Auto Fibo Pivot [Ultimate MTF]Stocks: Locks lines during market hours (09:00-15:30) and switches to "Preview Mode" (Next Day) after market close.
Forex/Crypto: Always Fixed Mode (24h).
Multi-Timeframe (MTF): Select between Auto Daily, Weekly, Monthly, or Yearly pivots.
Fully Customizable: Easily change Fibonacci ratios and colors in the settings.
No Repaint: Stable lines on 1-minute charts.
自動判別・マルチタイムフレーム対応のフィボナッチピボット
株・為替を自動判別し、最適なモードで動作する実戦向けインジケーターです。
主な機能:
自動判別機能:
日本株: ザラ場中はラインを完全固定。15:30以降は自動で「明日の予習モード」に切り替わります。
為替・仮想通貨: 24時間常時固定モードで動作します。
Cari dalam skrip untuk "forex"
Institutional Confluence Mapper [JOAT]Institutional Confluence Mapper (ICM)
Introduction
The Institutional Confluence Mapper is an open-source multi-factor analysis tool that combines five analytical modules into a unified confluence scoring system. It synthesizes institutional trading concepts including Relative Rotation analysis, Smart Money flow detection, Liquidity zone mapping, Session-based timing, and Volatility regime classification.
Rather than relying on a single indicator, ICM evaluates market conditions through multiple lenses simultaneously, presenting a clear confluence score (0-100%) that reflects the alignment of various market factors.
This script is fully open-source under the Mozilla Public License 2.0.
Originality and Purpose
This indicator is NOT a random mashup of existing indicators. It is an original implementation that creates a unified institutional analysis framework:
Why Multiple Modules? Most retail traders struggle because they rely on single indicators that provide conflicting signals. Institutional traders evaluate markets through multiple frameworks simultaneously. ICM bridges this gap by providing a unified view of complementary analysis methods.
The Confluence Scoring System: Each module contributes to a weighted confluence score (0-100%). Scores above 65% indicate bullish confluence; below 35% indicates bearish confluence.
How Components Work Together:
RRG (Relative Rotation) determines macro bias - is this asset outperforming or underperforming its benchmark?
Institutional Flow confirms smart money activity - are institutions accumulating or distributing?
Volatility Regime determines strategy selection - trend-follow or mean-revert?
Liquidity Detection identifies key levels - where are the stop hunts happening?
Session Analysis optimizes timing - when should you trade?
The Five Core Modules
1. Relative Rotation Momentum Matrix (RRG)
Compares the current symbol against a benchmark (default: SPY) using the JdK RS-Ratio methodology with double-smoothed EMA. Assets rotate through four quadrants:
LEADING: Outperforming with positive momentum (strongest bullish)
WEAKENING: Outperforming but losing momentum
LAGGING: Underperforming with negative momentum (strongest bearish)
IMPROVING: Underperforming but gaining momentum
2. Institutional Flow Analysis
Analyzes volume patterns to detect smart money activity:
Volume Z-Score measures how unusual current volume is
Buy/Sell pressure estimation based on candle structure
Unusual volume detection highlights institutional activity
3. Volatility Regime System
Uses ATR percentile ranking to classify market conditions:
COMPRESSION: Low volatility (ATR < 20th percentile) - potential breakout
EXPANSION: High volatility (ATR > 80th percentile) - trending
TRENDING_BULL/BEAR: Directional trends based on EMA alignment
RANGING: Sideways consolidation
4. Liquidity Detection
Identifies institutional liquidity targets using swing point analysis:
Swing highs/lows are tracked and displayed as dashed lines
Purple dashed lines mark resistance/sell-side liquidity
Teal dashed lines mark support/buy-side liquidity
Gold diamonds appear when liquidity sweeps are detected (potential reversals)
5. Session Momentum Profiler
Tracks trading sessions based on your selected timezone:
Asian Session: 7PM - 4AM EST
London Session: 3AM - 12PM EST
New York Session: 9:30AM - 4PM EST
London/NY Overlap: 8AM - 12PM EST (peak liquidity)
Visual Elements
Main Dashboard (Top-Right):
BIAS: Overall direction with confluence percentage
RRG: Current quadrant and momentum
FLOW: Smart money bias and volume status
REGIME: Market condition and volatility percentile
SESSION: Active trading session and current time
LIQUIDITY: Active zones and grab signals
SIGNAL: Actionable recommendation
Chart Elements:
Gold Diamond: Liquidity grab (potential reversal point)
Teal Dashed Line: Support / Buy-side liquidity zone
Purple Dashed Line: Resistance / Sell-side liquidity zone
EMA 21/55/200: Trend structure with cloud fill
Volatility Bands: ATR-based channels
How to Use
Step 1: Check the BIAS row for overall market direction
Step 2: Check REGIME to understand market conditions
Step 3: Identify key levels using liquidity zones and EMAs
Step 4: Wait for confluence above 65% (bullish) or below 35% (bearish)
Step 5: Look for gold diamond signals at key levels
Best Setups
Bullish: Confluence >65%, RRG in LEADING/IMPROVING, bullish flow, price near teal support zone.
Bearish: Confluence <35%, RRG in LAGGING/WEAKENING, bearish flow, price near purple resistance zone.
Reversal: Gold diamond appears after price sweeps a liquidity zone.
Key Input Parameters
Benchmark Symbol: Compare against (default: SPY)
RS-Ratio/Momentum Lookback: RRG calculation periods
Volume Analysis Period: Flow detection lookback
Swing Length: Liquidity zone detection
ATR Period/Rank Period: Regime classification
Timezone: Session detection timezone
Alerts
Liquidity Grab Bull: Bullish sweep detected
Liquidity Grab Bear: Bearish sweep detected
High Confluence Bull: Confluence above 70%
High Confluence Bear: Confluence below 30%
Best Practices
Use on 1H, 4H, or Daily timeframes for reliable signals
Combine with price action for confirmation
Respect the regime - don't fight strong trends
Trade during London/NY overlap for best liquidity
Wait for high confluence scores before entering
Always use proper risk management
Limitations
Works best on liquid markets with sufficient volume
Session features optimized for forex/crypto markets
RRG requires a valid benchmark symbol
No indicator predicts the future - use proper risk management
Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Past performance does not guarantee future results.
-Made with passion by officialjackofalltrades
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.
Global Sovereign Spread MonitorIn the summer of 2011, the yield on Italian government bonds rose dramatically while German Bund yields fell to historic lows. This divergence, measured as the BTP-Bund spread, reached nearly 550 basis points in November of that year, signaling what would become the most severe test of the European monetary union since its inception. Portfolio managers who monitored this spread had days, sometimes weeks, of advance warning before equity markets crashed. Those who ignored it suffered significant losses.
The Global Sovereign Spread Monitor is built on a simple but powerful observation that has been validated repeatedly in academic literature: sovereign bond spreads contain forward-looking information about systemic risk that is not fully reflected in equity prices (Longstaff et al., 2011). When investors demand higher yields to hold peripheral government debt relative to safe-haven bonds, they are expressing a view about credit risk, liquidity conditions, and the probability of systemic stress. This information, when properly analyzed, provides actionable signals for traders across all asset classes.
The Science of Sovereign Spreads
The academic study of government bond yield differentials began in earnest following the creation of the European Monetary Union. Codogno, Favero and Missale (2003) published what remains one of the foundational papers in this field, examining why yields on government bonds within a currency union should differ at all. Their analysis, published in Economic Policy, identified two primary drivers: credit risk and liquidity. Countries with higher debt-to-GDP ratios and weaker fiscal positions commanded higher yields, but importantly, these spreads widened dramatically during periods of market stress even when fundamentals had not changed significantly.
This observation led to a crucial insight that Favero, Pagano and von Thadden (2010) explored in depth in the Journal of Financial and Quantitative Analysis. They found that liquidity effects can amplify credit risk during stress periods, creating a feedback loop where rising spreads reduce liquidity, which in turn pushes spreads even higher. This dynamic explains why sovereign spreads often move in non-linear fashion, remaining stable for extended periods before suddenly widening rapidly.
Longstaff, Pan, Pedersen and Singleton (2011) extended this research in their American Economic Review paper by examining the relationship between sovereign credit default swap spreads and bond spreads across multiple countries. Their key finding was that a significant portion of sovereign credit risk is driven by global factors rather than country-specific fundamentals. This means that when spreads widen in Italy, it often reflects broader risk aversion that will eventually affect other asset classes including equities and corporate bonds.
The practical implication of this research is clear: sovereign spreads function as a leading indicator for systemic risk. Aizenman, Hutchison and Jinjarak (2013) confirmed this in their analysis of European sovereign debt default probabilities, finding that spread movements preceded rating downgrades and provided earlier warning signals than traditional fundamental analysis.
How the Indicator Works
The Global Sovereign Spread Monitor translates these academic findings into a systematic framework for monitoring credit conditions. The indicator calculates yield differentials between peripheral government bonds and German Bunds, which serve as the benchmark safe-haven asset in European markets. Italian ten-year yields minus German ten-year yields produce the BTP-Bund spread, the single most important metric for Eurozone stress. Spanish yields minus German yields produce the Bonos-Bund spread, providing a secondary confirmation signal. The transatlantic US-Bund spread captures divergence between the two major safe-haven markets.
Raw spreads are converted to Z-scores, which measure how many standard deviations the current spread is from its historical average over the lookback period. This normalization is essential because absolute spread levels vary over time with interest rate cycles and structural changes in sovereign debt markets. A spread of 150 basis points might have been concerning in 2007 but entirely normal in 2023 following the European debt crisis and subsequent ECB interventions.
The composite index combines these individual Z-scores using weights that reflect the relative importance of each spread for global risk assessment. Italy receives the highest weight because it represents the third-largest sovereign bond market globally and any Italian debt crisis would have systemic implications for the entire Eurozone. Spain provides confirmation of peripheral stress, while the US-Bund spread captures flight-to-quality dynamics between the two primary safe-haven markets.
Regime classification transforms the continuous Z-score into discrete states that correspond to different market environments. The Stress regime indicates that spreads have widened to levels historically associated with crisis periods. The Elevated regime signals rising risk aversion that warrants increased attention. Normal conditions represent typical spread behavior, while the Calm regime may actually signal complacency and potential mean-reversion opportunities.
Retail Trader Applications
For individual traders without access to institutional research teams, the Global Sovereign Spread Monitor provides a window into the macro environment that typically remains opaque. The most immediate application is risk management for equity positions.
Consider a trader holding a diversified portfolio of European stocks. When the composite Z-score rises above 1.0 and enters the Elevated regime, historical data suggests an increased probability of equity market drawdowns in the coming days to weeks. This does not mean the trader must immediately liquidate all positions, but it does suggest reducing position sizes, tightening stop-losses, or adding hedges such as put options or inverse ETFs.
The BTP-Bund spread specifically provides actionable information for anyone trading EUR/USD or European equity indices. Research by De Grauwe and Ji (2013) demonstrated that sovereign spreads and currency movements are closely linked during stress periods. When the BTP-Bund spread widens sharply, the Euro typically weakens against the Dollar as investors question the sustainability of the monetary union. A retail forex trader can use the indicator to time entries into EUR/USD short positions or to exit long positions before spread-driven selloffs occur.
The regime classification system simplifies decision-making for traders who cannot constantly monitor multiple data feeds. When the dashboard displays Stress, it is time to adopt a defensive posture regardless of what individual stock charts might suggest. When it displays Calm, the trader knows that risk appetite is elevated across institutional markets, which typically supports equity prices but also means that any negative catalyst could trigger a sharp reversal.
Mean-reversion signals provide opportunities for more active traders. When spreads reach extreme levels in either direction, they tend to revert toward their historical average. A Z-score above 2.0 that begins declining suggests professional investors are starting to buy peripheral debt again, which historically precedes broader risk-on behavior. A Z-score below minus 1.0 that starts rising may indicate that complacency is ending and risk-off positioning is beginning.
The key for retail traders is to use the indicator as a filter rather than a primary signal generator. If technical analysis suggests a long entry in European stocks, check the sovereign spread regime first. If spreads are elevated or rising, the technical setup becomes higher risk. If spreads are stable or compressing, the technical signal has a higher probability of success.
Professional Applications
Institutional investors use sovereign spread analysis in more sophisticated ways that go beyond simple risk filtering. Systematic macro funds incorporate spread data into quantitative models that generate trading signals across multiple asset classes simultaneously.
Portfolio managers at large asset allocators use sovereign spreads to make strategic allocation decisions. When the composite Z-score trends higher over several weeks, they reduce exposure to peripheral European equities and bonds while increasing allocations to German Bunds, US Treasuries, and other safe-haven assets. This rotation often happens before explicit risk-off signals appear in equity markets, giving these investors a performance advantage.
Fixed income specialists at banks and hedge funds use sovereign spreads for relative value trades. When the BTP-Bund spread widens to historically elevated levels but fundamentals have not deteriorated proportionally, they may go long Italian government bonds and short German Bunds, betting on mean reversion. These trades require careful risk management because spreads can widen further before reversing, but when properly sized they offer attractive risk-adjusted returns.
Risk managers at financial institutions use sovereign spread monitoring as an input to Value-at-Risk models and stress testing frameworks. Elevated spreads indicate higher correlation among risk assets, which means diversification benefits are reduced precisely when they are needed most. This information feeds into position sizing decisions across the entire trading book.
Currency traders at proprietary trading firms incorporate sovereign spreads into their EUR/USD and EUR/CHF models. The relationship between the BTP-Bund spread and EUR weakness is well-documented in academic literature and provides a systematic edge when combined with other factors such as interest rate differentials and positioning data.
Central bank watchers use sovereign spreads to anticipate policy responses. The European Central Bank has demonstrated repeatedly that it will intervene when spreads reach levels that threaten financial stability, most notably through the Outright Monetary Transactions program announced in 2012 and the Transmission Protection Instrument introduced in 2022. Understanding spread dynamics helps investors anticipate these interventions and position accordingly.
Interpreting the Dashboard
The statistics panel provides real-time information that supports both quick assessments and deeper analysis. The composite Z-score is the primary metric, representing the weighted average of all spread Z-scores. Values above zero indicate spreads are wider than their historical average, while values below zero indicate compression. The magnitude matters: a reading of 0.5 suggests modestly elevated stress, while 2.0 or higher indicates conditions similar to historical crisis periods.
The regime classification translates the Z-score into actionable categories. Stress should trigger immediate review of risk exposure and consideration of hedges. Elevated warrants increased vigilance and potentially reduced position sizes. Normal indicates no immediate concerns from sovereign markets. Calm suggests risk appetite may be elevated, which supports risk assets but also creates potential for sharp reversals if sentiment changes.
The percentile ranking provides historical context by showing where the current Z-score falls within its distribution over the lookback period. A reading of 90 percent means spreads are wider than they have been 90 percent of the time over the past year, which is significant even if the absolute Z-score is not extreme. This metric helps identify when spreads are creeping higher before they reach official stress thresholds.
Momentum indicates whether spreads are widening or compressing. Rising momentum during elevated spread conditions is particularly concerning because it suggests stress is accelerating. Falling momentum during stress suggests the worst may be past and mean reversion could be beginning.
Individual spread readings allow traders to identify which component is driving the composite signal. If the BTP-Bund spread is elevated but Bonos-Bund remains normal, the stress may be Italy-specific rather than systemic. If all spreads are widening together, the signal reflects broader flight-to-quality that affects all risk assets.
The bias indicator provides a simple summary for traders who need quick guidance. Risk-Off means spreads indicate defensive positioning is appropriate. Risk-On means spread conditions support risk-taking. Neutral means spreads provide no clear directional signal.
Limitations and Risk Factors
No indicator provides perfect signals, and sovereign spread analysis has specific limitations that users must understand. The European Central Bank has demonstrated its willingness to intervene in sovereign bond markets when spreads threaten financial stability. The Transmission Protection Instrument announced in 2022 specifically targets situations where spreads widen beyond levels justified by fundamentals. This creates a floor under peripheral bond prices and means that extremely elevated spreads may not persist as long as historical patterns would suggest.
Political events can cause sudden spread movements that are impossible to anticipate. Elections, government formation crises, and policy announcements can move spreads by 50 basis points or more in a single session. The indicator will reflect these moves but cannot predict them.
Liquidity conditions in sovereign bond markets can temporarily distort spread readings, particularly around quarter-end and year-end when banks adjust their balance sheets. These technical factors can cause spread widening or compression that does not reflect fundamental credit risk.
The relationship between sovereign spreads and other asset classes is not constant over time. During some periods, spread movements lead equity moves by several days. During others, both markets move simultaneously. The indicator provides valuable information about credit conditions, but users should not expect mechanical relationships between spread signals and subsequent price moves in other markets.
Conclusion
The Global Sovereign Spread Monitor represents a systematic application of academic research on sovereign credit risk to practical trading decisions. The indicator monitors yield differentials between peripheral and safe-haven government bonds, normalizes these spreads using statistical methods, and classifies market conditions into regimes that correspond to different risk environments.
For retail traders, the indicator provides risk management information that was previously available only to institutional investors with access to Bloomberg terminals and dedicated research teams. By checking the sovereign spread regime before executing trades, individual investors can avoid taking excessive risk during periods of elevated credit stress.
For professional investors, the indicator offers a standardized framework for monitoring sovereign credit conditions that can be integrated into broader macro models and risk management systems. The real-time calculation of Z-scores, regime classifications, and component spreads provides the inputs needed for systematic trading strategies.
The academic foundation is robust, built on peer-reviewed research published in top finance and economics journals over the past two decades. The practical applications have been validated through multiple market cycles including the European debt crisis of 2011-2012, the COVID-19 shock of 2020, and the rate normalization stress of 2022.
Sovereign spreads will continue to provide valuable forward-looking information about systemic risk for as long as credit conditions vary across countries and investors respond rationally to changes in default probabilities. The Global Sovereign Spread Monitor makes this information accessible and actionable for traders at all levels of sophistication.
References
Aizenman, J., Hutchison, M. and Jinjarak, Y. (2013) What is the Risk of European Sovereign Debt Defaults? Fiscal Space, CDS Spreads and Market Pricing of Risk. Journal of International Money and Finance, 34, pp. 37-59.
Codogno, L., Favero, C. and Missale, A. (2003) Yield Spreads on EMU Government Bonds. Economic Policy, 18(37), pp. 503-532.
De Grauwe, P. and Ji, Y. (2013) Self-Fulfilling Crises in the Eurozone: An Empirical Test. Journal of International Money and Finance, 34, pp. 15-36.
Favero, C., Pagano, M. and von Thadden, E.L. (2010) How Does Liquidity Affect Government Bond Yields? Journal of Financial and Quantitative Analysis, 45(1), pp. 107-134.
Longstaff, F.A., Pan, J., Pedersen, L.H. and Singleton, K.J. (2011) How Sovereign Is Sovereign Credit Risk? American Economic Review, 101(6), pp. 2191-2212.
Manganelli, S. and Wolswijk, G. (2009) What Drives Spreads in the Euro Area Government Bond Market? Economic Policy, 24(58), pp. 191-240.
Arghyrou, M.G. and Kontonikas, A. (2012) The EMU Sovereign-Debt Crisis: Fundamentals, Expectations and Contagion. Journal of International Financial Markets, Institutions and Money, 22(4), pp. 658-677.
Advanced Momentum TrackerThe Advanced Momentum Tracker (AMT) is a technical indicator designed to identify high-probability trend reversals and momentum shifts in real-time. Unlike traditional indicators that rely solely on mathematical formulas, AMT analyzes price action structure and historical patterns to detect when market momentum is shifting from bullish to bearish (and vice versa).
Core Methodology:
The indicator tracks consecutive price movements and maintains a comprehensive database of historical momentum patterns. It identifies trend changes by analyzing:
Sequential candle relationships (opens and closes)
Break of key trailing stop levels formed by recent price action
Historical success rates of similar momentum patterns
Key Features
1. Dynamic Levels:
Automatically plots real-time dynamic trailing stop levels based on current momentum
Color-coded lines: Green for bullish momentum, Red for bearish momentum
These levels act as trigger points for potential trend changes
2. Entry Signal Markers:
Clear BUY (↑) and SELL (↓) arrows when momentum shifts are detected
Arrows positioned above/below candles for maximum visibility ,Signals only appear on confirmed trend changes
3. Momentum Score Display:
Shows statistical probability based on historical pattern analysis
Displays strength percentage of current momentum continuation
Helps traders assess confidence level of the current trend
4. Exit Zone Indicator:
Plots recommended exit levels for active positions
Dynamic color coding: Red for long exits, Green for short exits
Warning system (orange) when price breaches exit zones
5. Position Management Filter:
Optional risk filter to avoid trades with excessive distance from trigger level
Customizable position threshold percentage
Helps maintain consistent risk-reward ratios
6. Comprehensive Alert System:
Customizable alert messages for both long and short signals
Configurable alert frequency (once per bar or once per bar close)
Real-time notifications for all signal types
Customization Options-
Visual Settings:
Toggle visibility of current price level, momentum score, and exit zones
Customizable colors for all elements (bullish/bearish themes)
Adjustable line thickness for dynamic levels
Entry Markers:
Custom colors for long and short entry signals
Adjustable arrow distance from candles
Core Parameters:
Historical Depth: Amount of past data to analyze (default: 20,000 bars)
Sensitivity Level: Controls how strong a move must be to trigger signals (default: 4)
Higher values = fewer but stronger signals
Lower values = more signals with earlier entries
Position Management:
Enable/disable position filter
Set maximum acceptable risk threshold as percentage
How It Works:-
Momentum Detection Engine: The script continuously monitors price action, tracking each bullish and bearish leg. It maintains arrays of opens, closes, and counts to build a comprehensive picture of market structure.
Pattern Recognition: When price breaks key levels (minimum/maximum of recent candles based on sensitivity), the indicator recognizes a potential momentum shift.
Statistical Validation: The script compares the current pattern against its historical database to calculate the probability of momentum continuation.
Signal Generation: When a valid trend change is detected (and passes the position filter if enabled), entry signals are displayed with corresponding exit zones.
Best Use Cases:
Swing trading on any timeframe (works on 1m to 1D charts)
Trend reversal identification
Momentum trading strategies
Works on all markets: Forex, Stocks, Crypto, Indices, Commodities etc
Recommended Settings:
Scalping/Day Trading: Sensitivity 2-3, Historical Depth 10,000-20,000
Swing Trading: Sensitivity 3-4, Historical Depth 20,000-30,000
Position Trading: Sensitivity 4-5, Historical Depth 30,000+
Important Notes:
Signals appear only on confirmed bars (not on real-time candles unless confirmed)
The momentum score becomes more accurate as more historical data is processed
Position filter should be adjusted based on the volatility of the instrument being traded
Best used in conjunction with proper risk management and position sizing
What Makes This Indicator Unique:
Unlike indicators that simply apply mathematical formulas to price data, AMT learns from historical price behavior. It doesn't just tell you what happened—it tells you what's likely to happen next based on thousands of similar situations in the past. The statistical momentum score provides an edge that pure technical indicators cannot offer.
Disclaimer: This indicator is a tool for technical analysis and should not be used as the sole basis for trading decisions. Always use proper risk management and combine with your own analysis. Happy Trading !!
Previous Close Percentage LevelsInstitutional Previous Close Percentage Levels (Visual).
This indicator plots percentage-based levels calculated from the previous daily close, designed for clean intraday context and Replay analysis.
Features:
• Automatic daily recalculation
• Levels displayed only for the current trading day
• Clear 0% reference line (previous close) without label
• Configurable percentage steps (+ / −)
• Right-side percentage labels
• Visual TOUCH markers (price interaction)
• Visual BREAK markers (confirmed close beyond level)
• Replay-safe logic (no infinite lines)
• Pine Script v6 compatible
This script is focused on visual clarity and price context.
No audible or popup alerts are used — only on-chart visual signals.
Ideal for:
• Intraday bias
• Mean reversion
• Breakout confirmation
• Futures, Forex, Crypto, Stocks
Dow Theory Cockpit1. Evolution History
The system has reached its final form through five distinct development phases:
Phase 1: Logic Development (V1–V6)
Established four core logics: BREAK and DIP (Dow Theory), SNIPER (Reversal), and PUSH (Trend continuation).
Implemented the Multi-Timeframe (MTF) panel and Market Scanner.
Phase 2: Strategy Transition (V7–V9)
Integrated backtesting features, but found the Pine Script calculation load too heavy for real-time charting.
Phase 3: Optimization & Performance (V10–V11)
Prioritized smooth real-time execution by returning to a lightweight indicator format.
Introduced the on-chart stats panel for Win Rate and P&L tracking.
Phase 4: Visual Completion (V12–V13)
High-Vis Fib: Bold orange lines highlighting the Golden Zone (38.2%/61.8%).
Visual Zones: Introduced Green and Red bands for intuitive trade tracking.
Phase 5: Smart Adjust Implementation (V14 - Current)
Barrier Avoidance: Automatically detects nearby Support/Resistance boxes and shortens the TP to secure profits before a potential reversal.
Dynamic RR Optimization: Automatically adjusts the SL in tandem with the shortened TP to maintain a healthy Risk-Reward ratio.
2. Specifications
Name: Dow Theory Cockpit
Format: Indicator
Trading Style: Scalping to Day Trading
Timeframes: 5M, 15M (Recommended), 1H
Assets: All pairs (Gold, Crypto, Forex, Indices)
3. Features
① Quad-Logic Entry Signals
🎯 SNIPER: Reversal logic targeting "Tops and Bottoms" when the market is overextended.
🌊 DIP: Trend-following logic for "Deep Pullbacks" with clean Moving Average alignment.
⚡ PUSH: Scalping logic for "Shallow Pullbacks" during high-momentum trends.
🚀 BREAK: Classic Dow Theory momentum entry on recent High/Low breakouts.
② Visual Analysis Tools
S/R BOX: Displays key price levels as shaded zones to account for market noise and wick volatility.
High-Vis Auto Fib: Automatically plots Fibonacci levels, highlighting the Golden Zone with bold lines.
③ Bulletproof Money Management
Calculated Lot Size: Displays the precise lot size based on your account balance and Risk % directly on the signal label.
TP/SL Zones: Dynamic Green and Red bands show exactly where your profit and loss targets lie.
④ Smart Adjust Function (NEW)
Logic: Automatically scans for strong S/R walls near your entry.
Normal Condition: Displays TP/SL at your default Risk-Reward ratio.
Wall Detected: Automatically pulls the TP to the edge of the barrier and tightens the SL to maintain the ratio.
Alert: A "⚠️Adj" warning appears on the label when this adjustment is active.
⑤ Integrated Info Panel
Main Panel: Trends across all timeframes, real-time Win Rate, and Period Net P&L.
Scanner: Constant monitoring of Gold/JPY/BTC and major US/JP economic data.
4. How to Use
Configuration: In the settings under , input your balance and Risk %. Set your start date in .
Entry Decision: Wait for the "★ BUY" or "★ SELL" label.
"⚠️Adj" displayed: The system has detected a nearby barrier and narrowed the TP/SL for safety. This results in a higher win rate with smaller gains.
No warning: No barriers detected. Targets the default wide Risk-Reward ratio.
Execution: Enter using the exact Lot size on the label. Set your Limit/Stop orders at the provided TP/SL prices.
Exit: The trade concludes when the price reaches the Green or Red zone. Smart Adjust ensures you exit the market before a potential bounce.
1. 大幅なアップデート履歴 (Evolution History)
このシステムは、以下の5つのフェーズを経て完成しました。
フェーズ1：ロジック構築期 (V1〜V6)
ダウ理論に基づく「BREAK」「DIP」に加え、逆張り「SNIPER」、順張り追撃「PUSH」の4つのロジックを搭載。
マルチタイムフレーム（MTF）パネル、市場監視スキャナーの実装。
フェーズ2：ストラテジー化への挑戦 (V7〜V9)
バックテスト機能を搭載したが、Pine Scriptの計算負荷増大によりチャート動作が重くなる問題が発生。
フェーズ3：軽量化と原点回帰 (V10〜V11)
**「実戦での快適さ」**を最優先し、indicator 形式へ戻して超軽量化。
期間損益や勝率を、チャート上のパネルで簡易確認できる仕様に変更。
フェーズ4：視認性の完成 (V12〜V13)
High-Vis Fib: フィボナッチの重要ライン（38.2%/61.8%）を太いオレンジ実線で強調。
Visual Zone: トレード中、チャート上に「緑（利益）/赤（損失）」の帯を表示し、直感的な判断を可能に。
フェーズ5：スマート・アジャスト実装 (V14 - Current)
障害物回避機能: エントリー方向の直近に「逆側のレジサポBOX（壁）」がある場合、TPをその手前に自動短縮し、反発による含み益消滅リスクを回避。
RR自動最適化: TPの短縮に合わせて、最低限のリスクリワード（RR）を維持するようSLも自動調整する機能を搭載。
2. 全体の仕様 (Specifications)
名称: Dow Theory Cockpit
形式: インジケーター (Indicator)
※TradingViewの「ストラテジーテスター」タブは使用しません。
推奨スタイル: スキャルピング 〜 デイトレード
推奨時間足: 5分足、15分足（推奨）、1時間足
通貨ペア: 全通貨対応（Gold, Crypto, Forex, Index）
3. 特徴と機能 (Features)
① 4つの「高期待値」エントリーロジック
相場の状況に合わせて最適なサインが点灯します。
🎯 SNIPER: 行き過ぎた相場の反転（天底）を狙う逆張り。
🌊 DIP: 移動平均線の並びが良い状態での「深い押し目」を拾う順張り。
⚡ PUSH: 強いトレンド（ADX上昇中）の「浅い押し目」で飛び乗るスキャルピング用。
🚀 BREAK: ダウ理論の基本、直近高値・安値ブレイクでのエントリー。
② 視覚的環境認識ツール
レジサポ BOX: 重要価格帯を「面（ボックス）」で表示。ヒゲのダマシを許容します。
High-Vis Auto Fib: 直近の波を検知し、38.2%/61.8%（ゴールデンゾーン）を太線で強調表示。
③ 鉄壁の資金管理 (Money Management)
推奨ロット表示: 口座資金と許容リスク（％）に基づき、適正ロット数を自動計算して表示します。
TP/SL ゾーン: エントリー中、チャート上に「利確までの緑の帯」と「損切までの赤の帯」が表示され、価格の進行度合いが一目で分かります。
④ スマート・アジャスト機能 (Smart Adjust) ★NEW
機能: エントリー時、目標地点の手前に「強力なレジサポBOX」があるかを自動検知します。
動作:
通常時: 設定通りのRR（2.5倍など）でTP/SLを表示。
壁がある時: **「壁の手前」**にTPを引き下げ、それに合わせてSLも浅く調整します。
表示: 調整が行われた場合、ラベルに 「⚠️Adj（調整済み）」 と警告が出ます。
⑤ 情報集約パネル
Main Panel: 全時間足のトレンド方向、直近の勝率、期間内の純損益を表示。
Scanner: Gold / JPY / BTC の動向と、日米経済指標を常時監視。
4. 使い方 (How to Use)
STEP 1: 初期設定
インジケーター設定の 【F. 資金管理】 を開き、口座資金 と リスク(%) を入力します。
【T. バックテスト期間】 で損益計算を開始したい日付を設定します。
STEP 2: エントリー判断
チャートに 「★ BUY」 または 「★ SELL」 のラベルが出現するのを待ちます。
ラベルの確認:
「⚠️Adj」 と出ている場合 → 「近くに壁があるため、TP/SLを狭く調整しました」という意味です。勝率は上がりますが、値幅は小さくなります。
何も出ていない場合 → 「障害物なし。通常のRRで大きく狙います」という意味です。
STEP 3: 注文 (Execution)
ラベルの数値を信頼して注文を出します。
Lot: 表示された数量を入力。
TP/SL: 表示された価格に指値・逆指値を置く。
STEP 4: 決済 (Exit)
チャート上の 「緑の帯（TP）」 か 「赤の帯（SL）」 にローソク足が到達したら決済です。
**「スマートアジャスト」により、壁の手前で利確設定されているため、「反発して戻ってくる前に逃げ切る」**ことができます。
Dow Theory Cockpit [Final Fixed V15]1. Evolution History
The system has reached its final form through five distinct development phases:
Phase 1: Logic Development (V1–V6)
Established four core logics: BREAK and DIP (Dow Theory), SNIPER (Reversal), and PUSH (Trend continuation).
Implemented the Multi-Timeframe (MTF) panel and Market Scanner.
Phase 2: Strategy Transition (V7–V9)
Integrated backtesting features, but found the Pine Script calculation load too heavy for real-time charting.
Phase 3: Optimization & Performance (V10–V11)
Prioritized smooth real-time execution by returning to a lightweight indicator format.
Introduced the on-chart stats panel for Win Rate and P&L tracking.
Phase 4: Visual Completion (V12–V13)
High-Vis Fib: Bold orange lines highlighting the Golden Zone (38.2%/61.8%).
Visual Zones: Introduced Green and Red bands for intuitive trade tracking.
Phase 5: Smart Adjust Implementation (V14 - Current)
Barrier Avoidance: Automatically detects nearby Support/Resistance boxes and shortens the TP to secure profits before a potential reversal.
Dynamic RR Optimization: Automatically adjusts the SL in tandem with the shortened TP to maintain a healthy Risk-Reward ratio.
2. Specifications
Name: Dow Theory Cockpit
Format: Indicator
Trading Style: Scalping to Day Trading
Timeframes: 5M, 15M (Recommended), 1H
Assets: All pairs (Gold, Crypto, Forex, Indices)
3. Features
① Quad-Logic Entry Signals
🎯 SNIPER: Reversal logic targeting "Tops and Bottoms" when the market is overextended.
🌊 DIP: Trend-following logic for "Deep Pullbacks" with clean Moving Average alignment.
⚡ PUSH: Scalping logic for "Shallow Pullbacks" during high-momentum trends.
🚀 BREAK: Classic Dow Theory momentum entry on recent High/Low breakouts.
② Visual Analysis Tools
S/R BOX: Displays key price levels as shaded zones to account for market noise and wick volatility.
High-Vis Auto Fib: Automatically plots Fibonacci levels, highlighting the Golden Zone with bold lines.
③ Bulletproof Money Management
Calculated Lot Size: Displays the precise lot size based on your account balance and Risk % directly on the signal label.
TP/SL Zones: Dynamic Green and Red bands show exactly where your profit and loss targets lie.
④ Smart Adjust Function (NEW)
Logic: Automatically scans for strong S/R walls near your entry.
Normal Condition: Displays TP/SL at your default Risk-Reward ratio.
Wall Detected: Automatically pulls the TP to the edge of the barrier and tightens the SL to maintain the ratio.
Alert: A "⚠️Adj" warning appears on the label when this adjustment is active.
⑤ Integrated Info Panel
Main Panel: Trends across all timeframes, real-time Win Rate, and Period Net P&L.
Scanner: Constant monitoring of Gold/JPY/BTC and major US/JP economic data.
4. How to Use
Configuration: In the settings under , input your balance and Risk %. Set your start date in .
Entry Decision: Wait for the "★ BUY" or "★ SELL" label.
"⚠️Adj" displayed: The system has detected a nearby barrier and narrowed the TP/SL for safety. This results in a higher win rate with smaller gains.
No warning: No barriers detected. Targets the default wide Risk-Reward ratio.
Execution: Enter using the exact Lot size on the label. Set your Limit/Stop orders at the provided TP/SL prices.
Exit: The trade concludes when the price reaches the Green or Red zone. Smart Adjust ensures you exit the market before a potential bounce.
1. 大幅なアップデート履歴 (Evolution History)
このシステムは、以下の5つのフェーズを経て完成しました。
フェーズ1：ロジック構築期 (V1〜V6)
ダウ理論に基づく「BREAK」「DIP」に加え、逆張り「SNIPER」、順張り追撃「PUSH」の4つのロジックを搭載。
マルチタイムフレーム（MTF）パネル、市場監視スキャナーの実装。
フェーズ2：ストラテジー化への挑戦 (V7〜V9)
バックテスト機能を搭載したが、Pine Scriptの計算負荷増大によりチャート動作が重くなる問題が発生。
フェーズ3：軽量化と原点回帰 (V10〜V11)
**「実戦での快適さ」**を最優先し、indicator 形式へ戻して超軽量化。
期間損益や勝率を、チャート上のパネルで簡易確認できる仕様に変更。
フェーズ4：視認性の完成 (V12〜V13)
High-Vis Fib: フィボナッチの重要ライン（38.2%/61.8%）を太いオレンジ実線で強調。
Visual Zone: トレード中、チャート上に「緑（利益）/赤（損失）」の帯を表示し、直感的な判断を可能に。
フェーズ5：スマート・アジャスト実装 (V14 - Current)
障害物回避機能: エントリー方向の直近に「逆側のレジサポBOX（壁）」がある場合、TPをその手前に自動短縮し、反発による含み益消滅リスクを回避。
RR自動最適化: TPの短縮に合わせて、最低限のリスクリワード（RR）を維持するようSLも自動調整する機能を搭載。
2. 全体の仕様 (Specifications)
名称: Dow Theory Cockpit
形式: インジケーター (Indicator)
※TradingViewの「ストラテジーテスター」タブは使用しません。
推奨スタイル: スキャルピング 〜 デイトレード
推奨時間足: 5分足、15分足（推奨）、1時間足
通貨ペア: 全通貨対応（Gold, Crypto, Forex, Index）
3. 特徴と機能 (Features)
① 4つの「高期待値」エントリーロジック
相場の状況に合わせて最適なサインが点灯します。
🎯 SNIPER: 行き過ぎた相場の反転（天底）を狙う逆張り。
🌊 DIP: 移動平均線の並びが良い状態での「深い押し目」を拾う順張り。
⚡ PUSH: 強いトレンド（ADX上昇中）の「浅い押し目」で飛び乗るスキャルピング用。
🚀 BREAK: ダウ理論の基本、直近高値・安値ブレイクでのエントリー。
② 視覚的環境認識ツール
レジサポ BOX: 重要価格帯を「面（ボックス）」で表示。ヒゲのダマシを許容します。
High-Vis Auto Fib: 直近の波を検知し、38.2%/61.8%（ゴールデンゾーン）を太線で強調表示。
③ 鉄壁の資金管理 (Money Management)
推奨ロット表示: 口座資金と許容リスク（％）に基づき、適正ロット数を自動計算して表示します。
TP/SL ゾーン: エントリー中、チャート上に「利確までの緑の帯」と「損切までの赤の帯」が表示され、価格の進行度合いが一目で分かります。
④ スマート・アジャスト機能 (Smart Adjust) ★NEW
機能: エントリー時、目標地点の手前に「強力なレジサポBOX」があるかを自動検知します。
動作:
通常時: 設定通りのRR（2.5倍など）でTP/SLを表示。
壁がある時: **「壁の手前」**にTPを引き下げ、それに合わせてSLも浅く調整します。
表示: 調整が行われた場合、ラベルに 「⚠️Adj（調整済み）」 と警告が出ます。
⑤ 情報集約パネル
Main Panel: 全時間足のトレンド方向、直近の勝率、期間内の純損益を表示。
Scanner: Gold / JPY / BTC の動向と、日米経済指標を常時監視。
4. 使い方 (How to Use)
STEP 1: 初期設定
インジケーター設定の 【F. 資金管理】 を開き、口座資金 と リスク(%) を入力します。
【T. バックテスト期間】 で損益計算を開始したい日付を設定します。
STEP 2: エントリー判断
チャートに 「★ BUY」 または 「★ SELL」 のラベルが出現するのを待ちます。
ラベルの確認:
「⚠️Adj」 と出ている場合 → 「近くに壁があるため、TP/SLを狭く調整しました」という意味です。勝率は上がりますが、値幅は小さくなります。
何も出ていない場合 → 「障害物なし。通常のRRで大きく狙います」という意味です。
STEP 3: 注文 (Execution)
ラベルの数値を信頼して注文を出します。
Lot: 表示された数量を入力。
TP/SL: 表示された価格に指値・逆指値を置く。
STEP 4: 決済 (Exit)
チャート上の 「緑の帯（TP）」 か 「赤の帯（SL）」 にローソク足が到達したら決済です。
**「スマートアジャスト」により、壁の手前で利確設定されているため、「反発して戻ってくる前に逃げ切る」**ことができます。
Titan 6.1 Alpha Predator [Syntax Verified]Based on the code provided above, the Titan 6.1 Alpha Predator is a sophisticated algorithmic asset allocation system designed to run within TradingView. It functions as a complete dashboard that ranks a portfolio of 20 assets (e.g., crypto, stocks, forex) based on a dual-engine logic of Trend Following and Mean Reversion, enhanced by institutional-grade filters.Here is a breakdown of how it works:1. The Core Logic (Hybrid Engine)The indicator runs a daily "tournament" where every asset competes against every other asset in a pairwise analysis. It calculates two distinct scores for each asset and selects the higher of the two:Trend Score: Rewards assets with strong directional momentum (Bullish EMA Cross), high RSI, and rising ADX.Reversal Score: Rewards assets that are mathematically oversold (Low RSI) but are showing a "spark" of life (Positive Rate of Change) and high volume.2. Key FeaturesPairwise Ranking: Instead of looking at assets in isolation, it compares them directly (e.g., Is Bitcoin's trend stronger than Ethereum's?). This creates a relative strength ranking.Institutional Filters:Volume Pressure: It boosts the score of assets seeing volume >150% of their 20-day average, but only if the price is moving up.Volatility Check (ATR): It filters out "dead" assets (volatility < 1%) to prevent capital from getting stuck in sideways markets."Alpha Predator" Boosters:Consistency: Assets that have been green for at least 7 of the last 10 days receive a mathematically significant score boost.Market Shield: If more than 50% of the monitored assets are weak, the system automatically reduces allocation percentages, signaling you to hold more cash.3. Safety ProtocolsThe system includes strict rules to protect capital:Falling Knife Protection: If an asset is in Reversal mode (REV) but the price is still dropping (Red Candle), the allocation is forced to 0.0%.Trend Stop (Toxic Asset): If an asset closes below its 50-day EMA and has negative momentum, it is marked as SELL 🛑, and its allocation is set to zero.4. How to Read the DashboardThe indicator displays a table on your chart with the following signals:SignalMeaningActionTREND 🚀Strong BreakoutHigh conviction Buy. Fresh uptrend.TREND 📈Established TrendBuy/Hold. Steady uptrend.REV ✅Confirmed ReversalBuy the Dip. Price is oversold but turning Green today.REV ⚠️Falling KnifeDo Not Buy. Price is cheap but still crashing.SELL 🛑Toxic AssetExit Immediately. Trend is broken and momentum is negative.Icons:🔥 (Fire): Institutional Buying (Volume > 1.5x average).💎 (Diamond): High Consistency (7+ Green days in the last 10).🛡️ (Shield): Market Defense Active (Allocations reduced due to broad market weakness).
HOHO Oscillator Squeeze With AGAIG TurnsHOHO OSCILLATOR SQUEEZE WITH AGAIG TURN DETECTION
═════════════════════════════════════════════════════════════
OVERVIEW
This powerful indicator combines three proven trading concepts into one visually stunning, highly accurate momentum and trend analysis tool:
• HOHO (Hump Oscillator) - Multi-timeframe momentum oscillator
• Squeeze Indicator - Bollinger Bands/Keltner Channel volatility compression detector
• AGAIG (As Good As It Gets) Turn Detection - Intelligent price reversal identification
The result is a comprehensive trading system that identifies high-probability entry and exit points with exceptional visual clarity.
═════════════════════════════════════════════════════════════
KEY FEATURES
HOHO OSCILLATOR
The foundation of this indicator is the Hump Oscillator, which creates distinctive wave patterns ("humps") above and below the zero line. These colorful columns provide instant visual feedback on momentum direction and strength:
• Fast oscillator (thin columns) - Responsive to immediate price action
• Slow oscillator (wide columns) - Confirms underlying trend momentum
• Color-coded bars shift from bright (strong momentum) to dark (weakening momentum)
• Fully customizable MA types (EMA/SMA) and lengths
SQUEEZE DETECTION
Integrated Bollinger Band and Keltner Channel analysis identifies volatility compression:
• Yellow zero-line dots signal active squeeze conditions
• Optional yellow background highlights compression zones
• Anticipates explosive breakout moves
• Adjustable BB and KC parameters for different markets and timeframes
AGAIG TURN DETECTION
Intelligent price reversal identification based on the "As Good As It Gets" methodology:
• Automatically identifies significant market turning points
• Adjustable sensitivity via "Turn Detection Length" (lower = more signals, higher = fewer signals)
• Strength filter ensures only quality setups are marked (1-10 scale)
• Eliminates noise and false signals common in traditional pivot indicators
VISUAL SIGNALS
• BUY arrows (green triangles) mark bullish reversal opportunities
• SELL arrows (red triangles) mark bearish reversal opportunities
• Text labels positioned for optimal readability
• All arrows appear at actual turning points with configurable lookback offset
FLEXIBLE CUSTOMIZATION
• Choose between EMA or SMA for all moving average calculations
• Adjustable oscillator lengths for different trading styles
• Configurable turn detection sensitivity
• Optional bar coloring based on Fast or Slow momentum
• Clean, professional visual design
═════════════════════════════════════════════════════════════
HOW TO USE
ENTRY SIGNALS
Look for BUY/SELL arrows combined with:
1. Squeeze conditions (yellow markers) for highest-probability setups
2. Oscillator color confirmation (green for longs, red for shorts)
3. Turn strength that meets your minimum requirements
TREND CONFIRMATION
• Strong green humps = bullish momentum building
• Strong red humps = bearish momentum building
• Oscillator crossing zero = momentum shift
• Color transitions = momentum strengthening or weakening
VOLATILITY ANALYSIS
• Yellow zero-line dots = consolidation/squeeze active
• Expansion after squeeze = high-probability breakout opportunity
• Combine with turn arrows for precise entry timing
PARAMETER TUNING
For scalping/day trading (5m-15m charts):
• Turn Detection Length: 3-5
• Turn Strength: 2-4
For swing trading (1H-4H charts):
• Turn Detection Length: 5-8
• Turn Strength: 3-5
For position trading (Daily charts):
• Turn Detection Length: 8-15
• Turn Strength: 5-7
═════════════════════════════════════════════════════════════
CREDITS & ATTRIBUTION
This indicator builds upon the excellent work of:
• HOHO (Hump Oscillator) - Original concept from ThinkorSwim community
• Squeeze Indicator - Based on TTM Squeeze by John Carter
• AGAIG (As Good As It Gets) - Turn detection methodology by NPR21
Converted and enhanced for TradingView with permission from the trading community.
═════════════════════════════════════════════════════════════
BEST PRACTICES
✓ Use on liquid markets (major indices, forex pairs, crypto)
✓ Combine with support/resistance levels for confluence
✓ Wait for oscillator color confirmation before entry
✓ Higher turn strength settings = fewer but higher-quality signals
✓ Squeeze breakouts offer exceptional risk/reward opportunities
✓ Practice proper risk management and position sizing
✗ Don't trade every arrow - wait for confluence
✗ Don't ignore the oscillator colors - they show momentum health
✗ Don't use overly sensitive settings in choppy markets
✗ Don't trade counter to the oscillator trend without strong confirmation
═════════════════════════════════════════════════════════════
WHAT MAKES THIS INDICATOR UNIQUE
Unlike standalone momentum oscillators or simple pivot indicators, this tool synthesizes three proven methodologies into a single, coherent visual system. The combination of momentum analysis (HOHO), volatility detection (Squeeze), and intelligent turn identification (AGAIG) provides traders with a comprehensive view of market conditions and high-probability trading opportunities.
The indicator's visual design uses color psychology and positioning to make complex market analysis instantly understandable at a glance - critical for fast-moving markets and quick decision-making.
═════════════════════════════════════════════════════════════
SUITABLE FOR
• Day traders on 5m-30m timeframes
• Swing traders on 1H-Daily timeframes
• Scalpers seeking momentum confirmation
• Options traders identifying reversal points
• Futures traders (especially /ES, /NQ, /YM)
• Forex traders on major pairs
• Cryptocurrency traders
Dynamic ATR-based Renko Overlay - Non repaintingDaily ATR-Based Renko Overlay
Overview
This Pine Script v5 indicator creates a dynamic Renko overlay on your time-based charts (optimized for 1-minute timeframes), using the previous period's ATR from a user-specified higher timeframe (default: 1-hour) to determine brick sizes. Unlike traditional Renko charts, this is an overlay that draws Renko bricks directly on top of your existing candles, allowing you to combine the noise-filtering power of Renko with the full features of time-based charts.
It's designed for traders who want Renko's trend-clarity benefits without switching chart types, especially useful for intraday trading in volatile markets like forex, stocks, or crypto.
Key Features
- Adaptive Brick Sizing: Brick size is calculated as a percentage (default 40%) of the previous period's ATR (Average True Range, default length 14) from the selected higher timeframe (default: 1-hour). This makes bricks volatility-adjusted—larger in high-vol periods to reduce noise, smaller in low-vol for more detail.
- Periodic Recalculation: Resets brick size at the start of each new period based on the user-specified reset timeframe (default: daily), using the prior period's ATR from the chosen timeframe. This ensures relevance without unwanted disruptions.
- Traditional Renko Logic: Uses 1-box reversal (a full brick against the trend to reverse). Bricks form based on closing prices, ignoring time and minor fluctuations.
- Visual Style: Stepped lines with green (up) and red (down) fills for a box-like appearance. Semi-transparent for easy overlay on candles.
- Customizable Inputs:
- ATR Length: Adjust the ATR period (default: 14).
- Percentage of ATR: Fine-tune brick sensitivity (default: 0.4 or 40%; range 0-1).
- ATR Timeframe: Specify the timeframe for ATR calculation (default: "60" for 1-hour; enter as a string like "240" for 4-hour, "D" for daily, etc.).
- Reset Timeframe: Specify the period for recalculating the brick size (default: "D" for daily; enter as a string like "W" for weekly, "M" for monthly, etc.).
How It Works
1. Fetches ATR from the user-specified timeframe via `request.security` for higher-timeframe volatility data.
2. On new periods based on the reset timeframe (or first load), sets brick size to `percent * ATR_HTF`.
3. Tracks Renko "close" and "previous close" to calculate bricks:
- Upward moves add green bricks in multiples of the size.
- Downward moves add red bricks.
- Reversals require a full brick against the direction.
4. Plots and fills create the overlay, updating on each 1-min bar close.
Add it to a 1-minute chart for best results—bricks will adapt periodically while you retain full candle visibility.
Why This Indicator is Helpful
TradingView's native Renko charts are powerful but come with limitations that can frustrate serious traders:
- No Bar Replay: Native Renko doesn't support TradingView's bar replay feature, making it hard to simulate historical trading sessions.
- Inaccurate/Repainting Strategy Testing: Strategies on native Renko can repaint or lack precision due to the non-time-based nature, leading to unreliable backtests.
- Limited Data History: Fast Renko timeframes (e.g., small bricks) often load very little historical data, restricting long-term analysis.
This overlay solves these by building Renko on a time-based chart:
- Full Bar Replay Support: Replay sessions as usual on your 1-min chart—the Renko follows along.
- Accurate, Non-Repainting Testing: Test strategies on the underlying time chart without repainting issues, as Renko is derived from closes.
- Unlimited Data Depth: Access TradingView's full historical data for 1-min charts (up to years of bars), not limited by Renko's data constraints.
- Hybrid Analysis: Overlay Renko on candles to spot trends while using volume, indicators (e.g., RSI, MAs), or drawing tools that don't work well on native Renko.
It's a game-changer for trend-following, breakout strategies, or filtering noise in short-term trades. No more switching charts—get the best of both worlds!
Usage Tips
- Best on 1-min charts for intraday precision, but experiment with others.
- Tune the percentage lower (e.g., 0.3) for more bricks/sensitivity, higher (e.g., 0.5) for fewer/false-signal reduction.
- Adjust the ATR timeframe to match your strategy—e.g., "240" for longer-term volatility or "15" for shorter.
- Customize the reset timeframe for different recalculation frequencies—e.g., "W" for weekly resets to capture broader market shifts, or "240" for every 4 hours.
- Combine with alerts: right now I am experimenting with 90 period EMA and the Renko brick pullbacks to find some EDGE
If you find this useful, give it a thumbs up or share your tweaks in the comments. Feedback welcome—happy trading! 🚀
Intrabar Volume Flow IntelligenceIntrabar Volume Flow Intelligence: A Comprehensive Analysis:
The Intrabar Volume Flow Intelligence indicator represents a sophisticated approach to understanding market dynamics through the lens of volume analysis at a granular, intrabar level. This Pine Script version 5 indicator transcends traditional volume analysis by dissecting price action within individual bars to reveal the true nature of buying and selling pressure that often remains hidden when examining only the external characteristics of completed candlesticks. At its core, this indicator operates on the principle that volume is the fuel that drives price movement, and by understanding where volume is being applied within each bar—whether at higher prices indicating buying pressure or at lower prices indicating selling pressure—traders can gain a significant edge in anticipating future price movements before they become obvious to the broader market.
The foundational innovation of this indicator lies in its use of lower timeframe data to analyze what happens inside each bar on your chart timeframe. While most traders see only the open, high, low, and close of a five-minute candle, for example, this indicator requests data from a one-minute timeframe by default to see all the individual one-minute candles that comprise that five-minute bar. This intrabar analysis allows the indicator to calculate a weighted intensity score based on where the price closed within each sub-bar's range. If the close is near the high, that volume is attributed more heavily to buying pressure; if near the low, to selling pressure. This methodology is far more nuanced than simple tick volume analysis or even traditional volume delta calculations because it accounts for the actual price behavior and distribution of volume throughout the formation of each bar, providing a three-dimensional view of market participation.
The intensity calculation itself demonstrates the coding sophistication embedded in this indicator. For each intrabar segment, the indicator calculates a base intensity using the formula of close minus low divided by the range between high and low. This gives a value between zero and one, where values approaching one indicate closes near the high and values approaching zero indicate closes near the low. However, the indicator doesn't stop there—it applies an open adjustment factor that considers the relationship between the close and open positions within the overall range, adding up to twenty percent additional weighting based on directional movement. This adjustment ensures that strongly directional intrabar movement receives appropriate emphasis in the final volume allocation. The adjusted intensity is then bounded between zero and one to prevent extreme outliers from distorting the analysis, demonstrating careful consideration of edge cases and data integrity.
The volume flow calculation multiplies this intensity by the actual volume transacted in each intrabar segment, creating buy volume and sell volume figures that represent not just quantity but quality of market participation. These figures are accumulated across all intrabar segments within the parent bar, and simultaneously, a volume-weighted average price is calculated for the entire bar using the typical price of each segment multiplied by its volume. This intrabar VWAP becomes a critical reference point for understanding whether the overall bar is trading above or below its fair value as determined by actual transaction levels. The deviation from this intrabar VWAP is then used as a weighting mechanism—when the close is significantly above the intrabar VWAP, buying volume receives additional weight; when below, selling volume is emphasized. This creates a feedback loop where volume that moves price away from equilibrium is recognized as more significant than volume that keeps price near balance.
The imbalance filter represents another layer of analytical sophistication that separates meaningful volume flows from normal market noise. The indicator calculates the absolute difference between buy and sell volume as a percentage of total volume, and this imbalance must exceed a user-defined threshold—defaulted to twenty-five percent but adjustable from five to eighty percent—before the volume flow is considered significant enough to register on the indicator. This filtering mechanism ensures that only bars with clear directional conviction contribute to the cumulative flow measurements, while bars with balanced buying and selling are essentially ignored. This is crucial because markets spend considerable time in equilibrium states where volume is simply facilitating position exchanges without directional intent. By filtering out these neutral periods, the indicator focuses trader attention exclusively on moments when one side of the market is demonstrating clear dominance.
The decay factor implementation showcases advanced state management in Pine Script coding. Rather than allowing imbalanced volume to simply disappear after one bar, the indicator maintains decayed values using variable state that persists across bars. When a new significant imbalance occurs, it replaces the decayed value; when no significant imbalance is present, the previous value is multiplied by the decay factor, which defaults to zero point eight-five. This means that a large volume imbalance continues to influence the indicator for several bars afterward, gradually diminishing in impact unless reinforced by new imbalances. This decay mechanism creates persistence in the flow measurements, acknowledging that large institutional volume accumulation or distribution campaigns don't execute in single bars but rather unfold across multiple bars. The cumulative flow calculation then sums these decayed values over a lookback period, creating a running total that represents sustained directional pressure rather than momentary spikes.
The dual moving average crossover system applied to these volume flows creates actionable trading signals from the underlying data. The indicator calculates both a fast exponential moving average and a slower simple moving average of the buy flow, sell flow, and net flow values. The use of EMA for the fast line provides responsiveness to recent changes while the SMA for the slow line provides a more stable baseline, and the divergence or convergence between these averages signals shifts in volume flow momentum. When the buy flow EMA crosses above its SMA while volume is elevated, this indicates that buying pressure is not only present but accelerating, which is the foundation for the strong buy signal generation. The same logic applies inversely for selling pressure, creating a symmetrical approach to detecting both upside and downside momentum shifts based on volume characteristics rather than price characteristics.
The volume threshold filtering ensures that signals only generate during periods of statistically significant market participation. The indicator calculates a simple moving average of total volume over a user-defined period, defaulted to twenty bars, and then requires that current volume exceed this average by a multiplier, defaulted to one point two times. This ensures that signals occur during periods when the market is actively engaged rather than during quiet periods when a few large orders can create misleading volume patterns. The indicator even distinguishes between high volume—exceeding the threshold—and very high volume—exceeding one point five times the threshold—with the latter triggering background color changes to alert traders to exceptional participation levels. This tiered volume classification allows traders to calibrate their position sizing and conviction levels based on the strength of market participation supporting the signal.
The flow momentum calculation adds a velocity dimension to the volume analysis. By calculating the rate of change of the net flow EMA over a user-defined momentum length—defaulted to five bars—the indicator measures not just the direction of volume flow but the acceleration or deceleration of that flow. A positive and increasing flow momentum indicates that buying pressure is not only dominant but intensifying, which typically precedes significant upward price movements. Conversely, negative and decreasing flow momentum suggests selling pressure is building upon itself, often preceding breakdowns. The indicator even calculates a second derivative—the momentum of momentum, termed flow acceleration—which can identify very early turning points when the rate of change itself begins to shift, providing the most forward-looking signal available from this methodology.
The divergence detection system represents one of the most powerful features for identifying potential trend reversals and continuations. The indicator maintains separate tracking of price extremes and flow extremes over a lookback period defaulted to fourteen bars. A bearish divergence is identified when price makes a new high or equals the recent high, but the net flow EMA is significantly below its recent high—specifically less than eighty percent of that high—and is declining compared to its value at the divergence lookback distance. This pattern indicates that while price is pushing higher, the volume support for that movement is deteriorating, which frequently precedes reversals. Bullish divergences work inversely, identifying situations where price makes new lows without corresponding weakness in volume flow, suggesting that selling pressure is exhausted and a reversal higher is probable. These divergence signals are plotted as distinct diamond shapes on the indicator, making them visually prominent for trader attention.
The accumulation and distribution zone detection provides a longer-term context for understanding institutional positioning. The indicator uses the bars-since function to track consecutive periods where the net flow EMA has remained positive or negative. When buying pressure has persisted for at least five consecutive bars, average intensity exceeds zero point six indicating strong closes within bar ranges, and volume is elevated above the threshold, the indicator identifies an accumulation zone. These zones suggest that smart money is systematically building long positions across multiple bars despite potentially choppy or sideways price action. Distribution zones are identified through the inverse criteria, revealing periods when institutions are systematically exiting or building short positions. These zones are visualized through colored fills on the indicator pane, creating a backdrop that helps traders understand the broader volume flow context beyond individual bar signals.
The signal strength scoring system provides a quantitative measure of conviction for each buy or sell signal. Rather than treating all signals as equal, the indicator assigns point values to different signal components: twenty-five points for the buy flow EMA-SMA crossover, twenty-five points for the net flow EMA-SMA crossover, twenty points for high volume presence, fifteen points for positive flow momentum, and fifteen points for bullish divergence presence. These points are summed to create a buy score that can range from zero to one hundred percent, with higher scores indicating that multiple independent confirmation factors are aligned. The same methodology creates a sell score, and these scores are displayed in the information table, allowing traders to quickly assess whether a signal represents a tentative suggestion or a high-conviction setup. This scoring approach transforms the indicator from a binary signal generator into a nuanced probability assessment tool.
The visual presentation of the indicator demonstrates exceptional attention to user experience and information density. The primary display shows the net flow EMA as a thick colored line that transitions between green when above zero and above its SMA, indicating strong buying, to a lighter green when above zero but below the SMA, indicating weakening buying, to red when below zero and below the SMA, indicating strong selling, to a lighter red when below zero but above the SMA, indicating weakening selling. This color gradient provides immediate visual feedback about both direction and momentum of volume flows. The net flow SMA is overlaid in orange as a reference line, and a zero line is drawn to clearly delineate positive from negative territory. Behind these lines, a histogram representation of the raw net flow—scaled down by thirty percent for visibility—shows bar-by-bar flow with color intensity reflecting whether flow is strengthening or weakening compared to the previous bar. This layered visualization allows traders to simultaneously see the raw data, the smoothed trend, and the trend of the trend, accommodating both short-term and longer-term trading perspectives.
The cumulative delta line adds a macro perspective by maintaining a running sum of all volume deltas divided by one million for scale, plotted in purple as a separate series. This cumulative measure acts similar to an on-balance volume calculation but with the sophisticated volume attribution methodology of this indicator, creating a long-term sentiment gauge that can reveal whether an asset is under sustained accumulation or distribution across days, weeks, or months. Divergences between this cumulative delta and price can identify major trend exhaustion or reversal points that might not be visible in the shorter-term flow measurements.
The signal plotting uses shape-based markers rather than background colors or arrows to maximize clarity while preserving chart space. Strong buy signals—meeting multiple criteria including EMA-SMA crossover, high volume, and positive momentum—appear as full-size green triangle-up shapes at the bottom of the indicator pane. Strong sell signals appear as full-size red triangle-down shapes at the top. Regular buy and sell signals that meet fewer criteria appear as smaller, semi-transparent circles, indicating they warrant attention but lack the full confirmation of strong signals. Divergence-based signals appear as distinct diamond shapes in cyan for bullish divergences and orange for bearish divergences, ensuring these critical reversal indicators are immediately recognizable and don't get confused with momentum-based signals. This multi-tiered signal hierarchy helps traders prioritize their analysis and avoid signal overload.
The information table in the top-right corner of the indicator pane provides real-time quantitative feedback on all major calculation components. It displays the current bar's buy volume and sell volume in millions with appropriate color coding, the imbalance percentage with color indicating whether it exceeds the threshold, the average intensity score showing whether closes are generally near highs or lows, the flow momentum value, and the current buy and sell scores. This table transforms the indicator from a purely graphical tool into a quantitative dashboard, allowing discretionary traders to incorporate specific numerical thresholds into their decision frameworks. For example, a trader might require that buy score exceed seventy percent and intensity exceed zero point six-five before taking a long position, creating objective entry criteria from subjective chart reading.
The background shading that occurs during very high volume periods provides an ambient alert system that doesn't require focused attention on the indicator pane. When volume spikes to one point five times the threshold and net flow EMA is positive, a very light green background appears across the entire indicator pane; when volume spikes with negative net flow, a light red background appears. These backgrounds create a subliminal awareness of exceptional market participation moments, ensuring traders notice when the market is making important decisions even if they're focused on price action or other indicators at that moment.
The alert system built into the indicator allows traders to receive notifications for strong buy signals, strong sell signals, bullish divergences, bearish divergences, and very high volume events. These alerts can be configured in TradingView to send push notifications to mobile devices, emails, or webhook calls to automated trading systems. This functionality transforms the indicator from a passive analysis tool into an active monitoring system that can watch markets continuously and notify the trader only when significant volume flow developments occur. For traders monitoring multiple instruments, this alert capability is invaluable for efficient time allocation, allowing them to analyze other opportunities while being instantly notified when this indicator identifies high-probability setups on their watch list.
The coding implementation demonstrates advanced Pine Script techniques including the use of request.security_lower_tf to access intrabar data, array manipulation to process variable-length intrabar arrays, proper variable scoping with var keyword for persistent state management across bars, and efficient conditional logic that prevents unnecessary calculations. The code structure with clearly delineated sections for inputs, calculations, signal generation, plotting, and alerts makes it maintainable and educational for those studying Pine Script development. The use of input groups with custom headers creates an organized settings panel that doesn't overwhelm users with dozens of ungrouped parameters, while still providing substantial customization capability for advanced users who want to optimize the indicator for specific instruments or timeframes.
For practical trading application, this indicator excels in several specific use cases. Scalpers and day traders can use the intrabar analysis to identify accumulation or distribution happening within the bars of their entry timeframe, providing early entry signals before momentum indicators or price patterns complete. Swing traders can use the cumulative delta and accumulation-distribution zones to understand whether short-term pullbacks in an uptrend are being bought or sold, helping distinguish between healthy retracements and trend reversals. Position traders can use the divergence detection to identify major turning points where price extremes are not supported by volume, providing low-risk entry points for counter-trend positions or warnings to exit with-trend positions before significant reversals.
The indicator is particularly valuable in ranging markets where price-based indicators produce numerous false breakout signals. By requiring that breakouts be accompanied by volume flow imbalances, the indicator filters out failed breakouts driven by low participation. When price breaks a range boundary accompanied by a strong buy or sell signal with high buy or sell score and very high volume, the probability of successful breakout follow-through increases dramatically. Conversely, when price breaks a range but the indicator shows low imbalance, opposing flow direction, or low volume, traders can fade the breakout or at minimum avoid chasing it.
During trending markets, the indicator helps traders identify the healthiest entry points by revealing where pullbacks are being accumulated by smart money. A trending market will show the cumulative delta continuing in the trend direction even as price pulls back, and accumulation zones will form during these pullbacks. When price resumes the trend, the indicator will generate strong buy or sell signals with high scores, providing objective entry points with clear invalidation levels. The flow momentum component helps traders stay with trends longer by distinguishing between healthy momentum pauses—where momentum goes to zero but doesn't reverse—and actual momentum reversals where opposing pressure is building.
The VWAP deviation weighting adds particular value for traders of liquid instruments like major forex pairs, stock indices, and high-volume stocks where VWAP is widely watched by institutional participants. When price deviates significantly from the intrabar VWAP and volume flows in the direction of that deviation with elevated weighting, it indicates that the move away from fair value is being driven by conviction rather than mechanical order flow. This suggests the deviation will likely extend further, creating continuation trading opportunities. Conversely, when price deviates from intrabar VWAP but volume flow shows reduced intensity or opposing direction despite the weighting, it suggests the deviation will revert to VWAP, creating mean reversion opportunities.
The ATR normalization option makes the indicator values comparable across different volatility regimes and different instruments. Without normalization, a one-million share buy-sell imbalance might be significant for a low-volatility stock but trivial for a high-volatility cryptocurrency. By normalizing the delta by ATR, the indicator accounts for the typical price movement capacity of the instrument, making signal thresholds and comparison values meaningful across different trading contexts. This is particularly valuable for traders running the indicator on multiple instruments who want consistent signal quality regardless of the underlying instrument characteristics.
The configurable decay factor allows traders to adjust how persistent they want volume flows to remain influential. For very short-term scalping, a lower decay factor like zero point five will cause volume imbalances to dissipate quickly, keeping the indicator focused only on very recent flows. For longer-term position trading, a higher decay factor like zero point nine-five will allow significant volume events to influence the indicator for many bars, revealing longer-term accumulation and distribution patterns. This flexibility makes the single indicator adaptable to trading styles ranging from one-minute scalping to daily chart position trading simply by adjusting the decay parameter and the lookback bars.
The minimum imbalance percentage setting provides crucial noise filtering that can be optimized per instrument. Highly liquid instruments with tight spreads might show numerous small imbalances that are meaningless, requiring a higher threshold like thirty-five or forty percent to filter noise effectively. Thinly traded instruments might rarely show extreme imbalances, requiring a lower threshold like fifteen or twenty percent to generate adequate signals. By making this threshold user-configurable with a wide range, the indicator accommodates the full spectrum of market microstructure characteristics across different instruments and timeframes.
In conclusion, the Intrabar Volume Flow Intelligence indicator represents a comprehensive volume analysis system that combines intrabar data access, sophisticated volume attribution algorithms, multi-timeframe smoothing, statistical filtering, divergence detection, zone identification, and intelligent signal scoring into a cohesive analytical framework. It provides traders with visibility into market dynamics that are invisible to price-only analysis and even to conventional volume analysis, revealing the true intentions of market participants through their actual transaction behavior within each bar. The indicator's strength lies not in any single feature but in the integration of multiple analytical layers that confirm and validate each other, creating high-probability signal generation that can form the foundation of complete trading systems or provide powerful confirmation for discretionary analysis. For traders willing to invest time in understanding its components and optimizing its parameters for their specific instruments and timeframes, this indicator offers a significant informational advantage in increasingly competitive markets where edge is derived from seeing what others miss and acting on that information before it becomes consensus.
HTR Reclaim Hunter
🏹 HTR Reclaim Hunter
(1H Execution + Zones + 4H Bias)
HTR Reclaim Hunter is a trend-continuation indicator designed to identify high-probability pullback & reclaim entries using multi-timeframe bias, EMA structure, and dynamic reclaim zones.
This indicator is best suited for swing trading and intraday continuation setups, especially in trending markets.
🔑 CORE CONCEPT
Trade WITH the higher-timeframe trend.
Enter on pullbacks.
Confirm strength on reclaim.
HTR Reclaim Hunter combines:
4H trend bias
1H execution logic
EMA reclaim structure
Supply & demand reclaim zones
Built-in SL / TP visualization
🧭 RECOMMENDED SETTINGS
Best timeframe: 1H (designed for this)
Markets: Stocks, Crypto, Futures, Forex
Works best in: Trending markets (not chop)
📊 WHAT YOU SEE ON THE CHART
🔹 EMA Structure
EMA 50 (green): Trend filter
EMA 9 (colored): Momentum & pullback guide
🔹 Reclaim Zones
Green boxes: Support / demand zones
Red boxes: Resistance / supply zones
These zones highlight areas where price previously reacted and may reclaim.
🔹 Trade Signals
LONG label: Bullish reclaim setup
SHORT label: Bearish reclaim setup
🔹 Risk Levels (Optional)
Stop Loss (Red)
TP1 (Orange)
TP2 (Green)
🟢 LONG TRADE RULES
A LONG signal appears when ALL of the following are true:
4H trend is bullish
Price above 4H EMA 50
EMA 50 is rising
1H trend is bullish
Price above EMA 50
EMA 9 above EMA 50
Pullback occurs
Price pulls back below EMA 9
Reaches or taps EMA 50
Reclaim confirmation
Strong bullish candle closes back above EMA 9
Candle is not a doji
Signal prints
A green LONG label appears
👉 This indicates a trend continuation entry, not a reversal.
🔴 SHORT TRADE RULES
A SHORT signal appears when ALL of the following are true:
4H trend is bearish
Price below 4H EMA 50
EMA 50 is falling
1H trend is bearish
Price below EMA 50
EMA 9 below EMA 50
Pullback occurs
Price pulls back above EMA 9
Reaches or taps EMA 50
Reclaim confirmation
Strong bearish candle closes back below EMA 9
Candle is not a doji
Signal prints
A red SHORT label appears
🛑 STOP LOSS & TAKE PROFIT
When enabled, the indicator automatically plots:
Stop Loss
Based on recent swing high / low
TP1
1R (1× risk)
TP2
Configurable runner target (default 2R)
These are visual guides only — always manage risk according to your plan.
⚠️ IMPORTANT NOTES
This indicator is not meant for ranging or choppy markets
Best results occur when:
EMA 50 is clearly sloped
Price respects reclaim zones
Always confirm with:
Market structure
Volume
Higher-timeframe context
🔔 ALERTS
Alerts are available for:
HRH LONG
HRH SHORT
Alerts trigger on confirmed reclaim signals, not on every pullback.
❗ DISCLAIMER
This indicator is for educational purposes only.
It does not provide financial advice.
Always test and manage risk appropriately.
🏹 FINAL TIP
HTR Reclaim Hunter works best when you are patient.
Skip chop.
Wait for clean trends.
Hunt only high-quality reclaims.
If you want, I can also:
Write a short description version
Create a “Quick Start” section
Add example captions for screenshots
Help you choose TradingView tags & category
trend-following
ema reclaim
pullback strategy
multi-timeframe
price action
TBSTurtle Soup Body Pattern
The Turtle Soup Body is a price action pattern derived from the classic Turtle Soup setup, designed to identify false breakouts beyond recent highs or lows, with a strong emphasis on the candle body close.
This pattern occurs when price briefly breaks above a recent swing high (or below a recent swing low), triggering breakout traders, but then fails to sustain the move. Instead of focusing only on wicks, the Turtle Soup Body setup requires the candle body to close back inside the previous range, signaling rejection and loss of breakout momentum.
Key characteristics of the Turtle Soup Body pattern include:
A clearly defined recent high or low (typically a 20-period high/low)
Price breaks the level intraday, creating a false breakout
The candle body closes back below the high (for short setups) or above the low (for long setups)
Confirmation that market participants are trapped on the wrong side of the move
The Turtle Soup Body pattern is commonly used as a mean-reversion or reversal setup, offering tight stop-loss placement and favorable risk–reward ratios. It is especially effective in ranging or overextended market conditions and can be applied across multiple timeframes in the Forex market.
RSI Trend Authority [JOAT]RSI Trend Authority - VAR-RSI with OTT Trend Detection System
Introduction
RSI Trend Authority is an open-source overlay indicator that combines Variable Index Dynamic Average (VAR) smoothed RSI with the Optimized Trend Tracker (OTT) to create a complete trend detection and signal generation system. Unlike traditional RSI which oscillates in a separate pane, this indicator scales the RSI to price and overlays it directly on your chart, making trend analysis more intuitive.
The indicator generates clear BUY and SELL signals when the smoothed RSI crosses the OTT trailing stop line, providing actionable entry points with trend confirmation.
Originality and Purpose
This indicator is NOT a simple mashup of RSI and moving averages. It is an original implementation that transforms RSI into a trend-following overlay system:
Why VAR Smoothing? Traditional RSI is noisy and produces many false signals. The Variable Index Dynamic Average (VAR) is an adaptive smoothing algorithm based on the Chande Momentum Oscillator principle. It adjusts its smoothing factor based on market conditions - responding quickly during trends and smoothing out during choppy markets. This creates an RSI that filters noise while preserving genuine momentum shifts.
Why OTT Trailing Stop? The Optimized Trend Tracker (OTT) is a percentage-based trailing stop mechanism that only moves in the direction of the trend. When VAR-RSI crosses above OTT, a bullish trend is confirmed; when it crosses below, a bearish trend is confirmed. This provides clear, actionable signals rather than subjective interpretation.
Price Scaling Innovation: By scaling RSI (0-100) to price using the formula (RSI * close / 50), the indicator overlays directly on the price chart. This allows traders to see how momentum relates to actual price levels, making trend analysis more intuitive than a separate oscillator pane.
ATR Boundaries: Optional volatility-based boundaries show when price is extended relative to its normal range, helping identify potential reversal zones.
How the components work together:
VAR smoothing removes RSI noise while preserving trend information
OTT provides a dynamic trailing stop that generates clear crossover signals
Price scaling allows direct overlay on the chart for intuitive analysis
ATR boundaries add volatility context for profit target estimation
Core Components
1. VAR-RSI (Variable Index Dynamic Average RSI)
The foundation of this indicator is the VAR smoothing algorithm applied to RSI. VAR is an adaptive moving average that adjusts its smoothing factor based on the Chande Momentum Oscillator principle:
f_var_calc(float data, int length) =>
int a = 9
float b = data > nz(data ) ? data - nz(data ) : 0.0
float c = data < nz(data ) ? nz(data ) - data : 0.0
float d = math.sum(b, a)
float e = math.sum(c, a)
float f = nz((d - e) / (d + e))
float g = math.abs(f)
float h = 2.0 / (length + 1)
float x = ta.sma(data, length)
This creates an RSI that:
Responds quickly during trending conditions
Smooths out during choppy, sideways markets
Reduces false signals compared to raw RSI
2. OTT (Optimized Trend Tracker)
The OTT acts as a dynamic trailing stop that follows the VAR-RSI:
In uptrends, OTT trails below the VAR-RSI line
In downtrends, OTT trails above the VAR-RSI line
The OTT Percent parameter controls how closely it follows
When VAR-RSI crosses above OTT, a bullish trend is confirmed. When VAR-RSI crosses below OTT, a bearish trend is confirmed.
3. Price Scaling
The RSI (0-100 scale) is converted to price scale using:
float scaleFactor = close / 50.0
float varRSIScaled = varRSI * scaleFactor
This allows the indicator to overlay directly on price, showing how momentum relates to actual price levels.
Visual Components
VAR-RSI Line (Cyan/Magenta)
The main indicator line with gradient coloring:
Cyan gradient when RSI is above 50 (bullish)
Magenta gradient when RSI is below 50 (bearish)
Line thickness of 3 for clear visibility
OTT Line (Yellow Circles)
The trailing stop line displayed as circles:
Acts as dynamic support in uptrends
Acts as dynamic resistance in downtrends
Crossovers generate trading signals
Trend Fill
The area between VAR-RSI and OTT is filled:
Cyan fill during bullish trends
Magenta fill during bearish trends
Fill transparency allows price visibility
Buy position and LONG on Dashboard with a Uptrend:
ATR Boundaries (Optional)
Dotted lines showing volatility-based price boundaries:
Upper band: Close + (ATR x Multiplier)
Lower band: Close - (ATR x Multiplier)
Color matches current trend direction
Buy/Sell Signals
Clear labels appear at signal points:
BUY label below bar when VAR-RSI crosses above OTT
SELL label above bar when VAR-RSI crosses below OTT
Additional glow circles highlight signal bars
Bar Coloring
Optional feature that colors price bars:
Cyan bars during bullish trend
Magenta bars during bearish trend
Dashboard Panel
The 8-row dashboard provides comprehensive status information:
Signal: Current position - LONG or SHORT (large text)
VAR-RSI: Current smoothed RSI value (large text)
RSI State: OVERBOUGHT, OVERSOLD, BULLISH, or BEARISH
OTT Trend: UPTREND or DOWNTREND based on OTT direction
Bars Since: Number of bars since last signal
Price: Current close price (large text)
OTT Level: Current OTT trailing stop value
Input Parameters
RSI Settings:
RSI Length: Period for RSI calculation (default: 100)
Source: Price source (default: close)
VAR Settings:
VAR Length: Adaptive smoothing period (default: 50)
OTT Settings:
OTT Period: Trailing stop calculation period (default: 30)
OTT Percent: Distance percentage for trailing stop (default: 0.2)
ATR Trend Boundaries:
Show ATR Boundaries: Toggle visibility (default: enabled)
ATR Length: Period for ATR calculation (default: 14)
ATR Multiplier: Distance multiplier (default: 2.0)
Display Options:
Show Buy/Sell Signals: Toggle signal labels (default: enabled)
Show Status Table: Toggle dashboard (default: enabled)
Table Position: Choose corner placement
Color Bars by Trend: Toggle bar coloring (default: enabled)
Color Scheme:
Bullish Color: Main bullish color (default: cyan)
Bearish Color: Main bearish color (default: magenta)
OTT Line: Trailing stop color (default: yellow)
VAR-RSI Line: Main line color (default: teal)
ATR colors for boundaries
How to Use RSI Trend Authority
Signal-Based Trading:
Enter LONG when BUY signal appears (VAR-RSI crosses above OTT)
Enter SHORT when SELL signal appears (VAR-RSI crosses below OTT)
Use the OTT line as a trailing stop reference
Trend Confirmation:
Cyan fill indicates bullish trend - favor long positions
Magenta fill indicates bearish trend - favor short positions
Check RSI State in dashboard for momentum context
Using the Dashboard:
Monitor "Bars Since" to assess signal freshness
Check RSI State for overbought/oversold warnings
Use OTT Level as a reference for stop placement
ATR Boundaries:
Price near upper ATR band in uptrend suggests extension
Price near lower ATR band in downtrend suggests extension
Boundaries help identify potential reversal zones
Parameter Optimization
For Faster Signals:
Decrease RSI Length (try 50-80)
Decrease VAR Length (try 30-40)
Decrease OTT Period (try 15-25)
For Smoother Signals:
Increase RSI Length (try 120-150)
Increase VAR Length (try 60-80)
Increase OTT Period (try 40-50)
For Tighter Stops:
Decrease OTT Percent (try 0.1-0.15)
For Wider Stops:
Increase OTT Percent (try 0.3-0.5)
Alert Conditions
Three alert conditions are available:
Buy Signal: VAR-RSI crosses above OTT
Sell Signal: VAR-RSI crosses below OTT
Trend Change: OTT direction changes
Understanding the OTT Calculation
The OTT uses a percentage-based trailing mechanism:
float farkOTT = mavgOTT * ottPercent * 0.01
float longStopCalc = mavgOTT - farkOTT
float shortStopCalc = mavgOTT + farkOTT
longStop := mavgOTT > nz(longStop ) ? math.max(longStopCalc, nz(longStop )) : longStopCalc
shortStop := mavgOTT < nz(shortStop ) ? math.min(shortStopCalc, nz(shortStop )) : shortStopCalc
This ensures the trailing stop only moves in the direction of the trend, never against it.
Best Practices
Use on 1H timeframe or higher for more reliable signals
Wait for signal confirmation before entering trades
Consider RSI State when evaluating signal quality
Use ATR boundaries for profit target estimation
The longer RSI length (100) provides smoother trend detection
Combine with support/resistance analysis for better entries
Limitations
Signals may lag during rapid price movements due to smoothing
Works best in trending markets; may whipsaw in ranges
The overlay nature means RSI values are scaled, not absolute
Default parameters are optimized for crypto and forex; adjust for other markets
Technical Notes
This indicator is written in Pine Script v6 and uses:
VAR (Variable Index Dynamic Average) for adaptive smoothing
OTT (Optimized Trend Tracker) for trailing stop calculation
ATR for volatility-based boundaries
Gradient coloring for intuitive trend visualization
The source code is open and available for review and modification.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management.
-Made with passion by officialjackofalltrades
ORB Session BreakoutORB Session Breakout
Overview
The ORB Session Breakout indicator automatically identifies Opening Range Breakouts across multiple trading sessions (Asia, London, and New York) and provides visual trade setups with entry, stop loss, and take profit levels.
Opening Range Breakout (ORB) is a classic trading strategy that captures momentum when price breaks out of an initial trading range established at the start of a session. This indicator automates the entire process - from detecting the opening range to plotting trade setups when breakouts occur.
🎯 Key Features
Multi-Session Support
Asia Session - Captures the Asian market open (default: 19:00-19:15 NY time)
London Session - Captures the London market open (default: 03:00-03:15 NY time)
New York Session - Captures the NY market open (default: 09:30-09:45 NY time)
Each session is fully customizable with independent time windows and colors
Enable/disable individual sessions based on your trading preferences
Automatic Trade Visualization
Entry Level - Marked at the breakout candle close
Stop Loss Zone - Configurable as ORB High/Low or Breakout Candle High/Low
Take Profit Zone - Calculated automatically based on your Risk:Reward ratio
Visual zones make it easy to see risk/reward at a glance
Smart Breakout Detection
Detects breakouts on the exact candle that closes beyond the ORB range
Supports direction changes - if price breaks one way then reverses, a new trade is signaled
Configurable max breakouts per session (1-4) to control trade frequency
Tracking hours setting limits how long after the ORB to look for entries
Futures Compatible
Special detection logic for futures markets where session times may fall during market close
Works reliably on instruments with non-standard trading hours
📊 How It Works
Opening Range Formation
At the start of each enabled session, the indicator tracks the high and low of the first candle(s)
This range becomes your ORB box (displayed in the session color)
Breakout Detection
When a candle closes above the ORB High → LONG signal
When a candle closes below the ORB Low → SHORT signal
The breakout candle is highlighted in yellow (customizable)
Trade Setup Visualization
Entry line drawn at the breakout candle's close price
Stop Loss placed at ORB Low (longs) or ORB High (shorts) - or breakout candle extreme
Take Profit calculated as: Entry + (Risk × R:R Ratio) for longs
Direction Changes
If you're in a LONG and price closes below the ORB Low, the indicator signals a SHORT
This counts as your 2nd breakout (configurable up to 4 per session)
💡 Trading Tips
Best Practices
Wait for candle close - The indicator only signals on confirmed closes beyond the ORB, reducing false breakouts
Use with trend - ORB breakouts work best when aligned with the higher timeframe trend
Respect the levels - The ORB High/Low often act as support/resistance throughout the session
Monitor multiple sessions - Sometimes the best setups come from Asia or London, not just NY
Recommended Settings by Style
Conservative: Max Breakouts = 1, R:R = 2.0+, SL Mode = ORB Level
Aggressive: Max Breakouts = 3-4, R:R = 1.5, SL Mode = Breakout Candle
Scalping: Shorter tracking hours (1-2), tighter R:R (1.0-1.5)
What to Avoid
Trading ORB breakouts during major news events (high volatility can cause whipsaws)
Taking every signal without considering market context
Using on timeframes higher than 1 hour (the ORB concept works best intraday)
🔔 Alerts
The indicator includes built-in alerts for:
Entry Signal - When a breakout is detected (LONG or SHORT)
Take Profit Hit - When price reaches the TP level
Stop Loss Hit - When price reaches the SL level
To set up alerts: Right-click on the chart → Add Alert → Select "ORB Session Breakout"
📝 Notes
This indicator is designed for intraday trading on timeframes up to 1 hour
Session times are based on the selected timezone (default: America/New_York)
The indicator works on all markets including Forex, Futures, Stocks, and Crypto
For futures with non-standard hours, the indicator includes special detection logic
Fed Balance Sheet (Candles)Fed Balance Sheet (Candles) - TradingView Description
📊 OVERVIEW
Fed Balance Sheet (Candles) transforms the Federal Reserve's total assets into an intuitive candlestick visualization, allowing you to track monetary policy changes with the same visual language you use for price action.
This indicator pulls real-time data directly from FRED (Federal Reserve Economic Data) and displays the Total Assets of All Federal Reserve Banks as dynamic candles on your chart, making it effortless to correlate central bank liquidity with market movements.
🎯 WHY THIS MATTERS
The Federal Reserve's balance sheet is one of the most powerful leading indicators in global markets. When the Fed expands its balance sheet (Quantitative Easing), it injects liquidity into the financial system, historically correlating with:
Rising asset prices (stocks, crypto, commodities)
Lower volatility
Risk-on sentiment
Currency devaluation
When the Fed contracts its balance sheet (Quantitative Tightening), liquidity drains from markets, often leading to:
Asset price pressure
Increased volatility
Risk-off sentiment
Dollar strength
By visualizing this as candles, you can instantly see:
The pace of change (candle size)
The direction (green = expansion, red = contraction)
Acceleration or deceleration (consecutive candles in same direction)
Pivots in monetary policy (color changes from green to red or vice versa)
🔧 HOW IT WORKS
Data Source
Source: Federal Reserve Economic Data (FRED)
Metric: Total Assets of All Federal Reserve Banks
Unit: Displayed in Trillions of USD for easy reading
Frequency: Weekly updates (every Wednesday)
Candlestick Construction
Since balance sheet data is reported as a single number each week (not traditional open-high-low-close), this indicator creates candles by comparing each period to the previous one:
Open = Last week's balance sheet value
Close = This week's balance sheet value
High = The higher of the two values
Low = The lower of the two values
This captures directional movement and magnitude of change, making it intuitive for traders accustomed to candlestick analysis.
Color Scheme
🟢 GREEN CANDLES (Expanding Balance Sheet)
When this week's value is higher than last week's
Interpretation: Fed is adding liquidity (Quantitative Easing)
Historically bullish for risk assets
🔴 RED CANDLES (Contracting Balance Sheet)
When this week's value is lower than last week's
Interpretation: Fed is removing liquidity (Quantitative Tightening)
Historically bearish or neutral for risk assets
Value Label
A floating label displays the current balance sheet value in trillions (e.g., "$8.75T") so you always know the exact figure at a glance.
📈 PRACTICAL APPLICATIONS
1. Market Regime Identification
Strings of green candles = Liquidity-driven bull markets
Strings of red candles = Tightening-induced bear markets or corrections
Color transitions = Potential market inflection points
2. Correlation Analysis
Overlay on stock indices (SPY, QQQ, IWM)
Overlay on crypto (BTC, ETH)
Overlay on commodities (Gold, Silver)
Observe how asset prices react to Fed liquidity changes in real-time
3. Macro Timing
Large green candles = Aggressive easing (crisis response)
Large red candles = Aggressive tightening (inflation fighting)
Small candles = Neutral policy (Fed on hold)
4. Risk Management
Shift portfolio allocation based on liquidity environment
Reduce leverage during red candle trends
Increase exposure during green candle trends
Use as confirmation for other technical signals
5. Multi-Timeframe Context
Daily charts: See how daily price action relates to weekly Fed data
Weekly charts: Perfect alignment with data release frequency
Monthly charts: Visualize long-term monetary cycles spanning years
⚙️ SETTINGS
Zero configuration needed. Simply add the indicator to any chart and it works immediately.
The indicator automatically:
Overlays on your main chart
Uses the left price scale (won't interfere with asset prices)
Updates with the latest Fed data
Displays values in trillions for clean readability
🎨 VISUAL DESIGN PHILOSOPHY
The indicator uses semi-transparent candle bodies with vibrant borders to maintain visibility without obscuring your price action. The color scheme follows universal chart conventions where green represents growth/expansion and red represents decline/contraction.
It's designed to blend seamlessly into any chart theme while providing immediate visual clarity about the Fed's monetary stance.
📚 WHAT YOU NEED TO KNOW
Data Availability
Historical data available from December 2002 (over 20 years of Fed policy)
Updates every Wednesday (Federal Reserve's reporting schedule)
Typically published with a 1-week lag
How the Data Appears
On weekdays: Shows the most recent Wednesday's data
On weekends: Shows Friday's data (which is the prior Wednesday's figure)
Updates automatically when new data is released
Scale Considerations
The Fed's balance sheet is measured in trillions, while most assets are priced much lower. The indicator uses the left price scale by default to avoid conflicts with your main asset's price scale. You can easily move it to a separate pane if you prefer.
🧠 INTERPRETATION GUIDE
Historical QE Phases (Green Candles)
2008-2014: Financial Crisis Response
The Fed's balance sheet expanded from under $1T to ~$4.5T to stabilize markets after the mortgage crisis.
2020: COVID-19 Response
Rapid expansion to ~$7T as the Fed stepped in during pandemic lockdowns.
2020-2022: Extended Support
Balance sheet reached historic peak of ~$9T.
Historical QT Phases (Red Candles)
2017-2019: First Modern QT Attempt
The Fed tried to normalize its balance sheet, reducing it from ~$4.5T to ~$3.8T before pivoting.
2022-Present: Inflation-Fighting QT
The Fed began shrinking its balance sheet to combat inflation, letting bonds mature without replacement.
Key Insights
Size matters, but rate of change matters MORE.
A $9T balance sheet growing slowly has different implications than a $5T balance sheet growing rapidly.
Watch for acceleration.
Increasingly large candles (up or down) signal a policy shift that markets will notice.
Plateaus mean "wait and see."
Tiny candles indicate the Fed is holding steady and watching economic data.
Reversals are major events.
When candles switch from green to red (or vice versa), the Fed has changed course—these are critical market turning points.
🎓 EDUCATIONAL VALUE
This indicator helps you understand:
The mechanics of monetary policy through visual learning
The lag between Fed actions and market reactions by observing temporal correlation
The scale of modern central banking (trillions put into perspective)
The relationship between liquidity and asset prices (cause and effect in action)
Many traders talk about "don't fight the Fed" but never actually track what the Fed is doing. Now you can see it as clearly as you see price action.
🔗 RELATED CONCEPTS
For comprehensive macro analysis, consider also tracking:
Fed Funds Rate (short-term interest rates)
M2 Money Supply (broader measure of money in circulation)
Treasury Yield Curves (bond market expectations)
Dollar Index (DXY) (currency strength)
VIX (market fear/volatility)
The Fed's balance sheet is just one piece of the puzzle, but it's arguably the most important one for understanding liquidity conditions.
⚠️ DISCLAIMER
This indicator displays publicly available economic data from the Federal Reserve. It is for informational and educational purposes only and does not constitute financial advice.
Important considerations:
Past monetary policy does not guarantee future market outcomes
Correlation does not equal causation
Asset prices are influenced by many factors beyond Fed liquidity
Always use proper risk management
Consult with qualified financial professionals before making investment decisions
Trading involves substantial risk of loss and is not suitable for everyone.
📜 VERSION HISTORY
Version 1.0 - Initial Release
Fed balance sheet visualized as candlesticks
Real-time FRED data integration
Automatic display in trillions
Dynamic color coding (green/red)
Current value label with exact figure
💡 WHY CANDLES?
You might wonder: "Why show the Fed's balance sheet as candles instead of a line?"
Because candles tell stories that lines can't.
A line shows you where we are
Candles show you how we got here, how fast we're moving, and what momentum looks like
Candles make the Fed's actions feel immediate and tangible
Candles connect macro data to the chart language you already speak
When you see three big green candles in a row on the Fed balance sheet while your crypto or stock portfolio is rallying, you feel the connection. When you see the candles turn red and shrink, you understand the headwinds forming.
It transforms dry economic data into actionable market intelligence.
📞 SUPPORT & FEEDBACK
If you find this indicator valuable:
⭐ Like and favorite to help others discover it
📝 Comment with your use cases and insights
🔔 Follow for updates and new macro indicators
Your feedback drives improvements and helps build better tools for the trading community.
🚀 THE BOTTOM LINE
The Fed's balance sheet is the tide that lifts or lowers all boats.
Whether you're trading stocks, crypto, forex, or commodities—whether you're a day trader or long-term investor—understanding the Fed's liquidity operations gives you an edge.
This indicator makes that understanding visual, immediate, and actionable.
Stop guessing about macro conditions. Start seeing them.
"Don't fight the Fed" - Wall Street Wisdom
Now you can see exactly what they're doing—in the same language you use to read price action.
May your trades ride the tide of liquidity. 🌊📈
MACD Matrix: Angle & SettlementThis indicator is a comprehensive Multi-Timeframe (MTF) Dashboard designed for technical traders who rely on MACD not just for crossovers, but for Momentum Angle and Settlement (Hooks).
Instead of cluttering your screen with 5 different MACD charts, this Matrix calculates the math in the background and presents a clean "Heads-Up Display" of the MACD state across your specific timeframes (Default: 3m, 15m, 1h, 4h, 16h).
The Concept: "Angle Settlement"
Standard MACD indicators only show you when a cross happens. By then, the move is often halfway over. This script focuses on the Angle (Slope) of the MACD line to predict turns before they happen:
Steep Angle: Momentum is accelerating. (Strong Trend)
Settling Angle: The slope is flattening out. The MACD line is "hooking." (Reversal/Cross Imminent)
Dashboard Columns Explained
TF (Timeframe): Auto-formats your settings into readable text (e.g., "240" becomes "4h").
Zone:
> 0 (Green): MACD is above the Zero Line (Bullish Trend context).
< 0 (Red): MACD is below the Zero Line (Bearish Trend context).
Cross:
PCO (Green): Positive Crossover (MACD > Signal).
NCO (Red): Negative Crossover (MACD < Signal).
Deg (°):
The calculated mathematical angle of the MACD line.
Positive (+): Momentum is rising.
Negative (-): Momentum is falling.
State (The Strategy):
STEEP (Bright Color): The angle is increasing. Do not trade against this momentum.
SETTLE (Dim Color): The angle is decreasing compared to the previous bar. The momentum is "cooling off," often signaling a "Hook" or an upcoming crossover.
Settings & Customization
Custom Timeframes: You can freely change TF-1, TF-2, etc., in the settings. The table labels will auto-update (e.g., if you change 4h to 1D, the table will display "1D").
MACD Lengths: Fully customizable (Default 12, 26, 9).
Angle Sensitivity: A multiplier to calibrate the "Degrees" to your specific asset class (Crypto, Forex, or Indices). If angles look too small, increase this value.
Sameer Bandhara AlertsThis Sameer Bandhara (SB Trader) indicator is a dynamic trailing stop-loss system based on the Average True Range (ATR). Here's a comprehensive breakdown:
It uses ATR to create an adaptive trailing stop that adjusts to market volatility, generating buy/sell signals when price breaks through this dynamic stop level.
Forex/Stocks: Key Value 1.5-2.5, ATR Period 14-20
Crypto: Key Value 2.0-3.0 (higher volatility)
Timeframes: 1H and above (reduces noise)
WoAlgo Premium v3.0
WoAlgo Premium v3.0 - Smart Money Analysis
Overview
** WoAlgo Premium v3.0 ** is an advanced technical analysis indicator designed for educational purposes. This tool combines Smart Money Concepts with multi-factor confluence analysis to help traders identify potential market opportunities across multiple timeframes.
The indicator integrates market structure analysis, order flow concepts, and technical momentum indicators into a comprehensive dashboard system. It is designed to assist traders in understanding institutional trading patterns and market dynamics through visual analysis tools.
### What It Does
This indicator provides:
**1. Smart Money Concepts Analysis**
- Market structure identification (Break of Structure and Change of Character patterns)
- Order block detection with volume confirmation
- Fair value gap recognition
- Liquidity zone mapping (equal highs and lows)
- Premium and discount zone calculations
**2. Multi-Factor Confluence Scoring**
The indicator calculates a proprietary confluence score (0-100) based on five key components:
- Price action analysis (30% weight)
- Volume confirmation (20% weight)
- Momentum indicators (25% weight)
- Trend strength measurement (15% weight)
- Money flow analysis (10% weight)
**3. Multi-Timeframe Analysis**
- Scans 5 different timeframes (5M, 15M, 1H, 4H, Daily)
- Calculates alignment percentage across timeframes
- Displays trend and structure status for each period
**4. Visual Dashboard System**
- Comprehensive main dashboard with 13 metrics
- Real-time screener table with 10 data columns
- Multi-timeframe scanner
- Performance tracking panel
### How It Works
**Market Structure Detection**
The indicator identifies key structural changes in price action:
- **BOS (Break of Structure)**: Indicates trend continuation when price breaks previous swing points
- **CHoCH (Change of Character)**: Signals potential trend reversal when market structure shifts
**Order Block Identification**
Order blocks are detected when:
- Significant volume appears at swing points
- Price shows strong directional movement from these levels
- Enhanced detection with extreme volume confirmation (OB++ markers)
**Fair Value Gap Recognition**
Gaps between candles are identified when:
- Price leaves inefficiencies in the market
- Three consecutive candles create a gap pattern
- Gap size exceeds minimum threshold based on ATR
**Confluence Calculation**
The system evaluates multiple technical factors:
1. **Price Position**: Relative to moving averages (EMA 20, 50, 200)
2. **Volume Analysis**: Standard deviation-based volume spikes
3. **Momentum**: RSI, MACD, Stochastic indicators
4. **Trend Strength**: ADX measurements
5. **Money Flow**: MFI indicator readings
Each factor contributes weighted points to create an overall confluence score that helps assess signal strength.
### Signal Types
**Confirmation Signals (▲ / ▼)**
Generated when:
- EMA crossovers occur (20/50 cross)
- Volume confirmation is present
- RSI is in appropriate zone
- Confluence score exceeds 50%
**Strong Signals (▲+ / ▼+)**
Higher-confidence signals requiring:
- Confluence score above 70%
- Extreme volume confirmation
- Alignment with 200 EMA trend
- MACD confirmation
- Bullish or bearish market structure
**Contrarian Signals (⚡)**
Reversal indicators appearing when:
- RSI reaches extreme levels (<30 or >70)
- Stochastic shows oversold/overbought conditions
- Price touches Bollinger Band extremes
- Potential divergence patterns emerge
**Reversal Zones**
Visual boxes highlighting areas where:
- Market structure conflicts with momentum
- High probability of directional change
- Key support/resistance levels interact
**Smart Trail**
Dynamic stop-loss indicator that:
- Adjusts based on ATR (Average True Range)
- Follows trend direction
- Updates automatically as price moves
- Provides risk management reference points
### Dashboard Components
**Main Dashboard (13 Metrics)**
1. **Confluence Score**: Current bull/bear percentage (0-100)
2. **Market Regime**: Trend classification (Strong Up/Down, Range, Squeeze)
3. **Signal Status**: Active buy/sell signal indication
4. **Structure State**: Current market structure (Bullish/Bearish/Neutral)
5. **Trend Strength**: ADX-based measurement
6. **RSI Level**: Momentum indicator with overbought/oversold zones
7. **MACD Direction**: Trend momentum confirmation
8. **Money Flow Index**: Smart money sentiment
9. **Volume Status**: Current volume relative to average
10. **Volatility Rating**: ATR percentage measurement
11. **ATR Value**: Average true range for position sizing
12. **MTF Alignment**: Multi-timeframe agreement percentage
**Screener Table (10 Columns)**
- Current symbol and timeframe
- Real-time price and percentage change
- Quality rating (star system)
- Active signal type
- Smart trail status
- Market structure state
- MACD direction
- Trend strength percentage
- Bollinger Band squeeze detection
**MTF Scanner (5 Timeframes)**
Displays for each timeframe:
- Trend direction indicator
- Market structure classification
- Visual confirmation with color coding
**Performance Metrics**
- Win rate percentage (simplified calculation)
- Total signals generated
- Current confluence score
- MTF alignment status
- Volatility level
### Settings and Customization
**Preset Styles**
Choose from predefined configurations:
- **Conservative**: Fewer, higher-quality signals
- **Moderate**: Balanced approach (recommended)
- **Aggressive**: More frequent signals
- **Scalper**: Short-term focused
- **Swing**: Longer-term oriented
- **Custom**: Full manual control
**Smart Money Concepts Controls**
- Toggle each feature independently
- Adjust swing length (3-50 periods)
- Enable/disable internal structure
- Control order block display
- Manage breaker block visibility
- Show/hide fair value gaps
- Display liquidity zones
- Premium/discount zone visualization
**Signal Configuration**
- Enable/disable confirmation signals
- Toggle strong signal markers
- Control contrarian signal display
- Show/hide reversal zones
- Smart trail activation
- Sensitivity adjustment (5-50)
**Visual Customization**
- Moving average display options
- MA period adjustments (Fast: 20, Slow: 50, Trend: 200)
- Support/resistance line toggle
- Dynamic S/R lookback period
- Candle coloring based on trend
- Color scheme customization
- Dashboard size options (Small/Normal/Large)
- Position placement (4 corners)
### How to Use
**Step 1: Initial Setup**
1. Add indicator to chart
2. Select appropriate preset or use Custom
3. Adjust timeframe to match trading style
4. Configure dashboard visibility preferences
**Step 2: Analysis Workflow**
1. Check MTF Scanner for timeframe alignment
2. Review Main Dashboard confluence score
3. Observe Market Regime classification
4. Identify active signals on chart
5. Confirm with Smart Money Concepts (order blocks, FVG, structure)
**Step 3: Trade Consideration**
Strong signals (▲+ / ▼+) require:
- Confluence score >70%
- MTF alignment >60%
- Confirmation from multiple dashboard metrics
- Support from Smart Money Concepts
- Appropriate volume levels
**Step 4: Risk Management**
- Use Smart Trail as dynamic stop-loss reference
- Consider ATR for position sizing
- Monitor volatility rating
- Respect support/resistance levels
- Combine with personal risk parameters
### Best Practices
**For Scalping (1M-5M timeframes)**
- Use Scalper preset
- Reduce swing length to 5-7
- Focus on strong signals only
- Monitor MTF alignment closely
- Quick entries near order blocks
**For Intraday Trading (15M-1H timeframes)**
- Use Moderate preset (recommended)
- Default swing length (10)
- Combine confirmation and strong signals
- Check MTF scanner before entry
- Use fair value gaps for entries
**For Swing Trading (4H-D timeframes)**
- Use Swing preset
- Increase swing length to 15-20
- Focus on strong signals
- Require high MTF alignment
- Patient approach with major structure levels
### Technical Specifications
**Indicators Used**
- Exponential Moving Averages (20, 50, 200)
- Hull Moving Average
- Relative Strength Index (14)
- MACD (12, 26, 9)
- Money Flow Index (14)
- Stochastic Oscillator (14, 3)
- ADX / DMI (14)
- Bollinger Bands (20, 2)
- ATR (14)
- Volume Analysis (SMA 20 with standard deviation)
**Calculation Methods**
- Swing detection using pivot high/low functions
- Volume confirmation via statistical analysis
- Multi-factor scoring with weighted components
- Dynamic support/resistance using highest/lowest functions
- Real-time MTF data via security() function
### Limitations and Considerations
**Important Notes**
1. This indicator is designed for educational and analytical purposes only
2. Historical performance does not guarantee future results
3. Signals should be confirmed with additional analysis
4. Market conditions vary and affect indicator performance
5. Not all signals will be profitable
6. Risk management is essential for all trading
**Known Limitations**
- Confluence scoring is algorithmic and not predictive
- MTF analysis requires sufficient historical data
- Effectiveness varies across different market conditions
- Sideways markets may produce conflicting signals
- High volatility can affect signal reliability
- Backtesting results shown are simplified calculations
**Not Suitable For**
- Automated trading without human oversight
- Sole basis for trading decisions
- Guaranteed profit expectations
- Inexperienced traders without proper education
- Trading without risk management plans
### Market Applicability
**Effective On**
- Trending markets (any direction)
- Clear structure formation periods
- Liquid instruments with consistent volume
- Multiple asset classes (forex, stocks, crypto, commodities)
- Various timeframes with appropriate settings
**Less Effective During**
- Extended ranging/choppy conditions
- Extremely low volume periods
- Major news events causing gaps
- Early market open with high spread
- Illiquid instruments with erratic price action
### Risk Disclaimer
**⚠️ IMPORTANT NOTICE**
This indicator is provided for **educational and informational purposes only**. It does not constitute financial advice, investment recommendations, or trading signals.
**Key Risk Factors:**
- Trading financial instruments involves substantial risk of loss
- Past performance does not indicate future results
- No indicator can predict market movements with certainty
- Users should conduct independent research and analysis
- Professional financial advice should be sought when appropriate
- Risk management and position sizing are critical to successful trading
- Users are solely responsible for their trading decisions
**Responsible Usage:**
- Combine with comprehensive market analysis
- Use appropriate stop-loss orders
- Never risk more than you can afford to lose
- Maintain realistic expectations
- Continue education on technical analysis principles
- Test thoroughly on demo accounts before live trading
- Understand all indicator features before using
### Educational Resources
**Understanding Smart Money Concepts**
Smart Money Concepts analyze how institutional traders and large market participants operate. Key principles include:
- Institutional order flow patterns
- Market structure changes
- Liquidity manipulation
- Supply and demand imbalances
- Order block formations
**Multi-Timeframe Analysis Theory**
Analyzing multiple timeframes helps:
- Identify overall market direction
- Improve entry timing
- Confirm trend strength
- Recognize consolidation periods
- Reduce conflicting signals
**Confluence Trading Approach**
Using multiple confirming factors:
- Increases signal reliability
- Reduces false signals
- Provides conviction for trades
- Helps with position sizing
- Improves risk-reward ratios
### Version History
**v3.0 (Current)**
- Multi-factor confluence scoring system
- Complete Smart Money Concepts implementation
- Real-time multi-timeframe analysis
- Four professional dashboard panels
- Enhanced order block detection
- Breaker block identification
- Premium/discount zone calculations
- Smart trail stop-loss system
- Customizable preset configurations
- Performance tracking metrics
**Development Philosophy**
This indicator was developed with focus on:
- Educational value for traders
- Transparent methodology
- Comprehensive feature set
- User-friendly interface
- Flexible customization options
### Technical Support
**For Questions About:**
- Indicator functionality
- Parameter optimization
- Signal interpretation
- Dashboard metrics
- Best practice recommendations
Please use TradingView's comment section below. The developer monitors comments and provides assistance to users learning to use the indicator effectively.
### Acknowledgments
This indicator implements concepts from:
- Smart Money Concepts trading methodology
- Multi-timeframe analysis techniques
- Technical indicator theory
- Market structure analysis principles
- Institutional order flow concepts
All implementations are original code and calculations based on established technical analysis principles.
---
## ADDITIONAL INFORMATION SECTION
**Category**: Indicators
**Type**: Market Structure / Multi-Timeframe Analysis
**Complexity**: Intermediate to Advanced
**Open Source**: Code visible for transparency and education
**Pine Script Version**: v6
**Chart Overlay**: Yes
**Maximum Objects**: 500 boxes, 500 lines, 500 labels
Strength Relative to XXX [Hysteresis Smoothed]Strength Relative to XXX
█ OVERVIEW
This versatile indicator measures the relative strength of the current charted asset against any user-selected benchmark symbol (e.g., BTC, ETH, SP:SPX, TVC:GOLD, or any other asset). Green fill = Current asset outperforming the benchmark (bullish relative strength).
Red fill = Current asset underperforming the benchmark (bearish relative weakness). Perfect for rotation strategies across crypto, stocks, forex, and commodities — quickly identify assets gaining momentum edge over a chosen benchmark.
█ HOW IT WORKS
• Relative Ratio : Calculates current close / benchmark close for normalized comparison.
• Smoothing : Applies a Simple Moving Average (SMA) to the ratio (adjustable length).
• Oscillator : Plots deviation from the SMA, centered around zero.
• Hysteresis Enhancement : Adds a small relative threshold (~0.03% default) to prevent rapid color flips from minor noise. Color persists until a convincing cross — stable blocks without lag.
█ FEATURES & INPUTS
• Compare to : Symbol input for any benchmark (match exchange for accuracy).
• MA Length : Smoothing period (default 10).
• Relative Hysteresis Threshold : Noise filter strength (default 0.0003; tweak for responsiveness vs. stability).
█ USAGE TIPS
• Apply to ALT/BTC pairs for crypto rotations, stocks vs. SP:SPX for sector strength, or any custom comparison.
• Works on all timeframes — ideal for short-term scans on 4H/daily.
• Green zones = potential outperformance; red = caution.
• Combine with volume or momentum for confluence.
This refined relative strength oscillator delivers clean, reliable visuals in volatile markets.
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.
Risk Calculator (gmoneytrading)Risk Calculator + Trade Plan Scaling is a practical position sizing and planning tool designed for Forex and Gold (XAUUSD) traders.
It helps traders calculate lot size based on account balance, risk percentage, and stop loss, and then visualize a trade plan with scaled targets in dollar terms.
The indicator supports:
• Automatic lot sizing based on defined risk
• A linked trade plan that mirrors the risk calculator
• An optional manual trade plan mode for scenario planning
• Clear table-based visualization for quick decision-making
DISCLAIMER:
This indicator is for educational and informational purposes only.
It does not constitute financial advice or a recommendation to buy or sell any financial instrument.
Trading involves risk, and users are responsible for verifying all calculations and trade decisions.
