The market is honest. Are you?"
Forex Monday RangeForex Monday Range. Refers to the price range (high to low) established during Monday's trading session, typically measured from midnight Sunday to midnight Monday (New York time).
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.
+ 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!
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.
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.
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
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
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).
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
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.
Fear and Greed Index [DunesIsland]The Fear and Greed Index is a sentiment indicator designed to measure the emotions driving the stock market, specifically investor fear and greed. Fear represents pessimism and caution, while greed reflects optimism and risk-taking. This indicator aggregates multiple market metrics to provide a comprehensive view of market sentiment, helping traders and investors gauge whether the market is overly fearful or excessively greedy.How It WorksThe Fear and Greed Index is calculated using four key market indicators, each capturing a different aspect of market sentiment:
Market Momentum (30% weight)
Measures how the S&P 500 (SPX) is performing relative to its 125-day simple moving average (SMA).
A higher value indicates that the market is trading well above its moving average, signaling greed.
Stock Price Strength (20% weight)
Calculates the net number of stocks hitting 52-week highs minus those hitting 52-week lows on the NYSE.
A greater number of net highs suggests strong market breadth and greed.
Put/Call Options (30% weight)
Uses the 5-day average of the put/call ratio.
A lower ratio (more call options being bought) indicates greed, as investors are betting on rising prices.
Market Volatility (20% weight)
Utilizes the VIX index, which measures market volatility.
Lower volatility is associated with greed, as investors are less fearful of large market swings.
Each component is normalized using a z-score over a 252-day lookback period (approximately one trading year) and scaled to a range of 0 to 100. The final Fear and Greed Index is a weighted average of these four components, with the weights specified above.Key FeaturesIndex Range: The index value ranges from 0 to 100:
0–25: Extreme Fear (red)
25–50: Fear (orange)
50–75: Neutral (yellow)
75–100: Greed (green)
Dynamic Plot Color: The plot line changes color based on the index value, visually indicating the current sentiment zone.
Reference Lines: Horizontal lines are plotted at 0, 25, 50, 75, and 100 to represent the different sentiment levels: Extreme Fear, Fear, Neutral, Greed, and Extreme Greed.
How to Interpret
Low Values (0–25): Indicate extreme fear, which may suggest that the market is oversold and could be due for a rebound.
High Values (75–100): Indicate greed, which may signal that the market is overbought and could be at risk of a correction.
Neutral Range (25–75): Suggests a balanced market sentiment, neither overly fearful nor greedy.
This indicator is a valuable tool for contrarian investors, as extreme readings often precede market reversals. However, it should be used in conjunction with other technical and fundamental analysis tools for a well-rounded view of the market.
Midas v1.0 by G-Track**MIDAS v1.0: See the market, simplified.**
This is a paid, invite-only script designed to turn complex market data into simple, intuitive signals.
For subscription details, please see the Author's instructions below.
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*Disclaimer: This indicator is provided for informational and educational purposes only. It is not financial advice. All investment decisions and responsibility lie solely with the user. Past performance does not guarantee future results.*
Vasyl Ivanov | Volatility with MAThis indicator calculates and displays the volatility value for each bar.
The main line shows the relative range (spread) of the current bar compared to its closing price.
This allows you to quickly assess how much the price fluctuated within the bar relative to where it closed.
The Simple Moving Average (SMA) with a length of 9 smooths the main indicator values, helping to identify volatility trends and filter out random spikes.
Practical Application:
The indicator can be useful for assessing current market volatility and identifying periods with unusually wide or narrow ranges.
The smoothed line helps track medium-term changes in volatility and can be used to confirm trading signals related to range expansion or contraction.
Bollinger BandWidth Squeeze BreakoutBollinger BandWidth Squeeze Breakout
Description:
This indicator merges classic Bollinger BandWidth (BBW) with TTM Squeeze Pro-style compression dots. It identifies volatility contractions, very effective at identifying chop or ranging markets, and color-codes the BBW line based on directional breakout bias—helping traders anticipate explosive moves before they happen.
It supports multi-level squeeze detection:
High Compression (Orange) : Tightest squeeze — highly coiled setup
Medium Compression (Red) : Moderate squeeze — building pressure
Low Compression (Black) : Light squeeze — early contraction
(No dot means no squeeze – free expansion)
How It Works
Bollinger BandWidth (BBW):
Calculated as the percent width between Bollinger Bands over a selected moving average (SMA, EMA, etc.). A rising BBW suggests volatility expansion; falling BBW indicates compression.
Directional Bias (BBW Color):
The line is colored green when recent bars show upside breakout pressure, red when downside pressure dominates, and gray when neutral. This is based on cumulative position of price relative to the Bollinger Bands.
TTM Squeeze Pro Dots:
Compression dots plotted on the zero line represent volatility squeeze levels, using up to 3 Keltner Channel thresholds:
Orange Dot : High compression (tightest squeeze zone)
Red Dot : Medium compression
Black Dot : Low compression
(No dot means no squeeze — price is expanding)
Expansion & Contraction Context:
Plots historical highest/lowest BBW values (user-defined period) to help spot extreme conditions.
How to Interpret:
Use squeeze dots to identify when the market is “chop/ranging.” Breakouts from these zones often come with sharp moves.
BBW Line Color = Bias Filter:
Green → Bullish expansion pressure
Red → Bearish expansion pressure
Gray → Neutral or undecided
Use this to filter direction before entering a breakout or momentum trade.
Inputs:
Length : Period for BB and Keltner calculations
MA Type : Choose from SMA, EMA, SMMA, WMA, VWMA, or None
StdDev : Standard deviation for BB
Expansion/Contraction Lengths : Historical window to track BBW extremes
Source : Input source for all calculations (default: Close)
Keltner Multipliers : Customize thresholds for high/mid/low compression
Best For:
Traders looking to anticipate breakout direction
Scalpers and swing traders seeking early volatility cues
Anyone using BB or TTM Squeeze logic in their setups
Pro Tips:
Combine with momentum tools (e.g., RSI, MACD, SMI, CCI) to confirm breakout thrust
Use squeeze dot color shifts (red/orange → no dot) as a breakout timing tool
Use historical BBW highs/lows as context for relative volatility expansion
MicroStructure Pulse Scalper - Lower📄 Description
⚙️ MPS Companion v1.0 is a custom-built utility indicator designed to complement the MicroStructure Pulse Scalper (MPS).
It visualizes pressure buildup from microstructural imbalances, volume surges, trend alignment, and liquidity sweeps — turning invisible market pressure into actionable intelligence.
🔍 What It Does
Pressure Oscillator: Calculates a normalized score from –100 to +100 showing how likely the market is to form a high-probability MPS trigger.
Adaptive Threshold Zones: Dynamic bullish/bearish levels adapt to volatility for smarter readings.
Microstructure Memory: A clustering model gauges how many valid entry conditions occurred recently.
Real-Time Dashboard: A floating panel shows trend direction, volume regime, liquidity sweep type, and more.
Background Zoning: Visually highlights when market bias enters a prime actionable zone.
✅ Core Logic
VWAP Z-Score Dislocation
Volume Spike Detection (Z-Score)
ATR-Based Expansion Analysis
EMA-Based Trend Direction
Liquidity Sweep Recognition
Signal Memory Weighting (clustering over recent bars)
🧠 How to Use It
Use the oscillator + background zone to anticipate potential MPS triggers.
Check the dashboard for bias clarity before acting on any signal.
Use adaptive zones to filter chop from high-conviction setups.
🎯 Recommended Settings
Works best on: 1m, 3m, 5m charts (BTC/USD, ETH, NASDAQ micros, etc.)
Combine with: MPS Strategy or Dashboard
Default values are tuned for fast-paced scalping.
🧬 About the Author
This tool is part of the MicroStructure Pulse System, engineered by Donald Clark for precision scalping with a blend of statistical models, microstructure theory, and volatility dynamics.
👉 For full access to the Full-Private MPS system, including entry engine and optimization suite, DM the author or visit the full strategy page.
Trend Following with Mean Reversion - IndicatorTrend Following with Mean Reversion Indicator
A comprehensive technical analysis tool that combines trend detection with momentum reversal signals for enhanced market timing.
Strategy Overview:
This indicator identifies high-probability entry points by combining two proven technical concepts:
Trend Following: Uses Exponential Moving Average (EMA) to determine market direction
Mean Reversion: Utilizes RSI oversold/overbought levels for optimal entry timing
Key Features:
📊 Core Indicators:
Customizable EMA for trend identification (default: 50 periods)
RSI momentum oscillator with adjustable overbought/oversold levels
Visual trend direction indicators
🎯 Signal Generation:
BUY Signals: Generated when price is above EMA (uptrend) AND RSI is oversold (<30)
SELL Signals: Generated when price is below EMA (downtrend) AND RSI is overbought (>70)
Clear visual labels on chart for easy identification
⏰ Advanced Time Management:
Customizable trading session filter (default: 0700-1500)
Multiple timezone support (GMT-8 to GMT+13)
Individual day exclusion controls (weekends excluded by default)
Visual background coloring for time restrictions
🎨 Visual Elements:
Color-coded trend indicators
RSI extreme level background highlighting
Time filter status visualization
Comprehensive information table showing current market conditions
🔔 Alert System:
Built-in alerts for valid entry signals
Notifications for signals occurring outside trading hours
Customizable alert messages
How It Works:
Trend Filter: EMA determines if market is trending up or down
Momentum Confirmation: RSI identifies when price has moved too far and is due for reversal
Time Validation: Ensures signals only occur during specified trading hours
Visual Confirmation: Clear BUY/SELL labels appear only when all conditions align
Best Use Cases:
Swing trading on higher timeframes (4H, Daily)
Counter-trend entries in strong trending markets
Combining with other technical analysis tools
Educational purposes for understanding trend/momentum relationships
Customization Options:
Adjustable EMA and RSI periods
Customizable overbought/oversold levels
Flexible time and day restrictions
Toggle visual elements on/off
Multiple display themes
Note: This is a technical analysis tool for educational and informational purposes. Always conduct your own analysis and consider risk management principles. Past performance does not guarantee future results.
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).
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.