Smart Impulse [Eric]Inspired by the hard work proofed by @OoKo.
Thank you.
Impulse == entry signal.
It can be a false signal, so you have to place the orders with stop loss.
This is the first algo for experimenting the market price action and volume impulse.
I will release a better update in the future.
חפש סקריפטים עבור "smart"
Smart RSIC [Eric]This RSIC can perform better than the normal RSI and RSIC on predicting the trend by representing different color and showing divergence also.
SMART RSISimilar to RSI in concept, but with a few enhancements!
Improvements over the standard RSI indicator?
1. Adaptive Decision Boundaries:
Who says 70-30 are the best decision boundaries to use for trading off of the RSI indicator? Why not 80-20, or another combination? Is 70-30 still the best when you shorten or lengthen the RSI indicator's look-back window? What about when you change the time frame? I wondered this for a while too, and thats what inspired me to create this indicator! Instead of using fixed lines for the boundaries, the boundaries are calculated based off of a user specified percentile. What this means is that the reference lines are calculated by looking at the values the RSI indicator took over some look back window, and calculating an upper and lower bound where the RSI actually stayed n% of the time over that look-back window. The default parameter given for this argument is 90. What that means is over the last n days, the RSI indicator spent 90% of it's time between the upper and lower bound.
2. Smoothing The RSI Indicator:
The RSI indicator on smaller time windows tends to be very noisy. However a simple linear regression over a short time period on the RSI indicator helps to cancel out this noise without losing too much information. This makes cross-overs more meaningful as they are less likely to happen due to small deviations. In addition, it also paints a smoothed picture of the price momentum that is easy and pleasant to read. The reference lines are also smoothed.
3. Color Coding Crosses When They Happen!
Wouldn't it be great if your software highlights cross overs when they happen for you so you would not have to go back over your chart and identify it for yourself? Well this software does! It paints red behind the indicator when the RSI indicator goes above the upper reference line, and paints blue when the RSI goes below the lower reference line.
The default parameters were selected based on what I feel is useful for daily candles on BTCUSD. However you are free to change the parameters as you see fit for different securities and time frames.
Smart Volume (alpha)This script distinguishes up/down volume based on lower resolution.
It's important to set correct inputs.
TuxAlgo Plus SMC u. Trap Toolkit Rel.V0.98r by McTogaTuxAlgo Plus – Smart Money Concepts + Smart Money Traps + Fair Value Gaps Version: V0.98r (Alpha/Pre-Release) with integrated 2% risk calculator
The “TuxAlgo Plus” indicator is a powerful, standalone, conceptual open-source project and self-sufficient “smart money toolkit” with automatic trap detection (SMT), liquidity grabs, FVG confluence, and complete bot setup signals for TradingView charts in the “H1 to H6” time frame and the daily chart.
The script is used to improve SMC/trap analysis, i.e., the structure and visualization logic for TradingView charts has been expanded in the “TuxAlgo++” project in line with Smart Money Concepts (SMC) and Smart Money Traps (SMT).
The “TuxAlgo” Pine script is a standalone implementation of smart money concepts (structure, BOS/CHOCH, simple order blocks, fair value gaps) written from scratch. Terms such as “BOS,” “CHOCH,” “order block,” and “fair value gap” are commonly used concepts in market technology. This means that the market structure is often visible on the ‘H4’ time frame
and the trigger on the “H1” time frame.
ORB Pro - NY Opening Range Breakout by Elev8+ORB Pro - NY Opening Range Breakout | Smart Support & Resistance
ORB Pro is a comprehensive, professional-grade toolkit designed for intraday traders who rely on the Opening Range Breakout (ORB) strategy.
Unlike standard ORB indicators that simply draw lines, this suite offers a complete dashboard-driven system that monitors four distinct sessions simultaneously, providing real-time status updates and precision alerts.
— — —
🎯 What is the Opening Range Breakout (ORB)?
The Opening Range is the price range established during the first period of the trading session (e.g., the first 15 or 30 minutes). This period represents the initial balance between buyers and sellers. A breakout from this range often signals the likely trend direction for the remainder of the session.
— — —
🚀 Key Features
1. Multi-ORB Monitoring
Stop switching settings constantly. This suite monitors four key ranges at once:
Pre-Market 15m (08:00 – 08:15 ET)
Pre-Market 30m (08:00 – 08:30 ET)
NY Cash Open 15m (09:30 – 09:45 ET)
NY Cash Open 30m (09:30 – 10:00 ET)
2. Smart Status Dashboard
A compact panel in the bottom-right corner gives you the live state of every session:
⏳ Waiting: The session has not started yet.
⚡ Forming: The range is currently being built.
↔️ Range: The range has formed, but price is still contained within the range.
🚀 BULL / 📉 BEAR: A confirmed breakout has occurred.
⛔ OFF: The session is disabled in settings.
3. "Dynamic Resolution" Technology
This is a unique pro feature.
Precision: The script always calculates the High/Low levels using 1-minute data , ensuring your support/resistance lines are pixel-perfect regardless of your chart timeframe.
Flexibility: Breakout signals (Alerts/Labels) are triggered based on your current chart timeframe. This allows you to trade a 5m or 15m breakout strategy while keeping 1m-level precision on your levels.
4. Visual Clarity
Breakout Labels: Automatically plots "BULL" or "BEAR" labels on the exact candle that confirms a breakout.
Profit Targets: Optional toggle to show 1x and 2x profit targets projected from the breakout level.
Time-Bound Signals: Signals are strictly time-bound to the active window to prevent late, low-quality alerts.
— — —
🛠️ How to Use
Add to Chart: Works best on intraday timeframes (1m, 5m, 15m).
Configure: Enable the sessions you trade (e.g., NY 15m) in the settings.
Wait for Forming: Watch the box form live. The dashboard will show "⚡ Forming".
Trade the Break: Wait for a candle Close outside the range. The dashboard will flip to "BULL" or "BEAR" and a label will appear.
Manage Risk: Use the opposite side of the range or the midline as your stop loss.
— — —
⚙️ Settings Overview
Global Settings: Toggle forming boxes, dashboard, and label visibility.
Breakout Method: Choose between Close (safer) or Wick (aggressive) for signal triggers.
Session Groups: Individually enable/disable the 4 distinct sessions and customize their colors/styles.
— — —
📝 Update Notes (Recent)
New PDH/PDL Levels: Added the ability to display Previous Day High and Previous Day Low lines on the chart.
Auto-Update & Cleanup: The PDH/PDL lines now automatically update daily and erase historical lines, ensuring only the current day's levels are visible to keep the chart clean.
Dashboard Positioning: Added a new setting to move the Status Dashboard to any corner of the screen.
Enhanced Customization: Added full styling options in settings for PDH/PDL lines and Dashboard positioning.
— — —
Disclaimer: This tool is for educational and analytical purposes only. Past performance of a strategy does not guarantee future results. Always manage your risk.
BLACK OPS Pro Edition (White Knight) v1.0BLACK OPS Pro Edition (White Knight) v1.0
Author: Mayo – Black Ops (WBI) Whales Belly Investments
Version: 1.0
Pine Script: v6
Overlay: Yes
Product Description
The BLACK OPS Pro Edition (White Knight) is a professional-grade TradingView overlay designed for traders seeking clarity, actionable insights, and multi-timeframe precision. This dashboard combines ultra SuperTrend flips, dynamic Delta Zones, ATR-based volatility detection, EMA trend analysis, and real-time trust indicators into a single powerful interface.
It’s built for intraday and swing traders who want instant visual cues on bullish or bearish momentum, consolidation zones, and high-confidence entry points—without cluttering the chart.
Key Features
Multi-Timeframe EMA Trend – Monitor EMA alignment across multiple timeframes for accurate trend detection.
Ultra SuperTrend Flips – Intrabar first-bar arrows highlight potential trend reversals immediately.
Delta Zones Buy/Sell Pressure – Non-persistent labels indicate strong buying or selling pressure.
ATR-Based Guidance – Stop-loss, take-profit, and volatility context for trade decisions.
Fog Overlay – Visual fog between EMAs shows short-term trend momentum; green = bullish, red = bearish.
Professional Dashboard – Upper-right table displays overall trend, signals, volatility, chop/trend status, and multi-timeframe consensus.
Trust Indicators – “✅ TRUST BUY / SELL” alerts when multiple confirmations align.
Customizable Inputs – Adjust EMAs, ATR periods, risk/reward, SuperTrend sensitivity, and visual options.
Non-Persistent Signals – Arrows and labels only display intrabar, keeping historical data uncluttered.
Installation & Instructions
Add to TradingView:
Open TradingView → Pine Editor → Paste the script → Add to Chart.
Adjust Inputs (Optional):
EMA Lengths & Filters: Fine-tune trend detection settings.
ATR / Risk Settings: Configure stop-loss and take-profit multipliers.
SuperTrend Factors: Adjust sensitivity for trend flips.
Display Options: Toggle fog overlay, labels, and arrows.
Using Signals:
Bullish Signals (🚀BUY): Confirm dashboard trend and trust indicators.
Bearish Signals (💥SELL): Check volatility, Delta Zones, and multi-timeframe consensus.
Trust Indicators: ✅ TRUST BUY / SELL appears when conditions align across trend, volatility, and multi-timeframe checks.
Dashboard Overview
Row Content Description
Overall BULL 🟢 / BEAR 🔴 / MIXED ⚪ Current market trend based on EMA + SuperTrend.
20m Trend BULL 🟢 / BEAR 🔴 / NEUTRAL ⚪ Short-term EMA trend reference.
Signals 🚀LONG / 💥SHORT Active buy/sell triggers.
Volatility HIGH ⚡ / LOW 💤 Market activity indicator using ATR.
Chop / Trend CHOP 🟡 / TRENDING 🟢 Detects consolidation vs trending conditions on lower timeframes.
Delta Zones Labels
Strong Buy: ✅ White Knight (below candle, intrabar only)
Strong Sell: ⚡ Black OPS (above candle, intrabar only)
High-confidence zones indicate significant buying or selling pressure and appear only when conditions are met to keep charts clean.
Visual Elements
Fog Overlay: Green = bullish, Red = bearish (adjustable transparency)
EMAs: Short- and medium-term EMAs plotted for trend reference
SuperTrend Arrows: Green = bullish flip, Red = bearish flip
Trust Labels: ✅ TRUST BUY / SELL signals when confirmations align
Lower-Left Watermark
Text: “Property of Black Ops Trading Company”
Semi-transparent, non-intrusive, updates dynamically with chart movement.
Lower-Right Disclaimer
⚠️ For educational purposes only. NOT financial advice.
Trading involves risk. Test strategies in paper trading first. Users are fully responsible for trades.
Marketing Blurbs
Long-Form:
“Unlock the BLACK OPS Pro Edition – your all-in-one TradingView tool for multi-timeframe trend detection, intrabar SuperTrend flips, and high-confidence Delta Zone alerts. Perfect for traders who want professional insights and actionable guidance instantly.”
“Track trend, volatility, and high-probability trade zones in real time with intuitive arrows, fog overlays, and a full dashboard. Make informed decisions faster and trade smarter.”
Short-Form / One-Liners:
“Black Ops Pro Edition: Spot trends, flips, and high-probability trades instantly!”
“Trade smarter with EMA trends, SuperTrend flips, and Delta Zone alerts!”
“See the trend, catch the flips, and know when the pros buy and sell!”
Quick Reference – Colors & Labels
Element Color
Bullish Arrows / Trust Buy Green
Bearish Arrows / Trust Sell Red
Fog Bullish Green
Fog Bearish Red
Delta Strong Buy White
Delta Strong Sell Gray
Dashboard Text Bull Green
Dashboard Text Bear Red
Dashboard Neutral / Mixed Gray / White
QQQ/ES Overlay on NQQQQ/ES Overlay on NQ
This indicator overlays QQQ or ES price levels onto your NQ chart, dynamically mapping reference levels from your chosen symbol to equivalent NQ prices. Perfect for tracking correlations between Nasdaq futures and related instruments.
Key Features
Dual Symbol Support - Toggle between QQQ and ES with a dropdown. Each symbol uses optimized defaults: QQQ shows every 1 point, ES shows every 5 points.
Pre-Market Ready - Extended session support starting at 4:00 AM ET captures pre-market movement. By 9:00 AM, levels accurately reflect overnight action.
Smart Level Mapping - Calculates real-time ratio between NQ and your overlay symbol, then maps round price levels (like QQQ 614 or ES 5985) to equivalent NQ prices.
Anti-Jitter Technology - Stability threshold prevents lines from shaking on minor movements while maintaining accuracy.
How It Works
The indicator fetches live prices from both QQQ and ES, calculates the dynamic ratio to NQ, and displays mapped reference levels. For example, if NQ trades at 21,500 and QQQ at 614, the ratio is approximately 35.016. This means QQQ 615 maps to roughly 21,535 on your NQ chart.
Customization
Choose overlay source (QQQ or ES)
Adjust level increments independently for each symbol
Set number of levels above/below price
Customize line style, width, and color
Control label appearance and position
Fine-tune update sensitivity
Use Cases
Track market correlations in real-time, identify divergences between instruments, trade off psychological round numbers from correlated markets, monitor pre-market relationships, and maintain consistent reference levels across timeframes.
Settings
Default configuration shows 20 levels above and below current price with white lines at 40% opacity. QQQ uses 1-point increments, ES uses 5-point increments. Labels appear 8 bars to the right with dashed lines. Minimum 0.5-point move required to update positions.
Technical Notes
Designed specifically for NQ charts. Uses extended session data (4:00 AM - 8:00 PM ET) for live calculations. Outside trading hours, maintains ratio from previous close. Real-time updates depend on active data feed for all symbols.
RiskyInvesting Algo PRORiskyInvesting Algo PRO
A premium multi-layer trend-following and momentum-confirmation system built on Heikin-Ashi candles, dual adaptive ATR trailing baselines, and intelligent multi-filter signal validation. The PRO version expands the core 5-parameter foundation with 4 additional advanced parameters, delivering significantly sharper entries, reduced false signals, and deeper market context for disciplined trend-flip trading.This model uses 9 parameters (vs 5 in the Free version), offering greater customization and precision. For more info, follow me on Twitter/X .
Disclaimer :
Must be used with Heikin-Ashi candle type.
Designed to complement your existing trading system. Signals and labels are not financial advice.
Core Features (Shared with Free Version) :
Heikin-Ashi Transformation: Smooths noise for clearer trend structure.
Dual Adaptive Trailing Baselines: ATR-based dynamic support/resistance lines (Parameters 1 & 2) that flip direction on confirmed breaks.
Directional Shift Detection: Buy/sell signals triggered by synchronized baseline flips.
Trend Bias Filtering: EMA vs SMMA relationship colors signals and defines macro bias.
Candle Strength Filter (Parameter 5): Requires meaningful momentum candles (≥30% of ATR body) for signal validity.
Exclusive PRO Version Upgrades :
Parameter 6: EMA/SMMA Proximity Filter
Highlights periods of indecision when the EMA and SMMA are extremely close (tick-based threshold, auto-adjusted by timeframe). Background turns semi-transparent purple to warn of unclear bias and discourage trading.
Parameter 7: Signal Mode Selection
Choose between Default (baselines can flip on separate candles) or Strict (both baselines must flip on the same candle) for higher-conviction entries.
Parameter 8: Retest Filter
Optional confirmation requiring price to retest the prior candle’s high/low (with buffer) after a flip, filtering out weak breakouts and improving win rate on reversals.
Parameter 9: Multi-Timeframe BB/KC Squeeze Filter
Monitors up to 7 higher timeframes (preset or user-customizable) for concurrent BB/KC squeezes — a powerful consolidation detector.
- Visual squeeze counter at chart bottom (color-coded by intensity).
- Real-time squeeze status table (toggleable).
- High squeeze count (5–6+) triggers strong purple consolidation warning.
Enhanced Visual & Alert System (PRO Exclusive) :
Smart Color-Coded Labels: Green/Blue (bullish), Red/Orange (bearish), or Purple (caution) based on bias, proximity, squeeze state, or counter-bias entries.
Star Rating on Signals: 🌟 or 🌟🌟 indicates how many strength filters (body + retest) were passed.
Position Sizing Emojis in Alerts:
🟩 = Full Position | 🟦 = Half Position
🟥 = Full Position | 🟧 = Half Position
Purple Caution Alerts: Clearly explain consolidation, unclear bias, or risky counter-bias setups.
EMA/SMMA Crossover Bias Alerts: Notifies on major macro trend shifts.
Real-Time Intrabar Baseline Cross Alerts: Early warning when price crosses trailing lines mid-bar.
Built for serious traders seeking a highly refined, low-noise trend-reversal system with institutional-grade filters, multi-timeframe awareness, and crystal-clear visual feedback — ideal for volatile intraday and swing setups.
ICT MTF FVG BPR Toolkit [D4A}The ICT MTF FVG BPR Toolkit encompasses the following 5 components:
- Fair Value Gaps - current timeframe
- Fair Value Gaps - higher timeframe
- BPR - Balanced Price Range
- Long Wicks - which are considered to be gaps by ICT
- Immediate Rebalance - it leaves no gaps, but is as important in assessing current workflow
This is advanced Fair Value Gaps script that uses trading methodology taught by ICT trader. To use it effectively it requires at least some basic knowledge of Smart Money Concepts (SMC) as outlined in ICT's lectures found on YT. I may publish another SMC related scripts in future if this kind of tool is useful to anybody.
The idea behind this work, is to have all the necessary tools related to Fair Value Gaps in one script that is easy to use (requires SMC knowledge), fully customizable and will keep the chart as clutter free as possible. Since, I could not find a ready-made script which would tick all my requirements, I created this new script, partially by borrowing some ideas and code from existing open source projects that I liked. Rather than re-inventing the wheel, I focused on adopting and improving existing solutions and have them work together in one tool that could present the information accurately and in a polished way, where the trader can customize almost everything. Full credit goes to other coders, who tackled this subject before me, but particularly to:
QuantVue
LuxAlgo
pmk07
The script have these unique features:
- Can present FVGs from up to 3 different timeframes at any given interval
- The amount and interval of higher timeframe FVGs is fully customizable
- FVGs can be displayed based on size
- Volume Imbalance can be included as part of FVG (as recommended by ICT)
- Higher timeframe FVGs can have quadrants displayed along with C.E. (based on ATR filter)
- Both current and higher timeframe FVGs can be displayed in different ways depending on price interactions
- BPR which works on current timeframe only
- Long Wick detection logic has been slightly changed from the original LuxAlgo code
- Immediate Rebalance code has been simplified and re-focused on clarity
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
SignalViper FangsSee where smart money is likely to react. Fangs automatically identifies high-probability support and resistance levels, displaying them as horizontal zones (cyan for support, magenta for resistance).
▸ Automatic detection of key reaction zones
▸ Institutional-level price structure analysis
▸ Dynamic level management (auto-removed when broken)
▸ Sensitivity presets controlling max levels and spacing
▸ Levels flip from S to R as price moves through
Multipower Entry SecretMultipower Entry Secret indicator is designed to be the ultimate trading companion for traders of all skill levels—especially those who struggle with decision-making due to unclear or overwhelming signals. Unlike conventional trading systems cluttered with too many lines and confusing alerts, this indicator provides a clear, adaptive, and actionable guide for market entries and exits.
Key Points:
Clear Buy/Sell/Wait Signals:
The script dynamically analyzes price action, candle patterns, volume, trend strength, and higher time frame context. This means it gives you “Buy,” “Sell,” or “Wait” signals based on real, meaningful market information—filtering out the noise and weak trades.
Multi-Timeframe Adaptive Analysis:
It synchronizes signals between higher and current timeframes, ensuring you get the most reliable direction—reducing the risk of getting caught in fake moves or sudden reversals.
Automatic Support, Resistance & Liquidity Zones:
Key levels like support, resistance, and liquidity zones are auto-detected and displayed directly on the chart, helping you make precise decisions without manual drawing.
Real-Time Dashboard:
All relevant information, such as trend strength, market intent, volume sentiment, and the reason behind each signal, is neatly summarized in a dashboard—making monitoring effortless and intuitive.
Customizable & Beginner-Friendly:
Whether you’re a newcomer wanting straightforward guidance or a professional needing advanced customization, the indicator offers flexible options to adjust analysis depth, timeframes, sensitivity, and more.
Visual & Clutter-Free:
The design ensures that your chart remains clean and readable, showing only the most important information. This minimizes mental overload and allows for instant decision-making.
Who Will Benefit?
Beginners who want to learn trading logic, avoid common traps, and see the exact reason behind every signal.
Advanced traders who require adaptive multi-timeframe analytics, fast execution, and stress-free monitoring.
Anyone who wants to save screen time, reduce analysis paralysis, and have more confidence in every trade they take.
1. No Indicator Clutter
Intent:
Many traders get confused by charts filled with too many indicators and signals. This often leads to hesitation, missed trades, or taking random, risky trades.
In this Indicator:
You get a clean and clutter-free chart. Only the most important buy/sell/wait signals and relevant support/resistance/liquidity levels are shown. These update automatically, removing the “overload” and keeping your focus sharp, so your decision-making is faster and stress-free.
2. Exact Entry Guide
Intent:
Traders often struggle with entry timing, leading to FOMO (fear of missing out) or getting trapped in sudden market reversals.
In this Indicator:
The system uses powerful adaptive logic to filter out weak signals and only highlight the strongest market moves. This not only prevents you from entering late or on noise, but also helps avoid losses from false breakouts or whipsaws. You get actionable suggestions—when to enter, when to hold back—so your entries are high-conviction and disciplined.
3. HTF+LTF Logic: Multitimeframe Sync Analysis
Intent:
Most losing trades happen when you act only on the short-term chart, ignoring the bigger market trend.
In this Indicator:
Signals are based on both the current chart timeframe (LTF) and a higher (HTF, like hourly/daily) timeframe. The indicator synchronizes trend direction, momentum, and structure across both levels, quickly adapting to show you when both are aligned. This filtering results in “only trade with the bigger trend”—dramatically increasing your win rate and market confidence.
4. Auto Support/Resistance & Liquidity Zones
Intent:
Drawing support/resistance and liquidity zones manually is time-consuming and error-prone, especially for beginners.
In this Indicator:
The system automatically identifies and plots the most crucial support/resistance levels and liquidity zones on your chart. This is based on adaptive, real-time price and volume analysis. These zones highlight where major institutional activity, trap setups, or real breakouts/reversals are most likely, removing guesswork and giving you a clear reference for entries, exits, and stop placements.
5. Clear Action/Direction
Intent:
Traders need certainty—what does the market want right now? Most indicators are vague.
In this Indicator:
Your dashboard always displays in plain words (like “BUY”, “SELL”, or “WAIT”) what action makes sense in the current market phase. Whether it’s a bull trap, volume spike, wick reversal, or exhaustion—it’s interpreted and explained clearly. No more confusion—just direct, real-time advice.
6. For Everyone (Beginner to Pro)
Intent:
Most advanced indicators are overwhelming for new traders; simple ones lack depth for professionals.
In this Indicator:
It is simple enough for a beginner—just add it to the chart and instantly see what action to consider. At the same time, it includes advanced adaptive analysis, multi-timeframe logic, and customizable settings so professional traders can fine-tune it for their strategies.
7. Ideal Usage and User Benefits
Instant Decision Support:
Whenever you’re unsure about a trade, just look at the indicator’s suggestion for clarity.
Entry Learning:
Beginners get real-time “practice” by not only seeing signals, but also the reason behind them—improving your chart reading and market understanding.
Screen Time & Stress Reduction:
Clear, relevant information only; no noise, less fatigue, faster decisions.
Makes Trading Confident & Simple:
The smart dashboard splits actionable levels (HTF, LTF, action) so you never miss a move, avoid traps, and stay aligned with high-probability trades.
8. Advanced Input Settings (Smart Customization)
Explained with Examples:
Enable Wick Analysis:
Finds candles with strong upper/lower wicks (signs of rejection/buying/selling force), alerting you to hidden reversals and protecting from FOMO entries.
Enable Absorption:
Detects when heavy order flow from one side is “absorbed” by the other (shows where institutional buyers/sellers are likely active, helps spot fake breakouts).
Enable Unusual Breakout:
Highlights real breakouts—large volatility plus high volume—so you catch genuine moves and avoid random spikes.
Enable Range/Expansion:
Smartly flags sudden range expansions—when the market goes from quiet to volatile—so you can act at the start of real trends.
Trend Bar Lookback:
Adjusts how many bars/candles are used in trend calculations. Short (fast trades, more signals), long (more reliability, fewer whipsaws).
Bull/Bear Bars for Strong Trend Min:
Sets how many candles in a row must support a trend before calling it “strong”—prevents flipping signals, keeps you disciplined.
Volume MA Length:
Lets you adjust how many bars back volume is averaged—fine-tune for your asset and trading style for best volume signals.
Swing Lookback Bars:
Set how many bars to use for swing high/low detection—short (quick swing levels), long (stronger support/resistance).
HTF (Bias Window):
Decide which higher timeframe the indicator should use for big-picture market mood. Adjustable for any style (scalp, swing, position).
Adaptive Lookback (HTF):
Choose how much HTF history is used for detecting major extremes/zones. Quick adjust for more/less sensitivity.
Show Support/Resistance, Liquidity Zones, Trendlines:
Toggle them on/off instantly per your needs—keeps your chart relevant and tailored.
9. Live Dashboard Sections Explained
Intent HTF:
Shows if the bigger timeframe currently has a Bullish, Bearish, or Neutral (“Chop”) intent, based on strict volume/price body calculations. Instant clarity—no more guessing on trend bias.
HTF Bias:
Clear message about which side (buy/sell/sideways) controls the market on the higher timeframe, so you always trade with the “big money.”
Chart Action:
The central action for the current bar—Whether to Buy, Sell, or Wait—calculated from all indicator logic, not just one rule.
TrendScore Long/Short:
See how many candles in your chosen window were bullish or bearish, at a glance. Instantly gauge market momentum.
Reason (WHY):
Every time a signal appears, the “reason” cell tells you the primary logic (breakout, wick, strong trend, etc.) behind it. Full transparency and learning—never trade blindly.
Strong Trend:
Shows if the market is currently in a powerful trend or not—helping you avoid choppy, risky entries.
HTF Vol/Body:
Displays current higher timeframe volume and candle body %—helping spot when big players are active for higher probability trades.
Volume Sentiment:
A real-time analysis of market psychology (strong bullish/bearish, neutral)—making your decision-making much more confident.
10. Smart and User-Friendly Design
Multi-timeframe Adaptive:
All calculations can now be drawn from your choice of higher or current timeframe, ensuring signals are filtered by larger market context.
Flexible Table Position:
You can set the live dashboard/summary anywhere on the chart for best visibility.
Refined Zone Visualization:
Liquidity and order blocks are visually highlighted, auto-tuning for your settings and always cleaning up to stay clutter-free.
Multi-Lingual & Beginner Accessible:
With Hindi and simple English support, descriptions and settings are accessible for a wide audience—anyone can start using powerful trading logic with zero language barrier.
Efficient Labels & Clear Reasoning:
Signal labels and reasons are shown/removed dynamically so your chart stays informative, not messy.
Every detail of this indicator is designed to make trading both simpler and smarter—helping you avoid the common pitfalls, learn real price action, stay in sync with the market’s true mood, and act with discipline for higher consistency and confidence.
This indicator makes professional-grade market analysis accessible to everyone. It’s your trusted assistant for making smarter, faster, and more profitable trading decisions—providing not just signals, but also the “why” behind every action. With auto-adaptive logic, clear visuals, and strong focus on real trading needs, it lets you focus on capturing the moves that matter—every single time.
LiquidEdge Original1️⃣ Why Most Traders Miss Key Market Turning Points
Most traders (you) struggle to identify true market pivots THE REAL TOP and BOTTOMS where reversals begin.
❌ You enter too early or too late because price alone doesn’t give enough confirmation
❌ You follow price blindly, unaware of the volume pressure building underneath
❌ You get caught in sideways markets, not realizing they’re often accumulation or distribution zones
❌ You can’t tell if momentum is building or fading, which leads to low confidence and inconsistent results
👉 LiquidEdge helps solve this by tracking volume momentum through a modified MFI slope and scoring system. It highlights potential pivots with real context, so you can see where smart money might be entering or exiting before price makes it obvious.
2️⃣ What LiquidEdge Actually Does and How
LiquidEdge helps solve common trading problems by adding structure and clarity to volume analysis.
✅ It builds on the classic Money Flow Index (MFI), but instead of just showing overbought/oversold levels, it calculates the slope of MFI to track real-time changes in volume momentum
✅ Each setup is scored based on a combination of factors: divergence strength, trend alignment using EMA, and whether the signal occurs inside a liquidity zone
✅ Hidden accumulation or distribution is revealed when volume pressure increases or fades while price remains flat or moves slightly, a sign of smart money positioning
✅ Divergences are only flagged when they occur near pivot zones and align with overall trend conditions, helping reduce false signals
✅ Potential pivots are identified when multiple factors overlap such as a liquidity zone breach, volume slope shift, and valid divergence which often signals entry or exit points for institutional players
👉 The result is a structured interpretation of price and volume flow, helping traders read momentum shifts and potential reversals more clearly in both trending and ranging markets.
3️⃣ What Makes LiquidEdge Different
LiquidEdge is built on top of the classic Money Flow Index (MFI), but adds structure that transforms it from a basic momentum tool into a decision-support system.
Instead of simply showing highs and lows, it scores each potential setup based on:
✅ The steepness and direction of the MFI slope (used to measure volume pressure)
✅ Whether the setup aligns with the broader trend using an EMA filter (default: 200 EMA)
✅ Whether the signal appears inside predefined liquidity zones (MFI above 80 or below 20)
👉 This scoring system reduces noise and helps you focus only on high-probability setups.
👉 It also checks volume pressure across multiple timeframes using MFI slope on 5M, 15M, 1H, 4H, and Daily charts. This reveals whether short-term moves are backed by longer-term volume momentum.
Color changes in the line and histogram are not decorative they reflect real shifts in volume pressure. Every visual cue is linked to live market logic.
What Makes It Stand Out
👉 Setup Scoring That Makes Sense
Each setup is scored by combining:
Signal strength (MFI slope intensity and stability)
Trend direction (via customizable EMA)
Liquidity zone relevance (MFI range filtering)
This structured scoring means you spend less time second-guessing and more time reading clean signals.
👉 Flow That Follows Real Momentum
The slope of the MFI tracks whether volume pressure is rising or falling:
🟢 Green = increasing inflow (buying pressure)
🔴 Red = increasing outflow (selling pressure)
👉 Multi-Timeframe Volume Context
LiquidEdge calculates flow direction independently on each major timeframe. You’ll know if short-term setups are confirmed by higher timeframe volume or going against it.
👉 Smart Divergence Filtering
Unlike simple divergence tools that compare price highs/lows directly, LiquidEdge filters divergences based on:
Local pivot zones (defined by lookback periods)
Trend confirmation (to eliminate countertrend noise)
4️⃣ How LiquidEdge Works (Under the Hood)
LiquidEdge tracks directional momentum using the slope of the Money Flow Index (MFI) giving you a real-time read on buying and selling pressure.
When the slope rises, it means buyers are stepping in and volume is supporting the move.
When it falls, sellers are taking control and volume outflow is increasing.
This slope acts like a pressure gauge for the market, helping you spot when a trend has strength or when it's starting to fade.
💡 Quick Comparison
RSI = momentum from price
MFI = momentum from price + volume
LiquidEdge takes it one step further by calculating the rate of change (slope) in MFI. That’s where the pressure signal comes from not just value, but directional flow.
Core Calculations (Simplified)
Typical Price = (High + Low + Close) ÷ 3
Raw Money Flow = Typical Price × Volume
MFI = 100 −
MFI ranges from 0 to 100.
High = strong buying volume
Low = growing selling pressure
LiquidEdge then calculates the slope of this MFI over time to track volume momentum dynamically.
Divergence Engine
LiquidEdge detects divergence by comparing price pivots with the direction of MFI slope.
❌ If price makes a higher high but MFI slope turns down, it’s a bearish divergence
✅ If price makes a lower low but MFI slope rises, it’s a bullish divergence
Divergences are only confirmed when they occur:
Near local pivot zones (defined by configurable lookback windows)
And, optionally, in alignment with the broader trend using an EMA filter
This filtering helps reduce false positives and keeps you focused on clean setups.
Structured Confidence Scoring
Each signal is visually scored based on:
➡️ Whether a valid divergence is detected
➡️ Whether the signal occurs inside a liquidity zone (MFI > 80 or < 20)
➡️ Whether the setup aligns with the overall trend direction (EMA filter)
More confluence = higher confidence
The scoring system helps prioritize setups that meet multiple criteria, not just one.
Liquidity Zones
Above 80: Signals possible buying exhaustion 👉 risk of reversal
Below 20: Indicates potential selling exhaustion 👉 watch for a bounce
Zones are shaded directly on the chart to highlight pressure extremes in real time.
Price + Volume Fusion
LiquidEdge blends price action with volume pressure using MFI slope and histogram behavior. It doesn’t just show you where price is moving. it shows whether the move is backed by real volume.
This lets you see:
Whether volume is confirming or fading behind a move
If a reversal is building even before price confirms it
Visual Feedback That Speaks Clearly
🟢 Green slope = increasing buying pressure
🔴 Red slope = increasing selling pressure
5️⃣ When Price Is Flat but LiquidEdge Moves: Volume Tells the Truth
One of the most useful things LiquidEdge can do is reveal pressure shifts when price looks neutral.
If price is moving sideways but the MFI slope or histogram rises, it may suggest that buying pressure is quietly increasing possibly pointing to early accumulation.
If price stays flat while the volume slope or histogram drops, this could indicate distribution, where sellers are exiting without moving the market noticeably.
These changes don’t guarantee a breakout or breakdown, but they often precede key moves especially when combined with other confluences like trend alignment or liquidity zones.
👉 LiquidEdge helps spot these setups by measuring volume momentum shifts beneath price action.
It doesn’t predict the future, but it gives you additional context to evaluate what may be developing before it’s visible on price alone.
6️⃣ Multi-Timeframe Flow Table
LiquidEdge includes a real-time table that tracks volume pressure across multiple timeframes including 5-minute, 15-minute, 1-hour, 4-hour, and daily charts.
Each row reflects the direction of the MFI slope on that timeframe, indicating whether volume pressure is increasing (inflow) or decreasing (outflow).
🟢 A rising slope suggests that buying momentum is building
🔴 A falling slope suggests selling pressure may be increasing
👉 This lets traders quickly assess whether short-term setups are aligned with higher timeframe volume trends a useful layer of confirmation for both intraday and swing strategies.
Rather than flipping between charts, the table gives you a snapshot of flow strength across the board, helping you stay focused on opportunities that align with broader market pressure.
7️⃣ Timeframes & Assets
Where LiquidEdge Works Best:
✅ Crypto: Supports major coins and high-volume altcoins (BTC, ETH, Top 100)
✅ Stocks: Effective on large-cap and mid-cap equities with consistent volume
✅ Futures: Tested on instruments like NQ, MNQ, ES, and MES
✅ Any liquid market where volume data is reliable and stable
For best results, use LiquidEdge on assets with consistent trading volume. It’s not recommended for ultra-low volume crypto pairs or micro-cap stocks, where irregular volume can distort signals.
Recommended Timeframes:
👉 Intraday trading: Works well on 3-minute, 5-minute, 15-minute, and 1-hour charts
👉 Swing trading: Performs reliably on 4-hour, daily, and weekly charts
👉 Ultra short-term (1-minute or less): Not recommended due to high noise and low reliability
LiquidEdge adapts to various trading styles from scalping short-term momentum shifts to analyzing broader volume trends across swing and positional setups. The key is choosing assets and timeframes with reliable volume flow for the tool to work effectively.
8️⃣ Common Mistakes to Avoid When Using LiquidEdge
❌ Using It in Isolation
LiquidEdge offers valuable context, but it’s not designed to function as a standalone trading system. Always combine it with key tools such as trendlines, support/resistance zones, chart structure, or fundamental data. The more supporting evidence you have, the stronger your analysis becomes.
❌ Relying on a Single Indicator
No indicator, including LiquidEdge, can account for every market condition. It’s important to use it alongside other forms of confirmation to avoid making decisions based on limited data.
❌ Misinterpreting Divergences as Reversals
A divergence between price and volume pressure doesn't always signal the end of a trend. If the broader direction remains strong (based on EMAs or higher timeframe volume flow), a divergence could reflect temporary consolidation rather than reversal.
❌ Ignoring Trend Alignment and Confidence Scoring
LiquidEdge includes confidence scoring to help validate signals. Disregarding this structure can lead to reacting to weak or out-of-context divergences, especially in choppy or low-volume environments.
❌ Using It on Second-Based or Tick Charts
Very low timeframes introduce too much noise, which can distort volume slope and divergence signals. For intraday analysis, start with 3-minute charts or higher. For swing trading, use 4H and up for clearer, more reliable structure.
9️⃣ LiquidEdge Settings Overview
A quick breakdown of what you can customize in the indicator and how each option affects what you see:
➡️ LiquidEdge Length
Controls how sensitive the indicator is to changes in volume pressure (via MFI slope).
Shorter values = faster response, more frequent signals
Longer values = smoother output, less noise
👉 Default: 14
➡️ EMA Trend Filter
Determines overall trend direction based on EMA slope. Used to filter out signals that go against the broader move.
Helps reduce countertrend entries
Adjustable to suit your strategy
👉 Recommended: 200 EMA
➡️ Pivot Lookback (Left & Right)
Defines how many bars the system looks back and forward to identify swing highs/lows for divergence detection.
Narrow: more responsive but can be noisy
Wide: slower but more stable pivot zones
👉 Default: 5 left / 5 right
➡️ Histogram Toggle
Enables a visual histogram showing how volume pressure deviates from its recent average.
Useful for spotting shifts in flow intensity
👉 Optional for added visual detail
➡️ Liquidity Zones
Highlights potential exhaustion zones based on MFI value:
Above 80 = potential distribution (buying pressure peaking)
Below 20 = possible accumulation (selling pressure fading)
👉 Zones are fully customizable (color, opacity, background)
➡️ Custom Threshold Zones
Set your own upper/lower boundaries for liquidity extremes helpful when adapting to different markets or asset classes.
👉 Especially useful outside of crypto/forex
➡️ Show LiquidEdge Line
Toggle the main MFI slope line. When turned off, liquidity zones and levels also disappear.
👉 Use if you prefer to focus only on histogram/divergences
➡️ Style Settings
Customize line colors, histogram appearance, and background shading
👉 Helps tailor visuals to your chart layout
➡️ Simplified Mode
Removes all colors and replaces visuals with a clean, grayscale output.
👉 Ideal for minimalist or distraction-free charting
➡️ Signal Score Label
Displays the confidence score of the current setup, based on:
Divergence presence
Liquidity zone positioning
Trend alignment (EMA)
👉 Tooltip explains how the score is calculated
➡️ Divergence Labels
Shows “Bullish” or “Bearish” labels at divergence points.
Optional Filters based on trend if EMA filter is active
➡️ Multi-Timeframe Flow Table
Shows directional flow (based on MFI slope) across: 5M, 15M, 1H, 4H, 1D
Color-coded (faded green/red) for clarity
👉 Table position is customizable on your chart
➡️ Alerts
Get notified when any of these conditions are met:
✅ Bullish or bearish divergence detected
✅ Price enters high/low liquidity zones
✅ Signal score reaches a defined value
➡️ Visibility Settings
Control which timeframes display the LiquidEdge indicator
👉 Best used on 3-minute and above
⚠️ Not recommended on ultra-low or second-based charts due to noise
🔟 Q&A – What Traders Usually Ask
➡️ Can this help reduce bad trades?
To a degree, yes. LiquidEdge is built to highlight areas where price may react, based on volume pressure, liquidity zones, and divergence patterns. It can offer clarity in sideways or messy markets, helping traders avoid impulsive or poorly timed entries.
That said, it’s not predictive or guaranteed. It works best when used with broader context including structure, support/resistance, trend, and volume-based confluence.
👉 Reminder: LiquidEdge is not a signal tool. It’s a decision-support framework designed to help you assess potential shifts, not replace judgment or trading rules.
➡️ Is this just another flashy signal tool?
No. LiquidEdge doesn’t give buy/sell alerts. Instead, it visualizes volume shifts using MFI slope, divergence filtering, and trend-based scoring. It’s built to help you understand why price action may be changing not just react to a one-dimensional signal.
You’re seeing how volume pressure evolves across timeframes, which gives added context to what’s unfolding in the market.
➡️ How do I know this isn’t just another overhyped tool?
LiquidEdge is based on real trading logic: volume pressure (via MFI slope), price behavior, and divergence within trend and liquidity zones. It was developed and tested by traders, not packaged by marketers.
No performance is guaranteed. It’s designed to support your decisions not promise results.
➡️ Will this work with my trading style?
If you trade any market with volume crypto, stocks, or futures LiquidEdge can add value.
✔️ Scalpers: Best from 3-minute and up
✔️ Swing traders: Works well on 4H, Daily, Weekly
✔️ Investors: Weekly charts show pressure buildup over time
⚠️ Avoid ultra-low timeframes (under 1M) or illiquid markets, as noise and irregular data can reduce reliability.
➡️ Can I trust the signals?
These are not buy/sell signals. LiquidEdge offers confidence-weighted insights based on:
✔️ Valid divergence
✔️ Zone positioning (above 80 / below 20)
✔️ Optional trend alignment (via EMA)
Each setup is scored visually to reflect how much confluence exists. You can combine that information with structure, price action, or your existing tools to evaluate opportunities.
👉 Think of LiquidEdge as a decision filter not a trigger.
It’s meant to slow down impulsive trades and help you make more context-aware decisions.
1️⃣1️⃣ Limitations – Know When It’s Less Effective
LiquidEdge performs best in stable, high-volume markets where volume data is consistent and structure is visible.
It’s not recommended for:
❌ Low-volume tokens
❌ Micro-cap or penny stocks
❌ Newly listed assets with limited trading history
These types of markets often show inconsistent or erratic volume behavior, making it difficult for LiquidEdge to accurately assess pressure or identify reliable divergences.
⚠️ During major news events or sudden volatility spikes, volume and price behavior can become disconnected or extreme. This may distort MFI slope calculations and reduce the accuracy of divergence or confidence scoring.
LiquidEdge is built to read structured volume flow. When market conditions become highly erratic or unpredictable, it's best to:
Wait for structure to return
Use it alongside other filters for additional confirmation
This isn't a flaw it's simply the nature of tools that rely on consistency in price and volume data.
1️⃣2️⃣ Real Chart Examples – See It in Action
Now that you’ve seen how LiquidEdge works, here are real-world chart examples from various asset classes
including:
✅ Crypto
✅ Stocks
✅ Futures
✅ Commodities
These examples demonstrate how LiquidEdge behaves under different conditions, and how both the line (MFI slope) and histogram (volume deviation) can be used to interpret market flow.
In each walkthrough, you’ll see:
How the histogram can highlight potential momentum shifts
When the slope line provides stronger directional clarity
Examples of possible hidden accumulation or distribution (before price responds)
What to watch out for such as weak volume, false divergences, or conflicting flow signals
👉 These are real examples based on live market data not theoretical setups. They’re meant to help you recognize how LiquidEdge reacts across multiple styles and timeframes.
Let’s walk through each one and break down the logic step by step, so you can understand how to evaluate setups using structure, volume behavior, and context-driven confluence.
Example: Microsoft (MSFT) – Possible Hidden Accumulation
In this setup, price was moving lower within a short-term downtrend. However, LiquidEdge began showing signs of increasing inflow pressure a common characteristic of accumulation, where volume rises even as price declines.
This divergence suggested that buying interest may have been increasing behind the scenes, despite weak price action on the surface.
Step-by-step breakdown:
👉 Trend context – Price was clearly trending down at the time
👉 Volume divergence – Price made lower lows, but LiquidEdge slope was rising = possible bullish divergence
👉 Accumulation clue – The rising slope, despite falling price, pointed to volume inflow often seen during quiet accumulation
👉 Histogram support – Volume pressure (via the histogram) also increased, confirming the flow shift
👉 Anticipating reaction – When liquidity pressure rises ahead of price, it can signal potential reversal interest
In this case, price later moved sharply higher. While not guaranteed, setups like this illustrate how divergence + volume flow may help highlight early accumulation zones before price confirms the shift.
Same Setup – Focusing on the Histogram Alone
Here, we’re revisiting the Microsoft setup but this time focusing only on the histogram, without the MFI slope line.
Even without the directional slope, the histogram showed rising volume pressure while price continued to drift lower. This visual pattern may indicate that buying interest was quietly increasing, despite weak price movement.
This is where the histogram adds value: it helps visualize the intensity of volume flow over time. When volume pressure builds during a flat or declining price phase, it can be consistent with accumulation where larger participants begin positioning before the market responds.
This example highlights how the histogram alone can provide early insight into underlying volume dynamics even before price shifts noticeably.
Filtering with EMA and why It Matters
Here, we revisit the Microsoft example this time applying the 200 EMA filter, which helps define the broader trend.
Once enabled, LiquidEdge automatically removed any bullish or bearish divergence signals that were against the prevailing trend. This helped reduce noise and focus only on setups aligned with market structure.
✅ The EMA acts as a contextual filter.
For example, if a bullish divergence occurs during a confirmed downtrend, LiquidEdge suppresses that signal helping you avoid setups that may carry more risk.
This filtering mechanism is especially useful in fast or choppy markets, where not all divergences are meaningful.
Want More Flexibility? Adjust the Filter
If you're a more aggressive trader or prefer shorter-term signals, you can reduce the EMA length (e.g., to 150, 50, or even 25). This increases the number of setups shown but also raises the importance of additional context and confirmation.
⚠️ Keep in mind:
❌ More signals doesn’t always mean better outcomes
✅ Focused, context-aware signals tend to be more consistent with broader market pressure
If you’re using this in combination with strategies like options trading, this filter can help refine your entry zones especially when paired with other structure or volatility tools.
Distribution Example and Bitcoin Setup Before a Major Drop
In this example, Bitcoin was trading in a relatively tight range while price continued to push upward. However, LiquidEdge began to show signs of volume outflow, which can suggest potential distribution.
Here’s what was observed:
🔴 Price was moving up inside a horizontal range
🔴 LiquidEdge’s slope indicated declining volume pressure
🔴 Several bearish divergence signals appeared during this consolidation phase
🔴 The histogram also showed weakening flow, even before price broke down
These overlapping signals pointed to a possible distribution phase, where buying momentum was fading despite price still holding up.
🧭 Signs to Watch for in Potential Distribution:
1️⃣ Price holding flat or rising slightly within a tight range
2️⃣ Volume pressure (line or histogram) sloping downward
3️⃣ Repeated bearish divergences forming at the highs
4️⃣ Lack of follow-through on bullish setups signaling hesitation in demand
While LiquidEdge can’t predict market outcomes, this scenario demonstrates how a combination of divergence, outflow, and failure to break out may serve as early warnings that momentum is shifting beneath the surface.
Failed Auction Example – Volume Shift Before a Breakdown
In this example, price attempted to break out above a recent high, creating the appearance of a bullish continuation. However, LiquidEdge began to signal volume outflow, despite the upward price move a potential sign of a failed auction.
Here’s what was observed:
👉 Price made a new high, appearing to break resistance
👉 LiquidEdge slope and histogram both showed declining liquidity
👉 The indicator formed lower lows, even as price pushed higher
👉 This divergence suggested that volume wasn’t supporting the breakout
Shortly after, price reversed and returned back inside the range which is a common characteristic of failed auction behavior.
🧭 Spotting a Potential Failed Auction with LiquidEdge:
1️⃣ Price breaks above a recent high
2️⃣ Volume flow (line + histogram) shows outflow, not inflow
3️⃣ Indicator forms lower lows while price makes higher highs (bearish divergence)
4️⃣ Market reverts back into the previous range without follow-through
While no tool can predict outcomes, this setup demonstrated how volume pressure and divergence can help identify moments where a breakout may lack real support offering context before price action confirms the shift.
Reading the Histogram - Spotting Pressure Fades
In this example, price was still rising but the LiquidEdge histogram showed falling volume pressure. This type of divergence between price and volume can serve as a potential early signal that momentum may be fading.
🔻 Histogram levels declined while price continued higher
🔻 This suggested that buying pressure was weakening, even though price hadn’t turned
🔻 Volume flow behavior didn’t support the continuation possibly indicating buyer exhaustion
Just before the peak, the histogram nearly reached its lower threshold, despite price still being near its highs.
💡 How to Read It:
When volume pressure (shown by the histogram) starts to fade while price is still rising, it can indicate that momentum is weakening. This may precede a pullback or reversal particularly if other factors like divergence or zone exhaustion are also present.
Conversely, rising histogram values during a price drop may suggest potential accumulation.
👉 Use the histogram as a volume intensity gauge, not a signal on its own especially when evaluating whether a move is supported by actual flow, or just price momentum.
The Table – Fast, Visual Multi-Timeframe Flow Insight
The multi-timeframe flow table in LiquidEdge provides a consolidated view of volume momentum across several key timeframes so you don’t need to switch between charts to compare flow strength.
👉 Instead of flipping from 5-minute to 15M, 1H, 4H, and Daily, the table displays flow direction on all of them at a glance.
Example layout:
🔼 Daily: Up
🔽 1H: Down
🔼 15M: Up
🔽 5M: Down
This setup gives you a quick read on whether volume momentum is aligned across multiple timeframes or diverging which can help frame your trade approach.
🧠 Why It’s Useful:
✅ Supports timeframe alignment
If higher timeframes show strong inflow while lower ones are mixed, you may interpret it as a swing-based opportunity. If short timeframes show pressure but higher frames are flat, it might suggest short-term setups with caution.
✅ Improves context awareness
Instead of interpreting a move in isolation, the table helps you assess whether short-term signals are part of a broader shift or going against higher timeframe flow.
💡 Pro Tip: Use the table as a starting point in your analysis. It’s a simple but effective snapshot of current liquidity pressure across the board helping you plan trades with broader context, rather than reacting chart-by-chart.
🔚 Final Thoughts
If you're focused on trading with better clarity and structure, LiquidEdge is designed to help you interpret what’s happening beneath the surface not just follow price movement.
While many tools highlight price alone, LiquidEdge combines volume pressure, divergence filtering, and trend-based context to help identify potential areas of accumulation, distribution, or momentum shifts even before they become obvious on a chart.
👉 This isn’t just another signal tool. It’s a framework to support smarter decision-making:
✔️ One that helps you filter out noise
✔️ One that scores setups using multiple layers of confirmation
✔️ One that brings volume context into every trade idea
Whether you're scalping on a 5-minute chart or managing a longer-term swing trade, LiquidEdge is built to help you stay aligned with volume-driven behavior not just react to price alone.
If you've struggled with late entries, unreliable setups, or second-guessing trades, this tool was designed to bring more structure to your process. It won’t remove all uncertainty but it can help you stay more selective, confident, and intentional.
✅ Trade with clarity
✅ Stay process-driven
✅ Focus on structure, not noise
LiquidEdge is not meant to replace your strategy. It’s here to enhance it.
In this chart, the 200 EMA filter was applied. As a result, only signals that aligned with the dominant trend direction were displayed helping to reduce distractions and focus on setups with stronger context.
💡 Using a higher EMA setting like 200 can reduce the number of signals shown, but may help you focus on higher-conviction opportunities.
That said, every trader is different:
Longer EMAs = fewer signals, but more trend-filtered setups
Shorter EMAs = more signals, faster entries but with potentially more noise
👉 Adjust the filter based on your trading style. Use a 200 EMA for swing trading, or reduce it to 50, 25, or even 5 if you're trading more aggressively or intraday.
LiquidEdge adapts to you not the other way around.
🔁 Adjusting EMA for Your Trading Style
Personal Tip: When trading more aggressively, I often use a 5 EMA filter especially when combining histogram strength with other tools. This increases signal responsiveness and may help highlight short-term flow shifts more quickly.
Below are visual examples that show how different EMA lengths impact the behavior of LiquidEdge:
50 EMA ON
25 EMA ON
5 EMA ON
Lower EMA Example – Gold with the 5 EMA
In this example, the 5 EMA filter was applied to Gold. As expected, more signals were plotted compared to higher EMA settings. The tool became more responsive to rapid shifts in volume momentum, making it more suitable for fast-paced trading environments.
This setting can help traders who prefer early entries but it also introduces more sensitivity, so context and additional confirmation become even more important.
Each setting affects signal frequency and filtering:
Higher EMA → fewer signals, more trend-confirmed setups
Lower EMA → more signals, quicker responses, but with more potential for noise
Choose what fits your approach:
Long-term swing → Stick with 200 EMA
Intraday or scalping → Consider shorter EMAs (50, 25, or 5)
💡 Reminder: EMA filtering is fully adjustable. LiquidEdge doesn’t lock you into one trading style it’s meant to adapt to your process, whether you’re swing trading or scalping short-term moves.
But There’s a Catch…
Using a lower EMA setting (like 5) opens up faster, more frequent signals but it also increases the need for precision and stronger trade management.
❗ More signals = More responsiveness
❗ Faster setups mean quicker decisions
❗ Risk control becomes even more important
💡 Lower Timeframes = More Detail, Less Margin for Error
A short EMA (like 5) can help you:
✅ Identify early momentum shifts
✅ Respond before traditional trend-followers
✅ Highlight short-term divergence and volume changes
But it also comes with tradeoffs:
❌ Greater signal noise
❌ Higher potential for misreads or fakeouts
❌ Requires clear structure and disciplined entries
🚩 Watch Out for Liquidity Grabs
In lower timeframes, a common trap is the liquidity grab where price pushes beyond recent highs or lows, triggers stops, then quickly reverses.
📌 These moves can look like breakouts, but often reverse quickly possibly reflecting institutional order placement or low-liquidity manipulation.
🧭 How to Approach It Smartly
✅ Use structure: Mark support and resistance to frame moves
✅ Confirm volume behavior: Is histogram strength rising or fading?
✅ Avoid chasing: Look for confluence, not just a single signal
✅ Be intentional with stops: Place them with structure in mind to avoid being swept out
NASDAQ Futures Example – Low Timeframe Setups with LiquidEdge
In this example, we look at how LiquidEdge was used to identify both short and long setups on the NASDAQ Futures (NQ) particularly on a low timeframe (5M), where quick decision-making and volume precision matter most.
⚠️ A Note on Futures and Volume
When trading futures, especially on intraday charts, it’s important to separate overnight volume from regular session activity.
🕒 Overnight Volume ≠ Real Volume Context
Overnight price action is informative, but the volume data itself may not reflect true market participation. In LiquidEdge, histogram and pressure calculations emphasize regular session flow helping avoid skewed signals that could come from low-volume overnight moves.
Using the Histogram to Spot Potential Shifts
One of the key cues I use is color transition in the histogram:
🔴 A flip from strong green to red can signal fading buying pressure, sometimes marking the beginning of a potential short setup.
🟢 A shift from red to green may indicate that buyers are returning, suggesting possible accumulation.
These shifts serve as early visual cues of changing pressure especially when confirmed by other tools or context.
🔁 Adding Context with the Line + Structure
After spotting a histogram shift, I look at:
1️⃣ Slope Line – Is it confirming the same directional pressure?
2️⃣ Support/Resistance – Are we near a meaningful zone?
3️⃣ Additional Tools – This includes trendlines, VWAP, EMAs, and overall price structure.
On lower timeframes like 5M, these pieces become even more important. LiquidEdge gives directional insight, but your full setup provides confirmation and execution logic.
⚠️ Disclaimer
LiquidEdge is not a signal tool. It’s a visual representation of market pressure and flow designed to help you make more informed trading and investing decisions. It shows you what’s happening beneath the price action but you are still responsible for your decisions.
Always combine LiquidEdge with your own strategy, research, and supporting tools. That includes trend analysis, support/resistance levels, chart patterns, and fundamentals (like P/E ratios, price-to-sales, debt ratios, etc.).
This tool should never be used alone or treated as financial advice.
Some content may include AI-powered enhancements for clarity or formatting.
Always do your own research. For personal financial guidance, speak with a licensed financial advisor.
CNagda-MomentumX - Institutional FlowMomentumX is designed to empower traders with a deeper understanding of market movements by focusing on Institutional Flow and advanced market structure analytics. The core goal is to identify and visualize where major market participants are operating, and to translate these complex footprints into clear, actionable trading signals — all in real time.
Real-time institutional activity mapping
Actionable entry and exit signals based on live market structure
Intuitive dashboard and dynamic chart visuals
Fully customizable modules for trend, liquidity, and order blocks
Core Logic Design
At the heart of MomentumX lies a robust algorithmic engine built to capture and surface institutional trading behavior. By leveraging advanced mathematical models, the indicator calculates institutional volume ratios and price momentum to pinpoint aggressive moves from large participants.
Institutional Volume & Price Momentum:
Utilizes custom volume indicators and price change analysis to detect strong buying or selling pressure, filtering out retail noise.
Liquidity Grab Detection & Activity Zones:
The script identifies liquidity grabs by monitoring abrupt price sweeps at major support/resistance levels—often where institutions trigger stop hunts or reversals. All critical activity zones are automatically color-coded on the chart for instant recognition.
Dashboard Visualization:
A fully dynamic dashboard table overlays live scores for accumulation, distribution, strength, and weakness—giving traders a real-time scan of market health.
Trendline & Order Block Architecture:
The logic auto-detects pivot highs/lows to draw smart trendlines, while the order block system highlights key reversal areas and breaker zones—making market structure clear and actionable.
MomentumX is packed with high-performance modules, each engineered to simplify complex market behavior and enhance decision-making for traders:
Institutional Flow Signals:
Instantly identifies spots where institutional players drive momentum, using unique volume and price activity analytics.
Bullish/Bearish Liquidity Grab Detection:
Marks abrupt price moves that signal stop hunts or reversals, letting traders anticipate snap-backs or trend shifts.
Trendline Auto-Detection:
Smartly draws trendlines based on significant swing highs and lows, automatically adjusting as price evolves.
Order Block System (Rejection/Breaker):
Spots and highlights key reversal zones with order block rectangles, confirming rejections or breakouts at strategic levels.
Dashboard and Bar Coloring:
A clean dashboard overlay presents live market scores, while dynamic bar coloring makes trend, strength, and high-activity periods instantly visible.
User Input Toggles for Each Module:
Every major feature is fully customizable—enable or disable modules to match individual trading setups or preferences.
Scripting/Development
MomentumX’s scripting process is modular, enabling clarity, scalability, and fast optimization throughout development:
Initialization & Inputs:
Start by defining all user input options, module toggles, color settings, and calculation parameters—ensuring maximum flexibility early on.
Core Calculation Functions:
Script advanced institutional volume and price momentum algorithms. Build out swing length logic, market state filters, and activity scoring methods.
Detection Engines:
Develop and integrate engines for liquidity grabs, automated trendline detection, and order block identification—each with dedicated functions for speed and precision.
Visual Overlays & Plotting:
Implement powerful plotting logic for colored bars, score dashboards, trendlines, reversal zones, and liquidity markers—making every data point clear and actionable on the chart.
Testing Handlers:
Add diagnostic panels and debug outputs to refine calculations and assure accuracy in every market environment.
Sample Trade Setups (Usage)
Cnagda MomentumX delivers clarity for multiple trading styles by providing timely, actionable setups grounded in institutional behavior and market structure. Here’s how traders can leverage the indicator for confident decision-making:
Liquidity Grab Reversal
Enter trades around detected liquidity grabs when price sweeps major support/resistance and the dashboard signals a momentum shift.
Example: Wait for a bullish/Bearish grab near market lows/high, with institutional flow turning positive/negative—enter long/short for potential mean reversion.
Order Block Breakout
Trade breakouts when price cleanly rejects or flips key order block zones highlighted on the chart.
Example: Short at a marked breaker block after a rejection signal, confirmed by a downward institutional activity spike.
Trendline Continuation
Ride established market moves by entering on trendline confirmations plotted by the auto-detect system.
Example: Go long after a trendline retest, confirmed by a green bar color and dashboard strength score.
Dashboard Confirmation
Combine dashboard metrics (strength, accumulation, distribution) with bar color overlays for multi-factor entries.
Example: Enter trades only when all market signals align in real time for maximum probability.
For Short Entry check -- Weakness : For Long Entry Check - Strength With Other Indications
MomentumX is not just another indicator – it’s your edge for reading the market like an insider. By transparently mapping institutional flow, uncovering hidden liquidity zones, and color-coding every major structure shift, MomentumX transforms complexity into actionable clarity. Whether you’re scalping, swing trading, or investing, you’ll gain a decisive, real-time advantage on every chart.
Embrace smarter decisions, adapt to changing market conditions instantly, and join a new generation of technically empowered traders.
Customize, observe, and let the market reveal opportunities in a way you’ve never experienced before.
Happy Trading
Cnagda Liquidit Trading SystemCnagda Liquidit Trading System helps spot where price is likely to trap traders and reverse, then gives simple, actionable Level to entry, place SL, and take profits with confidence. It blends imbalance zones, trend bias, order blocks, liquidity pools, high-probability fake Signal, and context-aware candle patterns into one clean workflow.
🟩🟥 Imbalance boxes: “Crowd rushed, gaps left”
What it is: Green/red boxes mark fast, one-sided moves where price “skipped” orders—think FVG-like zones that often get revisited.
Why it helps: Price frequently pulls back to “fill” these zones, creating clean retest entries with logical stops.
⏩How to use:
Green box = potential demand retest; Red box = potential supply retest. Enter on pullback into box, not on first impulse. Put stop on far side of box and aim first targets at recent swing points.
↕️ Swing bias (HH/HL vs LH/LL): “Which way is the road?”
What it is: Higher-highs/higher-lows = up-bias; Lower-highs/lower-lows = down-bias. system plots Buy/Sell OB levels aligned with that bias.
Why it helps: Trading with the broader flow reduces “hero trades” against institutions. Bias gives clearer entries and cleaner drawdowns.
⏩How to use:
Up-bias: look for long on Buy OB retests. Down-bias: look for short on Sell OB retests. Wait for a small rejection/engulfing to confirm before triggering.
🧱Order blocks: “Where big players remember”
What it is: last opposite-colored candle before an impulsive move—these zones often hold memory and reaction. system plots these as Buy/Sell OB lines.
Why it helps: Many breakouts pull back to the origin. Good entries often happen on retest, not on the breakout chase.
⏩ How to use:
Let price return into the OB, show wick rejection, and decent volume. Enter with stop beyond OB; define risk-reward before entry.
📊Volume coloring: “How Volume is move?”
What it is: Bar color reflects relative volume; inside bars are black. The dashboard also shows Volume and “Volume vs Prev.”
Why it helps: Patterns without volume often fade; volume validates strength and intent of moves.
⏩ How to use:
Favor entries where imbalance/OB/liquidity-grab coincide with higher volume. If volume is weak, reduce size or skip.
🧲 BSL/SSL liquidity pools: “Fishing for stops”
What it is: Equal highs cluster stops above (BSL); equal lows cluster stops below (SSL). system plots these and highlights the nearest one (“magnet”).
Why it helps: Price often sweeps these pools to trigger stops before reversing. This is a prime trap-reversal location.
⏩ How to use:
Watch nearest BSL/SSL. If price wicks through and closes back inside, anticipate a reversal. Trade reaction, not first poke. When price closes beyond, consider that pool mitigated and move on.
🟢🔴 Advanced liquidity grab: “Catch fakeout”
What it is: Bullish grab = makes a new low beyond a prior low but closes back above it, with a long lower wick, small body, and higher volume. Bearish is mirror. Labeled automatically.
Why it helps: It exposes trap moves (stop hunts) and often precedes true direction.
⏩ How to use:
Best when it aligns with a nearby imbalance/OB and supportive volume. Enter on reversal candle break or on retest. Stop goes beyond sweep wick.
🧠 Smart candlestick patterns (only in right place)
What it is: Engulfing, Hammer, Shooting Star, Hanging Man, Doji (with high volume), Morning/Evening Star, Piercing—but marked “effective” only if context (swing/trend/location) agrees.
Why it helps: same pattern in the wrong place is noise; in the right place, it’s signal.
⏩ How to use:
Location first (BSL/SSL/OB/imbalance), then pattern. Treat pattern as trigger/confirmation—one fresh label shows to keep chart clean.
🧭 Dashboard: “Context in a glance”
⏩ Reversal Level: current swing anchor—expect turns or reactions nearby; great for alerts and planning.
⏩ Volume vs Prev + Volume: Strength meter for signal candle—higher adds conviction.
⏩ Nearest Pool: next “magnet” area—look for sweeps/rejections there.
🧩Step-by-step trading flow (with mindset)
⏩ Set bias: HH/HL = long bias, LH/LL = short bias. Counter-trend only on clean sweeps with strong confirmation.
⏩ Find magnet: Check Nearest Pool (BSL/SSL). Focus attention there; it saves screen time.
⏩ Wait for event: Look for a sweep/grab label, or sharp rejection at pool/OB/imbalance. Avoid FOMO.
⏩ Add confluence: Stack 2–3 of these—imbalance box, OB, contextual pattern, supportive volume.
⏩Plan entry: Bullish: trigger above reversal candle high or take retest of FVG/OB. Stop below sweep wick/zone. Target at least 1:1.5–1:2.
Bearish: mirror above.
⏩Manage smartly: Take partials, move to breakeven or trail thoughtfully. Don’t drag stops inside zone out of emotion.
🎛️ Parameter tuning (to reduce human error)
⏩ swingLen: Smaller = faster but noisier; larger = cleaner but slower. Backtest first, then go live.
⏩ Tolerance (ATR or percent): ATR tolerance adapts to volatility (good for fast markets and lower TFs). Start around 0.15–0.30. In calm markets, try percent 0.05–0.15%.
⏩ minBarsGap: Start with 3–5 so equal highs/lows are truly equal—reduces false pools.
❌Common mistakes → ✅ Better habits
⏩Chasing every breakout → Wait for sweep/rejection, then confirm.
⏩Ignoring volume → Validate strength; cut size or skip on weak volume.
⏩Losing history of pools → If reviewing/backtesting, keep mitigated pools visible (dashed/faded).
⏩Over-tight tolerance/too small swingLen → Increases false signals; backtest to find balance.
📝 checklist (before entry)
⏩ Is there a nearby BSL/SSL and did a sweep/grab happen there?
⏩ Is there a close imbalance/OB that price can retest?
⏩ Do we have an effective pattern plus supportive volume?
⏩Is the stop beyond the wick/zone and RR ≥ 1:1.5?
•?((¯°·._.• 🎀 𝐻𝒶𝓅𝓅𝓎 𝒯𝓇𝒶𝒹𝒾𝓃𝑔 🎀 •._.·°¯((?•
COT IndexTHE HIDDEN INTELLIGENCE IN FUTURES MARKETS
What if you could see what the smartest players in the futures markets are doing before the crowd catches on? While retail traders chase momentum indicators and moving averages, obsess over Japanese candlestick patterns, and debate whether the RSI should be set to fourteen or twenty-one periods, institutional players leave footprints in the sand through their mandatory reporting to the Commodity Futures Trading Commission. These footprints, published weekly in the Commitment of Traders reports, have been hiding in plain sight for decades, available to anyone with an internet connection, yet remarkably few traders understand how to interpret them correctly. The COT Index indicator transforms this raw institutional positioning data into actionable trading signals, bringing Wall Street intelligence to your trading screen without requiring expensive Bloomberg terminals or insider connections.
The uncomfortable truth is this: Most retail traders operate in a binary world. Long or short. Buy or sell. They apply technical analysis to individual positions, constrained by limited capital that forces them to concentrate risk in single directional bets. Meanwhile, institutional traders operate in an entirely different dimension. They manage portfolios dynamically weighted across multiple markets, adjusting exposure based on evolving market conditions, correlation shifts, and risk assessments that retail traders never see. A hedge fund might be simultaneously long gold, short oil, neutral on copper, and overweight agricultural commodities, with position sizes calibrated to volatility and portfolio Greeks. When they increase gold exposure from five percent to eight percent of portfolio allocation, this rebalancing decision reflects sophisticated analysis of opportunity cost, risk parity, and cross-market dynamics that no individual chart pattern can capture.
This portfolio reweighting activity, multiplied across hundreds of institutional participants, manifests in the aggregate positioning data published weekly by the CFTC. The Commitment of Traders report does not show individual trades or strategies. It shows the collective footprint of how actual commercial hedgers and large speculators have allocated their capital across different markets. When mining companies collectively increase forward gold sales to hedge thirty percent more production than last quarter, they are not reacting to a moving average crossover. They are making strategic allocation decisions based on production forecasts, cost structures, and price expectations derived from operational realities invisible to outside observers. This is portfolio management in action, revealed through positioning data rather than price charts.
If you want to understand how institutional capital actually flows, how sophisticated traders genuinely position themselves across market cycles, the COT report provides a rare window into that hidden world. But understand what you are getting into. This is not a tool for scalpers seeking confirmation of the next five-minute move. This is not an oscillator that flashes oversold at market bottoms with convenient precision. COT analysis operates on a timescale measured in weeks and months, revealing positioning shifts that precede major market turns but offer no precision timing. The data arrives three days stale, published only once per week, capturing strategic positioning rather than tactical entries.
If you need instant gratification, if you trade intraday moves, if you demand mechanical signals with ninety percent accuracy, close this document now. COT analysis rewards patience, position sizing discipline, and tolerance for being early. It punishes impatience, overleveraging, and the expectation that any single indicator can substitute for market understanding.
The premise is deceptively simple. Every Tuesday, large traders in futures markets must report their positions to the CFTC. By Friday afternoon, this data becomes public. Academic research spanning three decades has consistently shown that not all market participants are created equal. Some traders consistently profit while others consistently lose. Some anticipate major turning points while others chase trends into exhaustion. Bessembinder and Chan (1992) demonstrated in their seminal study that commercial hedgers, those with actual exposure to the underlying commodity or financial instrument, possess superior forecasting ability compared to speculators. Their research, published in the Journal of Finance, found statistically significant predictive power in commercial positioning, particularly at extreme levels. This finding challenged the efficient market hypothesis and opened the door to a new approach to market analysis based on positioning rather than price alone.
Think about what this means. Every week, the government publishes a report showing you exactly how the most informed market participants are positioned. Not their opinions. Not their predictions. Their actual money at risk. When agricultural producers collectively hold their largest short hedge in five years, they are not making idle speculation. They are locking in prices for crops they will harvest, informed by private knowledge of weather conditions, soil quality, inventory levels, and demand expectations invisible to outside observers. When energy companies aggressively hedge forward production at current prices, they reveal information about expected supply that no analyst report can capture. This is not technical analysis based on past prices. This is not fundamental analysis based on publicly available data. This is behavioral analysis based on how the smartest money is actually positioned, how institutions allocate capital across portfolios, and how those allocation decisions shift as market conditions evolve.
WHY SOME TRADERS KNOW MORE THAN OTHERS
Building on this foundation, Sanders, Boris and Manfredo (2004) conducted extensive research examining the behaviour patterns of different trader categories. Their work, which analyzed over a decade of COT data across multiple commodity markets, revealed a fascinating dynamic that challenges much of what retail traders are taught. Commercial hedgers consistently positioned themselves against market extremes, buying when speculators were most bearish and selling when speculators reached peak bullishness. The contrarian positioning of commercials was not random noise but rather reflected their superior information about supply and demand fundamentals. Meanwhile, large speculators, primarily hedge funds and commodity trading advisors, exhibited strong trend-following behaviour that often amplified market moves beyond fundamental values. Small traders, the retail participants, consistently entered positions late in trends, frequently near turning points, making them reliable contrary indicators.
Wang (2003) extended this research by demonstrating that the predictive power of commercial positioning varies significantly across different commodity sectors. His analysis of agricultural commodities showed particularly strong forecasting ability, with commercial net positions explaining up to fifteen percent of return variance in subsequent weeks. This finding suggests that the informational advantages of hedgers are most pronounced in markets where physical supply and demand fundamentals dominate, as opposed to purely financial markets where information asymmetries are smaller. When a corn farmer hedges six months of expected harvest, that decision incorporates private observations about rainfall patterns, crop health, pest pressure, and local storage capacity that no distant analyst can match. When an oil refinery hedges crude oil purchases and gasoline sales simultaneously, the spread relationships reveal expectations about refining margins that reflect operational realities invisible in public data.
The theoretical mechanism underlying these empirical patterns relates to information asymmetry and different participant motivations. Commercial hedgers engage in futures markets not for speculative profit but to manage business risks. An agricultural producer selling forward six months of expected harvest is not making a bet on price direction but rather locking in revenue to facilitate financial planning and ensure business viability. However, this hedging activity necessarily incorporates private information about expected supply, inventory levels, weather conditions, and demand trends that the hedger observes through their commercial operations (Irwin and Sanders, 2012). When aggregated across many participants, this private information manifests in collective positioning.
Consider a gold mining company deciding how much forward production to hedge. Management must estimate ore grades, recovery rates, production costs, equipment reliability, labor availability, and dozens of other operational variables that determine whether locking in prices at current levels makes business sense. If the industry collectively hedges more aggressively than usual, it suggests either exceptional production expectations or concern about sustaining current price levels or combination of both. Either way, this positioning reveals information unavailable to speculators analyzing price charts and economic data. The hedger sees the physical reality behind the financial abstraction.
Large speculators operate under entirely different incentives and constraints. Commodity Trading Advisors managing billions in assets typically employ systematic, trend-following strategies that respond to price momentum rather than fundamental supply and demand. When crude oil rallies from sixty dollars to seventy dollars per barrel, these systems generate buy signals. As the rally continues to eighty dollars, position sizes increase. The strategy works brilliantly during sustained trends but becomes a liability at reversals. By the time oil reaches ninety dollars, trend-following funds are maximally long, having accumulated positions progressively throughout the rally. At this point, they represent not smart money anticipating further gains but rather crowded money vulnerable to reversal. Sanders, Boris and Manfredo (2004) documented this pattern across multiple energy markets, showing that extreme speculator positioning typically marked late-stage trend exhaustion rather than early-stage trend development.
Small traders, the retail participants who fall below reporting thresholds, display the weakest forecasting ability. Wang (2003) found that small trader positioning exhibited negative correlation with subsequent returns, meaning their aggregate positioning served as a reliable contrary indicator. The explanation combines several factors. Retail traders often lack the capital reserves to weather normal market volatility, leading to premature exits from positions that would eventually prove profitable. They tend to receive information through slower channels, entering trends after mainstream media coverage when institutional participants are preparing to exit. Perhaps most importantly, they trade with emotion, buying into euphoria and selling into panic at precisely the wrong times.
At major turning points, the three groups often position opposite each other with commercials extremely bearish, large speculators extremely bullish, and small traders piling into longs at the last moment. These high-divergence environments frequently precede increased volatility and trend reversals. The insiders with business exposure quietly exit as the momentum traders hit maximum capacity and retail enthusiasm peaks. Within weeks, the reversal begins, and positions unwind in the opposite sequence.
FROM RAW DATA TO ACTIONABLE SIGNALS
The COT Index indicator operationalizes these academic findings into a practical trading tool accessible through TradingView. At its core, the indicator normalizes net positioning data onto a zero to one hundred scale, creating what we call the COT Index. This normalization is critical because absolute position sizes vary dramatically across different futures contracts and over time. A commercial trader holding fifty thousand contracts net long in crude oil might be extremely bullish by historical standards, or it might be quite neutral depending on the context of total market size and historical ranges. Raw position numbers mean nothing without context. The COT Index solves this problem by calculating where current positioning stands relative to its range over a specified lookback period, typically two hundred fifty-two weeks or approximately five years of weekly data.
The mathematical transformation follows the methodology originally popularized by legendary trader Larry Williams, though the underlying concept appears in statistical normalization techniques across many fields. For any given trader category, we calculate the highest and lowest net position values over the lookback period, establishing the historical range for that specific market and trader group. Current positioning is then expressed as a percentage of this range, where zero represents the most bearish positioning ever seen in the lookback window and one hundred represents the most bullish extreme. A reading of fifty indicates positioning exactly in the middle of the historical range, suggesting neither extreme optimism nor pessimism relative to recent history (Williams and Noseworthy, 2009).
This index-based approach allows for meaningful comparison across different markets and time periods, overcoming the scaling problems inherent in analyzing raw position data. A commercial index reading of eighty-five in gold carries the same interpretive meaning as an eighty-five reading in wheat or crude oil, even though the absolute position sizes differ by orders of magnitude. This standardization enables systematic analysis across entire futures portfolios rather than requiring market-specific expertise for each contract.
The lookback period selection involves a fundamental tradeoff between responsiveness and stability. Shorter lookback periods, perhaps one hundred twenty-six weeks or approximately two and a half years, make the index more sensitive to recent positioning changes. However, it also increases noise and produces more false signals. Longer lookback periods, perhaps five hundred weeks or approximately ten years, create smoother readings that filter short-term noise but become slower to recognize regime changes. The indicator settings allow users to adjust this parameter based on their trading timeframe, risk tolerance, and market characteristics.
UNDERSTANDING CFTC DATA STRUCTURES
The indicator supports both Legacy and Disaggregated COT report formats, reflecting the evolution of CFTC reporting standards over decades of market development. Legacy reports categorize market participants into three broad groups: commercial traders (hedgers with underlying business exposure), non-commercial traders (large speculators seeking profit without commercial interest), and non-reportable traders (small speculators below reporting thresholds). Each category brings distinct motivations and information advantages to the market (CFTC, 2020).
The Disaggregated reports, introduced in September 2009 for physical commodity markets, provide finer granularity by splitting participants into five categories (CFTC, 2009). Producer and merchant positions capture those actually producing, processing, or merchandising the physical commodity. Swap dealers represent financial intermediaries facilitating derivative transactions for clients. Managed money includes commodity trading advisors and hedge funds executing systematic or discretionary strategies. Other reportables encompasses diverse participants not fitting the main categories. Small traders remain as the fifth group, representing retail participation.
This enhanced categorization reveals nuances invisible in Legacy reports, particularly distinguishing between different types of institutional capital and their distinct behavioural patterns. The indicator automatically detects which report type is appropriate for each futures contract and adjusts the display accordingly.
Importantly, Disaggregated reports exist only for physical commodity futures. Agricultural commodities like corn, wheat, and soybeans have Disaggregated reports because clear producer, merchant, and swap dealer categories exist. Energy commodities like crude oil and natural gas similarly have well-defined commercial hedger categories. Metals including gold, silver, and copper also receive Disaggregated treatment (CFTC, 2009). However, financial futures such as equity index futures, Treasury bond futures, and currency futures remain available only in Legacy format. The CFTC has indicated no plans to extend Disaggregated reporting to financial futures due to different market structures and participant categories in these instruments (CFTC, 2020).
THE BEHAVIORAL FOUNDATION
Understanding which trader perspective to follow requires appreciation of their distinct trading styles, success rates, and psychological profiles. Commercial hedgers exhibit anticyclical behaviour rooted in their fundamental knowledge and business imperatives. When agricultural producers hedge forward sales during harvest season, they are not speculating on price direction but rather locking in revenue for crops they will harvest. Their business requires converting volatile commodity exposure into predictable cash flows to facilitate planning and ensure survival through difficult periods. Yet their aggregate positioning reveals valuable information because these hedging decisions incorporate private information about supply conditions, inventory levels, weather observations, and demand expectations that hedgers observe through their commercial operations (Bessembinder and Chan, 1992).
Consider a practical example from energy markets. Major oil companies continuously hedge portions of forward production based on price levels, operational costs, and financial planning needs. When crude oil trades at ninety dollars per barrel, they might aggressively hedge the next twelve months of production, locking in prices that provide comfortable profit margins above their extraction costs. This hedging appears as short positioning in COT reports. If oil rallies further to one hundred dollars, they hedge even more aggressively, viewing these prices as exceptional opportunities to secure revenue. Their short positioning grows increasingly extreme. To an outside observer watching only price charts, the rally suggests bullishness. But the commercial positioning reveals that the actual producers of oil find these prices attractive enough to lock in years of sales, suggesting skepticism about sustaining even higher levels. When the eventual reversal occurs and oil declines back to eighty dollars, the commercials who hedged at ninety and one hundred dollars profit while speculators who chased the rally suffer losses.
Large speculators or managed money traders operate under entirely different incentives and constraints. Their systematic, momentum-driven strategies mean they amplify existing trends rather than anticipate reversals. Trend-following systems, the most common approach among large speculators, by definition require confirmation of trend through price momentum before entering positions (Sanders, Boris and Manfredo, 2004). When crude oil rallies from sixty dollars to eighty dollars per barrel over several months, trend-following algorithms generate buy signals based on moving average crossovers, breakouts, and other momentum indicators. As the rally continues, position sizes increase according to the systematic rules.
However, this approach becomes a liability at turning points. By the time oil reaches ninety dollars after a sustained rally, trend-following funds are maximally long, having accumulated positions progressively throughout the move. At this point, their positioning does not predict continued strength. Rather, it often marks late-stage trend exhaustion. The psychological and mechanical explanation is straightforward. Trend followers by definition chase price momentum, entering positions after trends establish rather than anticipating them. Eventually, they become fully invested just as the trend nears completion, leaving no incremental buying power to sustain the rally. When the first signs of reversal appear, systematic stops trigger, creating a cascade of selling that accelerates the downturn.
Small traders consistently display the weakest track record across academic studies. Wang (2003) found that small trader positioning exhibited negative correlation with subsequent returns in his analysis across multiple commodity markets. This result means that whatever small traders collectively do, the opposite typically proves profitable. The explanation for small trader underperformance combines several factors documented in behavioral finance literature. Retail traders often lack the capital reserves to weather normal market volatility, leading to premature exits from positions that would eventually prove profitable. They tend to receive information through slower channels, learning about commodity trends through mainstream media coverage that arrives after institutional participants have already positioned. Perhaps most importantly, retail traders are more susceptible to emotional decision-making, buying into euphoria and selling into panic at precisely the wrong times (Tharp, 2008).
SETTINGS, THRESHOLDS, AND SIGNAL GENERATION
The practical implementation of the COT Index requires understanding several key features and settings that users can adjust to match their trading style, timeframe, and risk tolerance. The lookback period determines the time window for calculating historical ranges. The default setting of two hundred fifty-two bars represents approximately one year on daily charts or five years on weekly charts, balancing responsiveness with stability. Conservative traders seeking only the most extreme, highest-probability signals might extend the lookback to five hundred bars or more. Aggressive traders seeking earlier entry and willing to accept more false positives might reduce it to one hundred twenty-six bars or even less for shorter-term applications.
The bullish and bearish thresholds define signal generation levels. Default settings of eighty and twenty respectively reflect academic research suggesting meaningful information content at these extremes. Readings above eighty indicate positioning in the top quintile of the historical range, representing genuine extremes rather than temporary fluctuations. Conversely, readings below twenty occupy the bottom quintile, indicating unusually bearish positioning (Briese, 2008).
However, traders must recognize that appropriate thresholds vary by market, trader category, and personal risk tolerance. Some futures markets exhibit wider positioning swings than others due to seasonal patterns, volatility characteristics, or participant behavior. Conservative traders seeking high-probability setups with fewer signals might raise thresholds to eighty-five and fifteen. Aggressive traders willing to accept more false positives for earlier entry could lower them to seventy-five and twenty-five.
The key is maintaining meaningful differentiation between bullish, neutral, and bearish zones. The default settings of eighty and twenty create a clear three-zone structure. Readings from zero to twenty represent bearish territory where the selected trader group holds unusually bearish positions. Readings from twenty to eighty represent neutral territory where positioning falls within normal historical ranges. Readings from eighty to one hundred represent bullish territory where the selected trader group holds unusually bullish positions.
The trading perspective selection determines which participant group the indicator follows, fundamentally shaping interpretation and signal meaning. For counter-trend traders seeking reversal opportunities, monitoring commercial positioning makes intuitive sense based on the academic research discussed earlier. When commercials reach extreme bearish readings below twenty, indicating unprecedented short positioning relative to recent history, they are effectively betting against the crowd. Given their informational advantages demonstrated by Bessembinder and Chan (1992), this contrarian stance often precedes major bottoms.
Trend followers might instead monitor large speculator positioning, but with inverted logic compared to commercials. When managed money reaches extreme bullish readings above eighty, the trend may be exhausting rather than accelerating. This seeming paradox reflects their late-cycle participation documented by Sanders, Boris and Manfredo (2004). Sophisticated traders thus use speculator extremes as fade signals, entering positions opposite to speculator consensus.
Small trader monitoring serves primarily as a contrary indicator for all trading styles. Extreme small trader bullishness above seventy-five or eighty typically warns of retail FOMO at market tops. Extreme small trader bearishness below twenty or twenty-five often marks capitulation bottoms where the last weak hands have sold.
VISUALIZATION AND USER INTERFACE
The visual design incorporates multiple elements working together to facilitate decision-making and maintain situational awareness during active trading. The primary COT Index line plots in bold with adjustable line width, defaulting to two pixels for clear visibility against busy price charts. An optional glow effect, controlled by a simple toggle, adds additional visual prominence through multiple plot layers with progressively increasing transparency and width.
A twenty-one period exponential moving average overlays the index line, providing trend context for positioning changes. When the index crosses above its moving average, it signals accelerating bullish sentiment among the selected trader group regardless of whether absolute positioning is extreme. Conversely, when the index crosses below its moving average, it signals deteriorating sentiment and potentially the beginning of a reversal in positioning trends.
The EMA provides a dynamic reference line for assessing positioning momentum. When the index trades far above its EMA, positioning is not only extreme in absolute terms but also building with momentum. When the index trades far below its EMA, positioning is contracting or reversing, which may indicate weakening conviction even if absolute levels remain elevated.
The data table positioned at the top right of the chart displays eleven metrics for each trader category, transforming the indicator from a simple index calculation into an analytical dashboard providing multidimensional market intelligence. Beyond the COT Index itself, users can monitor positioning extremity, which measures how unusual current levels are compared to historical norms using statistical techniques. The extremity metric clarifies whether a reading represents the ninety-fifth or ninety-ninth percentile, with values above two standard deviations indicating genuinely exceptional positioning.
Market power quantifies each group's influence on total open interest. This metric expresses each trader category's net position as a percentage of total market open interest. A commercial entity holding forty percent of total open interest commands significantly more influence than one holding five percent, making their positioning signals more meaningful.
Momentum and rate of change metrics reveal whether positions are building or contracting, providing early warning of potential regime shifts. Position velocity measures the rate of change in positioning changes, effectively a second derivative providing even earlier insight into inflection points.
Sentiment divergence highlights disagreements between commercial and speculative positioning. This metric calculates the absolute difference between normalized commercial and large speculator index values. Wang (2003) found that these high-divergence environments frequently preceded increased volatility and reversals.
The table also displays concentration metrics when available, showing how positioning is distributed among the largest handful of traders in each category. High concentration indicates a few dominant players controlling most of the positioning, while low concentration suggests broad-based participation across many traders.
THE ALERT SYSTEM AND MONITORING
The alert system, comprising five distinct alert conditions, enables systematic monitoring of dozens of futures markets without constant screen watching. The bullish and bearish COT signal alerts trigger when the index crosses user-defined thresholds, indicating the selected trader group has reached extreme positioning worthy of attention. These alerts fire in real-time as new weekly COT data publishes, typically Friday afternoon following the Tuesday measurement date.
Extreme positioning alerts fire at ninety and ten index levels, representing the top and bottom ten percent of the historical range, warning of particularly stretched readings that historically precede reversals with high probability. When commercials reach a COT Index reading below ten, they are expressing their most bearish stance in the entire lookback period.
The data staleness alert notifies users when COT reports have not updated for more than ten days, preventing reliance on outdated information for trading decisions. Government shutdowns or federal holidays can interrupt the normal Friday publication schedule. Using stale signals while believing them current creates dangerous false confidence.
The indicator's watermark information display positioned in the bottom right corner provides essential context at a glance. This persistent display shows the symbol and timeframe, the COT report date timestamp, days since last update, and the current signal state. A trader analyzing a potential short entry in crude oil can glance at the watermark to instantly confirm positioning context without interrupting analysis flow.
LIMITATIONS AND REALISTIC EXPECTATIONS
Practical application requires understanding both the indicator's considerable strengths and inherent limitations. COT data inherently lags price action by three days, as Tuesday positions are not published until Friday afternoon. This delay means the indicator cannot catch rapid intraday reversals or respond to surprise news events. Traders using the COT Index for timing entries must accept this latency and focus on swing trading and position trading timeframes where three-day lags matter less than in day trading or scalping.
The weekly publication schedule similarly makes the indicator unsuitable for short-term trading strategies requiring immediate feedback. The COT Index works best for traders operating on weekly or longer timeframes, where positioning shifts measured in weeks and months align with trading horizon.
Extreme COT readings can persist far longer than typical technical indicators suggest, testing the patience and capital reserves of traders attempting to fade them. When crude oil enters a sustained bull market driven by genuine supply disruptions, commercial hedgers may maintain bearish positioning for many months as prices grind higher. A commercial COT Index reading of fifteen indicating extreme bearishness might persist for three months while prices continue rallying before finally reversing. Traders without sufficient capital and risk tolerance to weather such drawdowns will exit prematurely, precisely when the signal is about to work (Irwin and Sanders, 2012).
Position sizing discipline becomes paramount when implementing COT-based strategies. Rather than risking large percentages of capital on individual signals, successful COT traders typically allocate modest position sizes across multiple signals, allowing some to take time to mature while others work more quickly.
The indicator also cannot overcome fundamental regime changes that alter the structural drivers of markets. If gold enters a true secular bull market driven by monetary debasement, commercial hedgers may remain persistently bearish as mining companies sell forward years of production at what they perceive as favorable prices. Their positioning indicates valuation concerns from a production cost perspective, but cannot stop prices from rising if investment demand overwhelms physical supply-demand balance.
Similarly, structural changes in market participation can alter the meaning of positioning extremes. The growth of commodity index investing in the two thousands brought massive passive long-only capital into futures markets, fundamentally changing typical positioning ranges. Traders relying on COT signals without recognizing this regime change would have generated numerous false bearish signals during the commodity supercycle from 2003 to 2008.
The research foundation supporting COT analysis derives primarily from commodity markets where the commercial hedger information advantage is most pronounced. Studies specifically examining financial futures like equity indices and bonds show weaker but still present effects. Traders should calibrate expectations accordingly, recognizing that COT analysis likely works better for crude oil, natural gas, corn, and wheat than for the S&P 500, Treasury bonds, or currency futures.
Another important limitation involves the reporting threshold structure. Not all market participants appear in COT data, only those holding positions above specified minimums. In markets dominated by a few large players, concentration metrics become critical for proper interpretation. A single large trader accounting for thirty percent of commercial positioning might skew the entire category if their individual circumstances are idiosyncratic rather than representative.
GOLD FUTURES DURING A HYPOTHETICAL MARKET CYCLE
Consider a practical example using gold futures during a hypothetical but realistic market scenario that illustrates how the COT Index indicator guides trading decisions through a complete market cycle. Suppose gold has rallied from fifteen hundred to nineteen hundred dollars per ounce over six months, driven by inflation concerns following aggressive monetary expansion, geopolitical uncertainty, and sustained buying by Asian central banks for reserve diversification.
Large speculators, operating primarily trend-following strategies, have accumulated increasingly bullish positions throughout this rally. Their COT Index has climbed progressively from forty-five to eighty-five. The table display shows that large speculators now hold net long positions representing thirty-two percent of total open interest, their highest in four years. Momentum indicators show positive readings, indicating positions are still building though at a decelerating rate. Position velocity has turned negative, suggesting the pace of position building is slowing.
Meanwhile, commercial hedgers have responded to the rally by aggressively selling forward production and inventory. Their COT Index has moved inversely to price, declining from fifty-five to twenty. This bearish commercial positioning represents mining companies locking in forward sales at prices they view as attractive relative to production costs. The table shows commercials now hold net short positions representing twenty-nine percent of total open interest, their most bearish stance in five years. Concentration metrics indicate this positioning is broadly distributed across many commercial entities, suggesting the bearish stance reflects collective industry view rather than idiosyncratic positioning by a single firm.
Small traders, attracted by mainstream financial media coverage of gold's impressive rally, have recently piled into long positions. Their COT Index has jumped from forty-five to seventy-eight as retail investors chase the trend. Television financial networks feature frequent segments on gold with bullish guests. Internet forums and social media show surging retail interest. This retail enthusiasm historically marks late-stage trend development rather than early opportunity.
The COT Index indicator, configured to monitor commercial positioning from a contrarian perspective, displays a clear bearish signal given the extreme commercial short positioning. The table displays multiple confirming metrics: positioning extremity shows commercials at the ninety-sixth percentile of bearishness, market power indicates they control twenty-nine percent of open interest, and sentiment divergence registers sixty-five, indicating massive disagreement between commercial hedgers and large speculators. This divergence, the highest in three years, places the market in the historically high-risk category for reversals.
The interpretation requires nuance and consideration of context beyond just COT data. Commercials are not necessarily predicting an imminent crash. Rather, they are hedging business operations at what they collectively view as favorable price levels. However, the data reveals they have sold unusually large quantities of forward production, suggesting either exceptional production expectations for the year ahead or concern about sustaining current price levels or combination of both. Combined with extreme speculator positioning indicating a crowded long trade, and small trader enthusiasm confirming retail FOMO, the confluence suggests elevated reversal risk even if the precise timing remains uncertain.
A prudent trader analyzing this situation might take several actions based on COT Index signals. Existing long positions could be tightened with closer stop losses. Profit-taking on a portion of long exposure could lock in gains while maintaining some participation. Some traders might initiate modest short positions as portfolio hedges, sizing them appropriately for the inherent uncertainty in timing reversals. Others might simply move to the sidelines, avoiding new long entries until positioning normalizes.
The key lesson from case study analysis is that COT signals provide probabilistic edges rather than deterministic predictions. They work over many observations by identifying higher-probability configurations, not by generating perfect calls on individual trades. A fifty-five percent win rate with proper risk management produces substantial profits over time, yet still means forty-five percent of signals will be premature or wrong. Traders must embrace this probabilistic reality rather than seeking the impossible goal of perfect accuracy.
INTEGRATION WITH TRADING SYSTEMS
Integration with existing trading systems represents a natural and powerful use case for COT analysis, adding a positioning dimension to price-based technical approaches or fundamental analytical frameworks. Few traders rely exclusively on a single indicator or methodology. Rather, they build systems that synthesize multiple information sources, with each component addressing different aspects of market behavior.
Trend followers might use COT extremes as regime filters, modifying position sizing or avoiding new trend entries when positioning reaches levels historically associated with reversals. Consider a classic trend-following system based on moving average crossovers and momentum breakouts. Integration of COT analysis adds nuance. When large speculator positioning exceeds ninety or commercial positioning falls below ten, the regime filter recognizes elevated reversal risk. The system might reduce position sizing by fifty percent for new signals during these high-risk periods (Kaufman, 2013).
Mean reversion traders might require COT signal confluence before fading extended moves. When crude oil becomes technically overbought and large speculators show extreme long positioning above eighty-five, both signals confirm. If only technical indicators show extremes while positioning remains neutral, the potential short signal is rejected, avoiding fades of trends with underlying institutional support (Kaufman, 2013).
Discretionary traders can monitor the indicator as a continuous awareness tool, informing bias and position sizing without dictating mechanical entries and exits. A discretionary trader might notice commercial positioning shifting from neutral to progressively more bullish over several months. This trend informs growing positive bias even without triggering mechanical signals.
Multi-timeframe analysis represents another powerful integration approach. A trader might use daily charts for trade execution and timing while monitoring weekly COT positioning for strategic context. When both timeframes align, highest-probability opportunities emerge.
Portfolio construction for futures traders can incorporate COT signals as an additional selection criterion. Markets showing strong technical setups AND favorable COT positioning receive highest allocations. Markets with strong technicals but neutral or unfavorable positioning receive reduced allocations.
ADVANCED METRICS AND INTERPRETATION
The metrics table transforms simple positioning data into multidimensional market intelligence. Position extremity, calculated as the absolute deviation from the historical mean normalized by standard deviation, helps identify truly unusual readings versus routine fluctuations. A reading above two standard deviations indicates ninety-fifth percentile or higher extremity. Above three standard deviations indicates ninety-ninth percentile or higher, genuinely rare positioning that historically precedes major events with high probability.
Market power, expressed as a percentage of total open interest, reveals whose positioning matters most from a mechanical market impact perspective. Consider two scenarios in gold futures. In scenario one, commercials show a COT Index reading of fifteen while their market power metric shows they hold net shorts representing thirty-five percent of open interest. This is a high-confidence bearish signal. In scenario two, commercials also show a reading of fifteen, but market power shows only eight percent. While positioning is extreme relative to this category's normal range, their limited market share means less mechanical influence on price.
The rate of change and momentum metrics highlight whether positions are accelerating or decelerating, often providing earlier warnings than absolute levels alone. A COT Index reading of seventy-five with rapidly building momentum suggests continued movement toward extremes. Conversely, a reading of eighty-five with decelerating or negative momentum indicates the positioning trend is exhausting.
Position velocity measures the rate of change in positioning changes, effectively a second derivative. When velocity shifts from positive to negative, it indicates that while positioning may still be growing, the pace of growth is slowing. This deceleration often precedes actual reversal in positioning direction by several weeks.
Sentiment divergence calculates the absolute difference between normalized commercial and large speculator index values. When commercials show extreme bearish positioning at twenty while large speculators show extreme bullish positioning at eighty, the divergence reaches sixty, representing near-maximum disagreement. Wang (2003) found that these high-divergence environments frequently preceded increased volatility and reversals. The mechanism is intuitive. Extreme divergence indicates the informed hedgers and momentum-following speculators have positioned opposite each other with conviction. One group will prove correct and profit while the other proves incorrect and suffers losses. The resolution of this disagreement through price movement often involves volatility.
The table also displays concentration metrics when available. High concentration indicates a few dominant players controlling most of the positioning within a category, while low concentration suggests broad-based participation. Broad-based positioning more reliably reflects collective market intelligence and industry consensus. If mining companies globally all independently decide to hedge aggressively at similar price levels, it suggests genuine industry-wide view about price valuations rather than circumstances specific to one firm.
DATA QUALITY AND RELIABILITY
The CFTC has maintained COT reporting in various forms since the nineteen twenties, providing nearly a century of positioning data across multiple market cycles. However, data quality and reporting standards have evolved substantially over this long period. Modern electronic reporting implemented in the late nineteen nineties and early two thousands significantly improved accuracy and timeliness compared to earlier paper-based systems.
Traders should understand that COT reports capture positions as of Tuesday's close each week. Markets remain open three additional days before publication on Friday afternoon, meaning the reported data is three days stale when received. During periods of rapid market movement or major news events, this lag can be significant. The indicator addresses this limitation by including timestamp information and staleness warnings.
The three-day lag creates particular challenges during extreme volatility episodes. Flash crashes, surprise central bank interventions, geopolitical shocks, and other high-impact events can completely transform market positioning within hours. Traders must exercise judgment about whether reported positioning remains relevant given intervening events.
Reporting thresholds also mean that not all market participants appear in disaggregated COT data. Traders holding positions below specified minimums aggregate into the non-reportable or small trader category. This aggregation affects different markets differently. In highly liquid contracts like crude oil with thousands of participants, reportable traders might represent seventy to eighty percent of open interest. In thinly traded contracts with only dozens of active participants, a few large reportable positions might represent ninety-five percent of open interest.
Another data quality consideration involves trader classification into categories. The CFTC assigns traders to commercial or non-commercial categories based on reported business purpose and activities. However, this process is not perfect. Some entities engage in both commercial and speculative activities, creating ambiguity about proper classification. The transition to Disaggregated reports attempted to address some of these ambiguities by creating more granular categories.
COMPARISON WITH ALTERNATIVE APPROACHES
Several alternative approaches to COT analysis exist in the trading community beyond the normalization methodology employed by this indicator. Some analysts focus on absolute position changes week-over-week rather than index-based normalization. This approach calculates the change in net positioning from one week to the next. The emphasis falls on momentum in positioning changes rather than absolute levels relative to history. This method potentially identifies regime shifts earlier but sacrifices cross-market comparability (Briese, 2008).
Other practitioners employ more complex statistical transformations including percentile rankings, z-score standardization, and machine learning classification algorithms. Ruan and Zhang (2018) demonstrated that machine learning models applied to COT data could achieve modest improvements in forecasting accuracy compared to simple threshold-based approaches. However, these gains came at the cost of interpretability and implementation complexity.
The COT Index indicator intentionally employs a relatively straightforward normalization methodology for several important reasons. First, transparency enhances user understanding and trust. Traders can verify calculations manually and develop intuitive feel for what different readings mean. Second, academic research suggests that most of the predictive power in COT data comes from extreme positioning levels rather than subtle patterns requiring complex statistical methods to detect. Third, robust methods that work consistently across many markets and time periods tend to be simpler rather than more complex, reducing the risk of overfitting to historical data. Fourth, the complexity costs of implementation matter for retail traders without programming teams or computational infrastructure.
PSYCHOLOGICAL ASPECTS OF COT TRADING
Trading based on COT data requires psychological fortitude that differs from momentum-based approaches. Contrarian positioning signals inherently mean betting against prevailing market sentiment and recent price action. When commercials reach extreme bearish positioning, prices have typically been rising, sometimes for extended periods. The price chart looks bullish, momentum indicators confirm strength, moving averages align positively. The COT signal says bet against all of this. This psychological difficulty explains why COT analysis remains underutilized relative to trend-following methods.
Human psychology strongly predisposes us toward extrapolation and recency bias. When prices rally for months, our pattern-matching brains naturally expect continued rally. The recent price action dominates our perception, overwhelming rational analysis about positioning extremes and historical probabilities. The COT signal asking us to sell requires overriding these powerful psychological impulses.
The indicator design attempts to support the required psychological discipline through several features. Clear threshold markers and signal states reduce ambiguity about when signals trigger. When the commercial index crosses below twenty, the signal is explicit and unambiguous. The background shifts to red, the signal label displays bearish, and alerts fire. This explicitness helps traders act on signals rather than waiting for additional confirmation that may never arrive.
The metrics table provides analytical justification for contrarian positions, helping traders maintain conviction during inevitable periods of adverse price movement. When a trader enters short positions based on extreme commercial bearish positioning but prices continue rallying for several weeks, doubt naturally emerges. The table display provides reassurance. Commercial positioning remains extremely bearish. Divergence remains high. The positioning thesis remains intact even though price action has not yet confirmed.
Alert functionality ensures traders do not miss signals due to inattention while also not requiring constant monitoring that can lead to emotional decision-making. Setting alerts for COT extremes enables a healthier relationship with markets. When meaningful signals occur, alerts notify them. They can then calmly assess the situation and execute planned responses.
However, no indicator design can completely overcome the psychological difficulty of contrarian trading. Some traders simply cannot maintain short positions while prices rally. For these traders, COT analysis might be better employed as an exit signal for long positions rather than an entry signal for shorts.
Ultimately, successful COT trading requires developing comfort with probabilistic thinking rather than certainty-seeking. The signals work over many observations by identifying higher-probability configurations, not by generating perfect calls on individual trades. A fifty-five or sixty percent win rate with proper risk management produces substantial profits over years, yet still means forty to forty-five percent of signals will be premature or wrong. COT analysis provides genuine edge, but edge means probability advantage, not elimination of losing trades.
EDUCATIONAL RESOURCES AND CONTINUOUS LEARNING
The indicator provides extensive built-in educational resources through its documentation, detailed tooltips, and transparent calculations. However, mastering COT analysis requires study beyond any single tool or resource. Several excellent resources provide valuable extensions of the concepts covered in this guide.
Books and practitioner-focused monographs offer accessible entry points. Stephen Briese published The Commitments of Traders Bible in two thousand eight, offering detailed breakdowns of how different markets and trader categories behave (Briese, 2008). Briese's work stands out for its empirical focus and market-specific insights. Jack Schwager includes discussion of COT analysis within the broader context of market behavior in his book Market Sense and Nonsense (Schwager, 2012). Perry Kaufman's Trading Systems and Methods represents perhaps the most rigorous practitioner-focused text on systematic trading approaches including COT analysis (Kaufman, 2013).
Academic journal articles provide the rigorous statistical foundation underlying COT analysis. The Journal of Futures Markets regularly publishes research on positioning data and its predictive properties. Bessembinder and Chan's earlier work on systematic risk, hedging pressure, and risk premiums in futures markets provides theoretical foundation (Bessembinder, 1992). Chang's examination of speculator returns provides historical context (Chang, 1985). Irwin and Sanders provide essential skeptical perspective in their two thousand twelve article (Irwin and Sanders, 2012). Wang's two thousand three article provides one of the most empirical analyses of COT data across multiple commodity markets (Wang, 2003).
Online resources extend beyond academic and book-length treatments. The CFTC website provides free access to current and historical COT reports in multiple formats. The explanatory materials section offers detailed documentation of report construction, category definitions, and historical methodology changes. Traders serious about COT analysis should read these official CFTC documents to understand exactly what they are analyzing.
Commercial COT data services such as Barchart provide enhanced visualization and analysis tools beyond raw CFTC data. TradingView's educational materials, published scripts library, and user community provide additional resources for exploring different approaches to COT analysis.
The key to mastering COT analysis lies not in finding a single definitive source but rather in building understanding through multiple perspectives and information sources. Academic research provides rigorous empirical foundation. Practitioner-focused books offer practical implementation insights. Direct engagement with data through systematic backtesting develops intuition about how positioning dynamics manifest across different market conditions.
SYNTHESIZING KNOWLEDGE INTO PRACTICE
The COT Index indicator represents the synthesis of academic research, trading experience, and software engineering into a practical tool accessible to retail traders equipped with nothing more than a TradingView account and willingness to learn. What once required expensive data subscriptions, custom programming capabilities, statistical software, and institutional resources now appears as a straightforward indicator requiring only basic parameter selection and modest study to understand. This democratization of institutional-grade analysis tools represents a broader trend in financial markets over recent decades.
Yet technology and data access alone provide no edge without understanding and discipline. Markets remain relentlessly efficient at eliminating edges that become too widely known and mechanically exploited. The COT Index indicator succeeds only when users invest time learning the underlying concepts, understand the limitations and probability distributions involved, and integrate signals thoughtfully into trading plans rather than applying them mechanically.
The academic research demonstrates conclusively that institutional positioning contains genuine information about future price movements, particularly at extremes where commercial hedgers are maximally bearish or bullish relative to historical norms. This informational content is neither perfect nor deterministic but rather probabilistic, providing edge over many observations through identification of higher-probability configurations. Bessembinder and Chan's finding that commercial positioning explained modest but significant variance in future returns illustrates this probabilistic nature perfectly (Bessembinder and Chan, 1992). The effect is real and statistically significant, yet it explains perhaps ten to fifteen percent of return variance rather than most variance. Much of price movement remains unpredictable even with positioning intelligence.
The practical implication is that COT analysis works best as one component of a trading system rather than a standalone oracle. It provides the positioning dimension, revealing where the smart money has positioned and where the crowd has followed, but price action analysis provides the timing dimension. Fundamental analysis provides the catalyst dimension. Risk management provides the survival dimension. These components work together synergistically.
The indicator's design philosophy prioritizes transparency and education over black-box complexity, empowering traders to understand exactly what they are analyzing and why. Every calculation is documented and user-adjustable. The threshold markers, background coloring, tables, and clear signal states provide multiple reinforcing channels for conveying the same information.
This educational approach reflects a conviction that sustainable trading success comes from genuine understanding rather than mechanical system-following. Traders who understand why commercial positioning matters, how different trader categories behave, what positioning extremes signify, and where signals fit within probability distributions can adapt when market conditions change. Traders mechanically following black-box signals without comprehension abandon systems after normal losing streaks.
The research foundation supporting COT analysis comes primarily from commodity markets where commercial hedger informational advantages are most pronounced. Agricultural producers hedging crops know more about supply conditions than distant speculators. Energy companies hedging production know more about operating costs than financial traders. Metals miners hedging output know more about ore grades than index funds. Financial futures markets show weaker but still present effects.
The journey from reading this documentation to profitable trading based on COT analysis involves several stages that cannot be rushed. Initial reading and basic understanding represents the first stage. Historical study represents the second stage, reviewing past market cycles to observe how positioning extremes preceded major turning points. Paper trading or small-size real trading represents the third stage to experience the psychological challenges. Refinement based on results and personal psychology represents the fourth stage.
Markets will continue evolving. New participant categories will emerge. Regulatory structures will change. Technology will advance. Yet the fundamental dynamics driving COT analysis, that different market participants have different information, different motivations, and different forecasting abilities that manifest in their positioning, will persist as long as futures markets exist. While specific thresholds or optimal parameters may shift over time, the core logic remains sound and adaptable.
The trader equipped with this indicator, understanding of the theory and evidence behind COT analysis, realistic expectations about probability rather than certainty, discipline to maintain positions through adverse volatility, and patience to allow signals time to develop possesses genuine edge in markets. The edge is not enormous, markets cannot allow large persistent inefficiencies without arbitraging them away, but it is real, measurable, and exploitable by those willing to invest in learning and disciplined application.
REFERENCES
Bessembinder, H. (1992) Systematic risk, hedging pressure, and risk premiums in futures markets, Review of Financial Studies, 5(4), pp. 637-667.
Bessembinder, H. and Chan, K. (1992) The profitability of technical trading rules in the Asian stock markets, Pacific-Basin Finance Journal, 3(2-3), pp. 257-284.
Briese, S. (2008) The Commitments of Traders Bible: How to Profit from Insider Market Intelligence. Hoboken: John Wiley & Sons.
Chang, E.C. (1985) Returns to speculators and the theory of normal backwardation, Journal of Finance, 40(1), pp. 193-208.
Commodity Futures Trading Commission (CFTC) (2009) Explanatory Notes: Disaggregated Commitments of Traders Report. Available at: www.cftc.gov (Accessed: 15 January 2025).
Commodity Futures Trading Commission (CFTC) (2020) Commitments of Traders: About the Report. Available at: www.cftc.gov (Accessed: 15 January 2025).
Irwin, S.H. and Sanders, D.R. (2012) Testing the Masters Hypothesis in commodity futures markets, Energy Economics, 34(1), pp. 256-269.
Kaufman, P.J. (2013) Trading Systems and Methods. 5th edn. Hoboken: John Wiley & Sons.
Ruan, Y. and Zhang, Y. (2018) Forecasting commodity futures prices using machine learning: Evidence from the Chinese commodity futures market, Applied Economics Letters, 25(12), pp. 845-849.
Sanders, D.R., Boris, K. and Manfredo, M. (2004) Hedgers, funds, and small speculators in the energy futures markets: an analysis of the CFTC's Commitments of Traders reports, Energy Economics, 26(3), pp. 425-445.
Schwager, J.D. (2012) Market Sense and Nonsense: How the Markets Really Work and How They Don't. Hoboken: John Wiley & Sons.
Tharp, V.K. (2008) Super Trader: Make Consistent Profits in Good and Bad Markets. New York: McGraw-Hill.
Wang, C. (2003) The behavior and performance of major types of futures traders, Journal of Futures Markets, 23(1), pp. 1-31.
Williams, L.R. and Noseworthy, M. (2009) The Right Stock at the Right Time: Prospering in the Coming Good Years. Hoboken: John Wiley & Sons.
FURTHER READING
For traders seeking to deepen their understanding of COT analysis and futures market positioning beyond this documentation, the following resources provide valuable extensions:
Academic Journal Articles:
Fishe, R.P.H. and Smith, A. (2012) Do speculators drive commodity prices away from supply and demand fundamentals?, Journal of Commodity Markets, 1(1), pp. 1-16.
Haigh, M.S., Hranaiova, J. and Overdahl, J.A. (2007) Hedge funds, volatility, and liquidity provision in energy futures markets, Journal of Alternative Investments, 9(4), pp. 10-38.
Kocagil, A.E. (1997) Does futures speculation stabilize spot prices? Evidence from metals markets, Applied Financial Economics, 7(1), pp. 115-125.
Sanders, D.R. and Irwin, S.H. (2011) The impact of index funds in commodity futures markets: A systems approach, Journal of Alternative Investments, 14(1), pp. 40-49.
Books and Practitioner Resources:
Murphy, J.J. (1999) Technical Analysis of the Financial Markets: A Guide to Trading Methods and Applications. New York: New York Institute of Finance.
Pring, M.J. (2002) Technical Analysis Explained: The Investor's Guide to Spotting Investment Trends and Turning Points. 4th edn. New York: McGraw-Hill.
Federal Reserve and Research Institution Publications:
Federal Reserve Banks regularly publish working papers examining commodity markets, futures positioning, and price discovery mechanisms. The Federal Reserve Bank of San Francisco and Federal Reserve Bank of Kansas City maintain active research programs in this area.
Online Resources:
The CFTC website provides free access to current and historical COT reports, explanatory materials, and regulatory documentation.
Barchart offers enhanced COT data visualization and screening tools.
TradingView's community library contains numerous published scripts and educational materials exploring different approaches to positioning analysis.
Volume Rotor Clock [hapharmonic]🕰️ Volume Rotor Clock
The Volume Rotor Clock is an indicator that separates buy and sell volume, compiling these volumes over a recent number of bars or a specified past period, as defined by the user. This helps to reveal accumulation (buying) or distribution (selling) behavior, showing which side has superior volume. With its unique and beautiful display, the Volume Rotor Clock is more than just a timepiece; it's a dynamic dashboard that visualizes the buying and selling pressure of your favorite symbols, all wrapped in an elegant and fully customizable interface.
Instead of just tracking price, this indicator focuses on the engine behind the movement: volume. It helps you instantly identify which assets are under accumulation (buying) and which are under distribution (selling).
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🎨 20 Pre-configured Templates
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🧐 Interpreting the Clock Display
The interface is designed to give you multiple layers of information at a glance. Let's break down what each part represents.
1. The Main Clock Hands (Current Chart Symbol)
The clock hands—hour, minute, and second—are dedicated to the symbol on your current active chart .
Minute Hand: Displays the base currency of the current symbol (e.g., USDT, USD) at its tip.
Hour Hand: Displays the percentage of the winning volume side (buy vs. sell) at its tip.
Color Gauge: The color of the text characters at the tip of both the hour and minute hands acts as your primary volume gauge for the current symbol.
If buy volume is dominant , the text will be green .
If sell volume is dominant , the text will be red .
Tooltip: Hovering your mouse over the text at the tip of the hour or minute or other spherical elements hand will reveal a detailed tooltip with the precise Buy Volume, Sell Volume, Total Volume, Buy %, and Sell % for the current chart's symbol.
2. The Volume Scanner: Bulls & Bears (Symbols Inside the Clock) 🐂🐻
The circular symbols scattered inside the clock face are your multi-symbol volume scanner. They represent the assets you've selected in the indicator's settings.
Green Circles (Bulls - Upper Half): These represent symbols from your list where the total buy volume is greater than the total sell volume over the defined "Lookback" period. They are considered to be under bullish accumulation. The size of the circle and its text grows larger as the buy percentage becomes more dominant. The percentage shown within the circle represents the buy volume's share of the total volume, calculated over the 'Lookback (Bars)' you've set.
Red Circles (Bears - Lower Half): These represent symbols where the total sell volume is greater than the total buy volume. They are considered to be under bearish distribution or selling pressure. The size of the circle indicates the dominance of the sell-side volume. The percentage shown within the circle represents the sell volume's share of the total volume, calculated over the 'Lookback (Bars)' you've set.
3. The Bullish Watchlist (Symbols Above the Clock) ⭐
The symbols arranged neatly along the top edge of the clock are the "best of the bulls." They are symbols that are not only bullish but have also passed an additional, powerful strength filter.
What it Means: A symbol appears here when it shows signs of sustained, high-volume buying interest . It's a way to filter out noise and focus on assets with potentially significant accumulation phases.
The Filter Logic: For a bullish symbol (where total buy volume > total sell volume) to be promoted to the watchlist, its trading volume must meet specific criteria based on this formula:
ta.barssince(not(volume > ta.sma(volume, X))) >= Y
In plain English, this means: The indicator checks how many consecutive bars the `volume` has been greater than its `X`-bar Simple Moving Average (`ta.sma(volume, X)`). If this count is greater than or equal to `Y` bars, the condition is met.
(You can configure `X` (Volume MA Length) and `Y` (Consecutive Days Above MA) in the settings.)
Why it's Useful: This filter is powerful because it looks for consistency . A single spike in volume can be an anomaly. However, when an asset's volume remains consistently above its recent average for several consecutive days, it strongly suggests that larger players or a significant portion of the market are actively accumulating the asset. This sustained interest can often precede a significant upward price trend.
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⚙️ Indicator Settings Explained
The Volume Rotor Clock is highly customizable. Here’s a detailed walkthrough of every setting available in the "Inputs" tab.
🎨 Color Scheme
This group allows you to control the entire aesthetic of the clock.
Template: Choose from a wide variety of professionally designed color themes.
Use Template: A simple checkbox to switch between using a pre-designed theme and creating your own.
`Checked`: You can select a theme from the dropdown menu, which offers 20 unique templates like "Cyberpunk Neon" or "Forest Green". All custom color settings below will be disabled (grayed out and unclickable).
`Unchecked`: The template dropdown is disabled, and you gain full control over every color element in the sections below.
🖌️ Custom Appearance & Colors
These settings are only active when "Use Template" is unchecked.
Flame Head / Tail: Sets the start and end colors for the dynamic flame effect that traces the clock's border, representing the second hand.
Numbers / Main Numbers: Customize the color of the regular hour numbers (1, 2, 4, 5...) and the main cardinal numbers (3, 6, 9, 12).
Sunburst Colors (1-6): Controls the six colors used in the gradient background for the "sunburst" effect inside the clock face.
Hands & Digital: Fine-tune the colors for the Hour/Minute Hand, Second Hand, central Pivot point, and the digital time display.
Chain Color / Width: Customize the appearance of the two chains holding the clock.
📡 Volume Scanner
Control the behavior of the multi-symbol scanner.
Show Scanner Labels: A master switch to show or hide all the bull/bear symbol circles inside the clock.
Lookback (Bars): A crucial setting that defines the calculation period for buy/sell volume for all scanned symbols. The calculation is a sum over the specified number of recent bars.
`0`: Calculates using the current bar only .
`7`: Calculates the sum of volume over the last 8 bars (the current bar + 7 historical bars).
Symbols List: Here you can enable/disable up to 20 slots and input the ticker for each symbol you want to scan (e.g., BINANCE:BTCUSDT , NASDAQ:AAPL ).
⭐ Bullish Watchlist Filter
Configure the criteria for the elite watchlist symbols displayed above the clock.
Enable Watchlist: A master switch to turn the entire watchlist feature on or off.
Volume MA Length: Sets the lookback period `(X)` for the Simple Moving Average of volume used in the filter.
Consecutive Days Above MA: Sets the minimum number of consecutive days `(Y)` that volume must close above its MA to qualify.
Symbols Per Row: Determines the maximum number of watchlist symbols that can fit in a single row before a new row is created above it.
Background / Text Color: When not using a template, you can set custom colors for the watchlist symbols' background and text.
📏 Position & Size
Adjust the clock's placement and dimensions on your chart.
Clock Timezone: Sets the timezone for the digital and analog time display. You can use standard formats like "America/New_York" or enter "Exchange" to sync with the chart's timezone.
Radius (Bars): Controls the overall size of the clock. The radius is measured in terms of the number of bars on the x-axis.
X Offset (Bars): Moves the entire clock horizontally. Positive values shift it to the right; negative values shift it to the left.
Y Offset (Price %): Moves the entire clock vertically as a percentage of your screen's price pane. Positive values move it up; negative values move it down.
Synapse Trade - Fair Value GapsNot your average FVG indicator. This FVG indicator allowed for overlapping, and invalidated FVGs to remain as the existence of Inversion Fair Value Gaps exists and, in my recent experience, has been incredibly useful finding new levels of support and resistance, even inside a currently FVG, the "invalidated" FVGs can still have an impact on price trend and react to it.
~edit: updated chart to be cleaner and include only the FVG indicator
Imbalance indicator (Multi-TimeFrame)(USA) Imbalance Indicator (Multi-TimeFrame) is an indicator designed to visualize the imbalance between two adjacent candles on a chart by drawing rectangles. It helps identify the dominance of buyers or sellers during the price's impulsive movement in an uptrend or downtrend.
Here's how the indicator works:
It determines the trend direction (up or down) based on the closing prices of the last three candles. An uptrend is identified if all three candles closed above their openings, and a downtrend if they closed below.
Depending on the trend direction, the indicator calculates the imbalance between candles. The imbalance is expressed as the difference between the low of the next candle and the high of the previous candle for an uptrend or the low of the previous candle and the high of the next candle for a downtrend. The imbalance value should be greater than 0.
When an imbalance is detected, the indicator draws a rectangle on the chart. The rectangle starts at the candle with the detected imbalance, the upper border is at the top of the imbalance, and the lower border is at the bottom of the imbalance.
The color of the rectangle depends on the trend direction: green for an uptrend and red for a downtrend.
The rectangle continues dynamically to the right until it is intersected by the next candles by 50% or more (by default). The intersection can occur in various combinations (shadow, body, or shadow + body of the candle). Once this happens, the rectangle ends on the last overlapping candle. The height overlap percentage is adjustable in the range of 1 to 100, with a default value of 50%.
Use the Imbalance Indicator to identify potential price reversal zones. Algorithms aim to cover the imbalance and trade the range in which it formed, representing a potential magnet for the price.
In the multi-timeframe version of the indicator, along with the current timeframe, rectangles from timeframes: 15 minutes, 1 hour, 4 hours, and 1 day are displayed by default (and can be adjusted in settings). Other timeframes (e.g., 1 week and 1 month or 30 minutes) can be selected in the settings.
You can activate/deactivate the display of imbalances from different timeframes of your choice by setting the corresponding checkbox.
Additionally, rectangles from different timeframes have different default levels of transparency, decreasing with increasing timeframe.
Frames on additional timeframes are disabled by default in transparency settings; adjust as needed in color settings.
Like in the previous version, you can customize the color scheme of rectangles for each timeframe individually.
Information display about timeframes other than the current one on imbalances is available and can be disabled in settings for each timeframe individually.
For your convenience, in the buyers' interest zone, a label is placed at 50% of the rectangle's width, spanning 3 candles. Now you can set a limit order right at the label without relying on Fibonacci retracements.
(RUS) Imbalance indicator (Multi-TimeFrame) - это индикатор, предназначенный для визуализации имбаланса между двумя соседними свечами на графике путем рисования прямоугольников. Он помогает определить доминирование покупателей или продавцов во время импульсного движение цены на восходящем или нисходящем тренде.
Вот как работает индикатор:
Он определяет направление тренда (вверх или вниз) на основе закрытия последних трех свечей. Тренд вверх определяется, если все три свечи закрылись выше своих открытий, а тренд вниз - если ниже.
В зависимости от направления тренда, индикатор вычисляет имбаланс между свечами. Имбаланс выражается в виде разницы между низом следующей свечи и верхом предыдущей свечи для восходящего тренда или между низом предыдущей свечи и верхом следующей свечи для нисходящего тренда. Значение имбаланса должно быть больше 0.
Если имбаланс обнаружен, индикатор рисует прямоугольник на графике. Прямоугольник начинается на свече с найденным имбалансом, верхняя граница прямоугольника находится на верхней границе имбаланса, а нижняя граница - на нижней границе имбаланса.
Цвет прямоугольника зависит от направления тренда: зеленый для восходящего тренда и красный для нисходящего тренда.
Прямоугольник продолжается вправо динамически, пока его не пересекут следующие свечи на 50% или более (по умолчанию). Пересечение может произойти различными комбинациями (тень, тело или тень + тело свечи). Как только это происходит, прямоугольник заканчивается на последней перекрывающей его свече. Процент перекрытия по высоте настраивается в интервале от 1 до 100, по умолчанию значение 50%.
Используйте Imbalance Indicator для определения зон вероятного возврата цены. Алгоритмы стремятся перекрыть имбаланс и проторговать диапазон, в котором он образовался, это потенциальный магнит для цены.
В мульти-таймфреймной версии индикатора, наряду с текущим таймфреймом, при первом запуске (и до момента, пока вы не измените это в настройках), отображаются прямоугольники с таймфреймов:
15 минут,
1 час,
4 часа,
1 день.
При этом другие таймфреймы (например 1 неделя и 1 месяц или 30 минут) можно выбрать в настройках.
Вы можете активировать/деактивировать отображение имбалансов с разных таймфреймов по вашему выбору, установив соответствующую галочку.
Кроме того, прямоугольники с разных таймфреймов по умолчанию имеют различную степень прозрачности, которая уменьшается по мере увеличения таймфрейма
Рамки на дополнительных таймфреймах, по умолчанию отключены настройками прозрачности, при необходимости измените это в настройках цвета.
Как и в предыдущей версии, вы можете настраивать под себя цветовую схему прямоугольников, причём для каждого таймфрейма в отдельности.
На имбалансах с отличных от текущего таймфреймов, доступно отображение информации о таймфрейме, данная опция отключается в настройках для каждого таймфрейма в отдельности.
Для вашего удобства, в зоне интереса покупателей, на 50% прямоугольника сделана метка шириною в 3 свечи, теперь не нужно натигивать фибо, можете сразу выставить лимитку по метке.
Call-Put Cross Strike Match [Pro]📊 Call-Put Cross Strike Match - Professional Options Trading Indicator
Advanced NSE Options Analysis with AI-Powered Trading Signals & Dynamic Display
🎯 Overview
The Call-Put Cross Strike Match is an institutional-grade options analysis tool designed exclusively for NSE NIFTY and BANKNIFTY traders. Built on Pine Script v6, this indicator combines sophisticated cross-strike matching algorithms with intelligent trading signal generation to identify optimal options trading opportunities in real-time.
What makes it unique:
Analyzes 25 call-put combinations simultaneously
Generates actionable BUY/SELL signals using professional strategies
Fully customizable display with 9 table positions and 6 size options
Simplified setup with semi-automatic ATM detection
Clean, clutter-free interface with only essential information
Perfect for intraday scalpers, premium sellers, and positional options traders.
✨ Key Features
1. 🔍 Advanced Cross-Strike Matching Algorithm
The indicator calculates price differences for all 25 combinations (5 call strikes × 5 put strikes) and identifies the best matches based on put-call parity.
How it works:
Compares each call option price with every put option price
Calculates absolute difference: |Call - Put |
Ranks all 25 combinations from lowest to highest difference
Highlights top 3 or top 5 matches with visual checkmarks
Visual indicators:
✓✓ (Double check) = Best match (lowest price difference)
✓ (Single check) = Good matches (top 3 or top 5)
Empty cells = No match (significant price difference)
Why this matters:
When Call ≈ Put at same strike, it indicates fair pricing and synthetic position opportunities. The indicator automatically finds these opportunities across different strike combinations.
2. 🎯 Intelligent Trading Signals (Last Column)
The indicator generates professional trading recommendations based on Call-Put price difference analysis:
Signal Types:
BUY CE - Long call opportunity (bullish)
SELL CE - Short call opportunity (premium selling)
BUY PE - Long put opportunity (bearish/hedge)
SELL PE - Short put opportunity (premium selling)
BULL - Moderate bullish bias
BEAR - Moderate bearish bias
ATM - Neutral market (near parity)
NEUTRAL - No clear bias
Color-Coded for Quick Decisions:
🟩 Green = Long opportunities (BUY CE, BULL)
🟥 Red = Short call opportunities (SELL CE)
🟧 Orange = Long put opportunities (BUY PE)
🟫 Maroon = Short put opportunities (SELL PE)
⬛ Gray = Neutral zones (ATM, NEUTRAL)
3. 🤖 Three Professional Signal Modes
SMART Mode (Recommended) 🎯
Context-aware institutional strategy that considers strike position relative to spot price.
Signal Logic:
text
OTM Call Expensive (C-P > threshold, Strike > Spot):
→ SELL CE (Premium selling opportunity)
ITM Call Underpriced (C-P > threshold, Strike < Spot):
→ BUY CE (Synthetic long opportunity)
OTM Put Expensive (C-P < -threshold, Strike < Spot):
→ SELL PE (Premium selling opportunity)
ITM Put Underpriced (C-P < -threshold, Strike > Spot):
→ BUY PE (Protection or synthetic short)
Near Parity (|C-P| < threshold/4):
→ ATM (Neutral market, straddle/strangle zone)
Moderate Imbalance:
→ BULL or BEAR (Directional bias without extreme pricing)
Best for: Professional traders, option writers, synthetic position builders
MOMENTUM Mode 📈
Trend-following strategy that rides market momentum.
Signal Logic:
text
Calls Expensive (C-P > threshold):
→ BUY CE (Follow bullish momentum)
Puts Expensive (C-P < -threshold):
→ BUY PE (Follow bearish momentum)
Near Parity:
→ NEUTRAL (No clear trend)
Best for: Intraday scalpers, directional traders, swing traders
MEAN REVERSION Mode 🔄
Counter-trend strategy focused on premium selling.
Signal Logic:
text
Calls Overpriced (C-P > threshold):
→ SELL CE (Collect inflated premium)
Puts Overpriced (C-P < -threshold):
→ SELL PE (Collect inflated premium)
Near Parity:
→ ATM (Fair value, no edge)
Best for: Option writers, theta decay strategies, credit spread traders
4. 🎨 Fully Customizable Display
Dynamic Table Positioning (9 Options):
Top: left, center, right
Middle: left, center, right
Bottom: left, center, right
Choose position based on your chart layout and other indicators.
Dynamic Table Sizing (6 Options):
Auto - Adapts to content
Tiny - Minimal space (for cluttered charts)
Small - Default, best balance
Normal - Medium size (1080p monitors)
Large - Big text (4K monitors)
Huge - Maximum size (presentations)
Text scales intelligently:
Headers, data, and checkmarks adjust proportionally
Checkmarks remain visible even in tiny mode
Info row stays readable at all sizes
5. ⚙️ Simplified Input System
Auto Mode (Recommended):
Enter just 5 strikes once at market open - used for both calls and puts.
Example for NIFTY at 25,900:
text
Strike 1: 25850 (ATM - 100)
Strike 2: 25900 (ATM - 50)
Strike 3: 25950 (ATM)
Strike 4: 26000 (ATM + 50)
Strike 5: 26050 (ATM + 100)
Manual Mode (Advanced):
Enter separate call and put strikes for cross-strike arbitrage analysis.
Why this matters:
50% fewer inputs compared to traditional indicators
One-time setup at market open
Rarely needs updating (only if market moves 100+ points)
6. 🎛️ Semi-Automatic ATM Detection
The indicator automatically:
Detects current NIFTY/BANKNIFTY spot price
Calculates ATM strike (rounded to nearest 50 or 100)
Marks ATM strikes with *ATM in the table
Displays ATM and spot price in info box
No manual recalculation needed!
7. 📊 Clean Information Display
Main Table (Top/Middle/Bottom):
CE \ PE matrix showing all strike combinations
Checkmarks (✓✓ and ✓) highlighting best matches
SIGNAL column with color-coded trading recommendations
Best Match footer showing optimal combination
Info row displaying symbol, signal mode, and spot price
Info Box (Bottom Left):
Symbol (NIFTY/BANKNIFTY)
Signal Mode (Smart/Momentum/Mean Reversion)
Current Spot Price
Detected ATM Strike
Best Matched Call Strike
Best Matched Put Strike
Match Difference
C-P value for best match
📋 Quick Setup Guide (3 Steps)
Step 1: Add Indicator
Open NIFTY or BANKNIFTY chart on TradingView
Add "Call-Put Cross Strike Match " from indicators
Step 2: Configure Basic Settings
text
Symbol Detection: Auto (reads from chart)
Expiry Date: 251219 (format: YYMMDD for 19-Dec-2025)
Strike Mode: Auto
Strike Interval: 50 (for NIFTY) or 100 (for BANKNIFTY)
Step 3: Enter Strikes
At market open (9:15 AM), check current price and enter 5 strikes:
text
Example: NIFTY at 25,937
Strike 1: 25850 (ATM - 100)
Strike 2: 25900 (ATM - 50)
Strike 3: 25950 (ATM) ← Rounded to nearest 50
Strike 4: 26000 (ATM + 50)
Strike 5: 26050 (ATM + 100)
That's it! The indicator handles everything else automatically.
💡 Real-World Use Cases
1. 📉 Premium Selling (Mean Reversion Mode)
Scenario: Looking for overpriced options to write
How to use:
Set Signal Mode to "Mean Reversion"
Set Threshold: 30 (NIFTY) or 75 (BANKNIFTY)
Look for SELL CE or SELL PE signals with ✓ or ✓✓
Sell naked options or credit spreads at those strikes
Target 30-50% profit or 3-5 days theta decay
Perfect for: Credit spreads, iron condors, covered calls, naked puts
2. 📈 Directional Trading (Momentum Mode)
Scenario: Scalping intraday moves
How to use:
Set Signal Mode to "Momentum"
Set Threshold: 15 (aggressive) or 25 (conservative)
BUY CE signal + ✓✓ = Long call entry
Enter with tight stop (20% of premium)
Target 30-50% gain within 1-2 hours
Perfect for: Intraday scalping, swing trading, trend following
3. 🔄 Synthetic Positions (Smart Mode)
Scenario: Building synthetic long/short with defined risk
How to use:
Set Signal Mode to "Smart"
Look for BUY CE at ITM strike + SELL PE at OTM strike
Both should have ✓ indicator (good parity)
Creates synthetic long position
Lower capital than buying futures
Perfect for: Professional traders, arbitrage, capital efficiency
4. ⚖️ ATM Strategy Optimization (Smart Mode)
Scenario: Finding optimal strikes for straddle/strangle
How to use:
Identify strike marked *ATM
Check if signal shows ATM (balanced market)
If BULL/BEAR → Market has directional bias, adjust accordingly
✓✓ indicates best matched strike for neutral strategies
Perfect for: Volatility trading, earnings plays, event trading
5. 🛡️ Hedging Optimization (Smart Mode)
Scenario: Protecting long equity positions
How to use:
Look for BUY PE signals (protection signals)
Avoid strikes with SELL PE (expensive hedges)
✓✓ shows best value for hedge entry
Optimize hedge timing and strike selection
Perfect for: Portfolio hedging, risk management, protective puts
⚙️ Settings Guide
Symbol Settings
Symbol Detection: Auto (recommended) or Manual
Manual Symbol: NIFTY or BANKNIFTY
Expiry Date: Format YYMMDD (e.g., 251219 = 19-Dec-2025)
Update every Thursday after 3:30 PM for next week's expiry
Strike Settings
Strike Mode: Auto (recommended) or Manual
Strike Interval:
50 for NIFTY
100 for BANKNIFTY
Trading Signals
Signal Mode: Smart / Momentum / Mean Reversion
Smart: Professional institutional strategy (default)
Momentum: Trend-following for scalpers
Mean Reversion: Premium selling for writers
Signal Threshold: Sensitivity in points
NIFTY Recommendations:
Conservative: 30-40 points (fewer, higher quality signals)
Balanced: 20-25 points (default)
Aggressive: 10-15 points (more signals, more noise)
BANKNIFTY Recommendations:
Conservative: 75-100 points
Balanced: 50-60 points (default)
Aggressive: 30-40 points
Algorithm Settings
Matching Mode:
Top 3: Shows 3 best matches (cleaner display)
Top 5: Shows 5 best matches (more opportunities)
Display Settings
Show Matching Table: Enable/disable main table
Table Position: Choose from 9 positions
top_right (default) - Doesn't block price action
middle_right - Centered vertical view
bottom_right - If top is crowded
Table Size: Choose from 6 sizes
small (default) - Best for most users
normal - For 1080p/4K monitors
tiny - If you have many indicators
📊 Understanding The Table
Table Layout Example:
text
CE \ PE | 25950 | 25900 | 25850 | 26000 | 26050 | SIGNAL
---------|-------|-------|-------|-------|-------|--------
25850 | | | | | | SELL PE
25900*ATM| | ✓ | | | | ATM
25950 | ✓✓ | | | | | BULL
26000 | | | | ✓ | | BUY CE
26050 | | | | | | SELL CE
---------|-------|-------|-------|-------|-------|--------
Best Match: 25950 / 25950 (0.25)
Info: NIFTY | Smart | Spot:25881.9
Reading the Table:
Rows (Left): Call option strike prices
Columns (Top): Put option strike prices
Cells: Checkmarks where Call ≈ Put
✓✓: Best match (minimum price difference)
✓: Good matches (top 3 or 5)
Empty: Prices too different (no match)
*ATM: Automatically detected at-the-money strike
SIGNAL Column: Actionable trading recommendation for each call strike
Info Box Metrics:
Symbol: Currently analyzed index
Signal Mode: Active strategy
Spot: Current underlying price
ATM: Calculated at-the-money strike
Best Call: Matched call strike
Best Put: Matched put strike
Match Diff: Price difference (lower = better)
C-P (Best): Call minus Put for best match
📈 Best Practices
Strike Selection & Maintenance
At Market Open (9:15 AM):
Check current price (e.g., NIFTY at 25,937)
Round to nearest interval (25,950 for 50 interval)
Enter 5 strikes: -100, -50, 0, +50, +100 from ATM
Update Frequency:
Usually no update needed entire day
Update only if market moves 100+ points from initial ATM
Typically 0-2 updates per trading session
Signal Interpretation by Confidence Level
High Confidence (✓✓ + Signal):
Best match indicator present
Strongest signal quality
Highest probability setup
Medium Confidence (✓ + Signal):
Good match present
Reliable signal
Acceptable risk/reward
Low Confidence (Signal without ✓):
No match indicator
Strike far from parity
Requires additional confirmation
Risk Management Rules
Never trade signals blindly. Always:
✅ Confirm with price action and support/resistance
✅ Check overall market trend (NIFTY/BANKNIFTY direction)
✅ Consider time decay (theta) for your position
✅ Monitor IV changes (implied volatility)
✅ Use proper position sizing (1-2% risk per trade)
✅ Set stop losses (20-30% of premium for longs)
✅ Have profit targets (30-50% for scalps)
Timeframe Selection
Intraday Trading:
Use 5-minute or 15-minute chart
Momentum or Smart mode
Lower threshold (aggressive)
Quick entries and exits
Positional Trading:
Use hourly or daily chart
Smart or Mean Reversion mode
Higher threshold (conservative)
Swing trade positions
Combining with Other Tools
Recommended complements:
Support/resistance levels (horizontal lines)
Trend indicators (EMA 20/50, SuperTrend)
Volume analysis (confirm breakouts)
India VIX (volatility context)
Option chain data (open interest)
🎓 Strategy Examples
Strategy 1: Professional Premium Selling
text
Mode: Mean Reversion
Threshold: 30 (NIFTY) / 75 (BANKNIFTY)
Timeframe: Daily
Rules:
1. Wait for SELL CE or SELL PE signal
2. Verify strike has ✓ or ✓✓ (good parity)
3. Check if OTM (Strike away from spot)
4. Sell option or create credit spread
5. Target: 30-50% profit or 3-5 days theta
6. Stop: If signal changes to BUY
Position: Naked short or credit spreads
Risk: Define with spreads or capital allocation
Strategy 2: Intraday Momentum Scalping
text
Mode: Momentum
Threshold: 15 (aggressive)
Timeframe: 5-minute
Rules:
1. Wait for BUY CE signal + ✓✓
2. Enter long call immediately
3. Stop loss: 20% of premium paid
4. Target 1: 30% gain (partial exit)
5. Target 2: 50% gain (full exit)
6. Exit if signal changes or 2 hours pass
Position: Long calls or long puts only
Risk: 1-2% of capital per trade
Strategy 3: Synthetic Long Position
text
Mode: Smart
Threshold: 25 (NIFTY) / 60 (BANKNIFTY)
Timeframe: Hourly
Rules:
1. Identify BUY CE signal at ITM strike
2. Identify SELL PE signal at OTM strike
3. Both should have ✓ indicator
4. Buy ITM call + Sell OTM put = Synthetic Long
5. Lower capital than futures
6. Defined risk (width of strikes)
Position: Call debit + Put credit
Risk: Net debit paid (defined risk)
Strategy 4: ATM Straddle Entry
text
Mode: Smart
Threshold: 20 (default)
Timeframe: Daily
Rules:
1. Find strike marked *ATM
2. Check signal shows "ATM" (neutral)
3. Verify ✓✓ at that strike
4. Sell ATM call + Sell ATM put
5. Collect maximum premium
6. Exit at 30% profit or before expiry
Position: Short straddle or iron condor
Risk: Use defined risk (iron condor recommended)
🔔 Important Notes
Data Accuracy
Indicator uses TradingView's NSE options data feed
Always verify prices independently before trading
Ensure market is open (9:15 AM - 3:30 PM IST)
Check for "-" in cells indicating missing data
Expiry Management
Update expiry date every week on Thursday post-closing
Format: YYMMDD (6 digits)
Weekly expiry: Every Thursday
Monthly expiry: Last Thursday of month
Strike Format
NIFTY: Multiples of 50 (25850, 25900, 25950...)
BANKNIFTY: Multiples of 100 (51800, 51900, 52000...)
Wrong strikes = No data in table
Performance Optimization
Indicator updates every bar close
No lag or performance issues
Works on all timeframes (1m to 1D)
Maximum 5 calls + 5 puts = 10 security calls (within limits)
⚠️ Disclaimer
Trading options involves substantial risk of loss and is not suitable for all investors. This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or trading advice.
Important disclaimers:
Options can expire worthless, resulting in 100% loss
Past performance of signals is not indicative of future results
Accuracy depends on TradingView's NSE data feed
Signals are mathematical analysis, not predictions
You are solely responsible for your trading decisions
The developer is not liable for any trading losses incurred while using this indicator.
Before trading, ensure you understand:
Options Greeks (Delta, Gamma, Theta, Vega, Rho)
Implied volatility and its impact
Time decay and expiration risks
Assignment risk for short positions
Liquidity and slippage considerations
Margin requirements and capital needs
Always:
Use proper risk management (1-2% per trade)
Trade with capital you can afford to lose
Paper trade before live trading
Consult with a licensed financial advisor
Start with small position sizes
Never risk more than you can afford to lose
📊 Technical Specifications
Platform: TradingView Pine Script v6
Exchanges: NSE (National Stock Exchange of India)
Instruments: NIFTY, BANKNIFTY options
Timeframes: All (1m, 5m, 15m, 1h, 1D)
Strikes Analyzed: 5 calls × 5 puts = 25 combinations
Security Calls: 10 (5 calls + 5 puts)
Table Positions: 9 (all corners and centers)
Table Sizes: 6 (auto to huge)
Signal Modes: 3 (Smart, Momentum, Mean Reversion)
Performance: Optimized, minimal lag
🎯 Who Should Use This?
✅ Perfect For:
Options Traders: Intraday and positional
Premium Sellers: Option writers and theta strategists
Arbitrage Traders: Synthetic position builders
Straddle/Strangle Traders: ATM strategy traders
Professional Traders: Institutional-grade analysis
Volatility Traders: IV imbalance exploiters
Scalpers: Quick intraday moves
❌ Not Suitable For:
Stock options traders (NSE index-specific)
Equity-only traders (requires options knowledge)
International markets (NSE format only)
Complete beginners (requires basic options understanding)
💬 FAQ
Q: Why manual strike entry? Why not fully automatic?
A: Pine Script's type system limits fully automatic strike generation from live data. However, setup takes just 30 seconds once at market open, and the indicator handles all analysis automatically throughout the day.
Q: How often should I update strikes?
A: Rarely! Only when market moves 100+ points from initial ATM. Usually 0-2 times per day, even in volatile markets.
Q: Which Signal Mode is best?
A: Smart mode (default) for professional trading. Use Momentum for intraday scalping, Mean Reversion for premium selling.
Q: Can I use this for stock options?
A: No. The indicator is designed specifically for NSE index options (NIFTY and BANKNIFTY) with NSE format.
Q: Does it work on mobile?
A: Yes, but table display is optimized for desktop/tablet screens. Use "tiny" or "small" size on mobile.
Q: What if I see "-" in cells?
A: Check expiry format (YYMMDD), verify strikes match NSE strikes, and ensure market is open.
Q: What's the difference between ✓✓ and ✓?
A: ✓✓ = Best match (lowest price difference), highest quality. ✓ = Good matches (top 3-5), reliable quality.
Q: Can I backtest this indicator?
A: The indicator shows live analysis. For backtesting options strategies, you'll need historical options data and separate backtesting tools.
Q: What does the info box show?
A: Bottom-left box shows key metrics: symbol, signal mode, spot price, ATM strike, best matched strikes, match difference, and C-P value.
Q: Why no chart plotting?
A: v1.0 focuses on clean table display with maximum information density. Chart plotting may be added in future versions based on user feedback.
🙏 Credits
Developed by a professional options trader for the Indian trading community. Inspired by institutional trading desks and market makers who use call-put parity for daily trading decisions.
Found This Helpful?
⭐ Rate 5 stars if it improved your trading
💬 Comment with your strategy results
🔔 Follow for updates and new indicators
📢 Share with fellow options traders
Feature Requests
Continuous improvement based on trader feedback. Suggest features in comments!
Planned Features (v2.0):
Multi-expiry comparison
Greeks display (Delta, Theta, Vega)
Historical signal performance stats
Custom signal formulas
Export to CSV functionality
🏷️ Tags for Search
#Options #OptionsTrading #NIFTY #BANKNIFTY #NSE #India #OptionChain #CallPut #PutCallParity #Straddle #Strangle #ATM #TradingSignals #OptionsStrategy #PremiumSelling #OptionsScanner #Derivatives #IntradayTrading #VolatilityTrading #Arbitrage #SyntheticPosition #OptionsGreeks #OptionsSelling #OptionsWriting #IndianStockMarket #NSEOptions #OptionsAnalysis #TechnicalAnalysis #AlgoTrading #QuantTrading #ProfessionalTrading #TradingIndicator #PineScript #TradingView
📝 Version History
v1.0 (Current - Dec 2025)
Pine Script v6 implementation
Cross-strike matching (5×5 matrix, 25 combinations)
Three signal modes (Smart, Momentum, Mean Reversion)
Trading signal generation with color coding
Dynamic table positioning (9 positions)
Dynamic table sizing (6 sizes)
Intelligent text scaling
Semi-automatic ATM detection
Auto symbol detection
Simplified input system (50% fewer inputs in Auto mode)
Clean information display
Info box with key metrics
NSE NIFTY & BANKNIFTY support
Start trading smarter with institutional-grade options analysis! 📈💰🚀
Disclaimer: Options trading is subject to market risk. Please read all scheme-related documents carefully before investing.
SMC Structures and FVGThe SMC Structures and FVG indicator allows the user to easily identify trend continuations (Break Of Structure) or trend changes (CHange Of CHaracter) on any time frame. In addition, it display all FVG areas, whether they are bullish, bearish, or even mitigated.
Fair Value Gap :
The FVG process shows every bullish, bearish or even mitigated FVG liquidity area. When a FVG is fully mitigated it will directly be removed of the chart.
There is an history of FVG to show. By selecting specific number of FVG to show in the chart, the user can focus its analysis on lasts liquidity area.
Here's the rules for FVG color :
Green when it's a bullish FVG and has not been mitigated
Red when it's a bearish FVG and has not been mitigated
Gray when the bullish / bearish FVG has been mitigated
Removed when the FVG has been fully mitigated
Structures analysis:
The Structure process show BOS in grey lines and CHoCH in yellow lines. It shows to the user the lasts price action pattern.
The blue lines are the high value and the low value of the current structure.
