StdDev Supply/Demand Zone RefinerThis indicator uses standard deviation bands to identify statistically significant price extremes, then validates these levels through volume analysis and market structure. It employs a proprietary "Zone Refinement" technique that dynamically adjusts zones based on price interaction and volume concentration, creating increasingly precise support/resistance areas.
Key Features:
Statistical Extremes Detection: Identifies when price reaches 2+ standard deviations from mean
Volume-Weighted Zone Creation: Only creates zones at extremes with abnormal volume
Dynamic Zone Refinement: Automatically tightens zones based on touch points and volume nodes
Point of Control (POC) Identification: Finds the exact price with maximum volume within each zone
Volume Profile Visualization: Shows horizontal volume distribution to identify key liquidity levels
Multi-Factor Validation: Combines volume imbalance, zone strength, and touch count metrics
Unlike traditional support/resistance indicators that use arbitrary levels, this system:
Self-adjusts based on market volatility (standard deviation)
Refines zones through machine-learning-like feedback from price touches
Weights by volume to show where real money was positioned
Tracks zone decay - older, untested zones automatically fade
Volatilite
Momentum Breakout StrategyBacktest a strategy where, when a candlestick on a timeframe rises more than a certain %, it enters a trade.
RVOL with Breakout Signals
Key Features
RVOL Line : Displays RVOL as a gray line on the chart. Values above 1 indicate above-average volume; above 2 suggests strong activity.
Horizontal Lines :
Base Line (light pink dotted at 0): Reference baseline.
RVOL 1 (gray dashed): Threshold for average volume.
RVOL 2 (green dashed): Threshold for high volume activity.
Breakout Buy Signals : Pink upward triangles (above the bar) appear when the price closes above the highest high of the past breakout lookback period AND RVOL exceeds the set threshold (default 2). This confirms potential valid breakouts backed by volume.
How to Use
Add the indicator to your chart.
Adjust inputs in the settings:
RVOL Lookback Period (default 10): Number of bars to calculate average volume. For short-term trades (intraday to mid-term), 5-20 works best; test based on your timeframe.
Breakout Lookback Period (default 20): Bars to check for the previous high. Shorter for aggressive breakouts, longer for stronger confirmations.
RVOL Threshold for Breakout (default 2.0): Minimum RVOL required to confirm a breakout signal.
Look for pink triangles as buy signals during breakouts. Combine with your strategy (e.g., support/resistance, trends) for entries.
For position sizing: Higher RVOL (e.g., >2) allows larger positions due to better liquidity and reward potential.
When to Use
Breakout Plays : Ideal for spotting valid breakouts in volatile stocks. High RVOL confirms the move isn't a fakeout, as volume indicates real interest (e.g., institutional buying).
Short to Mid-Term Trades : Best on 5-min to daily charts for day trading or swings. Use on "In Play" stocks with news, earnings, or catalysts.
Avoid in Low Volume : If RVOL <1, skip or use small positions—low liquidity increases risk.
Inspired by traders like those at SMB Capital, who use RVOL to decide execution and sizing.
Example
See the attached screenshot on Bitcoin daily chart, showing multiple valid breakouts marked by pink triangles where price breaks highs with RVOL >2, leading to strong upward moves. This demonstrates how the indicator filters noise and highlights high-probability setups. Always backtest and use risk management!
Let me knows u have any idea to improve the indicator. Thank you all!
ADR% / AWR% / AMR% (v5)This indicator calculates on the time scale you choose by modifying the parameters as you are the average range in daily, weekly and monthly percentage.
By Mr. Le Besque
Supertrend Strategy with ATR TP and SLSupertrend Strategy with ATR TP and SL
Overview
The Supertrend strategy is a trend-following trading system that utilizes the Average True Range (ATR) to determine the market's volatility and to set dynamic support and resistance levels. This strategy employs the Supertrend indicator to identify entry and exit points for trades, specifically focusing on long and short positions in the market.
Key Components
Inputs
ATR Period: This defines the lookback period for calculating the ATR, which helps in understanding market volatility. The default value is set to 10.
Supertrend Multiplier: This multiplier adjusts the sensitivity of the Supertrend indicator. A value of 3 is used, affecting the upper and lower bands of the Supertrend calculation.
TP (Take Profit) ATR Multiplier: This multiplier is used to calculate the take profit level based on the ATR (default value is 3).
SL (Stop Loss) ATR Multiplier: This multiplier dictates the stop loss distance from the entry point concerning the ATR, set to a value of 1.5.
Number of Bars to Use for Backtest: This setting determines how many bars are analyzed during testing, set to a default of 240.
Trading Mode: Options are provided to choose whether to take only long positions or only short positions.
ATR Calculation
The ATR is computed using a specified period, allowing traders to gauge market volatility effectively. This is crucial for setting appropriate stop loss and take profit levels.
Supertrend Calculation
The Supertrend indicator is calculated using the ATR and the multiplier to derive upper and lower bands. The current market price is compared against these bands to determine the trend direction.
Trade Signals
Buy Signal: Generated when the price closes above the Supertrend line, indicating a potential upward trend.
Sell Signal: Generated when the price closes below the Supertrend line, indicating a potential downward trend.
Entry and Exit Strategies
When a buy signal is triggered, the strategy will enter a long position while setting the take profit and stop loss based on the ATR values.
Conversely, if a sell signal occurs, a short position is opened with respective take profit and stop loss levels.
Alert Conditions
Alerts are set up for both buy and sell signals, allowing users to be notified when trade opportunities arise.
Visualization
The Supertrend line is plotted on the chart, along with take profit and stop loss levels for each trade. Labels indicate entry points to facilitate easy tracking of trades.
Conclusion
This Supertrend strategy is designed to simplify trading decisions by automating the entry and exit points based on well-defined market conditions. By utilizing the ATR for dynamic risk management, traders can adapt their approach according to market volatility. This strategy is suitable for many trading styles and can be backtested to assess its performance across different market conditions.
Usage
To use this strategy, simply apply the script in TradingView and adjust the input parameters based on your trading preferences. The strategy can be modified further to enhance its performance according to specific market scenarios.
VSOVSO
This is similar to LazyBear's WaveTrend oscillator but handles momentum calculation differently and has some extra components for trade analysis.
The oscillator calculates an adaptive mean, then measures how far price deviates from that mean. Instead of just looking at raw deviation, it normalizes this by dividing by smoothed absolute deviation values.
The key difference is how it separates momentum - it splits the deviation into positive (up) and negative (down) components, then applies directional strength smoothing to each separately before combining them:
100 * (up_strength - down_strength) / (up_strength + down_strength)
This directional strength calculation gives more weight to sustained moves in either direction rather than just price volatility. The result is the main Momentum Wave oscillating between -100 and +100. The Signal Wave is just a smoothed version of this. The Momentum Gap shows the difference between them.
You'll see the Momentum Wave as a colored area/line with four color states, the Signal Wave as a white area, the Momentum Gap as a yellow line, the Drip Rate as cyan/purple area, and Velocity as a colored line at the bottom. The overbought/oversold zones are shaded, volatility bands adapt to current conditions, and major/minor signals show up as circles when the waves cross.
For trading, the Drip Rate is your long-term signal for bigger shifts. When it makes lower lows into resistance, look for reversals. Works great across multiple timeframes. Volatility squeezes signal big moves coming - use these with support/resistance and divergences. Top/bottom signals show momentum shifts and usually lead to pumps or drops.
Velocity shows breakout speed or rejections. Higher readings mean faster moves, regardless of direction. Wave colors reveal continuation patterns - green to purple to green means strong continuation up, red to cyan to red means continuation down.
The Momentum Gap can signal divergence on its own. The angle it crosses zero often hints at how fast the next move will be. When momentum goes outside the volatility bands, watch the next wave for divergence or confirmation.
Works best when you combine the Drip Rate across timeframes with squeeze setups and color changes for high-probability entries.
Works well with Heikin Ashi candles, or use the smoothed candle mode in the settings to mimic them. You can set the candle colors to the momentum wave colors as well, it can be helpful.
Here is a trade setup and how you can use it to take trades.
Overnight Gap Dominance Indicator (OGDI)The Overnight Gap Dominance Indicator (OGDI) measures the relative volatility of overnight price gaps versus intraday price movements for a given security, such as SPY or SPX. It uses a rolling standard deviation of absolute overnight percentage changes divided by the standard deviation of absolute intraday percentage changes over a customizable window. This helps traders identify periods where overnight gaps predominate, suggesting potential opportunities for strategies leveraging extended market moves.
Instructions
A
pply the indicator to your TradingView chart for the desired security (e.g., SPY or SPX).
Adjust the "Rolling Window" input to set the lookback period (default: 60 bars).
Modify the "1DTE Threshold" and "2DTE+ Threshold" inputs to tailor the levels at which you switch from 0DTE to 1DTE or multi-DTE strategies (default: 0.5 and 0.6).
Observe the OGDI line: values above the 1DTE threshold suggest favoring 1DTE strategies, while values above the 2DTE+ threshold indicate multi-DTE strategies may be more effective.
Use in conjunction with low VIX environments and uptrend legs for optimal results.
KAMA Trend Flip - SightLing LabsBuckle up, traders—this open-source KAMA Trend Flip indicator is your ticket to sniping trend reversals with a Kaufman Adaptive Moving Average (KAMA) that’s sharper than a Wall Street shark’s tooth. No voodoo, no fluff—just raw, volatility-adaptive math that dances with the market’s rhythm. It zips through trending rockets and chills in choppy waters, slashing false signals like a samurai. Not laggy like the others - this thing is the real deal!
Core Mechanics:
• Efficiency Ratio (ER): Reads the market’s pulse (0-1). High ER = turbo-charged MA, low ER = smooth operator.
• Adaptive Smoothing: Mixes fast (default power 2) and slow (default 30) constants to match market mood swings.
• Trend Signals: KAMA climbs = blue uptrend (bulls run wild). KAMA dips = yellow downtrend (bears take over). Flat = gray snooze-fest.
• Alerts: Instant pings on flips—“Trend Flip Up” for long plays, “Down” for shorts. Plug into bots for set-and-forget domination.
Why It Crushes:
• Smokes static MAs in volatile arenas (crypto, stocks, you name it). Backtests show 20-30% fewer fakeouts than SMA50.
• Visual Pop: Overlays price with bold blue/yellow signals. Slap it on BTC 1D to see trends light up like Times Square.
• Tweakable: Dial ER length (default 50) to your timeframe. Short for scalps, long for swing trades.
Example Settings in Action:
• 10s Chart (Hyper-Scalping): Set Source: Close, ER Length: 100, Fast Power: 1, Slow Power: 6. Catches micro-trends in crypto like a heat-seeking missile. Blue/yellow flips scream entry/exit on fast moves.
• 2m Chart (Quick Trades): Set Source: Close, ER Length: 14, Fast Power: 1, Slow Power: 6. Perfect for rapid trend shifts in stocks or forex. Signals align with momentum bursts—check historical flips for proof.
Deployment:
• Drop it on any chart. Backtest settings to match your asset’s volatility—tweak until it sings.
• Pair with RSI or volume spikes for killer confirmation. Pro move: Enter on flip + volume pop, exit on reverse.
• Strategy-Ready: Slap long/short logic on alerts to build a lean, mean trading machine.
Open source from SightLing Labs—grab it, hack it, profit from it. Share your tweaks in the comments and let’s outsmart the market together. Trade hard, win big!
FlowStateTrader FlowState Trader - Advanced Time-Filtered Strategy
## Overview
FlowState Trader is a sophisticated algorithmic trading strategy that combines precision entry signals with intelligent time-based filtering and adaptive risk management. Built for traders seeking to achieve their optimal performance state, FlowState identifies high-probability trading opportunities within user-defined time windows while employing dynamic trailing stops and partial position management.
## Core Strategy Philosophy
FlowState Trader operates on the principle that peak trading performance occurs when three elements align: **Focus** (precise entry signals), **Flow** (optimal time windows), and **State** (intelligent position management). This strategy excels at finding reversal opportunities at key support and resistance levels while filtering out suboptimal trading periods to keep traders in their optimal flow state.
## Key Features
### 🎯 Focus Entry System
**Support/Resistance Zone Trading**:
- Dynamic identification of key price levels using configurable lookback periods
- Entry signals triggered when price interacts with these critical zones
- Volume confirmation ensures genuine breakout/reversal momentum
- Trend filter alignment prevents counter-trend disasters
**Entry Conditions**:
- **Long Signals**: Price closes above support buffer, touches support level, with above-average volume
- **Short Signals**: Price closes below resistance buffer, touches resistance level, with above-average volume
- Optional trend filter using EMA or SMA for directional bias confirmation
### ⏰ FlowState Time Filtering System
**Comprehensive Time Controls**:
- **12-Hour Format Trading Windows**: User-friendly AM/PM time selection
- **Multi-Timezone Support**: UTC, EST, PST, CST with automatic conversion
- **Day-of-Week Filtering**: Trade only weekdays, weekends, or both
- **Lunch Hour Avoidance**: Automatically skips low-volume lunch periods (12-1 PM)
- **Visual Time Indicators**: Background coloring shows active/inactive trading periods
**Smart Time Features**:
- Handles overnight trading sessions seamlessly
- Prevents trades during historically poor performance periods
- Customizable trading hours for different market sessions
- Real-time trading window status in dashboard
### 🛡️ Adaptive Risk Management
**Multi-Level Take Profit System**:
- **TP1**: First profit target with optional partial position closure
- **TP2**: Final profit target for remaining position
- **Flexible Scaling**: Choose number of contracts to close at each level
**Dynamic Trailing Stop Technology**:
- **Three Operating Modes**:
- **Conservative**: Earlier activation, tighter trailing (protect profits)
- **Balanced**: Optimal risk/reward balance (recommended)
- **Aggressive**: Later activation, wider trailing (let winners run)
- **ATR-Based Calculations**: Adapts to current market volatility
- **Automatic Activation**: Engages when position reaches profitability threshold
### 📊 Intelligent Position Sizing
**Contract-Based Management**:
- Configurable entry quantity (1-1000 contracts)
- Partial close quantities for profit-taking
- Clear position tracking and P&L monitoring
- Real-time position status updates
### 🎨 Professional Visualization
**Enhanced Chart Elements**:
- **Entry Zone Highlighting**: Clear visual identification of trading opportunities
- **Dynamic Risk/Reward Lines**: Real-time TP and SL levels with price labels
- **Trailing Stop Visualization**: Live tracking of adaptive stop levels
- **Support/Resistance Lines**: Key level identification
- **Time Window Background**: Visual confirmation of active trading periods
**Dual Dashboard System**:
- **Strategy Dashboard**: Real-time position info, settings status, and current levels
- **Performance Scorecard**: Live P&L tracking, win rates, and trade statistics
- **Customizable Sizing**: Small, Medium, or Large display options
### ⚙️ Comprehensive Customization
**Core Strategy Settings**:
- **Lookback Period**: Support/resistance calculation period (5-100 bars)
- **ATR Configuration**: Period and multipliers for stops/targets
- **Reward-to-Risk Ratios**: Customizable profit target calculations
- **Trend Filter Options**: EMA/SMA selection with adjustable periods
**Time Filter Controls**:
- **Trading Hours**: Start/end times in 12-hour format
- **Timezone Selection**: Four major timezone options
- **Day Restrictions**: Weekend-only, weekday-only, or unrestricted
- **Session Management**: Lunch hour avoidance and custom periods
**Risk Management Options**:
- **Trailing Stop Modes**: Conservative/Balanced/Aggressive presets
- **Partial Close Settings**: Enable/disable with custom quantities
- **Alert System**: Comprehensive notifications for all trade events
### 📈 Performance Tracking
**Real-Time Metrics**:
- Net profit/loss calculation
- Win rate percentage
- Profit factor analysis
- Maximum drawdown tracking
- Total trade count and breakdown
- Current position P&L
**Trade Analytics**:
- Winner/loser ratio tracking
- Real-time performance scorecard
- Strategy effectiveness monitoring
- Risk-adjusted return metrics
### 🔔 Alert System
**Comprehensive Notifications**:
- Entry signal alerts with price and quantity
- Take profit level hits (TP1 and TP2)
- Stop loss activations
- Trailing stop engagements
- Position closure notifications
## Strategy Logic Deep Dive
### Entry Signal Generation
The strategy identifies high-probability reversal points by combining multiple confirmation factors:
1. **Price Action**: Looks for price interaction with key support/resistance levels
2. **Volume Confirmation**: Ensures sufficient market interest and liquidity
3. **Trend Alignment**: Optional filter prevents counter-trend positions
4. **Time Validation**: Only trades during user-defined optimal periods
5. **Zone Analysis**: Entry occurs within calculated buffer zones around key levels
### Risk Management Philosophy
FlowState Trader employs a three-tier risk management approach:
1. **Initial Protection**: ATR-based stop losses set at strategy entry
2. **Profit Preservation**: Trailing stops activate once position becomes profitable
3. **Scaled Exit**: Partial profit-taking allows for both security and potential
### Time-Based Edge
The time filtering system recognizes that not all trading hours are equal:
- Avoids low-volume, high-spread periods
- Focuses on optimal liquidity windows
- Prevents trading during news events (lunch hours)
- Allows customization for different market sessions
## Best Practices and Optimization
### Recommended Settings
**For Scalping (1-5 minute charts)**:
- Lookback Period: 10-20
- ATR Period: 14
- Trailing Stop: Conservative mode
- Time Filter: Major session hours only
**For Day Trading (15-60 minute charts)**:
- Lookback Period: 20-30
- ATR Period: 14-21
- Trailing Stop: Balanced mode
- Time Filter: Extended trading hours
**For Swing Trading (4H+ charts)**:
- Lookback Period: 30-50
- ATR Period: 21+
- Trailing Stop: Aggressive mode
- Time Filter: Disabled or very broad
### Market Compatibility
- **Forex**: Excellent for major pairs during active sessions
- **Stocks**: Ideal for liquid stocks during market hours
- **Futures**: Perfect for index and commodity futures
- **Crypto**: Effective on major cryptocurrencies (24/7 capability)
### Risk Considerations
- **Market Conditions**: Performance varies with volatility regimes
- **Timeframe Selection**: Lower timeframes require tighter risk management
- **Position Sizing**: Never risk more than 1-2% of account per trade
- **Backtesting**: Always test on historical data before live implementation
## Educational Value
FlowState serves as an excellent learning tool for:
- Understanding support/resistance trading
- Learning proper time-based filtering
- Mastering trailing stop techniques
- Developing systematic trading approaches
- Risk management best practices
## Disclaimer
This strategy is for educational and informational purposes only. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Users should thoroughly backtest the strategy and understand all risks before live trading. Always use proper position sizing and never risk more than you can afford to lose.
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*FlowState Trader represents the evolution of systematic trading - combining classical technical analysis with modern risk management and intelligent time filtering to help traders achieve their optimal performance state through systematic, disciplined execution.*
Realized Volatility (StdDev of Returns, %)📌 Realized Volatility (StdDev of Returns, %)
This indicator measures realized volatility directly from price returns, instead of the common but misleading approach of calculating standard deviation around a moving average.
🔹 How it works:
Computes close-to-close log returns (the most common way volatility is measured in finance).
Calculates the standard deviation of these returns over a chosen lookback period (default = 200 bars).
Converts results into percentages for easier interpretation.
Provides three key volatility measures:
Daily Realized Vol (%) – raw standard deviation of returns.
Annualized Vol (%) – scaled by √250 trading days (market convention).
Horizon Vol (%) – volatility over a custom horizon (default = 5 days, i.e. weekly).
🔹 Why use this indicator?
Shows true realized volatility from historical returns.
More accurate than measuring deviation around a moving average.
Useful for traders analyzing risk, position sizing, and comparing realized vs implied volatility.
⚠️ Note:
It is best used on the Daily Chart!
By default, this uses log returns (which are additive and standard in quant finance).
If you prefer, you can easily switch to simple % returns in the code.
Volatility estimates depend on your chosen lookback length and may vary across timeframes.
Vesperis v8.1 by JaeheeVesperis v8.1 by Jaehee
Overview
This script is a short-side trading strategy designed for trend-following conditions where bearish momentum aligns across multiple independent filters. It does not aim to predict tops or bottoms. Instead, it waits for confirmation that the market has entered a strong downtrend and then manages trades with structured risk controls.
Core Components
The strategy combines several classical concepts but applies them in a multi-filter consensus framework to reduce false signals:
• SSL Hybrid Filter → Defines directional bias using an EMA-based signal line
• MOBO Bands (modified Bollinger framework) → Measures volatility compression and breakout expansion
• EMA 20/50/100 Alignment → Confirms bearish structure when shorter averages remain under longer ones
• ADX Strength Gate → Trades are permitted only when trend strength (Wilder’s ADX) is above a chosen threshold
• Heikin Ashi Smoothing → Provides visual clarity and reduces noise in trend recognition
• Cooldown Rule → After a losing trade, the system waits a configurable number of bars before re-entry to enforce discipline
Risk Management
• Take-Profit (TP) and Stop-Loss (SL) are dynamically attached to each entry
• TP and SL are ratio-based relative to the entry price
• Cooldown logic prevents immediate re-entries after losses
• Position sizing is based on percentage of equity, with commissions factored in for realistic simulation
Visualization
• EMA 20/50/100 ribbon with soft gradient colors
• MOBO band plotted with contrasting tones for clarity
• SSL baseline overlay
• ADX values displayed every 10 bars for contextual strength
• Background shading highlights bullish vs bearish trend regimes
• Heikin Ashi candle coloring for directional bias emphasis
Why This Combination?
Each component addresses a different market dimension:
• Direction (SSL, EMA alignment)
• Volatility & Breakout Context (MOBO Bands)
• Strength (ADX filter)
• Trade Discipline (Cooldown rule)
When layered together, they reduce the chance of acting on a single misleading condition. For example, a close under MOBO support is acted upon only if ADX confirms strong momentum and EMA structure validates a broader bearish regime. This multi-gate approach balances selectivity with responsiveness, aiming for consistent entries during trending phases rather than over-trading in sideways conditions.
Important Notes
• This script is a strategy, not just an indicator. It performs backtestable entries and exits within TradingView’s framework
• Default properties include realistic assumptions: commission, slippage approximation, and percentage-based position sizing
• Results will vary by market and timeframe; this tool does not guarantee outcomes and should be combined with independent risk management
• Invite-only access ensures controlled distribution
Compliance with TradingView House Rules
• No external links, promotions, or contact information
• Clear explanation of what, how, and why without revealing full code logic
• Highlights originality: consensus-based filter design with combined ADX, SSL, MOBO, EMA gating
• Provides conceptual and educational value to traders while remaining distinct from classic single-element scripts
Range Percent Histogram📌 Range Percent Histogram – Indicator Description
The Range Percent Histogram is a custom indicator that behaves like a traditional volume histogram, but instead of showing traded volume it displays the percentage range of each candle.
In other words, the height of each bar represents how much the price moved (in percentage terms) within that candle, from its low to its high.
🔧 What it shows
The indicator has two main components:
Component Description
Histogram Bars Columns plotted in red or green depending on the candle direction (green = bullish candle, red = bearish). The height of each bar = (high - low) / low * 100. That means a candle that moved, for example, 1 % from its lowest point to its highest point will show a bar with 1 % height.
Moving Average (optional) A 20-period Simple Moving Average applied directly to the bar values. It can be turned ON/OFF via a checkbox and helps you detect whether current range activity is above or below the average range of the past candles.
⚙️ How it works
Every time a new candle closes, the indicator calculates its range and converts it into a percentage.
This value is drawn as a column under the chart.
If the closing price is above the opening price → the bar is green (bullish range).
If the closing price is below the opening price → the bar is red (bearish range).
When the Show Moving Average option is enabled, a smooth line is plotted on top of the histogram representing the average percentage range of the last 20 candles.
📈 How to use it
This indicator is very helpful for detecting moments of range expansion or contraction.
One powerful way to use it is similar to a volume exhaustion / low-volume pattern:
Situation Interpretation
Consecutive bars with very low height Price is in a period of low volatility → possible accumulation or "pause" phase.
A sudden large bar after a series of small ones Indicates a strong pickup in volatility → often marks the start of a new impulse in the direction of the breakout.
Auto Fib V2Auto Fib V2 — Advanced Fibonacci Mapping Tool
Introduction
Auto Fib V2 is an advanced Fibonacci retracement indicator that automatically adapts to recent market ranges. Rather than manually drawing Fibonacci lines, this script dynamically maps them based on the most recent highs and lows, allowing traders to see the chart as if it were a "navigation map." Its primary purpose is to help identify potential buy and sell zones with greater clarity.
Key Concept
The script is built on a simple but powerful interpretation of Fibonacci retracement:
When the price moves below the 0.236 level, it suggests an oversold zone, where buyers may step in and market reversal potential increases.
When the price rises above the 0.764 level, it highlights an overbought zone, where sellers may become more active and risk of reversal grows.
Between these extremes, the Golden Pocket (0.382–0.618 zone) is highlighted as the area where institutional traders and algorithms often react. Historically, this is one of the most respected Fibonacci areas in technical analysis.
Features & Customization
Automatic Range Detection: The indicator automatically finds the recent high/low (based on user-defined lookback bars) and applies Fibonacci levels.
Flexible Direction Setting: Traders can use Auto Mode to let the script decide direction from price movement, or manually choose upward/downward mapping.
Multiple Levels Display: Beyond the standard levels, extra fractional retracements (0.146, 0.309, 0.441, etc.) are included for more precise mapping.
Golden Pocket Highlighting: Visually emphasizes the 0.382–0.618 retracement zone for quick recognition.
Custom Styles: Switch between line-based and dot-based plotting, with adjustable colors and transparency for improved readability.
Practical Use
Auto Fib V2 is not intended as a direct buy/sell signal generator, but as a contextual guide. Traders can use it to:
Confirm whether the current price area is closer to an overbought or oversold condition.
Combine it with oscillators (RSI, MACD) or trend indicators (EMA, ADX) to strengthen trading decisions.
Identify confluence zones where Fibonacci levels overlap with key supports/resistances.
Quickly adapt to market shifts without the need to redraw Fibonacci retracement lines repeatedly.
Why Use Auto Fib V2?
Manual Fibonacci drawing can be subjective, often depending on the swing points a trader chooses. Auto Fib V2 reduces that subjectivity by using consistent logic, creating a more systematic approach. For intraday traders, it provides rapid context to assess whether the market is stretched or balanced. For swing traders, it offers a map of reaction zones across higher timeframes.
Machine Learning BBPct [BackQuant]Machine Learning BBPct
What this is (in one line)
A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system.
Background: %B in plain terms
Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes.
Why add (simplified) KNN?
Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas:
• Feature vector . Each bar is summarized by up to five normalized features:
– %B itself (normalized)
– Band width (volatility proxy)
– Price momentum (ROC)
– Volume momentum (ROC of volume)
– Price position within the bands
• Distance metric . Euclidean distance ranks the most similar recent bars.
• Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance.
• Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence.
This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration.
How the script is organized (by input groups)
1) BBPct Settings
• Price Source – Which price to evaluate (%B is computed from this).
• Calculation Period – Lookback for SMA basis and standard deviation.
• Multiplier – Standard deviation width (e.g., 2.0).
• Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B.
2) Thresholds
• Overbought/Oversold – Default 0.8 / 0.2 (inside ).
• Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions.
3) KNN Machine Learning
• Enable KNN – Switch between pure %B and hybrid.
• K (neighbors) – How many historical analogs to blend (default 8).
• Historical Period – Size of the search window for neighbors.
• ML Weight – Blend between raw %B and KNN estimate.
• Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows.
4) Filtering
• Method – None, Adaptive, Kalman-style (first-order),
or Hull smoothing.
• Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate.
5) Performance Tracking
• Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest).
• Early Entry Lookback – Horizon for forecasting a potential threshold cross.
• Profit Target / Stop Loss – Used only by the internal win-rate heuristic.
6) Self-Optimization
• Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes).
• Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is.
• Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3).
7) UI Settings
• Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays.
• Signal Line Width, Candle Painting, Colors – Visual preferences.
Step-by-step logic
A) Compute %B
Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev.
%B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB .
B) Build the feature vector
All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5).
C) Find nearest neighbors
For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K .
D) Predict and blend
Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient.
E) Adaptive thresholds
Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes.
F) Early entry heuristic
A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself.
G) Informational win-rate
The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest.
Outputs and visual language
• ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering.
• Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline.
• Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes.
• ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7.
• Early arrows – Optional small triangles for approaching OB/OS.
• Candle painting – Light green above the midline, light red below (optional).
• Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed.
Signal classification (informational)
The indicator does not fire trade commands; it labels state:
• STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds.
• BUY / SELL – finalBB beyond adaptive OS/OB.
• EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence.
• NEUTRAL – between adaptive bands.
Alerts (what you can automate)
• Entering adaptive OB/OS and extreme OB/OS.
• Midline cross (0.5).
• Overfitting detected (frequent parameter flipping).
• Early signals when early confidence > 0.7.
These are purely descriptive triggers around the indicator’s state.
Practical interpretation
• Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B.
• Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts.
• Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag.
• Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools.
• Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop.
Methodological notes
• Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that.
• Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts.
• Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias.
• Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA.
• Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator.
• Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative.
Limitations and cautions
• Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks).
• Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare.
• Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail.
• Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest.
• Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives.
Tuning guide
• Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength.
• Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest.
• Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges.
• Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes.
How to use it responsibly
Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation.
Summary
Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
VSA - The Volume HUDVSA Volume HUD: Your At-a-Glance Volume Dashboard
Tired of cluttered charts with multiple indicators taking up screen space?
The VSA Volume HUD is a clean, powerful, and fully customisable Heads-Up Display that puts all the critical volume and price action data you need into one compact box, right on your chart.
Designed for traders who rely on Volume Spread Analysis (VSA), this tool helps you instantly gauge the strength, conviction, and context behind every price move as it happens.
Key Features
This indicator isn't just about showing the current volume; it provides a comprehensive, real-time analysis of the market's activity.
Real-time VSA Dashboard: A persistent on-screen table that updates with every tick, giving you instant feedback without needing to look away from the price. The HUD is fully draggable (hold Ctrl/Cmd + click and drag) to place it anywhere you like.
Essential Volume Metrics:
Current Volume: Displayed in a clean, abbreviated format (e.g., 1.25M for millions, 54.3K for thousands).
% Change (vs. Previous Bar): Instantly see if volume is expanding or contracting.
Vs Short-Term Average: Compare the current bar's volume to a moving average to spot unusual spikes.
Volume Velocity: Measures the rate of change in volume over a short period, helping you spot acceleration or deceleration in market interest.
Relative Volume (RVOL): See how the current volume compares to the average for that specific time of day, perfect for identifying abnormally high or low activity.
Price Action & Volatility Context:
Range vs. ATR: Quickly determine if the current bar's volatility is expanding or contracting compared to the recent average.
Price vs. VWAP: See how far the current price has deviated from the session's Volume-Weighted Average Price, a key level for institutional traders.
Deep Customization is Key
Tailor the HUD to perfectly match your trading style and chart aesthetic.
Display & Layout:
Compact Mode: Remove the metric labels for a sleek, minimalist view that saves screen space.
Bar Meters: Enable optional visual bars next to key metrics for a quick, graphical representation of strength.
Total Control: Toggle every single metric on or off to build the exact dashboard you need. Adjust text size, position, and background opacity with ease.
Smart Coloring & Visual Alerts:
Advanced VSA Coloring: This isn't just about up/down candles. The script intelligently colors volume based on confluence. It highlights increasing volume on a strong up-bar (bullish confirmation) or increasing volume on a down-bar (potential climax or distribution), giving you a deeper VSA context.
High Volume Highlight: Make standout bars impossible to miss! The entire HUD background can change color automatically when volume surges past a custom threshold (e.g., over 150% of the average), instantly drawing your attention to critical moments.
Full Color Customization: Change every color to match your chart's theme, including separate colors for bullish/bearish moves, the background, and the border.
How to Use It
The VSA Volume HUD is a powerful confirmation tool. Use it to:
Confirm Breakouts: Look for a spike in Volume vs. Average and RVOL as price breaks a key level.
Spot Exhaustion: Notice high volume on a narrow-range candle after a long trend, visible through the Range/ATR metric.
Gauge Conviction: Use the Advanced Coloring to see if volume is supporting the price move (e.g., green volume on a green candle) or diverging from it.
Gemini All-in-OneDescription
The Gemini AIO (All-in-One) is a comprehensive overlay indicator designed for swing and position traders. It merges three distinct and powerful trading strategies into a single, cohesive tool to identify high-probability setups in stocks that are in confirmed uptrends.
What the Indicator Does:
Combines Three Strategies: Integrates a multi-scanner breakout system, a mean-reversion model, and a multi-year breakout tool into one indicator.
Main Modules
Signals Module:
1. Features six unique scanner signals (CS1-CS6) to identify a variety of bullish consolidation patterns.
2. Includes a full trade management framework with RVC (Red Volume Candle), PBP (Post Breakout Pivot Entry), and ISL (Initial Stop Loss) levels.
3. Identifies powerful Episodic Pivot (EP) and EP Entry (EPE) signals for stocks showing exceptional strength.
Reversal Module:
1. A mean-reversion strategy that primarily uses Bollinger Bands to find oversold conditions.
2. Provides a three-stage signal process: RA (Reversal Setup), Entry 1, and Entry 2 to time entries from a potential bottom.
Multi-Year Breakout (MYBO) Module:
1. Automatically identifies and plots historical, multi-year resistance and support levels.
2. Generates a clear signal when the price breaks out above these significant long-term levels.
Advanced Alerts: Features a highly customizable alert system that can be timed to trigger either on the bar's close or at a specific time of day (e.g., 2:30 PM IST), allowing for end-of-day style notifications.
How to Best Use It:
This indicator is most powerful when used with a systematic, rules-based approach. The core principle is to use long-term moving averages to define the trend and then use the indicator's signals to time entries within that trend.
The Foundation (Trend Filter): The most important rule is to only consider long setups on stocks where the 150-day SMA is above the 200-day EMA, and the 150-day SMA is sloping upwards. This keeps you aligned with the primary uptrend.
Strategy 1: The Momentum Breakout (PBP Entry)
1. Confirm the stock meets the primary trend filter rules.
2. Wait for an AIO setup signal (Super, Pls Buy, etc.) to draw a PBP line.
3. Enter when the price crosses above the PBP line or wait for a pull back after the price has crossed the PBP line.
Strategy 2: The Mean Reversion (RA Entry)
1. Confirm the stock meets the primary trend filter rules.
2. Wait for an "RA" (Reversal Setup) signal to appear on the chart.
3. Enter on the "ENTRY 1" (Risky Entry) or "ENTRY 2" signal (Safer Entry) or wait for a pull back after "ENTRY 1" or "ENTRY 2" signal.
Strategy 3: Multi-Year Breakout (MYBO) :
1. A breakout triangle (orange or fuchsia) appears below the candle, signaling a close above the "Recent High" (Orange) or "Older High" (Fuchsia).
2. Recent High refers to the highest price the stock has reached in last 12 months. Breaking above the "Recent High" is a sign of strong current demand.
3. Older High refers to the highest price the stock reached in a more distant, historical period - the period between 5 years ago and 1 year ago. Breaking above the "Older High" is a sign of VERY strong demand as it has broken a historic high.
4. Wait for a breakout triangle to appear on the chart.
5. Enter on the high of the candle marked with a breakout triangle or wait for a pull back after that signal.
Customize Your View: Use the "Inputs" tab to enable/disable the modules you want to focus on and configure the alerts you want to receive. Use the "Style" tab to hide any visual elements you don't need to keep your chart clean.
Transfer Function Filter [theUltimator5]The Transfer Function Filter is an engineering style approach to transform the price action on a chart into a frequency, then filter out unwanted signals using Butterworth-style filter approach.
This indicator allows you to analyze market structure by isolating or removing different frequency components of price movement—similar to how engineers filter signals in control systems and electrical circuits.
🔎 Features
Four Filter Types
1) Low Pass Filter – Smooths price data, highlighting long-term trends while filtering out short-term noise. This filter acts similar to an EMA, removing noisy signals, resulting in a smooth curve that follows the price of the stock relative to the filter cutoff settings.
Real world application for low pass filter - Used in power supplies to provide a clean, stable power level.
2) High Pass Filter – Removes slow-moving trends to emphasize short-term volatility and rapid fluctuations. The high pass filter removes the "DC" level of the chart, removing the average price moves and only outputting volatility.
Real world application for high pass filter - Used in audio equalizers to remove low-frequency noise (like rumble) while allowing higher frequencies to pass through, improving sound clarity.
3) Band Pass Filter – Allows signals to plot only within a band of bar ranges. This filter removes the low pass "DC" level and the high pass "high frequency noise spikes" and shows a signal that is effectively a smoothed volatility curve. This acts like a moving average for volatility.
Real world application for band pass filter - Radio stations only allow certain frequency bands so you can change your radio channel by switching which frequency band your filter is set to.
4) Band Stop Filter – Suppresses specific frequency bands (cycles between two cutoffs). This filter allows through the base price moving average, but keeps the high frequency volatility spikes. It allows you to filter out specific time interval price action.
Real world application for band stop filter - If there is prominent frequency signal in the area which can cause unnecessary noise in your system, a band stop filter can cancel out just that frequency so you get everything else
Configurable Parameters
• Cutoff Periods – Define the cycle lengths (in bars) to filter. This is a bit counter-intuitive with the numbering since the higher the bar count on the low-pass filter, the lower the frequency cutoff is. The opposite holds true for the high pass filter.
• Filter Order – Adjust steepness and responsiveness (higher order = sharper filtering, but with more delay).
• Overlay Option – Display Low Pass & Band Stop outputs directly on the price chart, or in a separate pane. This is enabled by default, plotting the filters that mimic moving averages directly onto the chart.
• Source Selection – Apply filters to close, open, high, low, or custom sources.
Histograms for Comparison
• BS–LP Histogram – Shows distance between Band Stop and Low Pass filters.
• BP–HP Histogram – Highlights differences between Band Pass and High Pass filters.
Histograms give the visualization of a pseudo-MACD style indicator
Visual & Informational Aids
• Customizable colors for each filter line.
• Optional zero-line for histogram reference.
• On-chart info table summarizing active filters, cutoff settings, histograms, and filter order.
📊 Use Cases
Trend Detection – Use the Low Pass filter to smooth noise and follow underlying market direction.
Volatility & Cycle Analysis – Apply High Pass or Band Pass to capture shorter-term patterns.
Noise Suppression – Deploy Band Stop to remove specific choppy frequencies.
Momentum Insight – Watch the histograms to spot divergences and relative filter strength.
Nasdaq Sentiment DashboardBuilds a composite sentiment state — RISK-ON / NEUTRAL / RISK-OFF — using three legs:
Volatility: CBOE VXN vs its moving average and absolute thresholds (risk-on when low & below MA; risk-off when high & above MA).
Breadth (quality of participation): QQEW/QQQ ratio vs its MA (equal-weight beating cap-weight = healthier breadth).
Advance/Decline (intraday breadth): advdec.nq vs its MA, with a magnitude filter (ignores tiny A/D days).
How it works
Pulls each series on your chosen signal timeframe (default Daily).
Creates binary signals per leg:
Vol: volOn if VXN < MA and < vxnLower; volOff if VXN > MA and > vxnUpper.
Breadth: brOn if QQEW/QQQ is above its MA by a deadband; brOff if below.
A/D: adOn if A/D > MA and above adMin; adOff if below MA and < -adMin.
Scores each leg (+1 on, −1 off, 0 neutral) → sums to −3…+3.
State rule (default): RISK-ON if score ≥ +2, RISK-OFF if ≤ −2, else NEUTRAL (i.e., need 2 of 3 to agree).
Detects flips (changes in state) and provides alert conditions that fire only on the flip bar.
What you see
Lines for VXN & MA, QQEW/QQQ & MA, A/D & MA.
Background color shows current composite state.
Triangle markers on the flip bar (up for ON, down for OFF).
A top-right table summarizing state, each leg vs its MA, and the composite score.
How to tune
Vol thresholds: vxnLower / vxnUpper.
Breadth whipsaw control: deadbandBps around the ratio’s MA.
A/D sensitivity: adMin and adMaLen.
Stricter regime: require all 3 to agree by changing the state line to score == 3 / -3.
ATR Stoploss 15m with EMA Trend 1H - Dotted Fixeduse this as a basic ATR stoploss. It uses 100 and 20 EMA on 1hr to determine trend.
Scalp Sense AI# Scalp Sense AI (No Repaint)
**Adaptive trend & reversal detector with an AI-driven score, multi-timeframe confirmations, robust volume filters, and a purpose-built Scalping Mode.**
Signals are generated **only on bar close** (no repaint), include structured alert payloads for webhooks, and come with optional ATR-based TP/SL visualization for study and validation.
---
## What it is (in one paragraph)
**Scalp Sense AI** combines classic market structure (DI/ADX, EMA, SMA, Keltner, ATR) with a continuous **AI Score** that fuses RSI normalization, EMA distance (in ATR units), and DI edge into a single, volatility-aware signal. It adaptively gates **trend** and **reversal** entries, applies **HTF confirmation** without lookahead, and enforces **guard rails** (e.g., strong-trend reversal blocking) unless a high-confidence AI override and volume confirmation are present. **Scalping Mode** compresses reaction times and adds micro price-action cues (wick rejections, micro-EMA crosses, small engulfing) to surface more—but disciplined—opportunities.
---
## Non-Repainting Design
* All signals, markers, state, and alerts are computed **after bar close** using `barstate.isconfirmed`.
* HTF data are requested with `lookahead_off`.
* No “future-peeking” constructs are used.
* Result: signals do **not** change after the candle closes.
---
## How the engine works (pipeline overview)
1. **Base metrics**
* **RSI**, **EMA**, **ATR** (+ ATR SMA for regime/volatility), **SMA long & short**, **Keltner** (EMA ± ATR×mult).
* **Manual DI/ADX** for fine control (DM+, DM−, true range smoothing).
2. **Volatility regime**
* Compares ATR to its SMA and scales thresholds by √(ATR/ATR\_SMA) → robust “high\_vol” gating.
3. **Volume & flow**
* **Volume Z-score**, **OBV slope**, and **MFI** (all computed manually) to confirm impulses and filter weak reversals.
4. **Higher-Timeframe confirmation (optional)**
* Imports HTF **PDI/MDI/ADX** and **SMA** (no lookahead) to require alignment when enabled.
5. **AI Score**
* Weighted fusion of **RSI (normalized around 0)**, **EMA distance (in ATR)**, and **DI edge**.
* Smoothed; then its **mean (μ)** and **volatility (σ)** are estimated to form **adaptive bands** (hi/lo), with optional **hysteresis**.
* **Debounce** (M in N bars) avoids flicker; **bias state** persists until truly invalidated.
6. **Signal logic**
* **Trend entries** require AI bias + trend confirmations (DI/ADX/SMA, HTF if enabled), volatility OK, and **anti-breakout** filter.
* **Reversal entries** come in **core**, **early**, and **scalp** flavors (progressively more frequent), guarded by strong-trend blocks that an **AI+volume+ADX-cooling override** can bypass.
7. **Scalping Mode**
* Adaptive parameter contraction (shorter lengths), gentler guards, micro-patterns (wick/engulf/micro-EMA cross), and reduced cooldown to increase high-quality opportunities.
8. **Cooldown & state**
* One signal per side after a configurable spacing in bars; internal “last direction” avoids clustering.
9. **Visualization & alerts**
* **Triangles** for trend, **circles** for reversals (offset by ATR to avoid overlap).
* **Single-line alert payload** (BUY/SELL, reason, AI, volZ, ADX) ready for webhooks.
---
## Signals & visualization
* **Trend Long/Short** → triangle markers (above/below) when:
* AI bias aligns with trend confirmations (DI edge, ADX above threshold, price vs long SMA, optional HTF alignment).
* Volatility regime agrees; **anti-breakout** prevents entries exactly at lookback highs/lows.
* **Reversal Long/Short** → circular markers when:
* **Core**: AI near “loose” band, OBV/MFI/volZ supportive, ADX cooling, DI spread relaxed, PA confirms (crosses/div).
* **Early**: anticipatory patterns (Keltner exhaustion, simple RSI “quasi-divergence”).
* **Scalp**: micro-EMA cross, wick rejection, mini-engulfing, with relaxed guards but AI/volume still in the loop.
* **Markers appear only on the bar that actually emitted the signal** (no repaint); offsets use ATR so shapes don’t overlap.
---
## Alerts (ready for webhooks)
Enable “**Any alert() function call**” and you’ll receive compact, single-line payloads once per bar:
```
action=BUY;reason=reversal-early;ai=0.1375;volZ=0.82;adx=27.5
action=SELL;reason=trend;ai=-0.2210;volZ=0.43;adx=31.9
```
* `action`: BUY / SELL
* `reason`: `trend` | `reversal-core` | `reversal-early` | `reversal-scalp`
* `ai`: current smoothed AI Score at signal bar
* `volZ`: volume Z-score
* `adx`: current ADX
---
## Inputs (exhaustive)
### 1) Core Inputs
* **RSI Length (Base)** (`rsi_length_base`, int)
Base RSI lookback. Shorter = more reactive; longer = smoother.
* **RSI Overbought Threshold** (`rsi_overbought`, int)
Informational for context; RSI is used normalized in the AI fusion.
* **RSI Oversold Threshold** (`rsi_oversold`, int)
Informational; complements visual context.
* **EMA Length (Base)** (`ema_length_base`, int)
Primary adaptive mean; also used for Keltner mid and distance metric.
* **ATR Length (Base)** (`atr_length_base`, int)
Volatility unit for Keltner, SL/TP (debug), and regime detection.
* **ATR SMA Length** (`atr_sma_len`, int)
Smooth baseline for ATR regime; supports “high\_vol” logic.
* **ATR Multiplier Base** (`atr_mult_base`, float)
Scales volatility gating (sqrt-scaled); higher = tighter high-vol requirement.
* **Disable Volatility Filter** (`disable_volatility_check`, bool)
Bypass volatility gating if true.
* **Price Change Period (bars)** (`price_change_period_base`, int)
Simple momentum check (+/−% over N bars) used in trend validation.
* **Base Cooldown Bars Between Signals** (`signal_cooldown_base`, int ≥ 0)
Minimum bars to wait between signals (per side).
* **Trend Confirmation Bars** (`trend_confirm_bars`, int ≥ 1)
Require persistence above/below long SMA for this many bars.
* **Use Higher Timeframe Confirmation** (`use_higher_tf`, bool)
Turn on/off HTF alignment (no repaint).
* **Higher Timeframe for Confirmation** (`higher_tf`, timeframe)
E.g., “60” to confirm M15 with H1; used for HTF PDI/MDI/ADX and SMA.
* **TP as ATR Multiple** (`tp_atr_mult`, float)
For **visual debug** only (drawn after entries); not an order manager.
* **SL as ATR Multiple** (`sl_atr_mult`, float)
For visual debug only.
* **Enable Scalping Mode** (`scalping_mode`, bool)
Compresses lengths/thresholds, unlocks micro-PA modules, reduces cooldown.
* **Show Debug Lines** (`show_debug`, bool)
Plots AI bands, DI/ADX, EMA/SMA, Keltner, vol metrics, and TP/SL (debug).
### 2) AI Score & Thresholds
* **AI Score Smooth Len** (`ai_len`, int)
EMA smoothing over the raw fusion.
* **AI Volatility Window** (`ai_sigma_len`, int)
Window to estimate AI mean (μ) and standard deviation (σ).
* **K High (sigma)** (`ai_k_hi`, float)
Upper band width (σ multiplier) for strong threshold.
* **K Low (sigma)** (`ai_k_lo`, float)
Lower band width (σ multiplier) for loose threshold.
* **Debounce Window (bars)** (`ai_debounce_m`, int ≥ 1)
Rolling window length used by the confirm counter.
* **Min Bars>Thr in Window** (`ai_debounce_n`, int ≥ 1)
Minimum confirmations inside the debounce window to validate a state.
* **Use Hysteresis Thresholds** (`ai_hysteresis`, bool)
Requires crossing back past a looser band to exit bias → fewer whipsaws.
* **Weight DI Edge (0–1)** (`ai_weight_di`, float)
Importance of DI edge within the fusion.
* **Weight EMA Dist (0–1)** (`ai_weight_ema`, float)
Importance of EMA distance (in ATR units).
* **Weight RSI Norm (0–1)** (`ai_weight_rsi`, float)
Importance of normalized RSI.
* **Sensitivity (0–1)** (`sensitivity`, float)
Contracts/expands bands (higher = more sensitive).
### 3) Volume Filters
* **Volume MA Length** (`vol_ma_len`, int)
Baseline for volume Z-score.
* **Volume Z-Score Window** (`vol_z_len`, int)
Std-dev window for Z-score; larger = fewer volume “spikes”.
* **Reversal: Min Volume Z for confirm** (`vol_rev_min_z`, float)
Minimum Z required to validate reversals (adaptively relaxed in scalping).
* **OBV Slope Lookback** (`obv_slope_len`, int)
Rising/falling OBV over this window supports bull/bear confirmations.
* **MFI Length** (`mfi_len`, int)
Money Flow Index lookback (manual calculation).
### 4) Filters (Breakout / ADX / Reversal)
* **Enable Breakout Filter** (`enable_breakout_fil`, bool)
Avoid trend entries at lookback highs/lows.
* **Breakout Lookback Bars** (`breakout_lookback`, int ≥ 1)
Window for the anti-breakout guard.
* **Base ADX Length** (`adx_length_base`, int)
Lookback for DI/ADX smoothing (also adapted in Scalping Mode).
* **Base ADX Threshold** (`adx_threshold_base`, float)
Minimum ADX to validate trend context (scaled in Scalping Mode).
* **Enable Reversal Filter** (`enable_rev_filter`, bool)
Master switch for reversal logic.
* **Max ADX for Reversal** (`rev_adx_max`, float)
Hard cap: above this ADX, reversals are blocked (unless overridden by AI if allowed in Guards).
### 5) Reversal Guard (regime protection & overrides)
* **Strong Trend: ADX add-above Thr** (`guard_adx_add`, float)
Extra ADX above `adx_threshold` to mark “strong” trend.
* **Strong Trend: min DI spread** (`guard_spread_min`, float)
Minimum DI separation to consider a trend “dominant”.
* **Require ADX drop from window max (%)** (`guard_adx_drop_min_pct`, float 0–1)
ADX must drop at least this fraction from its window maximum to consider “cooling”.
* **Regime Window (bars)** (`guard_regime_len`, int ≥ 10)
Window over which ADX max is measured for the “cooling” check.
* **EMA Slope Lookback** (`guard_slope_len`, int ≥ 2)
EMA slope horizon used alongside Keltner for strong-trend identification.
* **Keltner Mult (ATR)** (`guard_kc_mult`, float)
Keltner width for strong trend bands and exhaustion checks.
* **HTF Reversal Block Mode** (`htf_block_mode`, string: `Off` | `On` | `AI-controlled`)
* `Off`: never block by HTF.
* `On`: block reversals whenever HTF is strong.
* `AI-controlled`: block **unless** AI+volume+ADX-cooling override criteria are met.
* **AI-controlled: allow AI override** (`ai_htf_override`, bool)
Enables the override mechanism in `AI-controlled` mode.
* **AI override multiplier (vs band\_hi)** (`ai_override_mult`, float)
Strength needed beyond the high band to count as “strong AI”.
* **AI override: min bars beyond strong thr** (`ai_override_min_bars`, int ≥ 1)
Debounce on the override itself.
### 6) Markers
* **Reversal Circle ATR Offset** (`rev_marker_offset_atr`, float ≥ 0)
Vertical offset for reversal circles; trend triangles use a separate (internal) offset.
### 7) Scalping Mode Tuning
* **Reversal aggressiveness (0–1)** (`scalp_rev_aggr`, float)
Higher = looser guards and stronger AI sensitivity.
* **Wick: body multiple (bull/bear)** (`scalp_wick_body_mult`, float)
Wick must be at least this multiple of body to count as rejection.
* **Wick: ATR multiple (min)** (`scalp_wick_atr_mult`, float)
Minimal wick length in ATR units.
* **Micro EMA factor (vs EMA base)** (`scalp_ema_fast_factor`, float 0.2–0.9)
Fast EMA length = base EMA × factor (rounded/int).
* **Relax breakout filter in scalping** (`scalp_breakout_relax`, bool)
Lets more trend entries through in scalping context.
### 8) ICT-style SMA (bases)
* **ICT SMA Long Length (Base)** (`sma_long_len_base`, int)
Long-term baseline for regime/trend.
* **ICT SMA Short1 Length (Base)** (`sma_short1_len_base`, int)
Short baseline for price-action crosses.
* **ICT SMA Short2 Length (Base)** (`sma_short2_len_base`, int)
Companion short baseline used in PA cross checks.
> **Adaptive “effective” values:** When **Scalping Mode** is ON, the script internally shortens multiple lengths (RSI/EMA/ATR/ADX/μσ windows, SMAs) and gently relaxes guards (ADX drop %, DI spread, volume Z, override thresholds), reduces cooldown/confirm bars, and optionally relaxes the breakout filter—so you get **more frequent but still curated** signals.
---
## Plots & debug (optional)
* DI+/DI−, ADX (curr + HTF), EMA, long SMA, Keltner up/down (when strong), AI Score, AI mean, AI bands (hi/lo; low plots only when hysteresis is on), Volume MA and Z-score, and ATR-based TP/SL guide (after entries).
* These are **study aids**; the indicator does not manage trades.
---
## Recommended use
* **Timeframes**:
* Scalping Mode: M1–M15.
* Standard Mode: M15–H1 (or higher).
* **Markets**: Designed for liquid FX, indices, metals, and large-cap crypto.
* **Chart type**: Standard candles recommended (Heikin-Ashi alters inputs and hence signals).
* **Alerts**: Use “Any alert() function call”. Parse the key/value payloads server-side.
---
## Good to know
* **Why some alerts don’t draw shapes retroactively**: markers are drawn **only on** the bar that emitted the signal (no repaint by design).
* **Why a reversal didn’t fire**: strong-trend guards + HTF block may have been active; check ADX, DI spread, Keltner position, EMA slope, and whether AI override criteria were met.
* **Too many / too few signals**: tune **Scalping Mode**, `signal_cooldown_base`, AI bands (`ai_k_hi/lo`, `sensitivity`), volume Z (`vol_rev_min_z`), and guards (`rev_adx_max`, `guard_*`).
---
## Disclaimer
This is an **indicator**, not a strategy or an execution system. It does not place, modify, or manage orders. Markets carry risk—validate on historical data and demo before any live decisions. No performance claims are made.
---
### Version
**Scalp Sense AI v11.5** — Adaptive AI bands with hysteresis/debounce, HTF no-lookahead confirmations, guarded reversal logic with AI override, full volume suite (Z, OBV slope, MFI), anti-breakout filter, and a dedicated Scalping Mode with micro-PA cues.
Mutanabby_AI | ATR+ | Trend-Following StrategyThis document presents the Mutanabby_AI | ATR+ Pine Script strategy, a systematic approach designed for trend identification and risk-managed position entry in financial markets. The strategy is engineered for long-only positions and integrates volatility-adjusted components to enhance signal robustness and trade management.
Strategic Design and Methodological Basis
The Mutanabby_AI | ATR+ strategy is constructed upon a foundation of established technical analysis principles, with a focus on objective signal generation and realistic trade execution.
Heikin Ashi for Trend Filtering: The core price data is processed via Heikin Ashi (HA) methodology to mitigate transient market noise and accentuate underlying trend direction. The script offers three distinct HA calculation modes, allowing for comparative analysis and validation:
Manual Calculation: Provides a transparent and deterministic computation of HA values.
ticker.heikinashi(): Utilizes TradingView's built-in function, employing confirmed historical bars to prevent repainting artifacts.
Regular Candles: Allows for direct comparison with standard OHLC price action.
This multi-methodological approach to trend smoothing is critical for robust signal generation.
Adaptive ATR Trailing Stop: A key component is the Average True Range (ATR)-based trailing stop. ATR serves as a dynamic measure of market volatility. The strategy incorporates user-defined parameters (
Key Value and ATR Period) to calibrate the sensitivity of this trailing stop, enabling adaptation to varying market volatility regimes. This mechanism is designed to provide a dynamic exit point, preserving capital and locking in gains as a trend progresses.
EMA Crossover for Signal Generation: Entry and exit signals are derived from the interaction between the Heikin Ashi derived price source and an Exponential Moving Average (EMA). A crossover event between these two components is utilized to objectively identify shifts in momentum, signaling potential long entry or exit points.
Rigorous Stop Loss Implementation: A critical feature for risk mitigation, the strategy includes an optional stop loss. This stop loss can be configured as a percentage or fixed point deviation from the entry price. Importantly, stop loss execution is based on real market prices, not the synthetic Heikin Ashi values. This design choice ensures that risk management is grounded in actual market liquidity and price levels, providing a more accurate representation of potential drawdowns during backtesting and live operation.
Backtesting Protocol: The strategy is configured for realistic backtesting, employing fill_orders_on_standard_ohlc=true to simulate order execution at standard OHLC prices. A configurable Date Filter is included to define specific historical periods for performance evaluation.
Data Visualization and Metrics: The script provides on-chart visual overlays for buy/sell signals, the ATR trailing stop, and the stop loss level. An integrated information table displays real-time strategy parameters, current position status, trend direction, and key price levels, facilitating immediate quantitative assessment.
Applicability
The Mutanabby_AI | ATR+ strategy is particularly suited for:
Cryptocurrency Markets: The inherent volatility of assets such as #Bitcoin and #Ethereum makes the ATR-based trailing stop a relevant tool for dynamic risk management.
Systematic Trend Following: Individuals employing systematic methodologies for trend capture will find the objective signal generation and rule-based execution aligned with their approach.
Pine Script Developers and Quants: The transparent code structure and emphasis on realistic backtesting provide a valuable framework for further analysis, modification, and integration into broader quantitative models.
Automated Trading Systems: The clear, deterministic entry and exit conditions facilitate integration into automated trading environments.
Implementation and Evaluation
To evaluate the Mutanabby_AI | ATR+ strategy, apply the script to your chosen chart on TradingView. Adjust the input parameters (Key Value, ATR Period, Heikin Ashi Method, Stop Loss Settings) to observe performance across various asset classes and timeframes. Comprehensive backtesting is recommended to assess the strategy's historical performance characteristics, including profitability, drawdown, and risk-adjusted returns.
I'd love to hear your thoughts, feedback, and any optimizations you discover! Drop a comment below, give it a like if you find it useful, and share your results.
Средний дневной ATR (по High–Low)Test v.1
we calculate in % the average ATR passed in 1 day (for 5 days)
The Barking Rat LiteMomentum & FVG Reversion Strategy
The Barking Rat Lite is a disciplined, short-term mean-reversion strategy that combines RSI momentum filtering, EMA bands, and Fair Value Gap (FVG) detection to identify short-term reversal points. Designed for practical use on volatile markets, it focuses on precise entries and ATR-based take profit management to balance opportunity and risk.
Core Concept
This strategy seeks potential reversals when short-term price action shows exhaustion outside an EMA band, confirmed by momentum and FVG signals:
EMA Bands:
Parameters used: A 20-period EMA (fast) and 100-period EMA (slow).
Why chosen:
- The 20 EMA is sensitive to short-term moves and reflects immediate momentum.
- The 100 EMA provides a slower, structural anchor.
When price trades outside both bands, it often signals overextension relative to both short-term and medium-term trends.
Application in strategy:
- Long entries are only considered when price dips below both EMAs, identifying potential undervaluation.
- Short entries are only considered when price rises above both EMAs, identifying potential overvaluation.
This dual-band filter avoids counter-trend signals that would occur if only a single EMA was used, making entries more selective..
Fair Value Gap Detection (FVG):
Parameters used: The script checks for dislocations using a 12-bar lookback (i.e. comparing current highs/lows with values 12 candles back).
Why chosen:
- A 12-bar displacement highlights significant inefficiencies in price structure while filtering out micro-gaps that appear every few bars in high-volatility markets.
- By aligning FVG signals with candle direction (bullish = close > open, bearish = close < open), the strategy avoids random gaps and instead targets ones that suggest exhaustion.
Application in strategy:
- Bullish FVGs form when earlier lows sit above current highs, hinting at downward over-extension.
- Bearish FVGs form when earlier highs sit below current lows, hinting at upward over-extension.
This gives the strategy a structural filter beyond simple oscillators, ensuring signals have price-dislocation context.
RSI Momentum Filter:
Parameters used: 14-period RSI with thresholds of 80 (overbought) and 20 (oversold).
Why chosen:
- RSI(14) is a widely recognized momentum measure that balances responsiveness with stability.
- The thresholds are intentionally extreme (80/20 vs. the more common 70/30), so the strategy only engages at genuine exhaustion points rather than frequent minor corrections.
Application in strategy:
- Longs trigger when RSI < 20, suggesting oversold exhaustion.
- Shorts trigger when RSI > 80, suggesting overbought exhaustion.
This ensures entries are not just technically valid but also backed by momentum extremes, raising conviction.
ATR-Based Take Profit:
Parameters used: 14-period ATR, with a default multiplier of 4.
Why chosen:
- ATR(14) reflects the prevailing volatility environment without reacting too much to outliers.
- A multiplier of 4 is a pragmatic compromise: wide enough to let trades breathe in volatile conditions, but tight enough to enforce disciplined exits before mean reversion fades.
Application in strategy:
- At entry, a fixed target is set = Entry Price ± (ATR × 4).
- This target scales automatically with volatility: narrower in calm periods, wider in explosive markets.
By avoiding discretionary exits, the system maintains rule-based discipline.
Visual Signals on Chart
Blue “▲” below candle: Potential long entry
Orange/Yellow “▼” above candle: Potential short entry
Green “✔️”: Trade closed at ATR take profit
Blue (20 EMA) & Orange (100 EMA) lines: Dynamic channel reference
⚙️Strategy report properties
Position size: 25% equity per trade
Initial capital: 10,000.00 USDT
Pyramiding: 10 entries per direction
Slippage: 2 ticks
Commission: 0.055% per side
Backtest timeframe: 1-minute
Backtest instrument: HYPEUSDT
Backtesting range: Jul 28, 2025 — Aug 17, 2025
Note on Sample Size:
You’ll notice the report displays fewer than the ideal 100 trades in the strategy report above. This is intentional. The goal of the script is to isolate high-quality, short-term reversal opportunities while filtering out low-conviction setups. This means that the Barking Rat Lite strategy is very selective, filtering out over 90% of market noise. The brief timeframe shown in the strategy report here illustrates its filtering logic over a short window — not its full capabilities. As a result, even on lower timeframes like the 1-minute chart, signals are deliberately sparse — each one must pass all criteria before triggering.
For a larger dataset:
Once the strategy is applied to your chart, users are encouraged to expand the lookback range or apply the strategy to other volatile pairs to view a full sample.
💡Why 25% Equity Per Trade?
While it's always best to size positions based on personal risk tolerance, we defaulted to 25% equity per trade in the backtesting data — and here’s why:
Backtests using this sizing show manageable drawdowns even under volatile periods.
The strategy generates a sizeable number of trades, reducing reliance on a single outcome.
Combined with conservative filters, the 25% setting offers a balance between aggression and control.
Users are strongly encouraged to customize this to suit their risk profile.
What makes Barking Rat Lite valuable
Combines multiple layers of confirmation: EMA bands + FVG + RSI
Adaptive to volatility: ATR-based exits scale with market conditions
Clear, actionable visuals: Easy to monitor and manage trades
