Momentum Divergence Oscillator by JJMomentum Divergence Oscillator by JJ
A powerful, all-in-one momentum tool designed to streamline trade confluence, combining multi-timeframe trend analysis with automatic divergence spotting and classic MACD signals.
How to Use This Indicator
This oscillator is designed to be used in the lower pane of your chart, beneath your primary price chart. It provides three main types of signals:
1. Multi-Timeframe (MTF) Trend Confirmation
The background shading is your primary trend filter. It looks at the MACD trend on two higher timeframes (30m and 60m by default) to confirm the market's overarching direction.
Green Shading: Indicates that both higher timeframes are in a bullish trend (MACD above signal line). Focus on looking for BUY signals during this time.
Red Shading: Indicates that both higher timeframes are in a bearish trend. Focus on looking for SELL signals during this time.
Grey/No Shading: The higher timeframes are not in agreement or are consolidating. Exercise caution or stick to standard price action rules.
2. Automatic Divergence Signals
Divergence is a powerful early warning system where the indicator moves in the opposite direction of the price. The indicator automatically flags these occurrences:
"Bull RSI Div" (Green Label-Up): Bullish divergence identified using the RSI oscillator. This suggests a potential reversal to the upside after a downtrend.
"Bear RSI Div" (Red Label-Down): Bearish divergence identified using the RSI oscillator. This suggests a potential reversal to the downside after an uptrend.
Tip: These signals are often most reliable when they occur within the corresponding MTF background colour (e.g., a "Bull RSI Div" during a Green MTF background).
3. Momentum Shifts and Crossovers
The standard plots provide immediate insight into market momentum:
Blue/Orange Lines: The traditional MACD line (Blue) and Signal line (Orange).
Histogram (Green/Red Bars): Represents the momentum difference between the MACD and Signal lines.
Zero-Line Crosses (Triangles): Tiny triangles appear when the MACD line crosses the zero line, indicating a shift in long-term momentum.
Peaks & Troughs (X-Crosses): The 'X' markers identify local peaks and troughs in the histogram, sometimes indicating short-term exhaustion of the current move.
Disclaimer: Trading involves significant risk and is not suitable for every investor. This indicator is for educational purposes only and should not be considered financial advice. Always use appropriate risk management.
趋势分析
Liquidity ThermometerThis is a universal indicator that assesses market liquidity based on five key market parameters: volume, volatility, candlestick range, body size, and price momentum.
The indicator does not use open interest data and is suitable for all markets, including spot, futures, and Forex.
This indicator normalizes each metric historically and creates a composite index between 0 and 1, where higher values correspond to a stable and calm market environment, and lower values indicate periods of increased risk and potential liquidity stress.
LT generates an integral liquidity index in the range based on five normalized components:
-nVol — normalized volume, reflecting trading density and activity.
-nATR — the volatility component (ATR), inverted, as high volatility is typically associated with declining liquidity.
-nRange — the normalized candlestick range, also inverted to assess the structural narrowness of the price movement.
-nBody — the normalized candlestick body size (|close − open|), inverted to assess the balance of supply and demand.
-nMove — the normalized value of the price impulse movement (|Δclose|), reflecting short-term price spikes.
Each metric is linearly normalized over a sliding window (200 bars) using the formula:
norm(x) = (x − min) / (max − min),
where at max = min, the value is fixed at 0.5 to ensure stability.
The ALT index is calculated as a weighted combination:
ALT = 0.35 nVol + 0.20 (1 − nATR) + 0.20 (1 − nRange) + 0.15 (1 − nBody) + 0.10 (1 − nMove)
The result is further smoothed using EMA(3) to reduce micronoise.
Red Zone (MLI < 0.25) — Risk, Thin Liquidity
When the indicator falls into the red zone, it means the market is extremely volatile:
Characteristics:
Low volume — small trades have a strong impact on the price.
High volatility — candlesticks rise or fall sharply.
Wide candlestick range — the market is "breathing heavily," easily breaking price extremes.
Impulsive movements — small market shocks lead to sharp spikes.
Thin liquidity — few orders in the order book, large orders "eat up" the market.
What this means for a trader:
🔥 High risk of spikes and false breakouts.
⚠ Possible series of liquidations on leverage.
❌ It is not recommended to enter long or short positions without a filter or protection.
✅ Can be used for short scalping strategies if you know the entry point, but very carefully.
Green Zone (MLI > 0.75) — High Liquidity, Safe Zone
When the indicator rises into the green zone, it means the market is stable and balanced:
Characteristics:
High volume — the market is deep, orders are executed without a strong impact on the price.
Low volatility — candlesticks are stable, no sharp spikes.
Narrow candlestick range — price moves calmly.
Weak impulse movements — no sharp surges.
Sufficient liquidity — the market can handle large orders.
What this means for a trader:
✅ Safe zone for opening positions.
🔄 Easier to set stop-loss and take-profit orders.
💡 You can trade both up and down, the risk of sharp movements is minimal.
⚡ Under these conditions, there is a lower risk of spikes and accidental liquidations.
It does not predict price movements or guarantee results. It is an analytical tool intended for additional research into market structure.
Cjack COT IndexHere's the updated description with the formula and additional context:
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**Cjack COT Index - Commitment of Traders Positioning Indicator**
This indicator transforms raw Commitment of Traders (COT) data into normalized 0-100 index values, making it easy to identify extreme positioning across different trader categories.
**How It Works:**
The indicator calculates a min-max normalized index for three trader groups over your chosen lookback period (default 26 weeks):
- **Large Speculators** (Non-commercial positions) - typically trend followers
- **Small Speculators** (Non-reportable positions) - retail traders
- **Commercial Hedgers** - producers and consumers hedging business risk
The normalization formula is: **Index = (Current Position - Minimum Position) / (Maximum Position - Minimum Position) × 100**
This calculation shows where current net positioning sits between the minimum and maximum levels observed in the lookback window. A reading of 100 means current positioning equals the maximum net long over that period, 0 equals the minimum (most net short), and 50 is the midpoint of the range.
**Important:** The lookback period critically affects index readings - shorter lookbacks (13-26 weeks) make the index more sensitive to recent extremes, while longer lookbacks (52-78 weeks) provide broader historical context and identify truly exceptional positioning. Min-max normalization is essential because it makes positioning comparable across different contracts and time periods, regardless of the absolute size of positions.
**What It's Good For:**
The indicator excels at identifying **crowded trades** and potential reversals by tracking contrarian setups where commercials (smart money) position opposite to speculators. Background highlighting automatically flags:
- **Long setups** (green): Commercials heavily long while speculators are heavily short
- **Short setups** (red): Commercials heavily short while speculators are heavily long
The "Shift Index" option (enabled by default) displays last week's tradeable COT data aligned with current price action, ensuring you're working with actionable information since COT reports publish with a delay.
Works on weekly timeframes and below for commodities and futures with available COT data.
Ata✨SMAThis Pine Script v6 indicator performs three main functions on a trading chart:
Multiple Moving Averages (MA)
Displays 7 moving averages with fixed lengths (5, 10, 20, 30, 50, 100, 200).
Allows the user to select the MA type: SMA, EMA, WMA, or HMA.
Each MA has a distinct color and line width for clear visual differentiation.
Support and Resistance (S/R) Levels
Identifies key price levels based on pivot points (local highs/lows) within a user‑defined lookback period.
Filters levels by:
Minimum strength (number of touches).
Maximum zone width (as a percentage of price range).
Timeframe (user‑selectable: 5m to monthly).
Visualizes levels as horizontal zones (boxes) colored by type:
Red (res_col) for resistance.
Green (sup_col) for support.
Blue (inch_col) for indecision zones.
Optionally shows a table with level prices, types, and strength percentages.
Includes alert triggers for breakouts (price closing above resistance or below support).
Volume Profile (Side Volumes)
Builds a horizontal volume histogram to the right of the last bar, showing buy/sell volume distribution across price levels.
Highlights the Point of Control (POC) — the price with the highest total volume.
Colors:
Light blue for buy volume.
Light red for sell volume.
Yellow for POC line.
Allows customization of:
Number of bars used for calculation.
Rightward shift of the volume profile.
POC line extension leftward.
Includes tooltips explaining POC and trading scenarios.
Summary:
The script combines trend-following MAs, dynamic S/R zones with alerts, and volume profile analysis into a single indicator for multi‑faceted market structure assessment.
OSOK - One Shot One Kill( Macros w/ Body Swings, SD Prj)What you get:
Time windows: contiguous 50→10 (HH:50–(HH+1):10) and 20→40 (HH:20–HH:40), or both.
Kill Zones & Day filter: Asian, London, NY, London Close; weekdays toggles.
Static projection TF: compute swings on 5-minute (or custom) and display on any chart TF.
Fibonacci/SD ladder: internal retracements & multi-SD extensions with optional price labels.
Stats table: per-hour counts, average/ min/ max range, plus hit-rates for +1/+2/+3/+4 and −1/−2.
Sequence logic (optional): track conditional paths (e.g., 0→+2, +1→−2, etc.) to separate continuation vs. reversal behavior.
CSV export: push current table (filtered/sorted) to a chart label for copy-out.
NiftyScreenerNiftyScreener is a fast, on-chart technical screener that tracks India’s top 10 Nifty-50 weighted stocks in real time. It displays essential indicators inside a compact table directly on your chart—helping traders quickly identify trend strength, momentum, and buy/sell conditions without switching tickers.
🔹 What It Shows
For each of the top Nifty stocks, the screener calculates and displays:
Price
RSI (OB/OS color-coded)
ADX (trend strength with threshold coloring)
SuperTrend Direction (Up/Down)
EMA 9/21 Crossover (Buy/Sell)
Price above 50 EMA (trend confirmation)
🔹 Powerful Features
Real-time multi-indicator scan across the strongest Nifty leaders
Customizable stock list (enable/disable any of the 10 symbols)
Flexible table positioning (left/right)
Adjustable screen size/text size for readability
Color-coded signals for faster decision-making
Optional column filtering (Price, RSI, MACD, ADX, SuperTrend, EMA Cross, Price>50EMA)
Optimized for intraday & swing trading
🔹 Why Traders Love It
NiftyScreener gives instant clarity on market leadership by combining momentum, trend, and directional signals in a single glance. It eliminates the need to open multiple charts and is ideal for traders who want fast confirmation before entering trades.
EMA+SuperThis indicator integrates multiple trend-following components into a unified, clean, and easy-to-interpret chart overlay. Its purpose is to help traders observe short-term and long-term trend direction, momentum shifts, and potential areas of interest using established moving-average and volatility-based techniques.
🔹 Features
1. Multi-EMA Framework
Plots the 9, 21, 50, 100, and 200 EMAs to provide a structured view of short, medium, and long-term market trends.
2. Supertrend Overlay
Applies an ATR-based Supertrend to visualize potential directional shifts.
Both uptrend and downtrend zones are lightly shaded for improved clarity.
3. NovaWave-Style Trend Cloud
A dynamic cloud formed from:
Fast EMA
Slow EMA
Signal MA
The cloud automatically adapts its color based on the relationship between the fast and slow EMAs, offering a quick visual read of momentum bias.
4. Displaced Moving Averages (20 / 50 / 200 DMA)
Includes optional forward displacement to replicate commonly used DMA models in trend-following systems.
5. Crossover Buy/Sell Signals
Buy and sell markers appear when the fast EMA crosses above or below the slow EMA.
Users may create custom alerts via the TradingView alerts panel.
🔹 Alerts
This indicator supports built-in EMA crossover alerts:
Buy Alert – triggered when the fast EMA crosses above the slow EMA
Sell Alert – triggered when the fast EMA crosses below the slow EMA
Users can enable these alerts through the “Add Alert” panel and select the corresponding alert condition.
Alerts are evaluated on bar close for consistency and do not repaint.
🔹 How to Use
EMA structure helps define directional bias and market phase.
The Supertrend and Trend Cloud offer contextual confirmation.
EMA crossovers can help highlight momentum changes.
DMAs provide an additional perspective on smoothed trend levels.
This tool is intended for visual analysis and can complement other approaches such as volume studies, higher-timeframe trend analysis, or support/resistance mapping.
⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice or guarantee any outcome. Always perform independent analysis and apply proper risk management.
Alpha Signal by First TradeAlpha Signal by First Trade
Indicator signals for trend analysis and trading planning.
ILM & IFVG StrategyPlease feel free to adjust in any way possible. Let me know if you can create something better from this initial coding.
//═══════════════════════════════════════════════════════════════════════
// Inverted Liquidity Model (ILM) – Strategy
//═══════════════════════════════════════════════════════════════════════
//
// The **Inverted Liquidity Model (ILM)** is a liquidity-based algorithm
// built to capture high-probability reversals after:
//
// • A liquidity sweep (SSL/BSL taken)
// • Rejection back inside the range
// • A Fair Value Gap (FVG) forms
// • That FVG becomes invalidated → becomes an IFVG entry zone
//
// ILM combines:
// • LTF BOS / CHOCH structure confirmation
// • HTF structure (expansion) filtering
// • Premium / Discount filter (17:00 CST session midline)
// • Optional ATR volatility filter
// • Optional trading session restrictions
// • Optional partial profit-taking + runners
//
// When all conditions align, the strategy enters:
// ✔ Long after sweep of SSL + valid long IFVG + trend confirmation
// ✔ Short after sweep of BSL + valid short IFVG + trend confirmation
//
// Stops are placed at the sweep wick.
// Full target is set at the next structural high/low.
// Optional partial TP sends a runner to full target.
//
// Visual tools (labels, sweep lines, IFVG boxes, midline) assist
// with review and forward testing.
//
//───────────────────────────────────────────────────────────────────────
// USER CONFIGURABLE FEATURES
//───────────────────────────────────────────────────────────────────────
//
// • **Liquidity & Structure**
// - pivotLen → swing length for pivots / liquidity
// - htfOn → toggle higher-timeframe pivots
// - htfTF → timeframe for HTF structure/liquidity
// - useStructureFilter → enforce LTF BOS/CHOCH trend
// - useHtfExpansionFilter → enforce HTF trend
// - showStructureLabels → show BOS/CHOCH labels
// - showHtfStructureLabels → show HTF BOS/CHOCH labels
//
// • **Premium / Discount Midline**
// - usePremiumDiscountFilter → only long in discount / short in premium
// - pdSession → session used for midline (default 17:00 CST)
// - showPdMidLine → show 50% midline
//
// • **FVG / IFVG Detection**
// - useBodyGapFVG → FVG uses candle bodies instead of wicks
// - useDisplacementFVG → require displacement bar
// - dispAtrMult → minimum ATR threshold for displacement
// - showIFVG → draw IFVG boxes
//
// • **ATR / Volatility / Sessions**
// - useRangeFilter → require minimum ATR%
// - atrLen → ATR period
// - minAtrPerc → minimum ATR% of price
// - useSessionFilter → restrict trading hours
// - sessionTimes → allowed trading session
//
// • **Sweep Visualization**
// - showSweepLines → draw sweep lines at SSL/BSL sweeps
// - sweepLineWidth → thickness of sweep lines
//
// • **Exits: Partial Targets & Runners**
// - usePartialTargets → enable partial TP logic
// - tp1QtyPercent → percent closed at TP1
// - tp1FractionOfPath → TP1 relative to path to full target
//
// • **Formatting / Visibility**
// - labelFontSizeInput → tiny / small / normal / large / huge
// - showEntries → entry markers
// - showTargets → target lines
//
//═══════════════════════════════════════════════════════════════════════
// END OF STRATEGY DESCRIPTION
//═══════════════════════════════════════════════════════════════════════
Quant Master Flow [Cumulative Volume Delta]Quant Master Flow
The Quant Master Flow indicator is a tool that analyzes market aggression by tracking the Cumulative Volume Delta (CVD), providing critical insight into institutional participation and short-term liquidity absorption. It acts as the "Conviction Filter" to confirm the statistical signals provided by the Z-Oscillator.
Core Philosophy: Aggression vs. Absorption
The CVD measures the running total of the difference between aggressive buyer-initiated volume and aggressive seller-initiated volume. By plotting this cumulative total, the indicator reveals whether the net effect of market orders is one of accumulation (aggressive buying, driving the price up) or distribution (aggressive selling, driving the price down).
Key Components
Cumulative Tally: The indicator plots the running sum of the volume delta. A rising CVD suggests buyers are more aggressive than sellers; a falling CVD suggests the reverse.
Color Coding: The CVD is colored to visualize flow:
Green: Periods of net aggressive buying (accumulation).
Red: Periods of net aggressive selling (distribution).
Volume Thresholds (Optional/Implied): Allows for filtering of low-impact noise, ensuring the cumulative line only reflects significant shifts in order flow.
Strategic Use Cases
The power of the Quant Master Flow is realized by comparing its trajectory to the price action, validating Z-Score extremes, and spotting liquidity grabs.
1. High-Conviction Confirmation
Use the CVD to confirm a directional signal from the Z-Oscillator:
Bullish Confirmation: When the Z-Oscillator hits Oversold ($\pm 2\sigma$) and the price begins to move up, a strong rising (Green) CVD confirms that the reversal is being fueled by institutional accumulation.
Bearish Confirmation: When the Z-Oscillator hits Overbought ($\pm 2\sigma$) and the price begins to fall, a strong falling (Red) CVD confirms that the drop is being driven by institutional distribution.
2. Divergence (The Early Warning System)
Divergence between the CVD and price is the strongest signal of impending failure or reversal, indicating that the current price movement is unsupported by institutional commitment.
Bearish Divergence: Price makes a Higher High while the CVD makes a Lower High. This is a warning that institutional players are distributing into the rally, signaling a failure to continue the trend.
Bullish Divergence: Price makes a Lower Low while the CVD makes a Higher Low. This shows institutional accumulation is occurring despite falling prices, often preceding a strong reversal.
3. Flow Exhaustion
When the CVD line flattens out during a strong price rally or drop, it signals that the market aggression is exhausted. This often happens right before the Z-Oscillator hits its $\pm 3\sigma$ Extreme zone, providing the earliest warning of a statistical reversal.
Quant Master Z-Oscillator [Risk + Bias]his indicator is a statistically-driven oscillator designed to measure the extreme deviation of price from its recent mean, identifying both reversal risk and directional bias within the current trend. It reframes classic Z-Score analysis to provide a quantified framework for trade timing and risk assessment.
Core Philosophy
The primary goal is to determine the statistical probability of a mean-reversion event. By measuring how many standard deviations the current price is away from its simple moving average (the basis), the indicator identifies moments of maximum risk (Extremes) and optimal entry (Oversold/Overbought zones).
Key Components
Z-Score Calculation:
Measures the distance of the closing price from the Lookback Length Simple Moving Average (SMA), normalized by the Standard Deviation (Volatility).
The raw score is then smoothed using an Exponential Moving Average (EMA) to filter noise, providing a clearer reading of the underlying statistical position.
Statistical Thresholds:
$\pm 2\sigma$ (High/Low): Defines the standard Overbought/Oversold zones (Trigger Zones). Movement into these areas suggests a pullback or reversal is increasingly likely.
$\pm 3\sigma$ (Extreme): Defines the "Kill Zone" of maximum statistical risk. Price reaching this level is highly unlikely to sustain itself, triggering an Extreme Overbought/Oversold warning.
Risk & Bias Dashboard (Table):
A real-time dashboard displayed on the chart (bottom right) provides a quantified summary of the current market state:
Current Z: The exact Z-Score value and its gradient color (green for positive pressure, red for negative).
Market Risk: Flags the statistical risk (e.g., OVERBOUGHT or EXTREME OVERSOLD ⚠️) based on the $\sigma$ thresholds.
Next Bias: Suggests the immediate directional bias (e.g., LONG SETUP NEXT or SHORT REVERSAL), helping the user prepare for the next high-probability setup based on the Z-Score's position relative to the mean.
Divergence Engine:
Detects standard Bullish and Bearish divergences between the Z-Score and the price action, signaling potential trend exhaustion or hidden momentum shifts.
Interpretation & Use
Risk Management: Treat the $\pm 3\sigma$ (Extreme) levels as mandatory profit-taking or high-alert reversal zones. Trading against these extremes carries the highest statistical risk.
Entry Timing: High-probability entries are found when the Z-Score is at $\pm 2\sigma$ (Oversold/Overbought) and a momentum shift (e.g., a green bar after an Oversold red sequence) is observed.
Trend Confirmation: When the Z-Score operates between $0$ and $\pm 2\sigma$, it confirms the direction of the current trend (Positive Z-Score = Bullish bias).
Universal Sentiment Score — V3 Bottom DetectorThe Universal Sentiment Score (USS) condenses a wide range of market conditions into one easy-to-read oscillator. Instead of relying on a single signal, USS blends multiple forms of trend strength, momentum behavior, volatility shifts, and reversal conditions to generate a unified sentiment metric.
FxAST Ichi ProSeries Enhanced Full Market Regime EngineFxAST Ichi ProSeries v1.x is a modernized Ichimoku engine that keeps the classic logic but adds a full market regime engine for any market and instrument.”
Multi-timeframe cloud overlay
Oracle long-term baseline
Trend regime classifier (Bull / Bear / Transition / Range)
Chikou & Cloud breakout signals
HTF + Oracle + Trend dashboard
Alert-ready structure for automation
No repainting: all HTF calls use lookahead_off.
1. Core Ichimoku Engine
Code sections:
Input group: Core Ichimoku
Function: ichiCalc()
Variables: tenkan, kijun, spanA, spanB, chikou
What it does
Calculates the classic Ichimoku components:
Tenkan (Conversion Line) – fast Donchian average (convLen)
Kijun (Base Line) – slower Donchian average (baseLen)
Senkou Span A (Span A / Lead1) – (Tenkan + Kijun)/2
Senkou Span B (Span B / Lead2) – Donchian over spanBLen
Chikou – current close shifted back in time (displace)
Everything else in the indicator builds on this engine.
How to use it (trading)
Tenkan vs Kijun = short-term vs medium-term balance.
Tenkan above Kijun = short-term bullish control; below = bearish control.
Span A / B defines the cloud, which represents equilibrium and support/resistance.
Price above cloud = bullish bias; price below cloud = bearish bias.
Graphic
2. Display & Cloud Styling
Code sections:
Input groups: Display Options, Cloud Styling, Lagging Span & Signals
Variables: showTenkan, showKijun, showChikou, showCloud, bullCloudColor, bearCloudColor, cloudLineWidth, laggingColor
Plots: plot(tenkan), plot(kijun), plot(chikou), p1, p2, fill(p1, p2, ...)
What it does
Lets you toggle individual components:
Show/hide Tenkan, Kijun, Chikou, and the cloud.
Customize cloud colors & opacity:
bullCloudColor when Span A > Span B
bearCloudColor when Span A < Span B
Adjust cloud line width for clarity.
How to use it
Turn off components you don’t use (e.g., hide Chikou if you only want cloud + Tenkan/Kijun).
For higher-timeframe or noisy charts, use thicker Kijun & cloud so structure is easier to see.
Graphic
Before
After
3. HTF Cloud Overlay (Multi-Timeframe)
Code sections:
Input group: HTF Cloud Overlay
Vars: showHTFCloud, htfTf, htfAlpha
Logic: request.security(..., ichiCalc(...)) → htfSpanA, htfSpanB
Plots: pHTF1, pHTF2, fill(pHTF1, pHTF2, ...)
What it does
Pulls higher-timeframe Ichimoku cloud (e.g., 1H, 4H, Daily) onto your current chart.
Uses the same Ichimoku settings but aggregates on htfTf.
Plots an extra, semi-transparent cloud ahead of price:
Greenish when HTF Span A > Span B
Reddish when HTF Span B > Span A
How to use it
Trade LTF (e.g., 5m/15m) only in alignment with HTF trend:
HTF cloud bullish + LTF Ichi bullish → look for longs
HTF cloud bearish + LTF Ichi bearish → look for shorts
Treat HTF cloud boundaries as major S/R zones.
Graphic
4. Oracle Module
Code sections:
Input group: Oracle Module
Vars: useOracle, oracleLen, oracleColor, oracleWidth, oracleSlopeLen
Logic: oracleLine = donchian(oracleLen); slope check vs oracleLine
Plot: plot(useOracle ? oracleLine : na, "Oracle", ...)
What it does
Creates a long-term Donchian baseline (default 208 bars).
Uses a simple slope check:
Current Oracle > Oracle oracleSlopeLen bars ago → Oracle Bull
Current Oracle < Oracle oracleSlopeLen bars ago → Oracle Bear
Slope state is also shown in the dashboard (“Bull / Bear / Flat”).
How to use it
Think of Oracle as your macro anchor :
Only take longs when Oracle is sloping up or flat.
Only take shorts when Oracle is sloping down or flat.
Works well combined with HTF cloud:
HTF cloud bullish + Oracle Bull = higher conviction long bias.
Ideal for Gold / Indices swing trades as a trend filter.
Graphic idea
5. Trend Regime Classifier
Code sections:
Input group: Trend Regime Logic
Vars: useTrendRegime, bgTrendOpacity, minTrendScore
Logic:
priceAboveCloud, priceBelowCloud, priceInsideCloud
Tenkan vs Kijun alignment
Cloud bullish/bearish
bullScore / bearScore (0–3)
regime + regimeLabel + regimeColor
Visuals: bgcolor(regimeColor) and optional barcolor() in priceColoring mode.
What it does
Scores the market in three dimensions :
Price vs Cloud
Tenkan vs Kijun
Cloud Direction (Span A vs Span B)
Each condition contributes +1 to either bullScore or bearScore .
Then:
Bull regime when:
bullScore >= minTrendScore and bullScore > bearScore
Price in cloud → “Range”
Everything else → “Transition”
These regimes are shown as:
Background colors:
Teal = Bull
Maroon = Bear
Orange = Range
Silver = Transition
Optional candle recoloring when priceColoring = true.
How to use it
Filters:
Only buy when regime = Bull or Transition and Oracle/HTF agree.
Only sell when regime = Bear or Transition and Oracle/HTF agree.
No trade zone:
When regime = Range (price inside cloud), avoid new entries; wait for break.
Aggressiveness:
Adjust minTrendScore to be stricter (3) or looser (1).
Graphic
6. Signals: Chikou & Cloud Breakout
Code sections :
Logic:
chikouBuySignal = ta.crossover(chikou, close)
chikouSellSignal = ta.crossunder(chikou, close)
cloudBreakUp = priceInsideCloud and priceAboveCloud
cloudBreakDown = priceInsideCloud and priceBelowCloud
What it does
1. Two key signal groups:
Chikou Cross Signals
Buy when Chikou crosses up through price.
Sell when Chikou crosses down through price.
Classic Ichi confirmation idea: Chikou breaking free of price cluster.
2. Cloud Breakout Signals
Long trigger: yesterday inside cloud → today price breaks above cloud.
Short trigger: yesterday inside cloud → today price breaks below cloud.
Captures “equilibrium → expansion” moves.
These are conditions only in this version (no chart shapes yet) but are fully wired for alerts. (Future Updates)
How to use it
Use Chikou signals as confirmation, not standalone entries:
Eg., Bull regime + Oracle Bull + cloud breakout + Chikou Buy.
Use Cloud Breakouts to catch the first impulsive leg after consolidation.
Graphic
7. Alerts (Automation Ready)
[
b]Code sections:
Input group: Alerts
Vars: useAlertTrend, useAlertChikou, useAlertCloudBO
Alert lines like: "FxAST Ichi Bull Trend", "FxAST Ichi Bull Trend", "FxAST Ichi Cloud Break Up"
What it does
Provides ready-made alert hooks for:
Trend regime (Bull / Bear)
Chikou cross buy/sell
Cloud breakout up/down
Each type can be globally toggled on/off via the inputs (helpful if a user only wants one kind).
How to use it
In TradingView: set alerts using “Any alert() function call” on this indicator.
Then filter which ones fire by:
Turning specific alert toggles on/off in input panel, or
Filtering text in your external bot / webhook side.
Example simple workflow ---> Indicator ---> TV Alert ---> Webhook ---> Bot/Broker
8. FxAST Dashboard
Code sections:
Input group: Dashboard
Vars: showDashboard, dashPos, dash, dashInit
Helper: getDashPos() → position.*
Table cells (updated on barstate.islast):
Row 0: Regime + label
Row 1: Oracle status (Bull / Bear / Flat / Off)
Row 2: HTF Cloud (On + TF / Off)
Row 3: Scores (BullScore / BearScore)
What it does
Displays a compact panel with the state of the whole system :
Current Trend Regime (Bull / Bear / Transition / Range)
Oracle slope state
Whether HTF Cloud is active + which timeframe
Raw Bull / Bear scores (0–3 each)
Position can be set: Top Right, Top Left, Bottom Right, Bottom Left.
How to use it
Treat it like a pilot instrument cluster :
Quick glance: “Are my trend, oracle and HTF all aligned?”
Great for streaming / screenshots: everything important is visible in one place without reading the code.
Graphic (lower right of chart )
Trend Line Methods (TLM)Trend Line Methods (TLM)
Overview
Trend Line Methods (TLM) is a visual study designed to help traders explore trend structure using two complementary, auto-drawn trend channels. The script focuses on how price interacts with rising or falling boundaries over time. It does not generate trade signals or manage risk; its purpose is to support discretionary chart analysis.
Method 1 – Pivot Span Trendline
The Pivot Span Trendline method builds a dynamic channel from major swing points detected by pivot highs and pivot lows.
• The script tracks a configurable number of recent pivot highs and lows.
• From the oldest and most recent stored pivot highs, it draws an upper trend line.
• From the oldest and most recent stored pivot lows, it draws a lower trend line.
• An optional filled area can be drawn between the two lines to highlight the active trend span.
As new pivots form, the lines are recalculated so that the channel evolves with market structure. This method is useful for visualising how price respects a trend corridor defined directly by swing points.
Method 2 – 5-Point Straight Channel
The 5-Point Straight Channel method approximates a straight trend channel using five key points extracted from a fixed lookback window.
Within the selected window:
• The window is divided into five segments of similar length.
• In each segment, the highest high is used as a representative high point.
• In each segment, the lowest low is used as a representative low point.
• A straight regression-style line is fitted through the five high points to form the upper boundary.
• A second straight line is fitted through the five low points to form the lower boundary.
The result is a pair of straight lines that describe the overall directional channel of price over the chosen window. Compared to Method 1, this approach is less focused on the very latest swings and more on the broader slope of the market.
Inputs & Menus
Pivot Span Trendline group (Method 1)
• Enable Pivot Span Trendline – Turns Method 1 on or off.
• High trend line color / Low trend line color – Colors of the upper and lower trend lines.
• Fill color between trend lines – Base color used to shade the area between the two lines. Transparency is controlled internally.
• Trend line thickness – Line width for both high and low trend lines.
• Trend line style – Line style (solid, dashed, or dotted).
• Pivot Left / Pivot Right – Number of bars to the left and right used to confirm pivot highs and lows. Larger values produce fewer but more significant swing points.
• Pivot Count – How many historical pivot points are kept for constructing the trend lines.
• Lookback Length – Number of bars used to keep pivots in range and to extend the trend lines across the chart.
5-Point Straight Channel group (Method 2)
• Enable 5-Point Straight Channel – Turns Method 2 on or off.
• High channel line color / Low channel line color – Colors of the upper and lower channel lines.
• Channel line thickness – Line width for both channel lines.
• Channel line style – Line style (solid, dashed, or dotted).
• Channel Length (bars) – Lookback window used to divide price into five segments and build the straight high/low channel.
Using Both Methods Together
Both methods are designed to visualise the same underlying idea: price tends to move inside rising or falling channels. Method 1 emphasises the most recent swing structure via pivot points, while Method 2 summarises the broader channel over a fixed window.
When the Pivot Span Trendline corridor and the 5-Point Straight Channel boundaries align or intersect, they can highlight zones where multiple ways of drawing trend lines point to similar support or resistance areas. Traders can use these confluence zones as a visual reference when planning their own entries, exits, or risk levels, according to their personal trading plan.
Notes
• This script is meant as an educational and analytical tool for studying trend lines and channels.
• It does not generate trading signals and does not replace independent analysis or risk management.
• The behaviour of both methods is timeframe- and symbol-agnostic; they will adapt to whichever chart you apply them to.
Trend Following Volatility Trail*Script was previously removed by Moderators at 1.8k boosts* - This was out of my control. This script was very popular and seemed to help a lot of traders. I am re uploading to help the community!
Trend Following Volatility Trail
The Trend Following Volatility Trail is a dynamic trend-following tool that adapts its stop, bias, and zones to real-time volatility and trend strength. Instead of using static ATR multiples like a normal Supertrend or Chandelier Stop, it continuously adjusts itself based on how stretched the market is and how persistent the trend has been. This indicator is based on volatility weighted EMAC
This makes the system far more reactive during momentum phases and more conservative during consolidation, helping avoid fake flips and late entries.
How It Works
The indicator builds an adaptive trail around a smoothed price basis:
– It starts with a short EMA as the “core trend line.”
– It measures volatility expansion versus normal volatility.
– It measures trend persistence by reading whether price has been rising or falling consistently.
– These two components combine to adjust the ATR multiplier dynamically.
As volatility expands or the trend becomes more persistent, the bands widen.
When volatility compresses or the trend weakens, the bands tighten.
These adaptive bands form the foundation of the trailing system.
Bull & Bear State Logic
The tool constantly tracks whether price is above or below the adaptive trail:
Price above the upper trail → Bullish regime
Price below the lower trail → Bearish regime
But instead of flipping immediately, it waits for confirmation bars to avoid noise.
This greatly reduces whipsaws and keeps the focus on sustained moves.
Once a new regime is confirmed:
– A coloured cloud appears (bull or bear)
– A label marks the flip point
– Alerts can be triggered automatically
Best Uses
Identifying regime shifts early
Riding sustained trends with confidence
Avoiding choppy markets by requiring confirmation
Using the adaptive cloud as a directional bias layer
Percentage Distance from 200-Week SMA200-Week SMA % Distance Oscillator (Clean & Simple)
This lightweight, no-nonsense indicator shows how far the current price is from the classic 200-week Simple Moving Average, expressed as a percentage.
Key features:
• True percentage distance: (Price − 200w SMA) / 200w SMA × 100
• Auto-scaling oscillator (no forced ±100% range → the line actually moves and looks alive)
• Clean zero line
• +10% overbought and −10% oversold levels with subtle background shading
• Real-time table showing the exact current percentage
• Small label on the last bar for instant reading
• Alert conditions when price moves >10% above or below the 200-week SMA
Why 200-week SMA?
Many legendary investors and hedge funds (Stan Druckenmiller, Paul Tudor Jones, etc.) use the 200-week SMA as their ultimate long-term trend anchor. Being +10% or more above it has historically signaled extreme optimism, while −10% or lower has marked deep pessimism and generational buying opportunities.
Perfect for Bitcoin, SPX, gold, individual stocks – works on any timeframe (looks especially good on daily and weekly charts).
Open-source • No repainting • Minimalist & fast
Enjoy and trade well!
Distribution Day Grading [Blk0ut]Distribution Day Grading
This script is designed to give traders and investors a fast, objective, and modern read on market health by analyzing distribution days, and stall days, two forms of institutional selling that often begin to appear before trend weakness, failed breakouts, and sharp corrections.
The goal of this script isn’t to predict tops or bottoms, but instead, it measures the character of the tape in a way that’s simple, visual, and immediately actionable.
While distribution analysis has existed for decades, my implementation is, I think, a little more adaptive. Traditional rules for identifying distribution days, coming from CANSLIM methodology, were built for markets which had lower volatility, different liquidity profiles, and slower institutional rotation. This script updates the traditional method with modernized thresholds, recency-weighted decay, stall-day logic, and dynamic presets tuned uniquely for the personality of each major U.S. index (you can change the values yourself as well).
The results are displayed as a compact letter-grade that quantitatively reflects a measure of how much institutional supply has been hitting the market, as well as how recently. This helps determine whether conditions are supportive of breakouts, mean reversion trades, aggressive trend trades, or whether caution and lighter sizing are warranted.
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How It Works
The script evaluates each bar for two conditions:
1. Distribution Day
A bar qualifies as distribution when:
- Price closes down beyond a threshold (default 0.30%, adjustable)
- Volume is higher than the prior session (optional toggle)
Distribution days typically represent active institutional selling .
2. Stall Day
A softer form of supply:
-Price remains flat to slightly negative within a small threshold
-Close < open
-Volume higher than prior day
Stall days represent a passive distribution or hidden supply .
Each distribution day is counted as 1 unit by the script, each stall day as 0.5 units.
Recency Weighting
The script applies an optional half-life decay so that fresh distribution matters more than old distribution. This mimics the “aging out” effect that professional traders use, but does it in a smoother, more mathematically consistent way.
The script then produces:
A weighted distribution score
A raw distribution + stall count
A letter grade from A → F
Let's talk about the letters...
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Letter Grade Meaning
A — Very Healthy Tape
Minimal institutional selling.
Breakouts behave better, momentum holds, pullbacks are shallow, upside targets are hit more consistently.
B — Healthy / Slight Caution
Some isolated supply but nothing structural.
Conditions remain favorable for trend trades, pullbacks, and breakout continuation.
C — Mixed / Caution Warranted
Distribution is building.
Breakouts begin to fail faster, candles widen, rotation becomes unstable, and risk/reward compresses.
D — Weak / Risk Elevated
Institutional selling is becoming persistent.
Failed breakouts, sharp reversals, and failed rallies become more common. Position sizing should tighten.
F — Clear Deterioration
Broad, repeated institutional distribution.
This is where major tops, deeper pullbacks, and corrections often begin to form underneath the surface.
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Index-Tuned Presets (Auto Mode)
Market structure varies dramatically across indices.
To address this, the script includes auto-detect presets for:
SPY / SPX equivalents
QQQ / NASDAQ-100 equivalents
IWM / Russell 2000 equivalents
DIA / Dow 30 equivalents
Each preset contains optimized values based on volatility, liquidity, noise, and institutional behavior:
SPY / SPX
Low noise, deep liquidity → classic thresholds work well.
Distribution thresholds remain conservative.
QQQ
Higher volatility → requires a slightly larger down-percentage filter to avoid false signals.
IWM
Noisiest of the major indices → requires much stricter thresholds to filter out junk signals.
DIA
Slowest-moving index → tighter conditions catch real distribution earlier.
The script automatically detects which symbol family you’re viewing and loads the appropriate preset unless manual overrides are enabled.
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How to Interpret This Indicator
Grade A–B:
Breakouts have higher odds of clean continuation
Mean reversion is smoother
Position sizing can be more assertive
Grade C:
Start tightening risk
Focus on A- setups, not B- or C- risk ideas
Grade D–F:
Expect lower win rates
Expect breakout failures
Favor countertrend plays or reduced exposure
Take faster profits
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This indicator should help traders prevent themselves from fighting the tape or sizing aggressively when the underlying environment is deteriorating through:
- Modernized distribution logic, not the 1990s thresholds
- Recency-weighted decay instead of the old 5-week “aging out”
- Stall-day detection for subtle institutional supply
- Auto-presets tuned per index, adjusting thresholds to match volatility and liquidity
- Unified letter-grade scoring for visual clarity
- Independent application for any trading style, it helps with trend, momentum, mean reversion, and options
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Keep in mind: This script is provided strictly for educational and informational purposes.
Nothing in this indicator constitutes financial advice, trading advice, investment guidance, or a recommendation to buy or sell any security, option, cryptocurrency, or financial instrument.
No indicator should ever be used as the sole basis for a trading or investment decision.
Markets carry risk. Past performance does not predict future results.
Always perform your own analysis, use proper risk management, and consult a licensed professional if you need advice specific to your financial situation.
Happy Trading!
Blk0uts
Relative Performance Areas [LuxAlgo]The Relative Performance Areas tool enables traders to analyze the relative performance of any asset against a user-selected benchmark directly on the chart, session by session.
The tool features three display modes for rescaled benchmark prices, as well as a statistics panel providing relevant information about overperforming and underperforming streaks.
🔶 USAGE
Usage is straightforward. Each session is highlighted with an area displaying the asset price range. By default, a green background is displayed when the asset outperforms the benchmark for the session. A red background is displayed if the asset underperforms the benchmark.
The benchmark is displayed as a green or red line. An extended price area is displayed when the benchmark exceeds the asset price and is set to SPX by default, but traders can choose any ticker from the settings panel.
Using benchmarks to compare performance is a common practice in trading and investing. Using indexes such as the S&P 500 (SPX) or the NASDAQ 100 (NDX) to measure our portfolio's performance provides a clear indication of whether our returns are above or below the broad market.
As the previous chart shows, if we have a long position in the NASDAQ 100 and buy an ETF like QQQ, we can clearly see how this position performs against BTSUSD and GOLD in each session.
Over the last 15 sessions, the NASDAQ 100 outperformed the BTSUSD in eight sessions and the GOLD in six sessions. Conversely, it underperformed the BTCUSD in seven sessions and the GOLD in nine sessions.
🔹 Display Mode
The display mode options in the Settings panel determine how benchmark performance is calculated. There are three display modes for the benchmark:
Net Returns: Uses the raw net returns of the benchmark from the start of the session.
Rescaled Returns: Uses the benchmark net returns multiplied by the ratio of the benchmark net returns standard deviation to the asset net returns standard deviation.
Standardized Returns: Uses the z-score of the benchmark returns multiplied by the standard deviation of the asset returns.
Comparing net returns between an asset and a benchmark provides traders with a broad view of relative performance and is straightforward.
When traders want a better comparison, they can use rescaled returns. This option scales the benchmark performance using the asset's volatility, providing a fairer comparison.
Standardized returns are the most sophisticated approach. They calculate the z-score of the benchmark returns to determine how many standard deviations they are from the mean. Then, they scale that number using the asset volatility, which is measured by the asset returns standard deviation.
As the chart above shows, different display modes produce different results. All of these methods are useful for making comparisons and accounting for different factors.
🔹 Dashboard
The statistics dashboard is a great addition that allows traders to gain a deep understanding of the relationship between assets and benchmarks.
First, we have raw data on overperforming and underperforming sessions. This shows how many sessions the asset performance at the end of the session was above or below the benchmark.
Next, we have the streaks statistics. We define a streak as two or more consecutive sessions where the asset overperformed or underperformed the benchmark.
Here, we have the number of winning and losing streaks (winning means overperforming and losing means underperforming), the median duration of each streak in sessions, the mode (the number of sessions that occurs most frequently), and the percentages of streaks with durations equal to or greater than three, four, five, and six sessions.
As the image shows, these statistics are useful for traders to better understand the relative behavior of different assets.
🔶 SETTINGS
Benchmark: Benchmark for comparison
Display Mode: Choose how to display the benchmark; Net Returns: Uses the raw net returns of the benchmark. Rescaled Returns: Uses the benchmark net returns multiplied by the ratio of the benchmark and asset standard deviations. Standardized Returns: Uses the benchmark z-score multiplied by the asset standard deviation.
🔹 Dashboard
Dashboard: Enable or disable the dashboard.
Position: Select the location of the dashboard.
Size: Select the dashboard size.
🔹 Style
Overperforming: Enable or disable displaying overperforming sessions and choose a color.
Underperforming: Enable or disable displaying underperforming sessions and choose a color.
Benchmark: Enable or disable displaying the benchmark and choose colors.
Dresteghamat-Multi timeframe Regime & Exhaustion**Dresteghamat-Multi timeframe Regime & Exhaustion**
This script is a custom decision-support dashboard that aggregates volatility, momentum, and structural data across multiple timeframes to filter market noise. It addresses the problem of "Analysis Paralysis" by automating the correlation between lower timeframe momentum and higher timeframe structure using a weighted scoring algorithm.
### 🔧 Methodology & Calculation Logic
The core engine does not simply overlay indicators; it normalizes their outputs into a unified score (-100 to +100). The logic is hidden (Protected) to preserve the proprietary weighting algorithm, but the underlying concepts are as follows:
**1. Adaptive Timeframe Selection (Context Engine)**
Instead of static monitoring, the script detects the user's current chart timeframe (`timeframe.multiplier`) and dynamically assigns two relevant Higher Timeframes (HTF) as anchors.
* *Logic:* If Current TF < 5min, the script analyzes 15m and 1H data. If Current TF < 1H, it shifts to 4H and Daily data. This ensures the analysis is contextually relevant.
**2. Regime & Volatility Filter (ATR Based)**
We use the Average True Range (ATR) to determine the market regime (Trend vs. Range).
* **Calculation:** We compare the current Swing Range (High-Low lookback) against a smoothed ATR. A high Ratio (> 2.0) indicates a Trend Regime, activating Trend-Following logic. A low ratio dampens the signals.
**3. Directional Bias (Structure + Flow)**
Direction is not determined by a single crossover. It is a fusion of:
* **Swing Structure:** Using `ta.pivothigh/low` to identify Higher Highs/Lower Lows.
* **Volume Flow:** Calculating the cumulative delta of candle bodies over a lookback period.
* **Micro-Bias:** A short-term (default 5-bar) momentum filter to detect immediate order flow changes.
**4. Exhaustion Logic (Mean Reversion Warning)**
To prevent buying at tops, the script calculates an "Exhaustion Score" based on:
* **RSI Divergence:** Detecting discrepancies between price peaks and momentum.
* **Volatility Extension:** Identifying when price has deviated significantly from its volatility mean (VRSD logic).
* **Volume Anomalies:** Detecting low volume on new highs (Supply absorption).
### 📊 How to Read the Dashboard
The table displays the raw status of each timeframe. The **"MODE"** row is the output of the algorithmic decision tree:
* **BUY/SELL ONLY:** Generated when the Current TF momentum aligns with the dynamically selected HTF structure AND the Exhaustion Score is below the threshold (default 70).
* **PULLBACK:** Triggered when the HTF Structure is bullish, but Current Momentum is bearish (indicating a corrective phase).
* **HTF EXHAUST:** A safety warning triggered when the HTF Volatility or RSI metrics hit extreme levels, overriding any entry signals.
* **WAIT:** Default state when volatility is low (Range Regime) or signals conflict.
### ⚠️ Disclaimer
This tool provides algorithmic analysis based on historical price action and volatility metrics. It does not guarantee future results.
Bearish Engulfing Automatic Finding Script This is a bearish pattern formed by three candlesticks.
The pattern is based on the fact that the last candlestick must
completely engulf the previous two and be downward. The two preceding
candlesticks must also be upward. Candlestick wicks are not taken
into account.
Swing Traces [BigBeluga]🔵 OVERVIEW
The Swing Traces indicator identifies significant swing points in the market and extends them forward as fading traces. These traces represent the memory of recent highs and lows, showing how price interacts with past turning points over time. Traders can use the fading intensity and breakout signals to gauge when a swing has lost influence or when price reacts to it again.
🔵 CONCEPTS
Swing Detection – Detects recent upper and lower swing points using sensitivity-based highs and lows.
Trace Longevity – Each swing projects a “trace” forward in time, gradually fading with age until it expires.
Trace Size – Each trace is drawn with both a main level and a size extension (half of the bar range) to highlight swing influence.
Longevity Counters – Swings remain active for a customizable number of bars before fading out or being crossed by price.
Swing Retest – Labels appear when price retest above/below an active trace extension levels, confirming potential reversal.
🔵 FEATURES
Adjustable sensitivity length for swing detection.
Separate longevity controls for upper and lower swing traces.
Fading gradient coloring for visualizing how long a trace has been active.
Double-trace plotting: one at the swing level and one offset by trace size.
Clear BUY/SELL signals when price crosses a swing trace after it has matured.
🔵 HOW TO USE
Use blue (upper) traces as resistance zones; lime (lower) traces as support zones.
Watch for fading traces: the longer they persist, the weaker their influence becomes.
Retest dots (●) confirm when price retest a trace, signaling a potential reversal.
Shorter sensitivity values detect faster, smaller swings; longer values capture major swing structures.
Combine with trend indicators or volume to filter false breakout signals.
🔵 CONCLUSION
The Swing Traces indicator is a powerful tool for mapping price memory. By projecting recent swing highs and lows forward and fading them over time, it helps traders see where price may react, consolidate, or break through with strength. Its dynamic traces and breakout labels make it especially useful for swing traders, breakout traders, and liquidity hunters.
ITM EMA Scalper (9/15) + Dual Index ConfirmationITM EMA Scalper (9/15) + Dual Index Confirmation is a precision scalping tool designed for traders who want high-probability entries, tight risk, and clean momentum trades using ITM options on NIFTY & BANKNIFTY.
This indicator combines price action, EMA trend filters, momentum candle logic, and a dual-index confirmation system to eliminate fake signals and catch only high-quality moves.
🔥 Core Logic
This indicator uses:
9 EMA & 15 EMA for trend direction
EMA angle filter (≥30°) to ensure strong directional momentum
Momentum candle detection (Pin Bar, Big Body, Rejection Candle)
EMA touch/rejection logic for precision entries
Dual index alignment (NIFTY + BANKNIFTY) for institutional-level confirmation
Trades occur only when both indices agree, dramatically reducing false setups.
🎯 Entry Conditions
A BUY signal appears when:
9 EMA > 15 EMA
Both EMAs have strong upward slope
Momentum candle forms while touching/near EMAs
Candle closes bullish
Confirmation index (e.g., BankNifty) also bullish
A SELL signal is the exact opposite.
🛡 Risk Management Built-In
For every valid setup, the indicator automatically plots:
Entry level (break of candle high/low)
Stop-loss level (low/high of signal candle)
1:2 Risk–Reward Target
These lines extend until target or SL is hit (or are cleared automatically after N bars).
🧠 Why ITM Options?
Using ITM options gives:
Higher delta
Faster momentum capture
Lower time decay impact
Cleaner correlation with spot movement
Perfect for scalping.
📈 Ideal Timeframe
Designed for 5-minute charts
Works for both NIFTY and BANKNIFTY
⚡ Alerts Included
BUY Alert
SELL Alert
These alerts trigger exactly when the strategy identifies a high-probability setup.
🚫 Avoid False Signals
This indicator prevents trades if:
Trend is flat
EMAs lose angle
Opposite index contradicts the setup
Candle lacks momentum
Market is choppy or sideways
💡 Perfect For
Scalpers
Index option traders
ITM directional traders
Algo traders needing clean signal logic
Momentum strategy users
Reversal Correlation Pressure [OmegaTools]Reversal Correlation Pressure is a quantitative regime-detection and signal-filtering framework designed to enhance both reversal timing and breakout validation across intraday and multi-session markets.
It is built for discretionary and systematic traders who require a statistically grounded filter capable of adapting to changing market conditions in real time.
1. Purpose and Overview
Market conditions constantly rotate through phases of expansion, contraction, trend persistence, and noise-driven mean reversion. Many strategies break down not because the signal is wrong, but because the regime is unsuitable.
This indicator solves that structural problem.
The tool measures the evolving correlation relationship between highs and lows — a robust proxy for how “organized” or “fragmented” price discovery currently is — and transforms it into a regime pressure reading. This reading is then used as the core variable to validate or filter reversal and breakout opportunities.
Combined with an internal performance-based filter that learns from its past signals, the indicator becomes a dynamic decision engine: it highlights only the signals that statistically perform best under the current market regime.
2. Core Components
2.1 Correlation-Based Regime Mapping
The relationship between highs and lows contains valuable information about market structure:
High correlation generally corresponds to coherent, directional markets where momentum and breakouts tend to prevail.
Low or unstable correlation often appears in overlapping, rotational phases where price oscillates and mean-reversion behavior dominates.
The indicator continuously evaluates this correlation, normalizes it statistically, and displays it as a pressure histogram:
Higher values indicate regimes favorable to trend continuation or momentum breakouts.
Lower values indicate regimes where reversals, pullbacks, and fade setups historically perform better.
This regime mapping is the foundation upon which the adaptive filter operates.
2.2 Reversal Stress & Breakout Stress Signaling
Raw directional opportunities are identified using statistically significant deviations from short-term equilibrium (overbought/oversold dynamics).
However, unlike traditional mean-reversion or breakout tools, signals here are not automatically taken. They must first be validated by the regime framework and then compared against the performance of similar past setups.
This dual evaluation sharply reduces the noise associated with reversal attempts during strong trends, while also preventing breakout attempts during choppy, anti-directional conditions.
2.3 Adaptive Regime-Selection Backtester
A key innovation of this indicator is its embedded micro-backtester, which continuously tracks how reversal or breakout signals have performed under each correlation regime.
The system evaluates two competing hypotheses:
Signals perform better during high-correlation regimes.
Signals perform better during low-correlation or neutral regimes.
For each new trigger, the indicator looks back at a rolling sample of past setups and measures short-term performance under both regimes. It then automatically selects the regime that currently demonstrates the superior historical edge.
In other words, the indicator:
Learns from recent market behavior
Determines which regime supports reversals
Determines which regime supports breakouts
Applies the optimal filter in real time
Highlights only the signals that historically outperformed under similar conditions
This creates a dynamic, statistically supervised approach to signal filtering — a substantial improvement over static or fixed-threshold systems.
2.4 Visual Components
To support rapid decision-making:
Correlation Pressure Histogram:
Encodes regime strength through a gradient-based color system, transitioning from neutral contexts into strong structural phases.
Directional Markers:
Visual arrows appear when a signal passes all filters and conditions.
Bar Coloring:
Bars can optionally be recolored to reflect active bullish or bearish bias after the adaptive filter approves a signal.
These components integrate seamlessly to give the trader a concise but complete view of the underlying conditions.
3. How to Use This Indicator
3.1 Identifying Regimes
The histogram is the anchor:
High, brightly colored columns suggest trend-friendly behavior where breakout alignment and directional follow-through have historically been stronger.
Low or muted columns suggest mean-reversion contexts where counter-trend opportunities and reversal setups gain reliability.
3.2 Filtering Signals
The indicator automatically decides whether a reversal or breakout trigger should be respected based on:
the current correlation regime,
the learned performance of recent signals under similar conditions, and
the directional stress detected in price.
The user does not need to adjust anything manually.
3.3 Integration with Other Tools
This indicator works best when combined with:
VWAP or session levels
Market internals and breadth metrics
Volume, order flow, or delta-based tools
Local structural frameworks (support/resistance, liquidity highs and lows)
Its strength is in telling you when your other signals matter and when they should be ignored.
4. Strengths of the Framework
Automatically adapts to changing micro-regimes
Reduces false reversals during strong trends
Avoids false breakouts in overlapping, rotational markets
Learns from recent historical performance
Provides a statistically driven confirmation layer
Works on all liquid assets and timeframes
Suitable for both discretionary and automated environments
5. Disclaimer
This indicator is provided strictly for educational and analytical purposes.
It does not constitute trading advice, investment guidance, or a recommendation to buy or sell any financial instrument.
Past performance of any statistical filter or adaptive method does not guarantee future results.
All trading involves significant risk, and users are responsible for their own decisions and risk management.
By using this indicator, you acknowledge that you are fully responsible for your trading activity.
