Yasser Multiple Inside Bar Breakout SignalsDescription
Yasser Multiple Inside Bar Breakout Signals (Yasser_MIB) is a powerful TradingView indicator designed to detect high-probability breakout setups based on multiple inside bar (MIB) formations. Inside bar breakouts often precede strong market moves, making this tool ideal for traders who rely on price action, volatility compression, and breakout trading strategies.
🔑 Key Features:
✅ Automatic MIB Detection – Identifies and counts consecutive inside bars.
✅ Breakout Signals – Generates BUY/SELL signals upon valid breakout of the mother bar.
✅ Custom Risk:Reward Settings – Adjustable risk-to-reward ratio with built-in Stop Loss (SL) and Take Profit (TP) levels.
✅ ATR-based Stop Loss (Optional) – Dynamic volatility-based risk management.
✅ Trend Filter – Optional EMA filter to trade only in the trend direction.
✅ Visual Clarity – Mother bar levels, inside bar marks, entry/SL/TP lines, and breakout highlights.
✅ Alerts Ready – Receive instant alerts for MIB setups and breakouts.
This indicator is suitable for Forex, Stocks, Indices, Commodities, and Crypto markets across multiple timeframes. Whether you are a trend trader or a breakout trader, Yasser_MIB provides a structured approach to capture explosive market moves with disciplined risk management.
📂 Categories
Indicators
Technical Analysis
Price Action
Breakout Strategies
Risk Management
🏷 Tags
inside bar
multiple inside bar
MIB breakout
price action
mother bar
breakout strategy
trend filter
EMA filter
ATR stop loss
risk reward
forex trading
crypto trading
stocks
commodities
indices
Yasser indicators
Volatilidade
BB Crosses Optimized - [JTCAPITAL]BB Crosses Optimized - is a modified way to use Bollinger Bands combined with volatility filtering (ATR) and flexible smoothing methods for Trend-Following.
The indicator works by calculating in the following steps:
Source Selection & Smoothing
The script begins by letting the user select a preferred price source (default is Close, but options include Open, High, Low, HL2, etc.). This raw input is then passed through a smoothing process.
Multiple smoothing techniques can be chosen: SMA, EMA, HMA, DEMA, TEMA, RMA, and FRAMA. Each method reduces short-term noise differently, ensuring flexibility for traders who prefer faster or slower reaction speeds in trend detection.
Bollinger Band Construction
Once the smoothed source is prepared, Bollinger Bands are calculated. The middle band is a moving average of the smoothed data over the defined BB Period . The upper and lower bands are then generated by adding and subtracting the Standard Deviation × Deviation multiplier . These dynamic bands capture volatility and help define breakout zones.
ATR Volatility Measurement
Parallel to the band calculation, the Average True Range (ATR) is computed over the chosen ATR Period . This measures market volatility. The ATR can optionally act as a filter, refining buy and sell levels so signals adapt to current market conditions rather than being fixed to price alone.
Bollinger Band Signals
-If the smoothed price closes above the upper band, a potential bullish event is marked.
-If the smoothed price closes below the lower band, a potential bearish event is marked.
Trend Line Construction
When a bullish event occurs, the script anchors a trend-following line beneath price. If ATR filtering is enabled, the line is set at Low – ATR , otherwise at the simple Low. Conversely, when a bearish event occurs, the line is anchored above price at High + ATR (or just High without the filter). The line is designed to only move in the direction of the trend—if price action does not exceed the prior value, the previous level is held. This prevents unnecessary whipsaws and keeps the indicator aligned with dominant momentum.
Final Trend Detection
The slope of the trend line defines the trend itself:
-Rising line → bullish trend.
-Falling line → bearish trend.
Visual Output
The indicator plots the trend line with dynamic coloring: Blue for bullish phases, Purple for bearish phases. A subtle filled background area emphasizes the active trend zone for clearer chart interpretation.
Buy and Sell Conditions:
- Buy Signal : Triggered when smoothed price closes above the upper Bollinger Band. Trend line then anchors below price (with or without ATR offset depending on settings).
- Sell Signal : Triggered when smoothed price closes below the lower Bollinger Band. Trend line then anchors above price (with or without ATR offset).
Additional filtering is possible via:
- ATR Toggle : Switch ATR on or off to adapt the strategy to either volatile or steady markets.
- Smoothing Method : Adjust smoothing to speed up or slow down responsiveness.
- Deviation Multiplier : Tight or wide bands adjust the sensitivity of signals.
Features and Parameters:
- Source : Choose between Close, Open, High, Low, HL2, etc.
- Average Type : Options include SMA, EMA, HMA, DEMA, TEMA, RMA, FRAMA.
- ATR Period : Defines how ATR volatility is measured.
- BB Period : Lookback length for Bollinger Band construction.
- Deviation : Multiplier for the standard deviation in Bollinger Bands.
- Smoothing Period : Controls how much the source data is smoothed.
- ATR Filter On/Off : Enables or disables ATR integration in signal calculation.
Specifications:
Smoothing (MA Types)
Smoothing is essential to reduce chart noise. By offering multiple MA choices, traders can balance between lag (SMA, RMA) and responsiveness (EMA, HMA, FRAMA). This flexibility allows the indicator to adapt across asset classes and trading styles.
Bollinger Bands
Bollinger Bands measure price deviation around a moving average. They help identify volatility expansion and contraction. In this script, the bands serve as breakout triggers—price crossing outside suggests momentum strong enough to sustain a trend.
Standard Deviation
Standard Deviation is a statistical measure that quantifies the dispersion of price data around the mean. With a multiplier applied, it creates bands that contain a probabilistic portion of price action. Crossing beyond these suggests a higher likelihood of trend continuation.
ATR (Average True Range)
ATR measures the degree of volatility. Instead of simply reacting to price crossing the bands, ATR ensures the trend line placement adapts to current conditions. In volatile markets, wider buffers prevent premature signals; in calmer markets, tighter placement keeps signals responsive.
Trend Line Logic
The trend line only adjusts in the direction of the trend. If new values do not exceed the prior, the line remains unchanged. This prevents false reversals and makes the line a reliable visual confirmation of trend direction.
Signal Detection
The indicator does not repaint: signals are based on confirmed closes relative to the Bollinger Bands. This makes it more reliable for both live trading and backtesting scenarios.
Visual Enhancements
The use of dual plots and fill shading creates a clearer separation of bullish vs. bearish phases. This helps traders visually align entries and exits without second-guessing.
Enjoy!
Pro BTB Pour Samadi Indicator [TradingFinder] Back To Breakeven🔵 Introduction
The Pro BTB (Professional Back To Breakeven) strategy is one of the most advanced price action setups, designed and taught by Mohammad Ali Poursamadi, an international Iranian trader and a well-known instructor of financial market analysis.
The main logic of this strategy is based on the natural behavior of the market :
Breakout of a key level: Price moves beyond an important support or resistance.
Retest / Back To Breakeven: Price returns to the broken level.
Continuation of the main trend: Entry at this point allows alignment with the dominant market direction.
To better understand Pro BTB, it is necessary to first know the concept of a Spike. A spike refers to a sudden and powerful movement of price in one direction, usually caused by heavy order flow. Such a move creates an Imbalance between buyers and sellers. Because the market does not have enough time to distribute orders fairly, it leaves an Inefficiency on the chart.
The direct result of this process is the formation of a Fair Value Gap (FVG) a gap between candles that shows trades were not distributed evenly. In simple terms: the spike is the cause, and Imbalance, Inefficiency, and FVG are its consequences.
In practice, Pro BTB works effectively in both bullish and bearish structures. In a Bullish Setup, a bullish spike first breaks a resistance level. Then, when price returns to that same level, a safe and low-risk buying opportunity is created. Conversely, in a Bearish Setup, a bearish spike breaks a support level, and when price comes back to the broken level, it provides the best conditions for a short entry. These two examples illustrate how Pro BTB logic provides precise, low-risk entries in both directions of the market.
🔵 How to Use
The Pro BTB (Back To Breakeven) strategy allows traders to enter precisely after price returns to the breakout level; this way the entry aligns with the natural market flow while risk is minimized. In practice, this method is simple yet powerful: first, identify a valid breakout on a key level, then wait for price to return to that level, and finally, take the entry in the direction of the main trend.
🟣 Bullish Setup
When a bullish spike occurs and a key resistance is broken, price usually returns to the same level. This level, now acting as support, provides the best opportunity for a long entry. In this scenario, the stop-loss is placed behind the breakout candle or slightly below the broken level, and the take-profit target should be defined with at least a 1:2 risk-to-reward ratio. With strong momentum, higher targets can also be considered.
🟣 Bearish Setup
In a bearish scenario, a bearish spike breaks a key support. After the breakout, price usually returns to the same level, which now acts as resistance. This creates the best conditions for a short entry. The stop-loss is placed behind the breakout candle or slightly above the broken level, while the take-profit target is set with a risk-to-reward ratio greater than 1:2.
🟣 General Rules of Pro BTB
To apply Pro BTB correctly, several key rules must be followed :
The breakout must be valid and occur on a key level.
Always wait for the retest; do not enter immediately after the breakout.
Entry should only happen when price touches the broken level and shows candlestick confirmation.
The stop-loss (SL) must be placed behind the breakout candle or the broken level.
The take-profit (TP) must always be at least twice the trade risk.
For higher reliability, the breakout should align with the trend on higher timeframes.
🟣 Six Entry Methods in Pro BTB
For greater flexibility, Pro BTB offers six standard entry methods :
Market Entry : Enter immediately at the breakout level.
Limit Order : Place a limit order on the breakout level.
Stop Order : Enter only after confirmation of continuation.
Confirmation Candle : Enter after a confirmation candle closes on the level.
Pattern Entry : Enter based on candlestick patterns such as Pin Bar or Engulfing.
Zone Entry : Enter from a zone instead of an exact point to account for market noise.
🔵 Setting
🟣 Spike Filter | Movement
Minimum Spike Bars : Defines the minimum number of consecutive candles required for a valid spike.
Movement Power : Enables or disables the momentum-based spike filter.
Movement Power Level : Sets the strength threshold; higher values filter out weaker moves and only detect strong spikes.
🟣 Spike Filter | Gap
Gap Filter : Enables or disables the gap filter.
Gap Type : Selects which type of gap should be detected (All Gaps, Significant, Structural, Major).
🟣 Spike Filter | Doji
Doji Tolerance : Defines whether doji candles are allowed within a spike.
Max Doji Body Ratio : Maximum ratio of body-to-total candle size for classifying a candle as a doji.
Max Doji in Spike Ratio : Maximum percentage of doji candles allowed within a spike.
🟣 Position Management
Stop-Loss Threshold : Enables or disables the stop-loss threshold feature.
Stop-Loss Threshold Value : Defines the value of the stop-loss threshold for risk management.
Risk-Reward Ratio : Sets the desired risk-to-reward ratio (e.g., 1:1 or 1:2).
Include SL Threshold in R:R : Determines whether the stop-loss threshold is included in risk-to-reward calculations.
🟣 Display Settings
Display Mode : Chooses between Setup (showing setups) or Signal (showing trade signals).
Show Entry Levels: Displays entry levels on the chart (buy/sell zones) when enabled
Only Display the Last Position : Displays only the most recent position on the chart when enabled.
Setup Width Drawing : Adjusts the visual width of the setup drawings on the chart for better visibility.
🟣 Alert
Alert : Enables alert notifications. When turned on, you can set TradingView alerts to receive notifications once the setup or signal conditions are met
🔵 Conclusion
The Pro BTB (Back To Breakeven) strategy is a smart and structured entry method based on natural market behavior after a breakout and retest of the broken level. It helps traders avoid emotional, high-risk entries by waiting for market confirmation and entering precisely at a point that aligns with the main trend and sits closest to the key level.
The simplicity of its rules, flexibility in entry methods, and a risk-to-reward ratio above 2 have made Pro BTB one of the most popular tools among price action traders. Nevertheless, as with any strategy, it is recommended to practice it in demo accounts or through personal backtesting before applying it to real trading, in order to find the entry conditions that best suit your trading style.
VWAP CloudVWAP Cloud
– Dynamic Fair Value Zones with Standard Deviation Envelopes
This script combines a Volume-Weighted Average Price (VWAP) baseline with standard deviation envelopes to create a dynamic "VWAP Cloud."
The VWAP itself is a widely used fair-value benchmark, showing where trading activity is most concentrated relative to price. By adding volatility-based bands around it, this tool helps traders visualize how far price has moved away from VWAP and whether those deviations may represent normal fluctuations or potential extremes.
🔎 How the Components Work Together
VWAP Midline (optional): Provides the session or rolling fair value reference.
Inner Cloud (±1 standard deviation by default): Highlights areas where price is oscillating near VWAP. This zone often reflects balanced conditions, where price is neither excessively stretched nor deeply discounted relative to volume-weighted value.
Outer Cloud (±2 standard deviations by default): Marks wider volatility extremes. These can be used to study how price reacts to statistically significant deviations from VWAP—whether by consolidating, reverting, or extending trends.
Dynamic Coloring: The cloud adjusts color based on VWAP slope. A rising VWAP is shaded green, suggesting positive momentum, while a falling VWAP is shaded red, suggesting negative momentum. Neutral gray highlights the outer envelope to distinguish extreme zones.
⚙️ Inputs & Customization
Source: Select the price type for VWAP calculation (default: hlc3).
Session Reset: Choose between daily resetting VWAP (common for intraday strategies) or a rolling VWAP (continuous view).
Standard Deviation Lookback: Controls the sample window for volatility calculation.
Band Multipliers: Adjust the width of inner and outer clouds.
Midline Toggle: Show or hide the VWAP midline depending on chart preference.
Custom Colors: Configure bullish, bearish, and neutral shading to match your charting style.
📊 How to Use
Trend Context: Price trading above VWAP generally suggests bullish conditions, while trading below suggests bearish conditions.
Value Zones: The inner cloud helps visualize short-term balance around VWAP.
Volatility Extremes: The outer cloud highlights statistically stretched moves that traders may analyze for either continuation or mean-reversion opportunities.
Scalping, Day Trading, Swing Trading: The tool adapts to different styles, depending on whether you reset VWAP each session or use the rolling version.
⚠️ Notes
This script is for educational purposes only and should be combined with other confluence factors, proper risk management, and a trading plan.
It does not generate buy/sell signals on its own. Instead, it provides a framework to study price behavior relative to a dynamic VWAP-based fair value.
Please clean your chart of unrelated drawings/indicators before applying, so the plotted clouds and midline remain clear.
⚪ Liquidity Spike Marker
Description:
The Liquidity Spike Marker indicator helps to identify abnormal bursts of liquidity in the market. The logic is based on comparing the product of the volume by the minimum candle price (Volume × Low) with the threshold value set by the user.
When the value exceeds the threshold, a white triangle appears under the candle, indicating a possible influx of liquidity. This can help traders pay attention to the key points where large participants may enter the market.
Features:
Displays a placemark (⚪ white triangle) when the threshold is exceeded.
Configurable parameter Volume × Low Threshold.
The ability to set an alert for automatic notification.
A lightweight and minimalistic tool without unnecessary elements.
Note: The indicator is not a trading recommendation. Use it in combination with your own trading system and other analysis methods.
Market Pressure Oscillator█ OVERVIEW
The Market Pressure Oscillator is an advanced technical indicator for TradingView, enabling traders to identify potential trend reversals and momentum shifts through candle-based pressure analysis and divergence detection. It combines a smoothed oscillator with moving average signals, overbought/oversold levels, and divergence visualization, enhanced by customizable gradients, dynamic band colors, and alerts for quick decision-making.
█ CONCEPT
The indicator measures buying or selling pressure based on candle body size (open-to-close difference) and direction, with optional smoothing for clarity and divergence detection between price action and the oscillator. It relies solely on candle data, offering insights into trend strength, overbought/oversold conditions, and potential reversals with a customizable visual presentation.
█ WHY USE IT?
- Divergence Detection: Identifies bullish and bearish divergences to reinforce signals, especially near overbought/oversold zones.
- Candle Pressure Analysis: Measures pressure based on candle body size, normalized to a ±100 scale.
- Signal Generation: Provides buy/sell signals via overbought/oversold crossovers, zero-line crossovers, moving average zero-line crossovers, and dynamic band color changes.
- Visual Clarity: Uses dynamic colors, gradients, and fill layers for intuitive chart analysis.
Flexibility: Extensive settings allow customization to individual trading preferences.
█ HOW IT WORKS?
- Candle Pressure Calculation: Computes candle body size as math.abs(close - open), normalized against the average body size over a lookback period (avgBody = ta.sma(body, len)). - Candle direction (bullish: +1, bearish: -1, neutral: 0) is multiplied by body weight to derive pressure.
- Cumulative Pressure: Sums pressure values over the lookback period (Lookback Length) and normalizes to ±100 relative to the maximum possible value.
- Smoothing: Optionally applies EMA (Smoothing Length) to normalized pressure.
- Moving Average: Calculates SMA (Moving Average Length) for trend confirmation (Moving Average (SMA)).
- Divergence Detection: Identifies bullish/bearish divergences by comparing price and oscillator pivot highs/lows within a specified range (Pivot Length). Divergence signals appear with a delay equal to the Pivot Length.
- Signals: Generates signals for:
Crossing oversold upward (buy) or overbought downward (sell).
Crossing the zero line by the oscillator or moving average (buy/sell).
Bullish/bearish divergences, marked with labels, enhancing signals, especially near overbought/oversold zones.
Dynamic band color changes when the moving average crosses MA overbought/oversold thresholds (green for oversold, red for overbought).
- Visualization: Plots the oscillator and moving average with dynamic colors, gradient fills, transparent bands, and labels, with customizable overbought/oversold levels.
Alerts: Built-in alerts for divergences, overbought/oversold crossovers, and zero-line crossovers (oscillator and moving average).
█ SETTINGS AND CUSTOMIZATION
- Lookback Length: Period for aggregating candle pressure (default: 14).
- Smoothing Length (EMA): EMA length for smoothing the oscillator (default: 1). Higher values smooth the signal but may reduce signal frequency; adjust overbought/oversold levels accordingly.
- Moving Average Length (SMA): SMA length for the moving average (default: 14, minval=1). Higher values make SMA a trend indicator, requiring adjusted MA overbought/oversold levels.
- Pivot Length (Left/Right): Candles for detecting pivot highs/lows in divergence calculations (default: 2, minval=1). Higher values reduce noise but add delay equal to the set value.
- Enable Divergence Detection: Enables divergence detection (default: true).
- Overbought/Oversold Levels: Thresholds for the oscillator (default: 30/-30) and moving average (default: 10/-10). For the moving average, no arrows appear; bands change color from gray to green (oversold) or red (overbought), reinforcing entry signals.
- Signal Type: Select signals to display: "None", "Overbought/Oversold", "Zero Line", "MA Zero Line", "All" (default: "Overbought/Oversold").
- Colors and Gradients: Customize colors for bullish/bearish oscillator, moving average, zero line, overbought/oversold levels, and divergence labels.
- Transparency: Adjust gradient fill transparency (default: 70, minval=0, maxval=100) and band/label transparency (default: 40, minval=0, maxval=100) for consistent visuals.
- Visualizations: Enable/disable moving average, gradients for zero/overbought/oversold levels, and gradient fills.
█ USAGE EXAMPLES
- Momentum Analysis: Observe the MPO Oscillator above 0 for bullish momentum or below 0 for bearish momentum. The SMA, being smoother, reacts slower and can confirm trend direction as a noise filter.
- Reversal Signals: Look for buy triangles when the oscillator crosses oversold upward, especially when the SMA is below the MA oversold threshold and the band turns green. Similarly, seek sell triangles when crossing overbought downward, with the SMA above the MA overbought threshold and the band turning red.
- Using Divergences: Treat bullish (green labels) and bearish (red labels) divergences as reinforcement for other signals, especially near overbought/oversold zones, indicating stronger potential trend reversals.
- Customization: Adjust lookback length, smoothing, and moving average length to specific instruments and timeframes to minimize false signals.
█ USER NOTES
Combine the indicator with tools like Fibonacci levels or pivot points to enhance accuracy.
Test different settings for lookback length, smoothing, and moving average length on your chosen instrument and timeframe to find optimal values.
JDB MA Breakout IndicatorAll credit goes to JDB_Trading . Follow on X.
This indicator visualises one of his strategies.
1. Detecting the dominant moving average.
2. Price is supposed to be at least 70 candles below it for buy signals/40 above for sells.
3. detects break on dominant MA + BB 20,2.
4. Used on W & M timeframes.
5. alerts possible.
Sortable Relative Performance | viResearchSortable Relative Performance | viResearch
Conceptual Foundation and Purpose
The Sortable Relative Performance indicator from viResearch is designed as a multi-asset ranking and comparison system that allows traders to evaluate the relative strength of up to 14 different assets over a user-defined lookback period. Unlike single-symbol indicators, this tool provides a comparative view of performance, making it ideal for traders seeking to understand how assets perform relative to each other within a watchlist, sector, or market segment. The indicator calculates the percentage return of each asset from a chosen starting point and presents the results both graphically and in a sorted, tabular format, helping traders identify outperformers and underperformers at a glance.
Technical Composition and Methodology
At its core, the script calculates the relative performance of each selected asset by comparing its current closing price with the closing price from the lookback period. This performance metric is expressed as a percentage and computed using Pine Script’s request.security() function, allowing for seamless cross-asset analysis within a single pane. Each asset is visually represented as a vertical column, color-coded according to a predefined identity map that reflects common asset branding. The best-performing asset is dynamically labeled on the chart, displaying its name and current return, while a real-time performance table updates and ranks all active assets in descending order based on their return values. The table and columns automatically adjust based on the user’s selection, creating an interactive and responsive comparative dashboard.
Features and Configuration
The indicator includes a customizable date filter, allowing traders to activate the display from a specific start date. This is particularly useful for performance reviews tied to events, such as earnings reports, Fed meetings, or macroeconomic releases. The lookback period is adjustable and determines how far back in time performance is measured, making the tool adaptable to both short-term and long-term strategies. Traders can toggle individual assets on or off, enabling focused analysis on specific coins, stocks, or indices. Up to 14 assets can be analyzed simultaneously, with each one clearly distinguished by unique, branded colors in both the plot and the ranking table. The script intelligently highlights the top performer with a floating label, drawing immediate attention to the strongest asset within the group.
Strategic Use and Application
This indicator is especially valuable for traders employing relative strength or momentum-based strategies. By visualizing asset performance in real time, it becomes easier to rotate capital into strong assets and away from laggards. Whether tracking cryptocurrencies, sectors, or forex pairs, the ability to assess comparative returns without switching charts provides an operational edge. The tool supports portfolio analysis, sector rotation, and cross-market studies, making it suitable for discretionary traders, systematic investors, and even macro analysts looking for a visual breakdown of market behavior.
Conclusion and Practical Value
The Sortable Relative Performance indicator by viResearch delivers a clean and effective way to measure and rank asset performance over time. By combining visual clarity with real-time calculation and dynamic sorting, it offers a powerful lens through which traders can evaluate market leadership and laggard behavior. Its flexibility and modular design ensure it can be integrated into a wide range of strategies and trading styles. Whether you're managing a crypto portfolio or monitoring traditional markets, this tool provides essential insights into where momentum resides and how capital is flowing across assets.
Note: Backtests are based on past results and are not indicative of future performance.
RSI + Volume ConfirmationFOR PRIVATE USE ONLY.
-Use to detect the trend changes based on RSI and Volume
-Both needed to align before putting in any trade entry
-Must understand how to use S&R
-Its not a foolproof. Do not use if you dont understand how to trade.
-Version is currently on BEta testing mode and will update from time to time.
Full credit goes to BOSS/CRC/CBC community
Colby Cheese VWAP Setup [v1.0]🧀 Colby Cheese VWAP Setup
A tribute to Colby’s structural clarity, refined for sniper-grade entries.
🧭 Strategy Overview
This setup blends CHoCH (Change of Character) detection with VWAP deviation bands, EMA stack bias, delta/CVD conviction, and FRVP-based entry zones. It’s designed for traders who value narratable structure, directional conviction, and modular clarity.
🔍 Core Modules
• CHoCH Detection: Identifies structural breaks using swing highs/lows from local or 3-minute feeds.
• VWAP Bands: Dynamic support/resistance zones based on VWAP ± standard deviation.
• EMA Stack Bias: Confirms directional bias using 13/35/50 EMA alignment.
• Delta/CVD Filter: Measures volume aggression and cumulative conviction.
• Strongest Imbalance Logic: Scores recent bars for directional strength using delta, CVD, and price change.
• Engulfing Confirmation (optional): Adds candle strength validation post-CHoCH.
• FRVP Entry Zones: Pullback entries based on recent range extremes—directionally aware.
• Visual Aids: CHoCH lines, candle coloring, entry labels, and optional stop loss markers.
🎯 Trade Logic
• Bullish CHoCH:
• Trigger: Price closes above last swing high
• Filters: Strong body, volume, delta, optional engulfing
• Bias: EMA stack bullish
• Entry: Pullback to bottom of FRVP range
• Visual: Green CHoCH line + “Enter” label
• Bearish CHoCH:
• Trigger: Price closes below last swing low
• Filters: Strong body, volume, delta, optional engulfing
• Bias: EMA stack bearish
• Entry: Pullback to top of FRVP range
• Visual: Red CHoCH line + “Enter” label
🛠 Notes for Overlay Builders
• All modules are toggleable for clarity and experimentation.
• CHoCH logic is atomic and timestamped—ideal for audit trails.
• FRVP zones are now directionally aware (thanks to David’s refinement).
• Imbalance scoring is reversible and narratable—perfect for diagnostic overlays.
Adaptive Market Regime Identifier [LuciTech]What it Does:
AMRI visually identifies and categorizes the market into six primary regimes directly on your chart using a color-coded background. These regimes are:
-Strong Bull Trend: Characterized by robust upward momentum and low volatility.
-Weak Bull Trend: Indicates upward momentum with less conviction or higher volatility.
-Strong Bear Trend: Defined by powerful downward momentum and low volatility.
-Weak Bear Trend: Suggests downward momentum with less force or increased volatility.
-Consolidation: Periods of low volatility and sideways price action.
-Volatile Chop: High volatility without clear directional bias, often seen during transitions or indecision.
By clearly delineating these states, AMRI helps traders quickly grasp the overarching market context, enabling them to apply strategies best suited for the current conditions (e.g., trend-following in strong trends, range-bound strategies in consolidation, or caution in volatile chop).
How it Works (The Adaptive Edge)
AMRI achieves its adaptive classification by continuously analyzing three core market dimensions, with each component dynamically adjusting to current market conditions:
1.Adaptive Moving Average (KAMA): The indicator utilizes the Kaufman Adaptive Moving Average (KAMA) to gauge trend direction and strength. KAMA is unique because it adjusts its smoothing period based on market efficiency (noise vs. direction). In trending markets, it becomes more responsive, while in choppy markets, it smooths out noise, providing a more reliable trend signal than static moving averages.
2.Adaptive Average True Range (ATR): Volatility is measured using an adaptive version of the Average True Range. Similar to KAMA, this ATR dynamically adjusts its sensitivity to reflect real-time changes in market volatility. This helps AMRI differentiate between calm, ranging markets and highly volatile, directional moves or chaotic periods.
3.Normalized Slope Analysis: The slope of the KAMA is normalized against the Adaptive ATR. This normalization provides a robust measure of trend strength that is relative to the current market volatility, making the thresholds for strong and weak trends more meaningful across different instruments and timeframes.
These adaptive components work in concert to provide a nuanced and responsive classification of the market regime, minimizing lag and reducing false signals often associated with fixed-parameter indicators.
Key Features & Originality:
-Dynamic Regime Classification: AMRI stands out by not just indicating trend or range, but by classifying the type of market regime, offering a higher-level analytical framework. This is a meta-indicator that provides context for all other trading tools.
-Adaptive Core Metrics: The use of KAMA and an Adaptive ATR ensures that the indicator remains relevant and responsive across diverse market conditions, automatically adjusting to changes in volatility and trend efficiency. This self-adjusting nature is a significant advantage over indicators with static lookback periods.
-Visual Clarity: The color-coded background provides an immediate, at-a-glance understanding of the current market regime, reducing cognitive load and allowing for quicker decision-making.
-Contextual Trading: By identifying the prevailing regime, AMRI empowers traders to select and apply strategies that are most effective for that specific environment, helping to avoid costly mistakes of using a trend-following strategy in a ranging market, or vice-versa.
-Originality: While components like KAMA and ATR are known, their adaptive integration into a comprehensive, multi-regime classification system, combined with normalized slope analysis for trend strength, offers a novel approach to market analysis not commonly found in publicly available indicators.
Multi-Symbol Volatility Tracker with Range DetectionMulti-Symbol Volatility Tracker with Range Detection
🎯 Main Purpose:
This indicator is specifically designed for scalpers to quickly identify symbols with high volatility that are currently in ranging conditions . It helps you spot the perfect opportunities for buying at lows and selling at highs repeatedly within the same trading session.
📊 Table Data Explanation:
The indicator displays a comprehensive table with 5 columns for 4 major symbols (GOLD, SILVER, NASDAQ, SP500):
SYMBOL: The trading instrument being analyzed
VOLATILITY: Color-coded volatility levels (NORMAL/HIGH/EXTREME) based on ATR values
Last Candle %: The percentage range of the most recent 5-minute candle
Last 5 Candle Avg %: Average percentage range over the last 5 candles
RANGE: Shows "YES" (blue) or "NO" (gray) indicating if the symbol is currently ranging
🔍 How to Identify Trading Opportunities:
Look for symbols that combine these characteristics:
RANGE column shows "YES" (highlighted in blue) - This means the symbol is moving sideways, perfect for range trading
VOLATILITY shows "HIGH" or "EXTREME" - Ensures there's enough movement for profitable scalping
Higher candlestick percentages - Indicates larger candle ranges, meaning more profit potential per trade
⚡ Optimal Usage:
Best Timeframe: Works optimally on 5-minute charts where the ranging patterns are most reliable for scalping
Trading Strategy: When you find a symbol with "YES" in the RANGE column, switch to that symbol and look for opportunities to buy near the lows and sell near the highs of the ranging pattern
Risk Management: Higher volatility symbols offer more profit potential but require tighter risk management
⚙️ Settings:
ATR Length: Adjusts the Average True Range calculation period (default: 14)
Range Sensitivity: Fine-tune range detection sensitivity (0.1-2.0, lower = more sensitive)
💡 Pro Tips:
The indicator updates in real-time, so monitor for symbols switching from "NO" to "YES" in the RANGE column
Combine HIGH/EXTREME volatility with RANGE: YES for the most profitable scalping setups
Use the candlestick percentages to gauge potential profit per trade - higher percentages mean more movement
The algorithm uses advanced statistical analysis including standard deviation, linear regression slopes, and range efficiency to accurately detect ranging conditions
Perfect for day traders and scalpers who want to quickly identify which symbols offer the best ranging opportunities for consistent buy-low, sell-high strategies.
Stiffness IndexStiffness Index Indicator
Overview
The Stiffness Index is a technical analysis indicator created by Markos Katsanos and first introduced in the November 2018 issue of Technical Analysis of Stocks & Commodities magazine. This indicator attempts to recognize strong price trends by counting the number of times price was above the 100-day moving average during the indicator period.
Core Philosophy
The premise is the fewer number of times price penetrates the MA, the stronger the trend. The philosophy behind this indicator is that traders should trade when the trend is at its strongest point - when the trend is at its "stiffest". Based on the observation that in strong long-lasting uptrends, price seldom penetrates the 100-bar simple moving average, this indicator helps assess the quality and strength of an uptrend.
How It Works
The Stiffness Index operates through several key components:
1. Moving Average Baseline: Uses a 100-period moving average as the primary reference level
2. Volatility Threshold: Includes a volatility threshold to eliminate minor movements - typically 0.2 standard deviations to reject minimal penetrations above the moving average
3. Counting Mechanism: Calculates the stiffness coefficient as the ratio of the number of times the price has closed above the moving average during the indicator period to the length of that period
4. Smoothing: Applies additional smoothing to the final result for cleaner signals
Key Components
Input Parameters
- Period 1 (100): The moving average period for the baseline calculation
- MA Method 1: Type of moving average for the baseline (SMA, EMA, SMMA, LWMA)
- Summation Period (60): The lookback period for counting closes above the moving average
- Period 2 (3): Smoothing period for the final signal line
- MA Method 2: Smoothing method for the signal line
- Threshold Level (80): Reference level for identifying strong trends
Visual Elements
- Blue Signal Line: The main stiffness reading showing trend strength
- Dotted Line: Adjustable threshold level for reference
Interpretation and Trading Applications
Signal Readings
- High Values (Above Threshold): Indicates a "stiff" trend where price consistently stays above the moving average with minimal penetrations
- Low Values (Below Threshold): Suggests a weaker trend with frequent penetrations of the moving average
- Original threshold levels mentioned in research range from 75-95
Trading Strategy
The original strategy suggests entering long positions when the stiffness reading reaches 90 or higher, with exits when the reading drops below 50. Some implementations use a threshold of 75 for entry confirmation.
Key Characteristics
- Designed primarily for stocks and instruments with upward bias
- Trades infrequently - typically about once per year when using strict parameters
- Best suited for trend-following strategies in strongly trending markets
Advantages
- Trend Quality Assessment: Quantifies the "stiffness" or quality of trends
- Volatility Filtering: Built-in volatility threshold reduces false signals from minor price movements
- Objective Measurement: Provides a numerical assessment of trend strength
- Customizable: Multiple parameters allow adaptation to different markets and timeframes
Best Practices
- Use in conjunction with baseline trend indicators for confirmation
- Most effective in markets with strong directional bias
- Consider the low frequency of signals when developing trading strategies
- May not be suitable for instruments that "twitch up and down" frequently
*Note: This indicator is specifically designed to identify and trade the strongest trending periods, which naturally results in fewer but potentially higher-quality trading opportunities.*
Options Max Pain Calculator [BackQuant]Options Max Pain Calculator
A visualization tool that models option expiry dynamics by calculating "max pain" levels, displaying synthetic open interest curves, gamma exposure profiles, and pin-risk zones to help identify where market makers have the least payout exposure.
What is Max Pain?
Max Pain is the theoretical expiration price where the total dollar value of outstanding options would be minimized. At this price level, option holders collectively experience maximum losses while option writers (typically market makers) have minimal payout obligations. This creates a natural gravitational pull as expiration approaches.
Core Features
Visual Analysis Components:
Max Pain Line: Horizontal line showing the calculated minimum pain level
Strike Level Grid: Major support and resistance levels at key option strikes
Pin Zone: Highlighted area around max pain where price may gravitate
Pain Heatmap: Color-coded visualization showing pain distribution across prices
Gamma Exposure Profile: Bar chart displaying net gamma at each strike level
Real-time Dashboard: Summary statistics and risk metrics
Synthetic Market Modeling**
Since Pine Script cannot access live options data, the indicator creates realistic synthetic open interest distributions based on configurable market parameters including volume patterns, put/call ratios, and market maker positioning.
How It Works
Strike Generation:
The tool creates a grid of option strikes centered around the current price. You can control the range, density, and whether strikes snap to realistic market increments.
Open Interest Modeling:
Using your inputs for average volume, put/call ratios, and market maker behavior, the indicator generates synthetic open interest that mirrors real market dynamics:
Higher volume at-the-money with decay as strikes move further out
Adjustable put/call bias to reflect current market sentiment
Market maker inventory effects and typical short-gamma positioning
Weekly options boost for near-term expirations
Pain Calculation:
For each potential expiry price, the tool calculates total option payouts:
Call options contribute pain when finishing in-the-money
Put options contribute pain when finishing in-the-money
The strike with minimum total pain becomes the Max Pain level
Gamma Analysis:
Net gamma exposure is calculated at each strike using standard option pricing models, showing where hedging flows may be most intense. Positive gamma creates price support while negative gamma can amplify moves.
Key Settings
Basic Configuration:
Number of Strikes: Controls grid density (recommended: 15-25)
Days to Expiration: Time until option expiry
Strike Range: Price range around current level (recommended: 8-15%)
Strike Increment: Spacing between strikes
Market Parameters:
Average Daily Volume: Baseline for synthetic open interest
Put/Call Volume Ratio: Market sentiment bias (>1.0 = bearish, <1.0 = bullish) It does not work if set to 1.0
Implied Volatility: Current option volatility estimate
Market Maker Factors: Dealer positioning and hedging intensity
Display Options:
Model Complexity: Simple (line only), Standard (+ zones), Advanced (+ heatmap/gamma)
Visual Elements: Toggle individual components on/off
Theme: Dark/Light mode
Update Frequency: Real-time or daily calculation
Reading the Display
Dashboard Table (Top Right):
Current Price vs Max Pain Level
Distance to Pain: Percentage gap (smaller = higher pin risk)
Pin Risk Assessment: HIGH/MEDIUM/LOW based on proximity and time
Days to Expiry and Strike Count
Model complexity level
Visual Elements:
Red Line: Max Pain level where payout is minimized
Colored Zone: Pin risk area around max pain
Dotted Lines: Major strike levels (green = support, orange = resistance)
Color Bar: Pain heatmap (blue = high pain, red = low pain/max pain zones)
Horizontal Bars: Gamma exposure (green = positive, red = negative)
Yellow Dotted Line: Gamma flip level where hedging behavior changes
Trading Applications
Expiration Pinning:
When price is near max pain with limited time remaining, there's increased probability of gravitating toward that level as market makers hedge their positions.
Support and Resistance:
High open interest strikes often act as magnets, with max pain representing the strongest gravitational pull.
Volatility Expectations:
Above gamma flip: Expect dampened volatility (long gamma environment)
Below gamma flip: Expect amplified moves (short gamma environment)
Risk Assessment:
The pin risk indicator helps gauge likelihood of price manipulation near expiry, with HIGH risk suggesting potential range-bound action.
Best Practices
Setup Recommendations
Start with Model Complexity set to "Standard"
Use realistic strike ranges (8-12% for most assets)
Set put/call ratio based on current market sentiment
Adjust implied volatility to match current levels
Interpretation Guidelines:
Small distance to pain + short time = high pin probability
Large gamma bars indicate key hedging levels to monitor
Heatmap intensity shows strength of pain concentration
Multiple nearby strikes can create wider pin zones
Update Strategy:
Use "Daily" updates for cleaner visuals during trading hours
Switch to "Every Bar" for real-time analysis near expiration
Monitor changes in max pain level as new options activity emerges
Important Disclaimers
This is a modeling tool using synthetic data, not live market information. While the calculations are mathematically sound and the modeling realistic, actual market dynamics involve numerous factors not captured in any single indicator.
Max pain represents theoretical minimum payout levels and suggests where natural market forces may create gravitational pull, but it does not guarantee price movement or predict exact expiration levels. Market gaps, news events, and changing volatility can override these dynamics.
Use this tool as additional context for your analysis, not as a standalone trading signal. The synthetic nature of the data makes it most valuable for understanding market structure and potential zones of interest rather than precise price prediction.
Technical Notes
The indicator uses established option pricing principles with simplified implementations optimized for Pine Script performance. Gamma calculations use standard financial models while pain calculations follow the industry-standard definition of minimized option payouts.
All visual elements use fixed positioning to prevent movement when scrolling charts, and the tool includes performance optimizations to handle real-time calculation without timeout errors.
StdDev Supertrend {CHIPA}StdDev Supertrend ~ C H I P A is a supertrend style trend engine that replaces ATR with standard deviation as the volatility core. It can operate on raw prices or log return volatility, with optional smoothing to control noise.
Key features include:
Supertrend trailing rails built from a stddev scaled envelope that flips the regime only when price closes through the opposite rail.
Returns-based mode that scales volatility by log returns for more consistent behavior across price regimes.
Optional smoothing on the volatility input to tune responsiveness versus stability.
Directional gap fill between price and the active trend line on the main chart; opacity adapts to the distance (vs ATR) so wide gaps read stronger and small gaps stay subtle.
Secondary pane view of the rails with the same adaptive fade, plus an optional candle overlay for context.
Clean alerts that fire once when state changes
Use cases: medium-term trend following, stop/flip systems, and visual regime confirmation when you prefer stddev-based distance over ATR.
Note: no walk-forward or robustness testing is implied; parameter choices and risk controls are on you.
Market Internals Dashboard (Table) v5 - FixedHas a Dashboard for Market Internals and 3 Indices, very helpful
Institutional Levels (CNN) - [PhenLabs]📊Institutional Levels (Convolutional Neural Network-inspired)
Version : PineScript™v6
📌Description
The CNN-IL Institutional Levels indicator represents a breakthrough in automated zone detection technology, combining convolutional neural network principles with advanced statistical modeling. This sophisticated tool identifies high-probability institutional trading zones by analyzing pivot patterns, volume dynamics, and price behavior using machine learning algorithms.
The indicator employs a proprietary 9-factor logistic regression model that calculates real-time reaction probabilities for each detected zone. By incorporating CNN-inspired filtering techniques and dynamic zone management, it provides traders with unprecedented accuracy in identifying where institutional money is likely to react to price action.
🚀Points of Innovation
● CNN-Inspired Pivot Analysis - Advanced binning system using convolutional neural network principles for superior pattern recognition
● Real-Time Probability Engine - Live reaction probability calculations using 9-factor logistic regression model
● Dynamic Zone Intelligence - Automatic zone merging using Intersection over Union (IoU) algorithms
● Volume-Weighted Scoring - Time-of-day volume Z-score analysis for enhanced zone strength assessment
● Adaptive Decay System - Intelligent zone lifecycle management based on touch frequency and recency
● Multi-Filter Architecture - Optional gradient, smoothing, and Difference of Gaussians (DoG) convolution filters
🔧Core Components
● Pivot Detection Engine - Advanced pivot identification with configurable left/right bars and ATR-normalized strength calculations
● Neural Network Binning - Price level clustering using CNN-inspired algorithms with ATR-based bin sizing
● Logistic Regression Model - 9-factor probability calculation including distance, width, volume, VWAP deviation, and trend analysis
● Zone Management System - Intelligent creation, merging, and decay algorithms for optimal zone lifecycle control
● Visualization Layer - Dynamic line drawing with opacity-based scoring and optional zone fills
🔥Key Features
● High-Probability Zone Detection - Automatically identifies institutional levels with reaction probabilities above configurable thresholds
● Real-Time Probability Scoring - Live calculation of zone reaction likelihood using advanced statistical modeling
● Session-Aware Analysis - Optional filtering to specific trading sessions for enhanced accuracy during active market hours
● Customizable Parameters - Full control over lookback periods, zone sensitivity, merge thresholds, and probability models
● Performance Optimized - Efficient processing with controlled update frequencies and pivot processing limits
● Non-Repainting Mode - Strict mode available for backtesting accuracy and live trading reliability
🎨Visualization
● Dynamic Zone Lines - Color-coded support and resistance levels with opacity reflecting zone strength and confidence scores
● Probability Labels - Real-time display of reaction probabilities, touch counts, and historical hit rates for active zones
● Zone Fills - Optional semi-transparent zone highlighting for enhanced visual clarity and immediate pattern recognition
● Adaptive Styling - Automatic color and opacity adjustments based on zone scoring and statistical significance
📖Usage Guidelines
● Lookback Bars - Default 500, Range 100-1000, Controls the historical data window for pivot analysis and zone calculation
● Pivot Left/Right - Default 3, Range 1-10, Defines the pivot detection sensitivity and confirmation requirements
● Bin Size ATR units - Default 0.25, Range 0.1-2.0, Controls price level clustering granularity for zone creation
● Base Zone Half-Width ATR units - Default 0.25, Range 0.1-1.0, Sets the minimum zone width in ATR units for institutional level boundaries
● Zone Merge IoU Threshold - Default 0.5, Range 0.1-0.9, Intersection over Union threshold for automatic zone merging algorithms
● Max Active Zones - Default 5, Range 3-20, Maximum number of zones displayed simultaneously to prevent chart clutter
● Probability Threshold for Labels - Default 0.6, Range 0.3-0.9, Minimum reaction probability required for zone label display and alerts
● Distance Weight w1 - Controls influence of price distance from zone center on reaction probability
● Width Weight w2 - Adjusts impact of zone width on probability calculations
● Volume Weight w3 - Modifies volume Z-score influence on zone strength assessment
● VWAP Weight w4 - Controls VWAP deviation impact on institutional level significance
● Touch Count Weight w5 - Adjusts influence of historical zone interactions on probability scoring
● Hit Rate Weight w6 - Controls prior success rate impact on future reaction likelihood predictions
● Wick Penetration Weight w7 - Modifies wick penetration analysis influence on probability calculations
● Trend Weight w8 - Adjusts trend context impact using ADX analysis for directional bias assessment
✅Best Use Cases
● Swing Trading Entries - Enter positions at high-probability institutional zones with 60%+ reaction scores
● Scalping Opportunities - Quick entries and exits around frequently tested institutional levels
● Risk Management - Use zones as dynamic stop-loss and take-profit levels based on institutional behavior
● Market Structure Analysis - Identify key institutional levels that define current market structure and sentiment
● Confluence Trading - Combine with other technical indicators for high-probability trade setups
● Session-Based Strategies - Focus analysis during high-volume sessions for maximum effectiveness
⚠️Limitations
● Historical Pattern Dependency - Algorithm effectiveness relies on historical patterns that may not repeat in changing market conditions
● Computational Intensity - Complex calculations may impact chart performance on lower-end devices or with multiple indicators
● Probability Estimates - Reaction probabilities are statistical estimates and do not guarantee actual market outcomes
● Session Sensitivity - Performance may vary significantly between different market sessions and volatility regimes
● Parameter Sensitivity - Results can be highly dependent on input parameters requiring optimization for different instruments
💡What Makes This Unique
● CNN Architecture - First indicator to apply convolutional neural network principles to institutional-level detection
● Real-Time ML Scoring - Live machine learning probability calculations for each zone interaction
● Advanced Zone Management - Sophisticated algorithms for zone lifecycle management and automatic optimization
● Statistical Rigor - Comprehensive 9-factor logistic regression model with extensive backtesting validation
● Performance Optimization - Efficient processing algorithms designed for real-time trading applications
🔬How It Works
● Multi-timeframe pivot identification - Uses configurable sensitivity parameters for advanced pivot detection
● ATR-normalized strength calculations - Standardizes pivot significance across different volatility regimes
● Volume Z-score integration - Enhanced pivot weighting based on time-of-day volume patterns
● Price level clustering - Neural network binning algorithms with ATR-based sizing for zone creation
● Recency decay applications - Weights recent pivots more heavily than historical data for relevance
● Statistical filtering - Eliminates low-significance price levels and reduces market noise
● Dynamic zone generation - Creates zones from statistically significant pivot clusters with minimum support thresholds
● IoU-based merging algorithms - Combines overlapping zones while maintaining accuracy using Intersection over Union
● Adaptive decay systems - Automatic removal of outdated or low-performing zones for optimal performance
● 9-factor logistic regression - Incorporates distance, width, volume, VWAP, touch history, and trend analysis
● Real-time scoring updates - Zone interaction calculations with configurable threshold filtering
● Optional CNN filters - Gradient detection, smoothing, and Difference of Gaussians processing for enhanced accuracy
💡Note
This indicator represents advanced quantitative analysis and should be used by traders familiar with statistical modeling concepts. The probability scores are mathematical estimates based on historical patterns and should be combined with proper risk management and additional technical analysis for optimal trading decisions.
Irrationality Index by CRYPTO_ADA_BTC"The market can be irrational longer than you can stay solvent" ~ John Maynard Keynes
This indicator, the Irrationality Index, measures how far the current market price has deviated from a smoothed estimate of its "fair value," normalized for recent volatility. It provides traders with a visual sense of when the market may be behaving irrationally, without giving direct buy or sell signals.
How it works:
1. Fair Value Calculation
The indicator estimates a "fair value" for the asset using a combination of a long-term EMA (exponential moving average) and a linear regression trend over a configurable period. This fair value serves as a smoothed baseline for price, balancing trend-following and mean-reversion.
2. Volatility-Adjusted Z-Score
The deviation between price and fair value is measured in standard deviations of recent log returns:
Z = (log(price) - log(fairValue)) / volatility
This standardization accounts for different volatility environments, allowing comparison across assets.
3. Irrationality Score (0–100)
The Z-score is transformed using a logistic mapping into a 0–100 scale:
- 50 → price near fair value (rational zone)
- >75 → high irrationality, price stretched above fair value
- >90 → extreme irrationality, unsustainable extremes
- <25 → high irrationality, price stretched below fair value
- <10 → extreme bearish irrationality
4. Price vs Fair Value (% deviation)
The indicator plots the percentage difference between price and fair value:
pctDiff = (price - fairValue) / fairValue * 100
- Positive values → Percentage above fair value (optimistic / overvalued)
- Negative values → Percentage below fair value (pessimistic / undervalued)
Visuals:
- Irrationality (%) Line (0–100) shows irrationality level.
- Background Colors: Yellow= high bullish irrationality, Green= extreme bullish irrationality, Orange= high bearish irrationality, Red= extreme bearish irrationality.
- Price - FairValue (%) plot: price deviation vs fair value (%), Colored green above 0 and red below 0.
- Label: display actual price, estimated fair value, and Z-score for the latest bar.
- Alerts: configurable thresholds for high and extreme irrationality.
How to read it:
- 50 → Market trading near fair value.
- >75 / >90 → Price may be irrationally high; risk of pullback increases.
- <25 / <10 → Price may be irrationally low; potential rebound zones, but trends can continue.
- Price - FairValue (%) plot → visual guide for % price stretch relative to fair value.
Notes / Warnings:
- Measures relative deviation, not fundamental value!
- High irrationality scores do not automatically indicate trades; markets can remain can be irrational longer than you can stay solvent .
- Best used with other tools: momentum, volume, divergence, and multi-timeframe analysis.
Andean Oscillator (Version 3.0 Sr.K)Andean Oscillator (Version 3.0 Sr.K)
This indicator is a momentum-based oscillator that measures the balance between bullish and bearish pressure.
🔧 How it works:
It calculates two adaptive envelopes around price and derives a "bullish" and "bearish" component.
The oscillator value is simply Bull - Bear, showing which side dominates.
A signal line (EMA of the oscillator) smooths the raw value.
Optionally, ±1σ levels are plotted to highlight statistically strong moves.
📊 What you see:
Histogram: Positive bars = bullish momentum, negative bars = bearish.
Orange Line: Signal line (EMA) used to confirm or anticipate reversals.
Zero Line: The equilibrium point. Crosses of this level signal a shift in market bias.
Green / Red Triangles: Buy and sell signals, either when crossing zero or crossing the signal line (depending on selected mode).
⚡ Early Signal Mode:
When enabled, signals trigger earlier — at the crossover between the oscillator and its signal line — allowing traders to enter potential reversals before a full zero-cross confirmation.
✅ Use cases:
Identify momentum shifts before price reversals.
Spot potential long/short setups with reduced lag.
Combine with price action or support/resistance for confirmation.
⚠️ Note: This is a tool for discretionary/manual trading. It does not open or close trades automatically. Always confirm with your own analysis and risk management.
TTT v6 — Price Action, Structure & Info Box v.250919TTT v6 is a trade-readiness tool that fuses EMA trend, structure breaks, and an ATR trailing stop. It prints gated BUY/SELL labels, shows a clear “NO TRADE → TRADE (LONG/SHORT)” Info Box with risk/sizing, supports session filtering, and includes alertconditions for signals and trade-ready flips.
VWAP + Range Breakout (Pre-Signal for Manual Entry)WHAT IT DOES
This tool highlights potential breakout opportunities when price sweeps the previous day’s high or low and aligns with VWAP and short-term range levels. It provides both pre-signals (early warnings) and confirmed signals (breakout closed) so traders can prepare before momentum accelerates.
Works on all timeframes and across markets (indices, forex, crypto). Especially useful during active London and New York sessions.
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KEY FEATURES
Daily sweep logic: previous day high/low as liquidity reference
VWAP with cumulative calculation
Adjustable range breakout levels
Optional SMA trend filter
Session filter (London / NY trading hours)
Pre-Signal markers (early alert before breakout)
Confirmed LONG/SHORT signals after breakout close
Alerts for Pre-Long, Pre-Short, and Confirmed entries
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HOW TO USE
1. Wait for price to sweep the previous day high/low.
2. Look for alignment with VWAP and the defined range breakout levels.
3. Use trend/session filters for higher accuracy.
4. Combine with your own risk management rules.
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SETTINGS TIPS
Adjust range lookback for different timeframes (shorter for fast intraday, longer for higher timeframes).
Enable/disable session filters depending on your market.
Use SMA trend filter to stay aligned with higher-timeframe bias.
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WHO IT’S FOR
Scalpers, intraday, and swing traders who want early signals when liquidity is taken and price is preparing for a breakout.
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NOTES
For educational purposes only. No financial advice.
This script is open-source; redistribution follows TradingView rules.
Chhatrapati Indicator by TradeNitiX (Nitin Hajare)⚔️ Chhatrapati Indicator by TradeNitiX
A precision-driven trading system built to capture strong trends and avoid market noise. It blends range filtering, momentum checks, and volatility-based risk control for clean, confident entries and exits.
🔍 Core Strategy Components
1. Range Filter – Trend Detection
2. RSI – Momentum Confirmation
3. ADX – Trend Strength Filter
4. ATR – Volatility-Based Risk Management
💎 Highlights – Chhatrapati Indicator
✔ Display Profit/Loss values above each candle
✅ Clear Buy/Sell Signals – No guesswork, just precision entries and exits
📊 High Accuracy – Filters out false signals using multi-layer confirmation
⚡ Beginner-Friendly – Simple logic, powerful results for all skill levels
🔥 Multi-Market Compatibility – Works seamlessly on Forex, crypto, indices, stocks
🎯 Volatility-Based Risk Control – ATR-driven SL/TP for realistic, dynamic targets
🧠 Smart Trend Detection – Combines range filtering with ADX for strong setups
💡 Live Trade Demos – Real-time examples to build trader confidence
📈 Momentum + Strength Filters – RSI + ADX combo avoids weak or choppy trades
🛡️ Risk-Reward Focused – Built-in 3:1 RR logic for disciplined growth
🚀 Tested & Trusted – Proven results across multiple market conditions
⚙️ Key Advantages of Chhatrapati Indicator
✅ Noise-Free Trend Detection – Filters weak moves, locks onto strong trends
📊 RSI + ADX Confirmation – Only trades with real momentum and strength
🎯 ATR-Based Risk Control – Smart SL/TP placement, adapts to volatility
⏱️ Multi-Timeframe Ready – Works for scalping, swing, and intraday setups
👁️ Visual Clarity – Clean signals, SL/TP zones, and trend markers
🎯 Ideal Users
✔ Trend Followers – Ride strong moves with confidence
✔ Swing Traders – Target medium-term setups with solid RR
✔ Scalpers – Quick, precise entries with minimal noise
✔ Algo Traders – Use alerts for automated execution
Pairs Trading Scanner [BackQuant]Pairs Trading Scanner
What it is
This scanner analyzes the relationship between your chart symbol and a chosen pair symbol in real time. It builds a normalized “spread” between them, tracks how tightly they move together (correlation), converts the spread into a Z-Score (how far from typical it is), and then prints clear LONG / SHORT / EXIT prompts plus an at-a-glance dashboard with the numbers that matter.
Why pairs at all?
Markets co-move. When two assets are statistically related, their relationship (the spread) tends to oscillate around a mean.
Pairs trading doesn’t require calling overall market direction you trade the relative mispricing between two instruments.
This scanner gives you a robust, visual way to find those dislocations, size their significance, and structure the trade.
How it works (plain English)
Step 1 Pick a partner: Select the Pair Symbol to compare against your chart symbol. The tool fetches synchronized prices for both.
Step 2 Build a spread: Choose a Spread Method that defines “relative value” (e.g., Log Spread, Price Ratio, Return Difference, Price Difference). Each lens highlights a different flavor of divergence.
Step 3 Validate relationship: A rolling Correlation checks if the pair is moving together enough to be tradable. If correlation is weak, the scanner stands down.
Step 4 Standardize & score: The spread is normalized (mean & variability over a lookback) to form a Z-Score . Large absolute Z means “stretched,” small means “near fair.”
Step 5 Signals: When the Z-Score crosses user-defined thresholds with sufficient correlation , entries print:
LONG = long chart symbol / short pair symbol,
SHORT = short chart symbol / long pair symbol,
EXIT = mean reversion into the exit zone or correlation failure.
Core concepts (the three pillars)
Spread Method Your definition of “distance” between the two series.
Guidance:
Log Spread: Focuses on proportional differences; robust when prices live on different scales.
Price Ratio: Classic relative value; good when you care about “X per Y.”
Return Difference: Emphasizes recent performance gaps; nimble for momentum-to-mean plays.
Price Difference: Straight subtraction; intuitive for similar-scale assets (e.g., two ETFs).
Correlation A rolling score of co-movement. The scanner requires it to be above your Min Correlation before acting, so you’re not trading random divergence.
Z-Score “How abnormal is today’s spread?” Positive = chart richer than pair; negative = cheaper. Thresholds define entries/exits with transparent, statistical context.
What you’ll see on the chart
Correlation plot (blue line) with a dashed Min Correlation guide. Above the line = green zone for signals; below = hands off.
Z-Score plot (white line) with colored, dashed Entry bands and dotted Exit bands. Zero line for mean.
Normalized spread (yellow) for a quick “shape read” of recent divergence swings.
Signal markers :
LONG (green label) when Z < –Entry and corr OK,
SHORT (red label) when Z > +Entry and corr OK,
EXIT (gray label) when Z returns inside the Exit band or correlation drops below the floor.
Background tint for active state (faint green for long-spread stance, faint red for short-spread stance).
The two built-in dashboards
Statistics Table (top-right)
Pair Symbol Your chosen partner.
Correlation Live value vs. your minimum.
Z-Score How stretched the spread is now.
Current / Pair Prices Real-time anchors.
Signal State NEUTRAL / LONG / SHORT.
Price Ratio Context for ratio-style setups.
Analysis Table (bottom-right)
Avg Correlation Typical co-movement level over your window.
Max |Z| The recent extremes of dislocation.
Spread Volatility How “lively” the spread has been.
Trade Signal A human-readable prompt (e.g., “LONG A / SHORT B” or “NO TRADE” / “LOW CORRELATION”).
Risk Level LOW / MEDIUM / HIGH based on current stretch (absolute Z).
Signals logic (plain English)
Entry (LONG): The spread is unusually negative (chart cheaper vs pair) and correlation is healthy. Expect mean reversion upward in the spread: long chart, short pair.
Entry (SHORT): The spread is unusually positive (chart richer vs pair) and correlation is healthy. Expect mean reversion downward in the spread: short chart, long pair.
Exit: The spread relaxes back toward normal (inside your exit band), or correlation deteriorates (relationship no longer trusted).
A quick, repeatable workflow
1) Choose your pair in context (same sector/theme or known macro link). Think: “Do these two plausibly co-move?”
2) Pick a spread lens that matches your narrative (ratio for relative value, returns for short-term performance gaps, etc.).
3) Confirm correlation is above your floor no corr, no trade.
4) Wait for a stretch (Z beyond Entry band) and a printed LONG / SHORT .
5) Manage to the mean (EXIT band) or correlation failure; let the scanners’ state/labels keep you honest.
Settings that matter (and why)
Spread Method Defines the “mispricing” you care about.
Correlation Period Longer = steadier regime read, shorter = snappier to regime change.
Z-Score Period The window that defines “normal” for the spread; it sets the yardstick.
Use Percentage Returns Normalizes series when using return-based logic; keep on for mixed-scale assets.
Entry / Exit Thresholds Set your stretch and your target reversion zone. Wider entries = rarer but stronger signals.
Minimum Correlation The gatekeeper. Raising it favors quality over quantity.
Choosing pairs (practical cheat sheet)
Same family: two index ETFs, two oil-linked names, two gold miners, two L1 tokens.
Hedge & proxy: stock vs. sector ETF, BTC vs. BTC index, WTI vs. energy ETF.
Cross-venue or cross-listing: instruments that are functionally the same exposure but price differently intraday.
Reading the cues like a pro
Divergence shape: The yellow normalized spread helps you see rhythm fast spike and snap-back versus slow grind.
Corr-first discipline: Don’t fight the “Min Correlation” line. Good pairs trading starts with a relationship you can trust.
Exit humility: When Z re-centers, let the EXIT do its job. The edge is the journey to the mean, not overstaying it.
Frequently asked (quick answers)
“Long/Short means what exactly?”
LONG = long the chart symbol and short the pair symbol.
SHORT = short the chart symbol and long the pair symbol.
“Do I need same price scales?” No. The spread methods normalize in different ways; choose the one that fits your use case (log/ratio are great for mixed scales).
“What if correlation falls mid-trade?” The scanner will neutralize the state and print EXIT . Relationship first; trade second.
Field notes & patterns
Snap-back days: After a one-sided session, return-difference spreads often flag cleaner intraday mean reversions.
Macro rotations: Ratio spreads shine during sector re-weights (e.g., value vs. growth ETFs); look for steady corr + elevated |Z|.
Event bleed-through: If one symbol reacts to news and its partner lags, Z often flags a high-quality, short-horizon re-centering.
Display controls at a glance
Show Statistics Table Live state & key numbers, top-right.
Show Analysis Table Context/risk read, bottom-right.
Show Correlation / Spread / Z-Score Toggle the sub-charts you want visible.
Show Entry/Exit Signals Turn markers on/off as needed.
Coloring Adjust Long/Short/Neutral and correlation line colors to match your theme.
Alerts (ready to route to your workflow)
Pairs Long Entry Z falls through the long threshold with correlation above minimum.
Pairs Short Entry Z rises through the short threshold with correlation above minimum.
Pairs Trade Exit Z returns to neutral or the relationship fails your correlation floor.
Correlation Breakdown Rolling correlation crosses your minimum; relationship caution.
Final notes
The scanner is designed to keep you systematic: require relationship (correlation), quantify dislocation (Z-Score), act when stretched, stand down when it normalizes or the relationship degrades. It’s a full, visual loop for relative-value trading that stays out of your way when it should and gets loud only when the numbers line up.
