MA Zone Candle Color 8.0This indicator plots a selected moving average (any type: EMA, VWAP, HMA, ALMA, custom composites, RVWAP, etc.) and creates a symmetrical grid of horizontal levels/bands spaced at precise, predefined increments around it. The spacing between levels can be set in two modes:
Percent (%) of the current MA value
Points (fixed price units)
The available increment sizes follow a specific geometric-like sequence (very similar to Gann square-of-9 derived steps), giving you clean, repeatable distance choices such as 0.61, 1.22, 2.44, 4.88, 9.77 points (or their percentage equivalents).
Core purpose
It visually marks exactly how far price has moved away from your chosen moving average — in multiples of the increment you selected.
Main practical use cases -
1. Measuring distance from key reference level
VWAP or EMA(20–89), Points mode, 1.22–4.88 incr.
"Price is currently 3.5 increments above VWAP" → quick context for context
2. Identifying structured price levels
Points mode + 2.44 or 4.88 increment
Treat every band as potential support/resistance or target zone
3. Comparing extension size across instruments
Percent mode, same increment value across symbols
Makes extensions visually comparable (BTC vs ETH vs SPX vs NQ)
4. Session / intraday structure mapping
RVWAP or session VWAP + Points mode
See how many "steps" price has made since session open / reset
5. Setting objective take-profit / scale-out levels
Any MA + medium increment (4.88–19.53 points)
"I'll take partials at +2×, +4×, +6× increment" — very mechanical
6. Volatility-adjusted grid (crypto/forex)
Points mode with larger increments
Prevents bands from becoming too wide/narrow during huge volatility swings
Most common combo
MA: VWAP or RVWAP (session/day reset)
Mode: Points
Increment: 1.220704 or 2.441408 or 4.8828125
Bands per side: 30–60
→ Creates a clean, evenly-spaced ladder of levels around the daily/intraday average that traders can use purely for distance measurement and objective level marking.
In short:
It's a very precise, repeatable distance ruler built around any moving average you choose — nothing more, nothing less.
Wyszukaj w skryptach "NQ"
Kalman Absorption/Distribution Tracker 3-State EKFQuant-Grade Institutional Flow: 3-State EKF Absorption Tracker
SUMMARY
An advanced, open-source implementation of a 3-State Extended Kalman Filter (EKF) designed to track institutional Order Flow. By analyzing 1-second intrabar microstructure data, this script estimates the true Position, Velocity, and Volatility of the Cumulative Volume Delta (CVD), revealing hidden Absorption and Distribution events in real-time.
INTRODUCTION: THE SIGNAL AMIDST THE NOISE
In the world of technical analysis, noise is the enemy. Traditional indicators rely on Moving Averages (SMA, EMA) to smooth out price and volume data. The problem is the "Lag vs. Noise" paradox: to get a smooth signal, you must accept lag; to get a fast signal, you must accept noise.
This indicator solves that paradox by introducing aerospace-grade mathematics to the TradingView community: The 3-State Extended Kalman Filter (EKF).
Unlike moving averages that blindly average past data, a Kalman Filter is a probabilistic state-space model. It constantly predicts where the order flow "should" be, compares it to the actual measurement, and updates its internal model based on the calculated uncertainty of the market.
This script is not just another volume oscillator. It is a full microstructure analysis engine that digests intrabar data (down to 1-second resolution) to track the true intent of "Smart Money" while filtering out the noise of retail chop.
THE INNOVATION: WHY 3 STATES?
Most Kalman Filters found in public libraries are "1-State" (tracking price only) or occasionally "2-State" (tracking price and velocity). This script introduces a highly advanced 3-State EKF.
The filter tracks three distinct variables simultaneously in a feedback loop:
State 1: Position (The True CVD)
This is the noise-filtered estimate of the Cumulative Volume Delta. It represents the actual inventory accumulation of aggressive buyers versus sellers, stripped of random noise.
State 2: Velocity (The Momentum)
This tracks the rate of change of the order flow. Is buying accelerating? Is selling pressure fading even as price drops? This provides a leading signal before the cumulative value even turns.
State 3: Volatility (The Adaptive Regime)
This is the game-changer. The filter estimates the current volatility of the order flow (Log-Volatility). In high-volatility environments (like news events), the filter automatically widens its uncertainty bands (Covariance) and reacts faster. In low-volatility environments (chop), it tightens up and ignores minor fluctuations.
THE LOGIC: DETECTING ABSORPTION AND DISTRIBUTION
The core philosophy of this indicator is based on Wyckoff Logic: Effort vs. Result.
-- Effort: Represented by the CVD (Buying/Selling pressure).
-- Result: Represented by Price Movement.
When these two diverge, we have an actionable signal. The script uses the EKF Velocity state to detect these moments:
Absorption (Bullish)
This occurs when the EKF detects high negative Velocity (aggressive selling), but Price refuses to drop. The "Smart Money" is absorbing the sell orders via limit buys. The indicator highlights this as a Blue Event in the dashboard.
Distribution (Bearish)
This occurs when the EKF detects high positive Velocity (aggressive buying), but Price refuses to rise. Limit sellers are capping the market. The indicator highlights this as an Orange Event.
TECHNICAL DEEP DIVE: UNDER THE HOOD
For the developers and quants, here is how the Pine Script is architected using the "type" and "method" features of Pine Script v5.
1. Data Ingestion (Microstructure)
The script uses "request.security_lower_tf" to pull intrabar data regardless of your chart timeframe. This allows the script to see "inside" the bar. A 5-minute candle might look green, but the microstructure might reveal that 80% of the volume was selling absorption at the wick. This script sees that.
2. Tick Classification
Standard CVD assumes that if Price Close is greater than Price Open, all volume is buying. This is often flawed. This script offers three modes of tick handling, including a "High-Low Distribution" method that statistically apportions volume based on where the tick closed relative to its high and low.
3. The EKF Mathematics
The script implements the standard Extended Kalman Filter equations manually. It calculates the Jacobian matrix to handle the non-linear relationship between volatility and price. The "Process Noise Matrix" (Q) is dynamically scaled by the Volatility State. This means the mathematics of the indicator literally "breathe" with the market conditions—expanding during expansion and contracting during consolidation.
THE DASHBOARD & VISUALS:
The indicator features a professional-grade HUD (Heads Up Display) located on the chart table.
-- EKF State Vector: Displays the real-time Position, Velocity, and Volatility values derived from the matrix.
-- Ease of Movement (Wyckoff): Calculates how much price moves per 1,000 contracts of CVD. For example, if Price moves +5 points per 1k Buy CVD, but only -2 points per 1k Sell CVD, the "Path of Least Resistance" is clearly UP.
-- Session State: Tracks cumulative confirmed Bullish vs. Bearish events for Today, Yesterday, and the Day Before (3-Day Profile).
-- Bias Summary: An algorithmic conclusion telling you if the day is "Confirmed Bullish," "Accumulating," or "Neutral."
HOW TO TRADE THIS INDICATOR
Strategy A: The Reversal (Absorption Play)
Look for price making a Lower Low.
Look for the EKF Velocity (Histogram) to be Deep Red (High Selling Pressure).
Watch the Dashboard "Absorption" count increase.
SIGNAL: When EKF Velocity crosses back toward zero and turns grey/green, the absorption is complete. This indicates sellers are exhausted and limit buyers have control.
Strategy B: The Trend Continuation (Ease of Movement)
Check the Dashboard "Ease of Movement" section.
If "Price per +1K CVD" is significantly higher than "Price per -1K CVD", buyers are efficient.
Wait for a pullback where EKF Velocity hits the "Neutral Zone" (Gray).
SIGNAL: Enter Long when Velocity ticks positive again, aligning with the dominant Ease of Movement stats.
CONFIGURATION GUIDE:
Because this is a quant-grade tool, the settings allow for fine-tuning the physics of the filter.
-- Velocity Decay: Controls how fast momentum resets to zero. Set high (0.98) for trending markets, or lower (0.85) for mean-reverting chop.
-- Volatility Persistence: Controls how "sticky" volatility regimes are.
-- Process Noise: Increase this if the filter feels too laggy; decrease it if the filter feels too jittery (noisy).
-- Measurement Noise: Increase this to trust the Mathematical Model more than the Price Data (smoother output).
WHY OPEN SOURCE?
Complex statistical filtering is often sold behind closed doors in expensive "Black Box" algorithms. By releasing this 3-State EKF open source, the goal is to raise the standard of development on TradingView.
I encourage the community to inspect the code, specifically the "ekf_update_3state" function, to understand how matrix operations can be simulated in Pine Script to create adaptive, self-correcting indicators. And also update me for improvements.
DISCLAIMER:
This tool analyzes microstructure volume data. It requires a subscription plan that supports Intrabar inspection (Premium/Pro recommended for best results). Past performance of the Kalman Filter logic does not guarantee future results. Volume analysis is subjective and should be used as part of a comprehensive strategy.
SUGGESTED SETTINGS
-- Timeframe: Works best on 1m, 3m, or 5m charts (Intrabar data is fetched from 1S).
-- Asset Class: Highly effective on Futures (ES, NQ, BTC) and high-volume Forex/Crypto pairs where volume data is reliable.
-- Background: Dark mode recommended for Dashboard visibility.
WHAT IS A KALMAN FILTER?
Imagine driving a car into a tunnel where your GPS signal is lost.
Prediction: Your car knows its last speed (Velocity) and position. It predicts where you are every second inside the tunnel.
Update: When you exit the tunnel, the GPS connects again. The system compares where it thought you were versus where the satellite says you are.
Correction: It corrects your position and updates its estimate of your speed.
Now apply this to trading:
-- The Tunnel: Market Noise, wicks, and Fake-outs.
-- The Car: The True Market Trend.
-- This Indicator: The navigation system that tells you where the market actually is, ignoring the noise of the tunnel.
Enjoy the indicator and trade safe!
Dr. Jay Desai
(Investment Management & Derivatives Area, Gujarat University)
SA Trump Volatility Pattern Wick + Volume Shock ReversalDisclaimer (read first)
Educational use only — not financial advice. This script does not provide entries/exits, targets, position sizing, or profit guarantees. Trading (especially options/futures) involves substantial risk and can result in loss of principal (and more for leveraged products). Use at your own discretion.
Best use cases on the 2-Hour timeframe
On 2H, this script becomes a high-signal-quality “shock reversal” detector instead of a noisy candle toy. You’re essentially filtering for:
Large wick rejection
Small real body
Statistically unusual volume (Z-score > threshold)
Context alignment (trend filter + prior bar direction + optional RSI)
What 2H is best for
1) Detecting “event shock” reversals
2H bars often capture:
Macro headlines
Fed commentary
earnings reactions (for equities)
sudden volatility expansions
When the script fires on 2H, it often means:
“Aggressive push happened, liquidity got rejected, and participation was unusually high.”
That’s a structural clue, not a trade instruction.
2) Filtering false breakouts / breakdowns
The wick requirement is basically “failed continuation.”
On 2H, this is powerful around:
prior day highs/lows
weekly pivots
obvious consolidation edges
key moving averages (fast SMA / slow SMA gate)
Bull pattern = flush + reclaim behavior.
Bear pattern = pop + rejection behavior.
3) Options traders: timing “premium exposure windows”
On 2H, this is great for options traders who want to avoid buying premium into a fake move.
BullTrump on 2H can be used as a “don’t chase puts / be cautious short” context shift.
BearTrump on 2H can be used as a “don’t chase calls / be cautious long” context shift.
It’s a “regime hint” for the next few sessions, not a one-bar command.
4) Futures traders: rotation vs continuation framework
A 2H “Trump Candle” often marks:
the end of a liquidation leg
a stop-run / squeeze peak
a pivot moment where the market shifts from impulse to balance
Use it to decide whether you’re in:
continuation mode (trend carries)
or rotation mode (mean-reversion / two-way)
How to use it (2H workflow)
Step A — Keep it strict at first
Recommended defaults for 2H:
wickFracThreshold: 0.40–0.55
bodyMaxFrac: 0.35–0.45
volZThresh: 1.0–1.5
useRSIFilter: ON
RSI bull min / bear max: 45 / 55 (good baseline)
Step B — Treat triggers as “context events”
When it prints, ask 3 questions:
Where did it happen? (key level or random spot)
Was it aligned with trend gate? (SMA fast/slow)
Did volume Z-score spike? (true shock vs normal wick)
Higher quality triggers happen when:
the wick pierces a known level (prior swing / range edge)
and the close re-enters the range
and volume Z-score is meaningfully positive
Step C — Confirm with the next 1–2 candles (optional)
On 2H, it’s reasonable to wait for:
a follow-through close
or a hold above/below fast SMA
or a second “acceptance” candle
You can do this manually without changing code.
Other recommended timeframes (best to worst)
✅ 4H (even cleaner, fewer signals)
Use for:
swing context
multi-day pivots
big reversal points
✅ 1H (more signals, still structured)
Use for:
intraday + overnight context
day-trade bias shifts
✅ 30m (for active traders)
Use for:
tighter responsiveness
more setups
But requires more discretion; noise increases.
⚠️ 15m and below (only if you increase strictness)
If you want to run it on 5m/15m:
raise volZThresh (ex: 1.5–2.0)
raise wickFracThreshold (ex: 0.50–0.65)
lower bodyMaxFrac (ex: 0.25–0.35)
Otherwise it will trigger too often.
Best markets for this script
Works best on:
Index futures: /NQ, /ES (big volume makes Z-score meaningful)
Liquid ETFs: SPY, QQQ
High-volume large caps (AAPL, MSFT, NVDA etc.)
Less reliable on:
thin small caps (volume Z-score gets weird)
low-volume premarket candles
illiquid options underlyings
Signal Inside the Script ✅ SA ZoneEngine Bias Filtered is a market-structure bias and confirmation tool designed for futures To request access: 👉 Purchase here: trianchor.gumroad.com
Best GBT for this indicator
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DTG Open Range Breakout
Description:
Overview The Open Range Breakout (ORB) is one of the most statistically significant strategies for day traders, particularly in Futures (ES/NQ) and Forex markets. This indicator automates the process of identifying the "Opening Range" (e.g., the first 30 minutes of the New York session) and visualizing the key High/Low levels that define the day's bias.
Unlike standard indicators that clutter the chart, this tool focuses on Price Action context. It highlights the critical volatility window and alerts you only when price makes a definitive move outside of this established range.
Key Features
Fully Customizable Session: Defaults to 09:30–10:00 (ET), but can be adjusted for any market (London Open, Tokyo Open, etc.).
Visual "No-Trade" Zone: Draws a shaded box representing the range formation period. This helps traders avoid "choppy" price action during the initial volatility.
Auto-Reset: The script automatically detects a new trading day and resets the range, keeping your chart clean without manual intervention.
Dynamic Support/Resistance: Once the range is closed, the High and Low lines extend forward, acting as key support or resistance levels for the rest of the session.
Smart Alerts: Alerts are programmed to trigger only after the range has fully formed, preventing false signals during the volatility establishment phase.
Reversals: If price breaks out but immediately fails and re-enters the box, consider this a "Fakeout" and look for a move to the opposite side.
Settings
Open Range Session: The specific time window to measure (Format: HHMM-HHMM).
Range Box Color: Visual preference for the shaded area.
Extend High/Low Lines: Toggle the dashed projection lines on/off.
DON.TRADES.GOLD@GMAIL.COM
Disclaimer This script is for educational and analytical purposes only. Past performance of a breakout strategy does not guarantee future results. Always manage risk.
Basic Key Levels | Feng FuturesKey Levels | Feng Futures (Basic) automatically plots the most essential daily reference levels used by futures traders to establish intraday context and structure.
This lightweight version focuses on the three levels that matter most for session bias and liquidity reference:
Previous Day High (PDH)
Previous Day Low (PDL)
Session Open (18:00 NY for futures)
These levels are commonly used by professional and institutional participants as decision points for:
directional bias
continuation vs. reversal context
risk definition and invalidation
Features:
• Auto-plotted PDH and PDL
• Futures session open (18:00 NY)
• Clean, non-repainting levels
• Lines extend forward for intraday use
• Optional price labels pinned to the right edge
• Minimal design to reduce chart clutter
• Full color, width, and label customization
• Optimized for intraday futures trading
This indicator does not provide trade signals or alerts.
It is designed to support planning, execution, and review within your own trading framework.
Best used on:
ES, NQ, RTY, YM (intraday timeframes)
PDH / PDL levels can be used as take profit targets or to help form bias. For example, if we break out of PDH, we may look for longs.
Disclaimer:
This indicator is for educational purposes only and does not constitute financial advice. Trading futures involves significant risk and may not be suitable for all investors. Always do your own research and use proper risk management.
ORB | Feng FuturesThe ORB | Feng Futures indicator automatically detects the Opening Range Breakout (ORB) for each trading session, plotting the High, Low, and Midline in real time. This tool is built for futures traders who rely on ORB structure to confirm trends, identify breakout zones, and recognize reversal areas early in the session.
Features:
• Auto-calculated ORB High, Low, and Midline
• Multi-timezone session support (NY, Chicago, London, Tokyo, etc.)
• Customize ORB time range and time window for display
• Real-time updating lines that freeze at session close
• Optional labels with customizable size, color, and offset
• Save and view multiple previous ORB sessions
• Full color customization for all levels
• Automatically hides on higher timeframes (Daily+) to reduce clutter
• Works on ES, NQ, and all intraday futures charts
• Works on stocks, crypto, forex, and other tradeable assets where ORB is applicable
Disclaimer: This indicator is for educational purposes only and does not constitute financial advice. Trading futures involves significant risk and may not be suitable for all investors. Always do your own research and use proper risk management.
Delta/Volume Bubble Strategy [Quant Z-Score] Maxxed VersionDelta/Volume Bubble Signals Maxxed Verison
This indicator combines advanced volume delta analysis with smart filtering to generate high-conviction intraday signals on futures like YM, ES, and NQ (5-minute charts perform particularly well in testing).
Special thanks to L&L Capital for the LNL Trend System, which provides the excellent dynamic chop detection and cloud visuals used here.
A very BIG thanks to tncylyv for the original volume delta bubble script — its Z-score normalization on extreme volume/delta is the foundation of the core detection logic.This entire system is now possible thanks to TradingView's addition of Volume Delta data in the Footprint chart, allowing accurate lower-timeframe delta aggregation without external feeds. Core Concept the indicator identifies extreme volume/delta spikes — moments when significant buying or selling pressure appears — and only signals when multiple confluence filters align. This results in lower-frequency, higher-quality trades that aim to capture institutional momentum while avoiding noise.
How It Works — Key Components Volume Delta Detection (The Heart of the System) Uses TradingView's built-in footprint delta (aggregated from lower TF, default 1-second bars).
Calculates absolute delta and applies a rolling Z-score (default lookback 60 bars) to normalize extremes across different volatility regimes and instruments.
Bubbles visualize spikes above threshold (default 1.7σ).
BUY/SELL signals require the same threshold plus additional filters.
Absorption Filter (Enabled by Default) Detects high volume/delta with minimal price movement ("effort vs result" failure = trapped traders).
Purple glow on bubbles + optional alert.
Signals are suppressed on absorption bars to avoid counter-trend traps.
Trend Filter (Nadaraya-Watson from jdehorty as default) Non-repainting kernel regression line for smooth, adaptive trend following.
Signals only fire when price is on the correct side of the trend line (above for longs, below for shorts). Can be disabled or switched to EMA/WMA/KAMA.
LNL Chop Filter (Tight Mode by Default) Dynamic ATR-based stop zones from L&L's system.
When stop levels appear on both sides of price = sideways/chop (no-go zone).
Signals completely suppressed during chop.
Usage Tips Best on intraday futures (YM 5-min has shown strong results in testing).
Defaults are tuned for balance: 1.7σ threshold, Tight LNL mode, absorption on.
Strategy version (separate script) adds LNL trailing stops for actual backtesting/exits.
Customize freely — try different LNL modes (Net for wider range), trend types, or Z-thresholds.
Also available the matching indicator by yours truly.
Important: Forward Test Thoroughly This indicator was refined on historical data, so there's always risk of over-fitting.
Always forward test on live or paper accounts for weeks/months before real capital: Validate across different market regimes (trending, ranging, high/low volatility).
Compare out-of-sample periods.
Adjust one parameter at a time and re-validate forward.
Markets change — what worked yesterday may need tweaking tomorrow.
Feel free to use, modify, and share. Good luck, and trade well! — Max
Delta/Volume Bubble Signals [Quant Z-Score] Maxxed Version Delta/Volume Bubble Signals Maxxed Verison
This indicator combines advanced volume delta analysis with smart filtering to generate high-conviction intraday signals on futures like YM, ES, and NQ (5-minute charts perform particularly well in testing).
Special thanks to L&L Capital for the LNL Trend System, which provides the excellent dynamic chop detection and cloud visuals used here.
A very BIG thanks to tncylyv for the original volume delta bubble script — its Z-score normalization on extreme volume/delta is the foundation of the core detection logic.This entire system is now possible thanks to TradingView's addition of Volume Delta data in the Footprint chart, allowing accurate lower-timeframe delta aggregation without external feeds. Core Concept the indicator identifies extreme volume/delta spikes — moments when significant buying or selling pressure appears — and only signals when multiple confluence filters align. This results in lower-frequency, higher-quality trades that aim to capture institutional momentum while avoiding noise.
How It Works — Key Components Volume Delta Detection (The Heart of the System) Uses TradingView's built-in footprint delta (aggregated from lower TF, default 1-second bars).
Calculates absolute delta and applies a rolling Z-score (default lookback 60 bars) to normalize extremes across different volatility regimes and instruments.
Bubbles visualize spikes above threshold (default 1.7σ).
BUY/SELL signals require the same threshold plus additional filters.
Absorption Filter (Enabled by Default) Detects high volume/delta with minimal price movement ("effort vs result" failure = trapped traders).
Purple glow on bubbles + optional alert.
Signals are suppressed on absorption bars to avoid counter-trend traps.
Trend Filter (Nadaraya-Watson from jdehorty as default) Non-repainting kernel regression line for smooth, adaptive trend following.
Signals only fire when price is on the correct side of the trend line (above for longs, below for shorts). Can be disabled or switched to EMA/WMA/KAMA.
LNL Chop Filter (Tight Mode by Default) Dynamic ATR-based stop zones from L&L's system.
When stop levels appear on both sides of price = sideways/chop (no-go zone).
Signals completely suppressed during chop.
Signals & Visuals
BUY: Small blue "BUY" label below bar.
SELL: Small red "SELL" label above bar.
CLOSE LONG: Tiny dark grey "CLOSE" label above bar (on opposite SELL signal or stop hit).
CLOSE SHORT: Tiny dark grey "CLOSE" label below bar (on opposite BUY signal or stop hit).
No overlap — closes only appear on actual exit/reversal bars.
Alerts (Fully Separate)Individual toggles for:
BUY Signal
SELL Signal
CLOSE LONG (opposite SELL)
CLOSE SHORT (opposite BUY)
Absorption Detected
Unusual Volume/Delta
Usage Tips Best on intraday futures (YM 5-min has shown strong results in testing).
Defaults are tuned for balance: 1.7σ threshold, Tight LNL mode, absorption on.
Strategy version (separate script) adds LNL trailing stops for actual backtesting/exits.
Customize freely — try different LNL modes (Net for wider range), trend types, or Z-thresholds.
To backtest and optimize using the matching strategy which I created as well.
Important: Forward Test Thoroughly This indicator was refined on historical data, so there's always risk of over-fitting.
Always forward test on live or paper accounts for weeks/months before real capital: Validate across different market regimes (trending, ranging, high/low volatility).
Compare out-of-sample periods.
Adjust one parameter at a time and re-validate forward.
Markets change — what worked yesterday may need tweaking tomorrow.
Feel free to use, modify, and share. Good luck, and trade well! — Max
[Greeny] RTH Only Naked VPOCWhat it does
Calculates and displays daily Volume Point of Control (VPOC) levels based on RTH (Regular Trading Hours) session only. Tracks which VPOCs remain "naked" (untouched) and which have been hit - but only counts hits during RTH hours, ignoring overnight/globex touches.
Key Features
One VPOC per trading day calculated from entire RTH session volume profile
RTH-only hit detection - levels only marked as hit when touched during RTH, not overnight
Works on all timeframes - daily, hourly, or any chart timeframe
Volume-based filtering - automatically skips low-liquidity sessions (pre-front-month contract data)
Visual markers - small dash on origin bar shows where each VPOC was, even after being hit
Visual Guide
Yellow dashed line - Naked VPOC (not yet touched during RTH)
White dashed line - Hit VPOC (was touched during RTH)
Small dash on candle - POC origin marker
Settings
Display options: Toggle to show only naked POCs, customize hit/naked colors, adjust line width and style (solid/dashed/dotted), enable/disable line extension and origin markers.
RTH Session: Configure start and end time in NY timezone. Default is 9:30-16:00 (US equity market hours), which equals 15:30-22:00 Budapest time.
Advanced: Adjust volume profile resolution (default 250 bins), data source timeframe for calculations (5min recommended for daily charts), and minimum volume threshold to filter out low-liquidity sessions like pre-rollover contract data (default 10% of average).
Best For
ES/MES, NQ/MNQ futures traders
Mean reversion strategies using VPOC as support/resistance
Auction Market Theory practitioners
Anyone wanting clean RTH-only volume profile levels
Note on Contract Rollovers
When using specific contract symbols (e.g., ESH2026 instead of ES1!), the script may show many naked VPOCs from months before the contract became active. This happens because futures contracts have very low liquidity before becoming the front-month, creating unreliable VPOCs with gaps that never get hit. The volume filter helps reduce this, but you may need to increase the "Min Volume % of Average" setting or simply ignore older levels when viewing back-month data.
MAG7 Market Cap Weighted Index [Reflex]Summary
A synthetic intraday index built from the MAG7, weighted by market cap and plotted as true OHLC candles.
Usage
This indicator was designed for market breadth analyses. Since it uses market cap weighting, it behaves like any other index (eg. SPX).
It shows where mega-cap leadership is actually trading, making it useful for trend confirmation, divergence analysis versus NQ/ES, and contextualizing the breadth of the market.
The index is intentionally gated to the NY RTH session to avoid distorted behavior when component data is unavailable.
Advanced Volume & Liquidity SuiteThe Institutional Code is an advanced trading system designed to reveal the footprint of "Smart Money" in the Futures and Indices markets. Unlike traditional indicators that track price, this algorithm tracks Real Volume and Liquidity, comparing retail data with institutional (CME) data to identify zones of manipulation and absorption.
This script transforms your chart into an institutional command board, ideal for trading NQ (Nasdaq), ES (S&P 500), and YM (Dow Jones) with surgical precision.
Adaptive Market Wave TheoryAdaptive Market Wave Theory
🌊 CORE INNOVATION: PROBABILISTIC PHASE DETECTION WITH MULTI-AGENT CONSENSUS
Adaptive Market Wave Theory (AMWT) represents a fundamental paradigm shift in how traders approach market phase identification. Rather than counting waves subjectively or drawing static breakout levels, AMWT treats the market as a hidden state machine —using Hidden Markov Models, multi-agent consensus systems, and reinforcement learning algorithms to quantify what traditional methods leave to interpretation.
The Wave Analysis Problem:
Traditional wave counting methodologies (Elliott Wave, harmonic patterns, ABC corrections) share fatal weaknesses that AMWT directly addresses:
1. Non-Falsifiability : Invalid wave counts can always be "recounted" or "adjusted." If your Wave 3 fails, it becomes "Wave 3 of a larger degree" or "actually Wave C." There's no objective failure condition.
2. Observer Bias : Two expert wave analysts examining the same chart routinely reach different conclusions. This isn't a feature—it's a fundamental methodology flaw.
3. No Confidence Measure : Traditional analysis says "This IS Wave 3." But with what probability? 51%? 95%? The binary nature prevents proper position sizing and risk management.
4. Static Rules : Fixed Fibonacci ratios and wave guidelines cannot adapt to changing market regimes. What worked in 2019 may fail in 2024.
5. No Accountability : Wave methodologies rarely track their own performance. There's no feedback loop to improve.
The AMWT Solution:
AMWT addresses each limitation through rigorous mathematical frameworks borrowed from speech recognition, machine learning, and reinforcement learning:
• Non-Falsifiability → Hard Invalidation : Wave hypotheses die permanently when price violates calculated invalidation levels. No recounting allowed.
• Observer Bias → Multi-Agent Consensus : Three independent analytical agents must agree. Single-methodology bias is eliminated.
• No Confidence → Probabilistic States : Every market state has a calculated probability from Hidden Markov Model inference. "72% probability of impulse state" replaces "This is Wave 3."
• Static Rules → Adaptive Learning : Thompson Sampling multi-armed bandits learn which agents perform best in current conditions. The system adapts in real-time.
• No Accountability → Performance Tracking : Comprehensive statistics track every signal's outcome. The system knows its own performance.
The Core Insight:
"Traditional wave analysis asks 'What count is this?' AMWT asks 'What is the probability we are in an impulsive state, with what confidence, confirmed by how many independent methodologies, and anchored to what liquidity event?'"
🔬 THEORETICAL FOUNDATION: HIDDEN MARKOV MODELS
Why Hidden Markov Models?
Markets exist in hidden states that we cannot directly observe—only their effects on price are visible. When the market is in an "impulse up" state, we see rising prices, expanding volume, and trending indicators. But we don't observe the state itself—we infer it from observables.
This is precisely the problem Hidden Markov Models (HMMs) solve. Originally developed for speech recognition (inferring words from sound waves), HMMs excel at estimating hidden states from noisy observations.
HMM Components:
1. Hidden States (S) : The unobservable market conditions
2. Observations (O) : What we can measure (price, volume, indicators)
3. Transition Matrix (A) : Probability of moving between states
4. Emission Matrix (B) : Probability of observations given each state
5. Initial Distribution (π) : Starting state probabilities
AMWT's Six Market States:
State 0: IMPULSE_UP
• Definition: Strong bullish momentum with high participation
• Observable Signatures: Rising prices, expanding volume, RSI >60, price above upper Bollinger Band, MACD histogram positive and rising
• Typical Duration: 5-20 bars depending on timeframe
• What It Means: Institutional buying pressure, trend acceleration phase
State 1: IMPULSE_DN
• Definition: Strong bearish momentum with high participation
• Observable Signatures: Falling prices, expanding volume, RSI <40, price below lower Bollinger Band, MACD histogram negative and falling
• Typical Duration: 5-20 bars (often shorter than bullish impulses—markets fall faster)
• What It Means: Institutional selling pressure, panic or distribution acceleration
State 2: CORRECTION
• Definition: Counter-trend consolidation with declining momentum
• Observable Signatures: Sideways or mild counter-trend movement, contracting volume, RSI returning toward 50, Bollinger Bands narrowing
• Typical Duration: 8-30 bars
• What It Means: Profit-taking, digestion of prior move, potential accumulation for next leg
State 3: ACCUMULATION
• Definition: Base-building near lows where informed participants absorb supply
• Observable Signatures: Price near recent lows but not making new lows, volume spikes on up bars, RSI showing positive divergence, tight range
• Typical Duration: 15-50 bars
• What It Means: Smart money buying from weak hands, preparing for markup phase
State 4: DISTRIBUTION
• Definition: Top-forming near highs where informed participants distribute holdings
• Observable Signatures: Price near recent highs but struggling to advance, volume spikes on down bars, RSI showing negative divergence, widening range
• Typical Duration: 15-50 bars
• What It Means: Smart money selling to late buyers, preparing for markdown phase
State 5: TRANSITION
• Definition: Regime change period with mixed signals and elevated uncertainty
• Observable Signatures: Conflicting indicators, whipsaw price action, no clear momentum, high volatility without direction
• Typical Duration: 5-15 bars
• What It Means: Market deciding next direction, dangerous for directional trades
The Transition Matrix:
The transition matrix A captures the probability of moving from one state to another. AMWT initializes with empirically-derived values then updates online:
From/To IMP_UP IMP_DN CORR ACCUM DIST TRANS
IMP_UP 0.70 0.02 0.20 0.02 0.04 0.02
IMP_DN 0.02 0.70 0.20 0.04 0.02 0.02
CORR 0.15 0.15 0.50 0.10 0.10 0.00
ACCUM 0.30 0.05 0.15 0.40 0.05 0.05
DIST 0.05 0.30 0.15 0.05 0.40 0.05
TRANS 0.20 0.20 0.20 0.15 0.15 0.10
Key Insights from Transition Probabilities:
• Impulse states are sticky (70% self-transition): Once trending, markets tend to continue
• Corrections can transition to either impulse direction (15% each): The next move after correction is uncertain
• Accumulation strongly favors IMP_UP transition (30%): Base-building leads to rallies
• Distribution strongly favors IMP_DN transition (30%): Topping leads to declines
The Viterbi Algorithm:
Given a sequence of observations, how do we find the most likely state sequence? This is the Viterbi algorithm—dynamic programming to find the optimal path through the state space.
Mathematical Formulation:
δ_t(j) = max_i × B_j(O_t)
Where:
δ_t(j) = probability of most likely path ending in state j at time t
A_ij = transition probability from state i to state j
B_j(O_t) = emission probability of observation O_t given state j
AMWT Implementation:
AMWT runs Viterbi over a rolling window (default 50 bars), computing the most likely state sequence and extracting:
• Current state estimate
• State confidence (probability of current state vs alternatives)
• State sequence for pattern detection
Online Learning (Baum-Welch Adaptation):
Unlike static HMMs, AMWT continuously updates its transition and emission matrices based on observed market behavior:
f_onlineUpdateHMM(prev_state, curr_state, observation, decay) =>
// Update transition matrix
A *= decay
A += (1.0 - decay)
// Renormalize row
// Update emission matrix
B *= decay
B += (1.0 - decay)
// Renormalize row
The decay parameter (default 0.85) controls adaptation speed:
• Higher decay (0.95): Slower adaptation, more stable, better for consistent markets
• Lower decay (0.80): Faster adaptation, more reactive, better for regime changes
Why This Matters for Trading:
Traditional indicators give you a number (RSI = 72). AMWT gives you a probabilistic state assessment :
"There is a 78% probability we are in IMPULSE_UP state, with 15% probability of CORRECTION and 7% distributed among other states. The transition matrix suggests 70% chance of remaining in IMPULSE_UP next bar, 20% chance of transitioning to CORRECTION."
This enables:
• Position sizing by confidence : 90% confidence = full size; 60% confidence = half size
• Risk management by transition probability : High correction probability = tighten stops
• Strategy selection by state : IMPULSE = trend-follow; CORRECTION = wait; ACCUMULATION = scale in
🎰 THE 3-BANDIT CONSENSUS SYSTEM
The Multi-Agent Philosophy:
No single analytical methodology works in all market conditions. Trend-following excels in trending markets but gets chopped in ranges. Mean-reversion excels in ranges but gets crushed in trends. Structure-based analysis works when structure is clear but fails in chaotic markets.
AMWT's solution: employ three independent agents , each analyzing the market from a different perspective, then use Thompson Sampling to learn which agents perform best in current conditions.
Agent 1: TREND AGENT
Philosophy : Markets trend. Follow the trend until it ends.
Analytical Components:
• EMA Alignment: EMA8 > EMA21 > EMA50 (bullish) or inverse (bearish)
• MACD Histogram: Direction and rate of change
• Price Momentum: Close relative to ATR-normalized movement
• VWAP Position: Price above/below volume-weighted average price
Signal Generation:
Strong Bull: EMA aligned bull AND MACD histogram > 0 AND momentum > 0.3 AND close > VWAP
→ Signal: +1 (Long), Confidence: 0.75 + |momentum| × 0.4
Moderate Bull: EMA stack bull AND MACD rising AND momentum > 0.1
→ Signal: +1 (Long), Confidence: 0.65 + |momentum| × 0.3
Strong Bear: EMA aligned bear AND MACD histogram < 0 AND momentum < -0.3 AND close < VWAP
→ Signal: -1 (Short), Confidence: 0.75 + |momentum| × 0.4
Moderate Bear: EMA stack bear AND MACD falling AND momentum < -0.1
→ Signal: -1 (Short), Confidence: 0.65 + |momentum| × 0.3
When Trend Agent Excels:
• Trend days (IB extension >1.5x)
• Post-breakout continuation
• Institutional accumulation/distribution phases
When Trend Agent Fails:
• Range-bound markets (ADX <20)
• Chop zones after volatility spikes
• Reversal days at major levels
Agent 2: REVERSION AGENT
Philosophy: Markets revert to mean. Extreme readings reverse.
Analytical Components:
• Bollinger Band Position: Distance from bands, percent B
• RSI Extremes: Overbought (>70) and oversold (<30)
• Stochastic: %K/%D crossovers at extremes
• Band Squeeze: Bollinger Band width contraction
Signal Generation:
Oversold Bounce: BB %B < 0.20 AND RSI < 35 AND Stochastic < 25
→ Signal: +1 (Long), Confidence: 0.70 + (30 - RSI) × 0.01
Overbought Fade: BB %B > 0.80 AND RSI > 65 AND Stochastic > 75
→ Signal: -1 (Short), Confidence: 0.70 + (RSI - 70) × 0.01
Squeeze Fire Bull: Band squeeze ending AND close > upper band
→ Signal: +1 (Long), Confidence: 0.65
Squeeze Fire Bear: Band squeeze ending AND close < lower band
→ Signal: -1 (Short), Confidence: 0.65
When Reversion Agent Excels:
• Rotation days (price stays within IB)
• Range-bound consolidation
• After extended moves without pullback
When Reversion Agent Fails:
• Strong trend days (RSI can stay overbought for days)
• Breakout moves
• News-driven directional moves
Agent 3: STRUCTURE AGENT
Philosophy: Market structure reveals institutional intent. Follow the smart money.
Analytical Components:
• Break of Structure (BOS): Price breaks prior swing high/low
• Change of Character (CHOCH): First break against prevailing trend
• Higher Highs/Higher Lows: Bullish structure
• Lower Highs/Lower Lows: Bearish structure
• Liquidity Sweeps: Stop runs that reverse
Signal Generation:
BOS Bull: Price breaks above prior swing high with momentum
→ Signal: +1 (Long), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bull: First higher low after downtrend, breaking structure
→ Signal: +1 (Long), Confidence: 0.75
BOS Bear: Price breaks below prior swing low with momentum
→ Signal: -1 (Short), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bear: First lower high after uptrend, breaking structure
→ Signal: -1 (Short), Confidence: 0.75
Liquidity Sweep Long: Price sweeps below swing low then reverses strongly
→ Signal: +1 (Long), Confidence: 0.80
Liquidity Sweep Short: Price sweeps above swing high then reverses strongly
→ Signal: -1 (Short), Confidence: 0.80
When Structure Agent Excels:
• After liquidity grabs (stop runs)
• At major swing points
• During institutional accumulation/distribution
When Structure Agent Fails:
• Choppy, structureless markets
• During news events (structure becomes noise)
• Very low timeframes (noise overwhelms structure)
Thompson Sampling: The Bandit Algorithm
With three agents giving potentially different signals, how do we decide which to trust? This is the multi-armed bandit problem —balancing exploitation (using what works) with exploration (testing alternatives).
Thompson Sampling Solution:
Each agent maintains a Beta distribution representing its success/failure history:
Agent success rate modeled as Beta(α, β)
Where:
α = number of successful signals + 1
β = number of failed signals + 1
On Each Bar:
1. Sample from each agent's Beta distribution
2. Weight agent signals by sampled probabilities
3. Combine weighted signals into consensus
4. Update α/β based on trade outcomes
Mathematical Implementation:
// Beta sampling via Gamma ratio method
f_beta_sample(alpha, beta) =>
g1 = f_gamma_sample(alpha)
g2 = f_gamma_sample(beta)
g1 / (g1 + g2)
// Thompson Sampling selection
for each agent:
sampled_prob = f_beta_sample(agent.alpha, agent.beta)
weight = sampled_prob / sum(all_sampled_probs)
consensus += agent.signal × agent.confidence × weight
Why Thompson Sampling?
• Automatic Exploration : Agents with few samples get occasional chances (high variance in Beta distribution)
• Bayesian Optimal : Mathematically proven optimal solution to exploration-exploitation tradeoff
• Uncertainty-Aware : Small sample size = more exploration; large sample size = more exploitation
• Self-Correcting : Poor performers naturally get lower weights over time
Example Evolution:
Day 1 (Initial):
Trend Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Reversion Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Structure Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
After 50 Signals:
Trend Agent: Beta(28,23) → samples ~0.55 (moderate confidence)
Reversion Agent: Beta(18,33) → samples ~0.35 (underperforming)
Structure Agent: Beta(32,19) → samples ~0.63 (outperforming)
Result: Structure Agent now receives highest weight in consensus
Consensus Requirements by Mode:
Aggressive Mode:
• Minimum 1/3 agents agreeing
• Consensus threshold: 45%
• Use case: More signals, higher risk tolerance
Balanced Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 55%
• Use case: Standard trading
Conservative Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 65%
• Use case: Higher quality, fewer signals
Institutional Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 75%
• Additional: Session quality >0.65, mode adjustment +0.10
• Use case: Highest quality signals only
🌀 INTELLIGENT CHOP DETECTION ENGINE
The Chop Problem:
Most trading losses occur not from being wrong about direction, but from trading in conditions where direction doesn't exist . Choppy, range-bound markets generate false signals from every methodology—trend-following, mean-reversion, and structure-based alike.
AMWT's chop detection engine identifies these low-probability environments before signals fire, preventing the most damaging trades.
Five-Factor Chop Analysis:
Factor 1: ADX Component (25% weight)
ADX (Average Directional Index) measures trend strength regardless of direction.
ADX < 15: Very weak trend (high chop score)
ADX 15-20: Weak trend (moderate chop score)
ADX 20-25: Developing trend (low chop score)
ADX > 25: Strong trend (minimal chop score)
adx_chop = (i_adxThreshold - adx_val) / i_adxThreshold × 100
Why ADX Works: ADX synthesizes +DI and -DI movements. Low ADX means price is moving but not directionally—the definition of chop.
Factor 2: Choppiness Index (25% weight)
The Choppiness Index measures price efficiency using the ratio of ATR sum to price range:
CI = 100 × LOG10(SUM(ATR, n) / (Highest - Lowest)) / LOG10(n)
CI > 61.8: Choppy (range-bound, inefficient movement)
CI < 38.2: Trending (directional, efficient movement)
CI 38.2-61.8: Transitional
chop_idx_score = (ci_val - 38.2) / (61.8 - 38.2) × 100
Why Choppiness Index Works: In trending markets, price covers distance efficiently (low ATR sum relative to range). In choppy markets, price oscillates wildly but goes nowhere (high ATR sum relative to range).
Factor 3: Range Compression (20% weight)
Compares recent range to longer-term range, detecting volatility squeezes:
recent_range = Highest(20) - Lowest(20)
longer_range = Highest(50) - Lowest(50)
compression = 1 - (recent_range / longer_range)
compression > 0.5: Strong squeeze (potential breakout imminent)
compression < 0.2: No compression (normal volatility)
range_compression_score = compression × 100
Why Range Compression Matters: Compression precedes expansion. High compression = market coiling, preparing for move. Signals during compression often fail because the breakout hasn't occurred yet.
Factor 4: Channel Position (15% weight)
Tracks price position within the macro channel:
channel_position = (close - channel_low) / (channel_high - channel_low)
position 0.4-0.6: Center of channel (indecision zone)
position <0.2 or >0.8: Near extremes (potential reversal or breakout)
channel_chop = abs(0.5 - channel_position) < 0.15 ? high_score : low_score
Why Channel Position Matters: Price in the middle of a range is in "no man's land"—equally likely to go either direction. Signals in the channel center have lower probability.
Factor 5: Volume Quality (15% weight)
Assesses volume relative to average:
vol_ratio = volume / SMA(volume, 20)
vol_ratio < 0.7: Low volume (lack of conviction)
vol_ratio 0.7-1.3: Normal volume
vol_ratio > 1.3: High volume (conviction present)
volume_chop = vol_ratio < 0.8 ? (1 - vol_ratio) × 100 : 0
Why Volume Quality Matters: Low volume moves lack institutional participation. These moves are more likely to reverse or stall.
Combined Chop Intensity:
chopIntensity = (adx_chop × 0.25) + (chop_idx_score × 0.25) +
(range_compression_score × 0.20) + (channel_chop × 0.15) +
(volume_chop × i_volumeChopWeight × 0.15)
Regime Classifications:
Based on chop intensity and component analysis:
• Strong Trend (0-20%): ADX >30, clear directional momentum, trade aggressively
• Trending (20-35%): ADX >20, moderate directional bias, trade normally
• Transitioning (35-50%): Mixed signals, regime change possible, reduce size
• Mid-Range (50-60%): Price trapped in channel center, avoid new positions
• Ranging (60-70%): Low ADX, price oscillating within bounds, fade extremes only
• Compression (70-80%): Volatility squeeze, expansion imminent, wait for breakout
• Strong Chop (80-100%): Multiple chop factors aligned, avoid trading entirely
Signal Suppression:
When chop intensity exceeds the configurable threshold (default 80%), signals are suppressed entirely. The dashboard displays "⚠️ CHOP ZONE" with the current regime classification.
Chop Box Visualization:
When chop is detected, AMWT draws a semi-transparent box on the chart showing the chop zone. This visual reminder helps traders avoid entering positions during unfavorable conditions.
💧 LIQUIDITY ANCHORING SYSTEM
The Liquidity Concept:
Markets move from liquidity pool to liquidity pool. Stop losses cluster at predictable locations—below swing lows (buy stops become sell orders when triggered) and above swing highs (sell stops become buy orders when triggered). Institutions know where these clusters are and often engineer moves to trigger them before reversing.
AMWT identifies and tracks these liquidity events, using them as anchors for signal confidence.
Liquidity Event Types:
Type 1: Volume Spikes
Definition: Volume > SMA(volume, 20) × i_volThreshold (default 2.8x)
Interpretation: Sudden volume surge indicates institutional activity
• Near swing low + reversal: Likely accumulation
• Near swing high + reversal: Likely distribution
• With continuation: Institutional conviction in direction
Type 2: Stop Runs (Liquidity Sweeps)
Definition: Price briefly exceeds swing high/low then reverses within N bars
Detection:
• Price breaks above recent swing high (triggering buy stops)
• Then closes back below that high within 3 bars
• Signal: Bullish stop run complete, reversal likely
Or inverse for bearish:
• Price breaks below recent swing low (triggering sell stops)
• Then closes back above that low within 3 bars
• Signal: Bearish stop run complete, reversal likely
Type 3: Absorption Events
Definition: High volume with small candle body
Detection:
• Volume > 2x average
• Candle body < 30% of candle range
• Interpretation: Large orders being filled without moving price
• Implication: Accumulation (at lows) or distribution (at highs)
Type 4: BSL/SSL Pools (Buy-Side/Sell-Side Liquidity)
BSL (Buy-Side Liquidity):
• Cluster of swing highs within ATR proximity
• Stop losses from shorts sit above these highs
• Breaking BSL triggers short covering (fuel for rally)
SSL (Sell-Side Liquidity):
• Cluster of swing lows within ATR proximity
• Stop losses from longs sit below these lows
• Breaking SSL triggers long liquidation (fuel for decline)
Liquidity Pool Mapping:
AMWT continuously scans for and maps liquidity pools:
// Detect swing highs/lows using pivot function
swing_high = ta.pivothigh(high, 5, 5)
swing_low = ta.pivotlow(low, 5, 5)
// Track recent swing points
if not na(swing_high)
bsl_levels.push(swing_high)
if not na(swing_low)
ssl_levels.push(swing_low)
// Display on chart with labels
Confluence Scoring Integration:
When signals fire near identified liquidity events, confluence scoring increases:
• Signal near volume spike: +10% confidence
• Signal after liquidity sweep: +15% confidence
• Signal at BSL/SSL pool: +10% confidence
• Signal aligned with absorption zone: +10% confidence
Why Liquidity Anchoring Matters:
Signals "in a vacuum" have lower probability than signals anchored to institutional activity. A long signal after a liquidity sweep below swing lows has trapped shorts providing fuel. A long signal in the middle of nowhere has no such catalyst.
📊 SIGNAL GRADING SYSTEM
The Quality Problem:
Not all signals are created equal. A signal with 6/6 factors aligned is fundamentally different from a signal with 3/6 factors aligned. Traditional indicators treat them the same. AMWT grades every signal based on confluence.
Confluence Components (100 points total):
1. Bandit Consensus Strength (25 points)
consensus_str = weighted average of agent confidences
score = consensus_str × 25
Example:
Trend Agent: +1 signal, 0.80 confidence, 0.35 weight
Reversion Agent: 0 signal, 0.50 confidence, 0.25 weight
Structure Agent: +1 signal, 0.75 confidence, 0.40 weight
Weighted consensus = (0.80×0.35 + 0×0.25 + 0.75×0.40) / (0.35 + 0.40) = 0.77
Score = 0.77 × 25 = 19.25 points
2. HMM State Confidence (15 points)
score = hmm_confidence × 15
Example:
HMM reports 82% probability of IMPULSE_UP
Score = 0.82 × 15 = 12.3 points
3. Session Quality (15 points)
Session quality varies by time:
• London/NY Overlap: 1.0 (15 points)
• New York Session: 0.95 (14.25 points)
• London Session: 0.70 (10.5 points)
• Asian Session: 0.40 (6 points)
• Off-Hours: 0.30 (4.5 points)
• Weekend: 0.10 (1.5 points)
4. Energy/Participation (10 points)
energy = (realized_vol / avg_vol) × 0.4 + (range / ATR) × 0.35 + (volume / avg_volume) × 0.25
score = min(energy, 1.0) × 10
5. Volume Confirmation (10 points)
if volume > SMA(volume, 20) × 1.5:
score = 10
else if volume > SMA(volume, 20):
score = 5
else:
score = 0
6. Structure Alignment (10 points)
For long signals:
• Bullish structure (HH + HL): 10 points
• Higher low only: 6 points
• Neutral structure: 3 points
• Bearish structure: 0 points
Inverse for short signals
7. Trend Alignment (10 points)
For long signals:
• Price > EMA21 > EMA50: 10 points
• Price > EMA21: 6 points
• Neutral: 3 points
• Against trend: 0 points
8. Entry Trigger Quality (5 points)
• Strong trigger (multiple confirmations): 5 points
• Moderate trigger (single confirmation): 3 points
• Weak trigger (marginal): 1 point
Grade Scale:
Total Score → Grade
85-100 → A+ (Exceptional—all factors aligned)
70-84 → A (Strong—high probability)
55-69 → B (Acceptable—proceed with caution)
Below 55 → C (Marginal—filtered by default)
Grade-Based Signal Brightness:
Signal arrows on the chart have transparency based on grade:
• A+: Full brightness (alpha = 0)
• A: Slight fade (alpha = 15)
• B: Moderate fade (alpha = 35)
• C: Significant fade (alpha = 55)
This visual hierarchy helps traders instantly identify signal quality.
Minimum Grade Filter:
Configurable filter (default: C) sets the minimum grade for signal display:
• Set to "A" for only highest-quality signals
• Set to "B" for moderate selectivity
• Set to "C" for all signals (maximum quantity)
🕐 SESSION INTELLIGENCE
Why Sessions Matter:
Markets behave differently at different times. The London open is fundamentally different from the Asian lunch hour. AMWT incorporates session-aware logic to optimize signal quality.
Session Definitions:
Asian Session (18:00-03:00 ET)
• Characteristics: Lower volatility, range-bound tendency, fewer institutional participants
• Quality Score: 0.40 (40% of peak quality)
• Strategy Implications: Fade extremes, expect ranges, smaller position sizes
• Best For: Mean-reversion setups, accumulation/distribution identification
London Session (03:00-12:00 ET)
• Characteristics: European institutional activity, volatility pickup, trend initiation
• Quality Score: 0.70 (70% of peak quality)
• Strategy Implications: Watch for trend development, breakouts more reliable
• Best For: Initial trend identification, structure breaks
New York Session (08:00-17:00 ET)
• Characteristics: Highest liquidity, US institutional activity, major moves
• Quality Score: 0.95 (95% of peak quality)
• Strategy Implications: Best environment for directional trades
• Best For: Trend continuation, momentum plays
London/NY Overlap (08:00-12:00 ET)
• Characteristics: Peak liquidity, both European and US participants active
• Quality Score: 1.0 (100%—maximum quality)
• Strategy Implications: Highest probability for successful breakouts and trends
• Best For: All signal types—this is prime time
Off-Hours
• Characteristics: Thin liquidity, erratic price action, gaps possible
• Quality Score: 0.30 (30% of peak quality)
• Strategy Implications: Avoid new positions, wider stops if holding
• Best For: Waiting
Smart Weekend Detection:
AMWT properly handles the Sunday evening futures open:
// Traditional (broken):
isWeekend = dayofweek == saturday OR dayofweek == sunday
// AMWT (correct):
anySessionActive = not na(asianTime) or not na(londonTime) or not na(nyTime)
isWeekend = calendarWeekend AND NOT anySessionActive
This ensures Sunday 6pm ET (when futures open) correctly shows "Asian Session" rather than "Weekend."
Session Transition Boosts:
Certain session transitions create trading opportunities:
• Asian → London transition: +15% confidence boost (volatility expansion likely)
• London → Overlap transition: +20% confidence boost (peak liquidity approaching)
• Overlap → NY-only transition: -10% confidence adjustment (liquidity declining)
• Any → Off-Hours transition: Signal suppression recommended
📈 TRADE MANAGEMENT SYSTEM
The Signal Spam Problem:
Many indicators generate signal after signal, creating confusion and overtrading. AMWT implements a complete trade lifecycle management system that prevents signal spam and tracks performance.
Trade Lock Mechanism:
Once a signal fires, the system enters a "trade lock" state:
Trade Lock Duration: Configurable (default 30 bars)
Early Exit Conditions:
• TP3 hit (full target reached)
• Stop Loss hit (trade failed)
• Lock expiration (time-based exit)
During lock:
• No new signals of same type displayed
• Opposite signals can override (reversal)
• Trade status tracked in dashboard
Target Levels:
Each signal generates three profit targets based on ATR:
TP1 (Conservative Target)
• Default: 1.0 × ATR
• Purpose: Quick partial profit, reduce risk
• Action: Take 30-40% off position, move stop to breakeven
TP2 (Standard Target)
• Default: 2.5 × ATR
• Purpose: Main profit target
• Action: Take 40-50% off position, trail stop
TP3 (Extended Target)
• Default: 5.0 × ATR
• Purpose: Runner target for trend days
• Action: Close remaining position or continue trailing
Stop Loss:
• Default: 1.9 × ATR from entry
• Purpose: Define maximum risk
• Placement: Below recent swing low (longs) or above recent swing high (shorts)
Invalidation Level:
Beyond stop loss, AMWT calculates an "invalidation" level where the wave hypothesis dies:
invalidation = entry - (ATR × INVALIDATION_MULT × 1.5)
If price reaches invalidation, the current market interpretation is wrong—not just the trade.
Visual Trade Management:
During active trades, AMWT displays:
• Entry arrow with grade label (▲A+, ▼B, etc.)
• TP1, TP2, TP3 horizontal lines in green
• Stop Loss line in red
• Invalidation line in orange (dashed)
• Progress indicator in dashboard
Persistent Execution Markers:
When targets or stops are hit, permanent markers appear:
• TP hit: Green dot with "TP1"/"TP2"/"TP3" label
• SL hit: Red dot with "SL" label
These persist on the chart for review and statistics.
💰 PERFORMANCE TRACKING & STATISTICS
Tracked Metrics:
• Total Trades: Count of all signals that entered trade lock
• Winning Trades: Signals where at least TP1 was reached before SL
• Losing Trades: Signals where SL was hit before any TP
• Win Rate: Winning / Total × 100%
• Total R Profit: Sum of R-multiples from winning trades
• Total R Loss: Sum of R-multiples from losing trades
• Net R: Total R Profit - Total R Loss
Currency Conversion System:
AMWT can display P&L in multiple formats:
R-Multiple (Default)
• Shows risk-normalized returns
• "Net P&L: +4.2R | 78 trades" means 4.2 times initial risk gained over 78 trades
• Best for comparing across different position sizes
Currency Conversion (USD/EUR/GBP/JPY/INR)
• Converts R-multiples to currency based on:
- Dollar Risk Per Trade (user input)
- Tick Value (user input)
- Selected currency
Example Configuration:
Dollar Risk Per Trade: $100
Display Currency: USD
If Net R = +4.2R
Display: Net P&L: +$420.00 | 78 trades
Ticks
• For futures traders who think in ticks
• Converts based on tick value input
Statistics Reset:
Two reset methods:
1. Toggle Reset
• Turn "Reset Statistics" toggle ON then OFF
• Clears all statistics immediately
2. Date-Based Reset
• Set "Reset After Date" (YYYY-MM-DD format)
• Only trades after this date are counted
• Useful for isolating recent performance
🎨 VISUAL FEATURES
Macro Channel:
Dynamic regression-based channel showing market boundaries:
• Upper/lower bounds calculated from swing pivot linear regression
• Adapts to current market structure
• Shows overall trend direction and potential reversal zones
Chop Boxes:
Semi-transparent overlay during high-chop periods:
• Purple/orange coloring indicates dangerous conditions
• Visual reminder to avoid new positions
Confluence Heat Zones:
Background shading indicating setup quality:
• Darker shading = higher confluence
• Lighter shading = lower confluence
• Helps identify optimal entry timing
EMA Ribbon:
Trend visualization via moving average fill:
• EMA 8/21/50 with gradient fill between
• Green fill when bullish aligned
• Red fill when bearish aligned
• Gray when neutral
Absorption Zone Boxes:
Marks potential accumulation/distribution areas:
• High volume + small body = absorption
• Boxes drawn at these levels
• Often act as support/resistance
Liquidity Pool Lines:
BSL/SSL levels with labels:
• Dashed lines at liquidity clusters
• "BSL" label above swing high clusters
• "SSL" label below swing low clusters
Six Professional Themes:
• Quantum: Deep purples and cyans (default)
• Cyberpunk: Neon pinks and blues
• Professional: Muted grays and greens
• Ocean: Blues and teals
• Matrix: Greens and blacks
• Ember: Oranges and reds
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: Learning the System (Week 1)
Goal: Understand AMWT concepts and dashboard interpretation
Setup:
• Signal Mode: Balanced
• Display: All features enabled
• Grade Filter: C (see all signals)
Actions:
• Paper trade ONLY—no real money
• Observe HMM state transitions throughout the day
• Note when agents agree vs disagree
• Watch chop detection engage and disengage
• Track which grades produce winners vs losers
Key Learning Questions:
• How often do A+ signals win vs B signals? (Should see clear difference)
• Which agent tends to be right in current market? (Check dashboard)
• When does chop detection save you from bad trades?
• How do signals near liquidity events perform vs signals in vacuum?
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to your instrument and timeframe
Signal Mode Testing:
• Run 5 days on Aggressive mode (more signals)
• Run 5 days on Conservative mode (fewer signals)
• Compare: Which produces better risk-adjusted returns?
Grade Filter Testing:
• Track A+ only for 20 signals
• Track A and above for 20 signals
• Track B and above for 20 signals
• Compare win rates and expectancy
Chop Threshold Testing:
• Default (80%): Standard filtering
• Try 70%: More aggressive filtering
• Try 90%: Less filtering
• Which produces best results for your instrument?
Phase 3: Strategy Development (Weeks 3-4)
Goal: Develop personal trading rules based on system signals
Position Sizing by Grade:
• A+ grade: 100% position size
• A grade: 75% position size
• B grade: 50% position size
• C grade: 25% position size (or skip)
Session-Based Rules:
• London/NY Overlap: Take all A/A+ signals
• NY Session: Take all A+ signals, selective on A
• Asian Session: Only A+ signals with extra confirmation
• Off-Hours: No new positions
Chop Zone Rules:
• Chop >70%: Reduce position size 50%
• Chop >80%: No new positions
• Chop <50%: Full position size allowed
Phase 4: Live Micro-Sizing (Month 2)
Goal: Validate paper trading results with minimal risk
Setup:
• 10-20% of intended full position size
• Take ONLY A+ signals initially
• Follow trade management religiously
Tracking:
• Log every trade: Entry, Exit, Grade, HMM State, Chop Level, Agent Consensus
• Calculate: Win rate by grade, by session, by chop level
• Compare to paper trading (should be within 15%)
Red Flags:
• Win rate diverges significantly from paper trading: Execution issues
• Consistent losses during certain sessions: Adjust session rules
• Losses cluster when specific agent dominates: Review that agent's logic
Phase 5: Scaling Up (Months 3-6)
Goal: Gradually increase to full position size
Progression:
• Month 3: 25-40% size (if micro-sizing profitable)
• Month 4: 40-60% size
• Month 5: 60-80% size
• Month 6: 80-100% size
Scale-Up Requirements:
• Minimum 30 trades at current size
• Win rate ≥50%
• Net R positive
• No revenge trading incidents
• Emotional control maintained
💡 DEVELOPMENT INSIGHTS
Why HMM Over Simple Indicators:
Early versions used standard indicators (RSI >70 = overbought, etc.). Win rates hovered at 52-55%. The problem: indicators don't capture state. RSI can stay "overbought" for weeks in a strong trend.
The insight: markets exist in states, and state persistence matters more than indicator levels. Implementing HMM with state transition probabilities increased signal quality significantly. The system now knows not just "RSI is high" but "we're in IMPULSE_UP state with 70% probability of staying in IMPULSE_UP."
The Multi-Agent Evolution:
Original version used a single analytical methodology—trend-following. Performance was inconsistent: great in trends, destroyed in ranges. Added mean-reversion agent: now it was inconsistent the other way.
The breakthrough: use multiple agents and let the system learn which works . Thompson Sampling wasn't the first attempt—tried simple averaging, voting, even hard-coded regime switching. Thompson Sampling won because it's mathematically optimal and automatically adapts without manual regime detection.
Chop Detection Revelation:
Chop detection was added almost as an afterthought. "Let's filter out obviously bad conditions." Testing revealed it was the most impactful single feature. Filtering chop zones reduced losing trades by 35% while only reducing total signals by 20%. The insight: avoiding bad trades matters more than finding good ones.
Liquidity Anchoring Discovery:
Watched hundreds of trades. Noticed pattern: signals that fired after liquidity events (stop runs, volume spikes) had significantly higher win rates than signals in quiet markets. Implemented liquidity detection and anchoring. Win rate on liquidity-anchored signals: 68% vs 52% on non-anchored signals.
The Grade System Impact:
Early system had binary signals (fire or don't fire). Adding grading transformed it. Traders could finally match position size to signal quality. A+ signals deserved full size; C signals deserved caution. Just implementing grade-based sizing improved portfolio Sharpe ratio by 0.3.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What AMWT Is NOT:
• NOT a Holy Grail : No system wins every trade. AMWT improves probability, not certainty.
• NOT Fully Automated : AMWT provides signals and analysis; execution requires human judgment.
• NOT News-Proof : Exogenous shocks (FOMC surprises, geopolitical events) invalidate all technical analysis.
• NOT for Scalping : HMM state estimation needs time to develop. Sub-minute timeframes are not appropriate.
Core Assumptions:
1. Markets Have States : Assumes markets transition between identifiable regimes. Violation: Random walk markets with no regime structure.
2. States Are Inferable : Assumes observable indicators reveal hidden states. Violation: Market manipulation creating false signals.
3. History Informs Future : Assumes past agent performance predicts future performance. Violation: Regime changes that invalidate historical patterns.
4. Liquidity Events Matter : Assumes institutional activity creates predictable patterns. Violation: Markets with no institutional participation.
Performs Best On:
• Liquid Futures : ES, NQ, MNQ, MES, CL, GC
• Major Forex Pairs : EUR/USD, GBP/USD, USD/JPY
• Large-Cap Stocks : AAPL, MSFT, TSLA, NVDA (>$5B market cap)
• Liquid Crypto : BTC, ETH on major exchanges
Performs Poorly On:
• Illiquid Instruments : Low volume stocks, exotic pairs
• Very Low Timeframes : Sub-5-minute charts (noise overwhelms signal)
• Binary Event Days : Earnings, FDA approvals, court rulings
• Manipulated Markets : Penny stocks, low-cap altcoins
Known Weaknesses:
• Warmup Period : HMM needs ~50 bars to initialize properly. Early signals may be unreliable.
• Regime Change Lag : Thompson Sampling adapts over time, not instantly. Sudden regime changes may cause short-term underperformance.
• Complexity : More parameters than simple indicators. Requires understanding to use effectively.
⚠️ RISK DISCLOSURE
Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Adaptive Market Wave Theory, while based on rigorous mathematical frameworks including Hidden Markov Models and multi-armed bandit algorithms, does not guarantee profits and can result in significant losses.
AMWT's methodologies—HMM state estimation, Thompson Sampling agent selection, and confluence-based grading—have theoretical foundations but past performance is not indicative of future results.
Hidden Markov Model assumptions may not hold during:
• Major news events disrupting normal market behavior
• Flash crashes or circuit breaker events
• Low liquidity periods with erratic price action
• Algorithmic manipulation or spoofing
Multi-agent consensus assumes independent analytical perspectives provide edge. Market conditions change. Edges that existed historically can diminish or disappear.
Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively before risking capital. Start with micro position sizing.
Never risk more than you can afford to lose completely. Use proper position sizing. Implement stop losses without exception.
By using this indicator, you acknowledge these risks and accept full responsibility for all trading decisions and outcomes.
"Elliott Wave was a first-order approximation of market phase behavior. AMWT is the second—probabilistic, adaptive, and accountable."
Initial Public Release
Core Engine:
• True Hidden Markov Model with online Baum-Welch learning
• Viterbi algorithm for optimal state sequence decoding
• 6-state market regime classification
Agent System:
• 3-Bandit consensus (Trend, Reversion, Structure)
• Thompson Sampling with true Beta distribution sampling
• Adaptive weight learning based on performance
Signal Generation:
• Quality-based confluence grading (A+/A/B/C)
• Four signal modes (Aggressive/Balanced/Conservative/Institutional)
• Grade-based visual brightness
Chop Detection:
• 5-factor analysis (ADX, Choppiness Index, Range Compression, Channel Position, Volume)
• 7 regime classifications
• Configurable signal suppression threshold
Liquidity:
• Volume spike detection
• Stop run (liquidity sweep) identification
• BSL/SSL pool mapping
• Absorption zone detection
Trade Management:
• Trade lock with configurable duration
• TP1/TP2/TP3 targets
• ATR-based stop loss
• Persistent execution markers
Session Intelligence:
• Asian/London/NY/Overlap detection
• Smart weekend handling (Sunday futures open)
• Session quality scoring
Performance:
• Statistics tracking with reset functionality
• 7 currency display modes
• Win rate and Net R calculation
Visuals:
• Macro channel with linear regression
• Chop boxes
• EMA ribbon
• Liquidity pool lines
• 6 professional themes
Dashboards:
• Main Dashboard: Market State, Consensus, Trade Status, Statistics
📋 AMWT vs AMWT-PRO:
This version includes all core AMWT functionality:
✓ Full Hidden Markov Model state estimation
✓ 3-Bandit Thompson Sampling consensus system
✓ Complete 5-factor chop detection engine
✓ All four signal modes
✓ Full trade management with TP/SL tracking
✓ Main dashboard with complete statistics
✓ All visual features (channels, zones, pools)
✓ Identical signal generation to PRO
✓ Six professional themes
✓ Full alert system
The PRO version adds the AMWT Advisor panel—a secondary dashboard providing:
• Real-time Market Pulse situation assessment
• Agent Matrix visualization (individual agent votes)
• Structure analysis breakdown
• "Watch For" upcoming setups
• Action Command coaching
Both versions generate identical signals . The Advisor provides additional guidance for interpreting those signals.
Taking you to school. - Dskyz, Trade with probability. Trade with consensus. Trade with AMWT.
Volume Level Monitor table Volume Level Monitor table and NQ/ES Futures PRO system
Features:
1. Volume Monitor Table (Top Left)
Level: Shows HIGH/MEDIUM/LOW with color coding
RED = High volume (≥150% of MA)
YELLOW = Medium volume
BLUE = Low volume (≤70% of MA)
vs MA: Current volume as percentage of moving average
Volume: Real-time volume display
MA: 20-period volume moving average
2. Enhanced Volume Calculations
Volume percentage relative to MA
CVD (Cumulative Volume Delta) calculation
Volume level classification with thresholds
4. Additional Volume Alerts
Alert when volume reaches HIGH threshold
Alert when volume drops to LOW threshold
5. Display Control
New toggle: "Show Volume Monitor Table" in Display settings
Can be turned on/off independently
How to Use:
Volume Monitor helps you:
HIGH Volume (Red): Confirms breakouts, strong moves, potential reversals
LOW Volume (Blue): Avoid choppy periods, wait for confirmation
MEDIUM Volume (Yellow): Normal trading conditions
Best Practice:
Combine Volume Monitor with main dashboard signals
Look for HIGH volume on entry signals for best confirmation
Avoid trading during LOW volume periods (reduces false signals)
The two tables work together: Main dashboard for trade signals, Volume Monitor for volume context!
Current & Prior Day OHLC Levels# Current & Prior Day OHLC Levels with 15-Minute Opening Range
## Overview
This comprehensive indicator plots key price levels for futures and stock traders, displaying Current Day levels, Prior Day levels, and the 15-Minute Opening Range. These levels serve as critical support and resistance zones that professional traders monitor throughout the trading session.
## Key Features
### Current Day Levels (Session-Based)
- **Current Open**: The opening price of the current trading session
- **Current High**: The highest price reached during the current session (updates in real-time)
- **Current Low**: The lowest price reached during the current session (updates in real-time)
The indicator properly recognizes **futures trading sessions**, which begin at their respective session start times (not midnight). For example, most equity index futures sessions begin at 6:00 PM ET the previous day, ensuring accurate session-based tracking for overnight and globex trading.
### Prior Day Levels
- **Prior Open**: Opening price from the previous trading session
- **Prior High**: High of the previous trading session
- **Prior Low**: Low of the previous trading session
- **Prior Close**: Closing price from the previous trading session
Prior day levels are some of the most widely watched technical levels in trading, often acting as psychological support and resistance zones where price action tends to react.
### 15-Minute Opening Range (NY Session)
- **OR High**: The high of the first 15 minutes after New York market open (9:30-9:45 AM ET)
- **OR Low**: The low of the first 15 minutes after New York market open (9:30-9:45 AM ET)
The opening range concept is a popular day trading strategy. The first 15 minutes often establishes the tone for the day, with these levels frequently serving as breakout or breakdown points. The indicator tracks these levels in real-time as they form, then locks them in after 9:45 AM ET.
## Visual Design
### Smart Line Extension
- Lines extend **left** to the exact bar that created each level (e.g., the bar that made the high)
- Lines extend **right** by a configurable number of bars (default: 50 bars)
- No infinite line extension cluttering your chart
### Intelligent Label Placement
- Labels positioned **above** highs and opens
- Labels positioned **below** lows
- Adjustable offset to position labels optimally for your timeframe
- Optional price display in labels (e.g., "Current High: 5,950.00")
- Semi-transparent label backgrounds for clean chart appearance
## Customization Options
### Individual Level Controls
Each level (Current Open, High, Low, Prior Open, High, Low, Close, OR High, OR Low) can be:
- Toggled on/off independently
- Assigned a custom color
- Given its own line style (Solid, Dashed, or Dotted)
- Adjusted for line width (1-5 pixels)
### Default Styling
- **Current Day**: Solid lines (Gold for Open, Green for High, Red for Low)
- **Prior Day**: Dashed lines (Steel Blue for Open, Dark Cyan for High, Crimson for Low, Slate Blue for Close)
- **Opening Range**: Dotted lines (Cyan for High, Tomato for Low)
This default styling provides clear visual distinction between level types while remaining professional and easy to read.
### Label Customization
- Toggle all labels on/off
- Show or hide price values in labels
- Adjust label offset (distance from current bar)
- Five label size options: Tiny, Small, Normal, Large, Huge
### Line Extension Control
- Configurable right extension (0-500 bars)
- Adjust based on your chart timeframe and preference
## Best Use Cases
### Futures Traders
The indicator's session-aware design makes it perfect for futures markets, properly handling:
- Electronic trading hours (Globex)
- Session rollovers at 5:00 PM or 6:00 PM ET (depending on contract)
- Overnight price action
### Day Traders
- Use Opening Range levels for breakout/breakdown strategies
- Monitor Current High/Low for intraday trend identification
- Watch Prior Day levels for profit targets and stop placement
### Swing Traders
- Prior Day High/Low often act as key decision points
- Prior Close serves as an important reference level
- Current Day levels help with intraday entry/exit timing
### Multi-Timeframe Analysis
Works on any intraday timeframe:
- 1-minute for scalping
- 5-minute for active day trading
- 15-minute or 30-minute for swing entries
- 1-hour for position context
## Technical Details
### Session Detection
- Uses TradingView's built-in session detection for accurate daily boundaries
- Properly handles futures contracts with non-midnight session starts
- New York timezone detection for Opening Range (9:30 AM ET)
### Real-Time Updates
- Current High and Low update dynamically as price moves
- Opening Range levels update live during the 9:30-9:45 AM window
- Lines redraw on each bar to maintain accurate positioning
### Performance
- Maximum 500 lines and 500 labels to ensure smooth chart performance
- Efficient line/label deletion and recreation on session changes
- Minimal computational overhead
## Tips for Optimal Use
1. **Adjust Line Extension**: For lower timeframes (1-min, 5-min), reduce right extension to 20-30 bars. For higher timeframes (1-hour), increase to 100+ bars.
2. **Combine with Price Action**: These levels work best when combined with candlestick patterns, volume analysis, and order flow.
3. **Watch for Level Tests**: Price often tests these levels multiple times before breaking through or reversing.
4. **Opening Range Breakouts**: Many traders wait for price to break and close above OR High or below OR Low before entering directional trades.
5. **Prior Day Levels as Targets**: Use Prior High as an upside target and Prior Low as a downside target for intraday trades.
## Compatibility
- Works on all instruments (Futures, Stocks, Forex, Crypto)
- Optimized for intraday timeframes (1-min to 1-hour)
- Best results on liquid instruments with clear session boundaries
- Designed specifically with ES, NQ, YM, and RTY futures traders in mind
## Credits
Ported from NinjaTrader indicators with enhanced features and TradingView-specific optimizations. Original concept based on classic technical analysis principles used by professional traders worldwide.
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*Note: These levels are for informational and educational purposes only. Past performance does not guarantee future results. Always practice proper risk management.*
CAP - CSI [Auto-MTF]The CAP - CSI is a Digital Signal Processing (DSP) tool based on the principles of Lars von Thienen’s "Dynamic Cycles." While traditional oscillators often fail in trending markets by staying "pinned" at extremes, the CSI uses a recursive dual-thrust processor to isolate the underlying market rhythm, helping traders identify when a cycle is genuinely exhausted.
Core Methodology
This script implements a Cycle Swing Momentum processor. It calculates the difference between short-term and long-term "thrusts" to extract the dominant cycle from price action. Unlike static indicators, it uses Dynamic Percentile Banding to adapt its overbought and oversold levels based on the market's recent "cyclic memory."
Key Features
Pivot Point Detection: Identifies exhaustion when the CSI extends outside its dynamic bands and begins to pivot back toward the mean.
Trend-Aware Coloring: The area fill uses slope-based logic to differentiate between "Rising/Falling" momentum and "Bullish/Bearish" strong zones.
HTF (5x): Built-in logic to define the larger cycle trend. I recommend using a 5x multiplier (e.g., viewing 4H cycles on a 1H chart) to ensure you are trading with the macro flow.
Zero Line Equilibrium: Clear visualization of the cycle's position relative to its center-point to determine the current market regime.
The "Trending" Challenge
A common pitfall with DSP-based cycle tools is that they can generate "phantom" signals during powerful, linear trending conditions. This script is my attempt to solve that by integrating HTF confluence and slope-based filtering. It is specifically optimized for:
Futures: ES, NQ, RTY, and GC.
US Equities: (NVDA, TSLA, etc.).
Additional tip, search for Strong relative strength Symbols, I've created this script : CAP - Mansfield Relative Strength, but there are many there "Mansfield Relative Strength" indicators available.
Why I am sharing this
This is an ongoing project. I am releasing this to the public to connect with other traders interested in Lars von Thienen’s work or John Ehlers’ DSP techniques. My goal is to collaborate with the community to refine the processor further and build a consistent, profitable system that can distinguish between a cycle turn and a trend continuation.
PEAKPROFIT MARKOUTThe PeakProfit indicator is a price-action–based day trading system designed to help traders identify high-probability entries, clear bias, and key reaction zones during the trading session.
It focuses on:
Market structure & trend direction
Key liquidity and institutional levels
High-confidence entry confirmations
Clean risk-to-reward trade setups
The indicator removes noise from the chart and highlights where smart money is most likely active, allowing traders to stop guessing and start executing with confidence. It works best for day trading ES, NQ, and major indices, but can be applied to any liquid market.
Built for traders who want clarity, discipline, and consistency, not random signals.
CAP - CSICSI is a Digital Signal Processing (DSP) tool based on the principles of Lars von Thienen’s "Dynamic Cycles." Unlike traditional momentum oscillators, the CSI uses a recursive dual-thrust processor to isolate cyclic price action, helping traders identify hidden rhythms in the market rather than just static overbought or oversold levels.
How to Read the Indicator
This script focuses on four primary technical components:
Dynamic Band Pivots: The indicator calculates a "cyclic memory" (default 34 periods) to create high and low bands. When the CSI moves outside these bands and begins to pivot, it signals a potential cycle exhaustion point.
Momentum Slope: The color-coded area fill identifies the direction of the cycle's slope. A change in slope is often the first warning of a cycle peak or trough.
The Zero Line: The zero line acts as the "equilibrium" point. Position relative to zero helps define whether the current cycle is in a bullish or bearish regime.
Multi-Timeframe Analysis (HTF): The script includes an HTF filter (suggested 5x the chart timeframe) to ensure you are trading in the direction of the dominant macro cycle.
Performance & Testing: The "Trending" Challenge
This indicator has been developed and tested primarily on Futures (ES, NQ, RTY) and US Equities.
Important Note on False Signals: While the CSI "nails" turning points during standard cyclic/swing conditions, users should be aware of "phantom" cycles or false signals during strong trending conditions. In a powerful trend, the indicator may signal a cycle peak while price continues to move linearly, leading to premature exhaustion signals. Filtering these "trend-drifts" is the current focus of development.
Community & Collaboration
This script is an ongoing project. I am making it public to find like-minded traders interested in Lars von Thienen’s work to:
Refine the processor logic for better signal-to-noise ratios during impulsive trends.
Discuss the best "Trend Shields" (Volume, HTF, or Volatility filters) to stay in winners longer.
Share specific settings for different asset classes in the Futures and Equity markets.
EvilAI | Survival SizerPosition sizing that adapts to market conditions. Define how many losses you can survive — the indicator calculates optimal size using ATR and volatility regime detection.
█ FEATURES
- Survival-based sizing — set losses to endure, not arbitrary risk %
- Volatility-adjusted positions:
└─ LOW vol: Size ↑ (be aggressive when markets are calm)
└─ NORMAL: Baseline sizing
└─ HIGH vol: Size ↓ (get defensive when chaos rises)
└─ EXTREME: Size ↓↓ (protect capital at all costs)
- ATR + Historical Volatility combined for regime detection
- Auto contract selection (GC/MGC, NQ/MNQ)
- Color-coded risk warnings
█ DESIGNED FOR
Prop firm traders (FundedNext, Topstep, Apex) who need adaptive risk management. When volatility spikes, you automatically size down. When markets are calm, you can push harder. All while respecting your survival floor.
█ HOW IT WORKS
1. Set your daily drawdown limit ($2,000)
2. Set target survivable losses (10)
3. Indicator calculates: $2,000 ÷ 10 = $200 max risk per trade
4. ATR determines stop distance → position size
5. Volatility regime adjusts final size up or down
6. Auto mode selects micro vs full contracts
█ DISPLAY
- Compact mode: Contracts, risk, survival count, vol regime
- Full mode: Complete breakdown with percentiles
- Survival shows actual vs target (e.g., "12L / 10L")
█ COLOR CODES
- Green: Meeting or exceeding survival target
- Yellow: Close to target / capped at max
- Cyan: Boosted (low volatility)
- Purple: Reduced (high volatility)
- Red: Below target — reconsider your sizing
Stop blowing accounts. Size positions properly.
Trend Speed Analyzer with Entries (Zeiierman)📈 Trend Speed Analyzer with Entry Signals (Zeiierman – Modified)
🔹 Overview
This indicator is a trend-following momentum system built around an adaptive (dynamic) moving average and a proprietary trend speed / wave strength engine.
It is designed to identify high-quality continuation entries after price confirms direction, not to predict tops or bottoms.
Best suited for:
Index futures (ES, NQ)
ETFs (SPY, QQQ)
Strongly trending stocks
Intraday or swing trading
🔹 Core Concepts
1️⃣ Dynamic Trend Line (Adaptive EMA)
Instead of using a fixed EMA length, this script dynamically adjusts:
EMA length based on normalized price movement
EMA responsiveness using an accelerator factor
Result:
Fast reaction during strong trends
Smooth behavior during choppy markets
Fewer false flips compared to traditional EMAs
This trend line acts as the primary regime filter.
2️⃣ Trend Speed & Wave Analysis
The indicator tracks trend speed, which represents cumulative directional pressure over time.
It also records:
Bullish wave sizes
Bearish wave sizes
Average vs maximum wave strength
Bull/Bear dominance
These statistics are displayed in an optional table to help assess:
Market bias
Momentum asymmetry
Whether the current move is weak, average, or exceptional
🔹 Entry Signal Logic (One Signal per Trend Shift)
Signals are not spammy.
Only one entry signal is allowed per crossover.
Long Entry Conditions
A long signal is generated when:
Price crosses above the dynamic trend line
A bullish candle forms
The candle body is at least X% of ATR (filters weak/doji candles)
The entire candle body is above the trend line
(Optional) Trend speed is positive
Short Entry Conditions
A short signal is generated when:
Price crosses below the dynamic trend line
A bearish candle forms
The candle body is at least X% of ATR
The entire candle body is below the trend line
(Optional) Trend speed is negative
📌 Once a signal fires, no additional signals will appear until a new crossover occurs.
🔹 What this indicator is NOT
❌ Not a mean-reversion system
❌ Not a prediction tool
❌ Not meant for sideways markets
This tool assumes structure → confirmation → continuation.
🔹 How to Trade It (Suggested Use)
Use higher timeframes (5m–30m) for cleaner signals
Trade in the direction of higher-timeframe bias
Combine with:
VWAP
Key levels (PDH / PDL / PMH / PML)
Market session context
🔹 Customization
Adjust Maximum Length for smoother vs faster trends
Adjust Accelerator Multiplier for sensitivity
Enable/disable speed filter for stricter momentum confirmation
ATR candle filter removes weak signals automatically
⚠️ Disclaimer
This indicator provides technical signals only and does not include trade management, stops, or targets.
Always apply proper risk management.
Jake's Candle by Candle UpgradedJake's Candle by Candle Upgraded
The "Story of the Market" Automated
This is not just another signal indicator. Jake's Candle by Candle Upgraded is a complete institutional trading framework designed for high-precision scalping on the 1-minute and 5-minute timeframes.
Built strictly on the principles of Al Brooks Price Action and Smart Money Concepts (SMC), this tool automates the rigorous "Candle-by-Candle" analysis used by professional floor traders. It moves beyond simple pattern recognition to read the "Story" of the market—Context, Setup, and Pressure—before ever allowing a trade.
The Philosophy: Why This Tool Was Built
Most retail traders fail for two reasons:
Getting Trapped: They enter on the first sign of a reversal (H1/L1), which is often an institutional trap.
Trading Chop: They bleed capital during low-volume, sideways markets.
This tool solves both problems with an Algorithmic Discipline Engine. It does not guess. It waits for the specific "Second Leg" criteria used by institutions and physically disables itself during dangerous market conditions.
Key Features
1. The Context Dashboard (HUD)
A professional Heads-Up Display in the top-right corner keeps you focused on the macro picture while you scalp.
FLOW: Monitors the 20-period Institutional EMA. (Green = Bull Flow, Red = Bear Flow). You are prevented from trading against the dominant trend.
STATE: A built-in "Volatility Compressor." If it says "⚠️ CHOP / RANGE", the algorithm is disabled. It protects you from overtrading during lunch hours or low-volume zones.
SETUP: Live tracking of the Al Brooks leg count. It tells you exactly when the algorithm is "Waiting for Pullback" or "Searching for Entry."
2. Smart "Trap Avoidance" Logic (H2/L2)
This tool uses the "Gold Standard" of scalping setups: The High 2 (H2) and Low 2 (L2).
It ignores the first breakout attempt (Leg 1), acknowledging it as a potential trap.
It waits for the pullback and only signals on the Second Leg, statistically increasing the probability of a successful trend resumption.
3. Volatility-Adaptive Risk Management
Stop calculating pips in your head. The moment a signal is valid, the tool draws your business plan on the chart:
Stop Loss (Red Line): Automatically placed behind the "Signal Bar" (the candle that created the setup) based on strict price action rules.
Take Profit (Green Line): Automatically projected at a 1.5 Risk-to-Reward Ratio.
Smart Adaptation: The targets expand and contract based on real-time market volatility. If the market is quiet, targets are tighter. If explosive, targets are wider.
4. The "Snap Entry" Signal
The BUY and SELL badges are not lagging. They are programmed with "Stop Entry" logic—appearing the exact moment price breaks the structure of the Signal Bar, ensuring you enter on momentum, not hope.
How to Trade Strategy
Check the HUD: Ensure FLOW matches your direction and STATE says "✅ VOLATILE".
Wait for the Badge: Do not front-run the tool. Wait for the BUY or SELL badge to print.
Set Your Orders: Once the signal candle closes:
Place your Stop Loss at the Red Line.
Place your Take Profit at the Green Line.
Walk Away: The trade is now a probability event. Let the math play out.
Technical Specifications
Engine: Pine Script v6 (Strict Compliance).
Best Timeframes: 1m, 5m.
Best Assets: Indices (NQ, ES), Gold (XAUUSD), and high-volume Crypto (BTC, ETH).
NY Opening Range [LuckyAlgo]
This custom ORM (Opening Range Move) indicator is designed as a tool for traders who focus not just on where a range is, but on the magnitude of the expansion following the initial morning volatility.
Here is a summary of the indicator and how it differentiates itself from standard Opening Range Breakout (ORB) tools.
Indicator Summary
The script captures the high and low of the market during the first 30 minutes of the NY session (09:30–10:00 AM EST). Once this range is set, it tracks the "Expansion Move" - the point distance from the range's boundary to the current session's high or low. It visualizes this through color-coded zones, dynamic labels at the session extremes, and a statistical table that benchmarks today's volatility against the recent past.
What specific questions does this indicator answer?
While most indicators tell you "the range is broken," this indicator answers quantitative questions vital for trade management:
1. "How far has the market stretched relative to the breakout?"
The indicator provides the exact point distance (+/-) from the range high/low. This helps you determine if the move is just beginning or if it has already extended significantly.
2. "Is the current move 'normal' or an outlier?"
By using the Stats Table, you can see if the current 40-point move on NQ is typical or if the average move over the last 10 days is actually 80 points. This prevents you from "fading" a move that still has average room to grow, or taking a "pro-trend" trade when the market is already exhausted.
3. "Where is the session extreme located?"
The inclusion of the dashed High of Day (HOD) and Low of Day (LOD) lines with attached labels tells you exactly where the "Move" calculation is peaking. If the HOD line hasn't moved for two hours, you know the bullish expansion has stalled.
4. "When is the data no longer relevant?"
Because of the 17:00 EST reset logic, the indicator answers the "end of day" question for futures traders. It stops measuring at the settlement/close of the electronic session, ensuring your charts are clean for the overnight (Globex) session or ready for the next morning.
Technical Advantage
Most scripts use a single "point in time" to reset. This script uses a Trading Window logic, which is much more robust. If a bar is missing at exactly 17:00 due to low volume or a data glitch, the indicator won't "break" or keep drawing old lines - it understands the entire window of time it is allowed to exist in.
Credit to @LuxAlgo for his initial Opening Range Breakout indicator used as a base to develop this version.
Opening Range BoxOPENING RANGE BOX + LEVELS (RTH)
OVERVIEW
This indicator draws the Opening Range for the U.S. Regular Trading Hours session starting at 9:30 AM New York time. It plots the Opening Range High, Low, and Midpoint, and can extend those levels for the rest of the session. It also displays the Opening Range size in points and ticks.
WHAT IT DRAWS
• Opening Range box for the first N minutes of RTH (ex: 5, 10, 15)
• OR High (ORH)
• OR Low (ORL)
• OR Midline (midpoint of ORH/ORL)
• Opening Range value label (range in points + ticks)
KEY FEATURES
• Time-anchored drawings (bar_time) so levels stay accurate on any intraday timeframe
• Configurable Opening Range length in minutes
• Configurable box fill/border colors
• Independent styling for OR High / OR Low / Midline (color, width, line style)
• Line extension modes:
Line extension modes
- To RTH Close
- Right Forever
- For N Minutes
- None
Optional label placement to the LEFT of the Opening Range so it doesn’t block new candles
Option to keep previous sessions’ Opening Ranges visible for context
BEST FOR
• Futures: ES / NQ / MNQ (and other RTH-based products)
• Intraday stocks and ETFs
• OR breakout, rejection/fade, and mean reversion workflows
NOTES
• Intended for intraday charts
• Opening Range is calculated strictly inside the selected time window (no extra bars)
• Session is America/New_York, 09:30–16:00
