Indikatoren und Strategien
Advanced Breakout SystemAdvanced Breakout System
Developed by: Mohammed Bedaiwi
This script hunts for high-probability breakouts by combining price consolidation zones, volume spikes vs. average volume, smart money flow (OBV), and a Momentum Override for explosive moves that skip consolidation. Additionally, it automatically identifies and plots Support and Resistance levels with price labels to help you visualize market structure.
The system follows a "Watch & Confirm" logic: it first prints a WATCH setup, then a BUY only if price confirms strength.
🔑 Color Legend (Visual Guide)
🟡 WATCH – Setup (Yellow Arrow Down) :
Potential breakout setup detected. Monitor the stock and do not enter yet. Triggered when price breaks out of a recent consolidation with strong volume or makes a big momentum move (e.g. >5%) in a single bar.
🟢 BUY – Confirmation (Green Arrow Up) :
Confirmed breakout. Consider entering a long position according to your own rules. Triggered when price trades above the high of the WATCH candle.
🟠 SELL – Break (Orange Arrow) :
Short-term trend weakness. Triggered when price closes below the Fast EMA (9). Used as a protective exit or partial profit-taking.
🔴 SELL – Dump (Dark Red Arrow) :
Distribution / volume dump. Triggered by a bearish candle with abnormally high volume compared to the average (e.g. ≥ Dump Volume Multiplier × average volume).
🟣 SELL – Pattern (Purple Arrow) :
Bearish price-action pattern (such as a bearish engulfing). Indicates a possible top or reversal.
🔴/🟢 Support & Resistance Lines :
Small horizontal lines plotted at key swing points. Red Line: Resistance (Swing High). Green Line: Support (Swing Low). Both include exact price labels for quick reference.
⚙️ Inputs
Entry settings: Consolidation Lookback (default 20) = bars used to detect consolidation. Consolidation Range % (default 12%) = max allowed range size; higher values make the script more sensitive. Volume Spike Multiplier (default 1.2) = factor above average volume to count as a spike. Force Signal on Big Moves (default ON) = forces a WATCH signal if price jumps more than a set % (e.g. 5%) even without consolidation/OBV confirmation.
Exit settings: Enable Fast Exit (EMA 9) toggles the SELL – Break signal. Dump Volume Multiplier defines what counts as “dump” volume (e.g. 2× average).
Support & Resistance: Adjustable Pivot Left/Right bars allow you to control the sensitivity of the support and resistance lines.
⚠️ Disclaimer
Trading involves significant risk of loss. This script is for educational and informational purposes only and is not financial advice or a recommendation to buy or sell any asset. BUY and SELL signals are rule-based and derived from historical behavior and do not guarantee future performance. Always use your own analysis and risk management.
AlphaNatt | FINAL REVELATION [Visual God]AlphaNatt | The Final Revelation
"Where Information Theory meets Market Geometery."
The AlphaNatt is a comprehensive market structure and volumetric analysis suite designed for the institutional-grade trader. It merges advanced quantitative concepts—specifically Shannon Entropy and Neural Pattern Filtering—with a "Holographic" visual interface that prioritizes clarity over clutter.
This is not just an indicator; it is a complete decision-support system that answers three critical questions:
Is the market chaotic or ordered? (Entropy Engine)
Where is the liquidity? (Volumetric Heatmap)
What is the true structure? (Fractal Geometry)
🌌 The Gen 100 Math Engine
At the core of this script lies a unique implementation of Information Theory.
1. Shannon Entropy (The Chaos Filter)
Most indicators fail because they try to predict "Noise". This script calculates the Entropy (in Bits) of the recent price action.
High Entropy: The market is in a "Random Walk" state. Visuals fade out, transparency increases, and signals are suppressed.
Low Entropy: The market is "Ordered" and approaching a singularity/decision point. Visuals glow brightly to indicate a high-probability environment.
2. Neural Pattern Recognition
The diamond signals (Cyan/Magenta) are not simple simple crossovers. They are driven by a composite logic simulating a neural filter:
Inputs: Normalised RSI + Momentum Divergence + Volatility State.
Logic: Signals only trigger when the market is statistically overextended AND showing signs of momentum decay.
💎 Holographic Features
🔥 Volumetric Heatmap
The script scans historical price action to build a Volume Profile Heatmap on the right side of the chart.
Purple/Blue Zones: These represent High Volume Nodes (HVNs). These act as "Gravity Wells" for price—often stopping trends or acting as launchpads for reversals.
POC (Point of Control): The bright green line indicates the price level with the absolute highest volume in the lookback period.
🌀 Fractal Structure Lines
Price action is often noisy. The script uses a Fractal Pivot Algorithm (Length 5) to identify the "True Highs" and "True Lows".
It connects these points with dashed "Neural Lines" to show the naked market skeleton.
This instantly reveals if you are in a trend of Higher Highs or a breakdown of Lower Lows.
🖥️ The Heads-Up Display (HUD)
A minimalist dashboard keeps you informed of the math underneath:
ENTROPY: The raw bit-score of market chaos.
REGIME: Tells you instantly if you are in "ORDER" (Tradeable) or "CHAOS" (Sit out).
STRUCT: Real-time status of the fractal structure (Breakout/Breakdown/Ranging).
⚙️ Settings & Configuration
Theme: Choose between "Cyber" (Neon), "Aeon" (Deep Blue), or "Gold" (Luxury).
Max Entropy: Adjust the sensitivity of the Chaos Filter. Lower values = stricter filtering (fewer trades).
Heatmap Depth: Control how far back the volume profile scans.
⚠️ Disclaimer
This tool is designed for educational market analysis. "Entropy" and "Neural" refer to the mathematical algorithms used to process price data and do not guarantee future performance. Always manage risk responsible.
Greater Moving AverageThe purpose for this indicator is to function as a comprehensive market-state detector, with the primary goal of avoiding a market crash.
Mendoza Lines (V-pattern detection) identify early crash conditions and warn when market structure becomes unstable.
RSI/volume-shaded candles + Supertrend confirm momentum and trend, creating a unified system to avoid major drawdowns.
Enhanced Wyckoff ranges with ATR.
Mendoza lines identify abrupt V-shaped reversals which often precede high-risk crash structures. By tracking both the formation and resolution of these patterns across multiple timeframes, the indicator provides early warning signals when the market is entering unstable territory, allowing traders to step aside before liquidity collapses or structural breakdowns begin.
Ideal configurations use Heikin Ashi to smooth out candle structure. Observe SPX on a Weekly Chart, which correctly identifies exits and entries during the 2001 and 2009 crashes. On a 6 hour chart, the Tariff low is correctly identified. The improved VWAP uses a cumulative metric rather than the built in ta.vwap calculation, and functions as a macro low beacon when crossed with the 200 EMA. Historically, these crosses have aligned closely with macro cycle lows.
To round out the system, the indicator overlays RSI-based and volume-weighted candle shading to reflect internal momentum and real buying/selling pressure directly on the chart, making shifts in strength immediately visible. A Supertrend confirmation layer acts as the final filter, smoothing noise and verifying trend direction before decisions are made.
CRR - GANAEMAs on the chart (visual trend)
EMA 15 (white), 30 (yellow), 200 (red).
2️⃣ DASH Engine 1m–5m–15m (+ 1H and 1D)
For each TF (1m, 5m, 15m) it calculates a bull/bear score using:
EMA structure (15, 30, 50, 100, 200).
MACD.
RSI.
Relationship with EMA 30 and VWAP.
FVG in favor.
ATR change (volatility **increasing**).
From this it derives:
t1 (1m), t2 (5m), t3 (15m),
t4 (1H) and t5 (1D) (only for EMA200).
It detects:
ALL BULL → “BULLISH - BUYS ONLY”.
ALL BEAR → “BEARISH - SELLS ONLY”.
Otherwise → “NEUTRAL / MIXED”.
In addition:
Calculates BULL TF vs BEAR TF (%) between 1m–5m–15m.
Displays a visual bar 🐂🟩 vs 🐻🟥.
3️⃣ GOLD News (manual)
Special bar that says:
Neutral
BUY (positive)
SELL (negative)
Paints the HUD with color according to the news you select.
4️⃣ NO RETRACEMENT Alerts (beast mode 💣)
Very strict conditions using the 5 TFs:
BUY NO RETRACEMENT if:
4 or more TFs in bull mode (bullTF_all >= 4),
1m ultra bull (EMA bull, RSI>60, MACD bull, high volume, price above EMA15 and VWAP, FVG ≥ 0).
SELL NO RETRACEMENT is the same but bearish.
Creates alerts:
CRR BUY NO RETRACEMENT
CRR SELL NO RETRACEMENT
5️⃣ PRO LITE Patterns: Double Top / Double Bottom
Detects double tops and double bottoms with:
Minimum bar distance.
Tolerance in %. Optional filters:
MACD, RSI, ATR (volatility), volume, FVG.
If everything aligns:
Plots SELL at double top.
Plots BUY at double bottom.
6️⃣ TOP Indicators Block (SMI + WaveTrend + Supertrend)
SMI (momentum), WaveTrend, and Supertrend:
Counts which are in bull mode and which are in bear mode.
Displays:
TOP IND: BULLS XX% | BEARS YY%.
7️⃣ Integrated Internal SMC Module
Structure HH, LH, HL, LL.
BMS (break of structure) and ChoCH (change of character).
Filter with ATR + volume + MACD + gaps.
Internal Fibonacci of the last range (38.2, 50, 61.8).
Dotted yellow lines of the current range (swing high/low).
🧠 In short:
It's your command center for XAUUSD:
Global mode (buy only / sell only / mixed),
% of timeframes favoring bulls/bears,
gold news,
no-lag alerts,
filtered double top/bottom,
TOP indicators,
and complete SMC (structure + BMS/ChoCH + Fibonacci + range)...
all integrated into a single CRAZY RAY RAY HUD
MeanReversion_tradeALERTOverview The Apex Reversal Predictor v2.5 is a specialized mean reversion strategy designed for scalping high-volatility assets like NQ (Nasdaq), ES (S&P 500), and Crypto. While most indicators chase breakouts, this system hunts for "Liquidity Sweeps"—moments where the market briefly breaks a key level to trap retail traders before snapping back to the true value (VWAP).
This is not just a signal indicator; it is a full Trade Manager that calculates your Entry, Stop Loss, and Take Profit levels automatically based on volatility (ATR).
The Logic: Why This Works Markets act like a rubber band. They can only stretch so far from their average price before snapping back. This script combines three layers of logic to identify these snap-back points:
The Stretch (Sigma Score): Measures how far price is from the VWAP relative to ATR. If the score > 2.0, the "rubber band" is overextended.
The Trap (Liquidity Sweep): Identifies Pivot Highs/Lows. It waits for price to break a pivot (luring in breakout traders) and then immediately reverse (trapping them).
The Exhaustion (RSI): Confirms that momentum is Overbought/Oversold to prevent trading against a strong trend.
Key Features
Dynamic Lines: Automatically draws Blue (Entry), Red (SL), and Green (TP) lines on the chart for active trades.
Smart Targets: Two modes for taking profit:
Mean Reversion: Targets the VWAP line (High Win Rate).
Fixed Ratio: Targets a specific Risk:Reward (e.g., 1:2).
Live Dashboard: Tracks Win Rate, Net Points, and the live "Stretch Score" in the bottom right corner.
Alert Ready: Formatted JSON alerts for easy integration with Discord or trading bots.
How & When to Use (User Guide)
1. Best Timeframes
5-Minute (5m): Best for NQ and volatile stocks (TSLA, NVDA). Filters out 1-minute noise but catches the intraday reversals.
15-Minute (15m): Best for Forex or slower-moving indices (ES).
2. The Setup Checklist Before taking a trade, look at the Dashboard in the bottom right:
Step 1: Check the "Stretch (Sigma)". Is it Orange or Red? This means price is extended and ripe for a reversal. If it's Green, the market is calm—be careful.
Step 2: Wait for the Signal.
"Apex BUY" (Green Label): Price swept a low and closed green.
"Apex SELL" (Red Label): Price swept a high and closed red.
Step 3: Execute. Enter at the close of the signal candle. Set your stop loss at the Red Line provided by the script.
3. Warning / When NOT to Use
Strong Trending Days: If the market is trending heavily (e.g., creating higher highs all day without looking back), do not fight the trend.
News Events: Avoid using this during CPI, FOMC, or NFP releases. The "rubber band" logic breaks during news because volatility expands indefinitely.
VIX/VXV Ratio (TitsNany)This script plots the VXV/VIX ratio, which compares medium-term volatility (90-day fear) to short-term volatility (30-day fear). When the ratio rises above key levels like 1.16 or 1.24, it signals that traders expect future stress, often preceding market pullbacks. When the ratio falls toward or below 1.0, short-term fear is spiking, which typically occurs during active selloffs or volatility events. In short, elevated readings warn of potential market drops ahead, while sharp declines in the ratio reflect panic already hitting the market.
Volume Profile on Grid with Zscore ColoringThis indicator takes (DeadCatCode) volume profile and starts a new profile when price reaches a new Grid Interval, chosen in the settings.
The candles are also colored by Z score (colors pulled from ChartPrime) based on the 5 deviations from the Daily TWAP, which is anchored from previous days settlement time, 14:59:30CT. The max number of deviations can be changed in the settings to change the sensitivity of the z score coloring.
Volume Profiles on Weekly TWAP and Zscore ColoringThis indicator takes (DeadCats) volume profile and starts a new profile when price reaches a new Weekly TWAP line or deviation line.
The candles are also colored by Z score based on the 5 deviations from the Daily TWAP, which is anchored from previous days settlement time, 14:59:30CT. The max number of deviations can be changed in the settings to change the sensitivity of the z score coloring.
ICT Quant-Core: Liquidity Intelligence [Dual-Engine]🔥 THE ULTIMATE LIQUIDITY FILTERING ENGINE
Most SMC traders lose money because they "catch falling knives" on every local wick. This algorithm solves this problem by using DUAL-CORE logic and a signal quality scoring system.
This is no ordinary pivot indicator.
⚙️ HOW DOES IT WORK? (DUAL-CORE LOGIC)
The algorithm analyzes the market on two levels simultaneously:
1️⃣ MACRO CORE (Lookback 50 - "WHALE 🐋")
Tracks key levels from recent weeks/months.
This is where institutions build their positions.
Signals from this core have the highest priority (Score 10/10).
2️⃣ LOCAL CORE (Lookback 20 - "ROACH 🐟")
Tracks internal market structure and noise.
Signals are filtered by the Main Trend. If the trend is down, Local Longs are marked as "TRAP."
🧠 SMART FILTERS (QUANT LAYERS)
Instead of entering on every line touch, the script requires confirmation:
✅ RECLAIM LOGIC: Price must close back above/below the liquidity level (Swing Failure Pattern).
✅ RVOL FILTER: Requires relative volume > 1.2x the average (institutional track).
✅ SCORING SYSTEM (0-10): Each signal receives a score.
- 10/10: Macro Grab in line with the trend + high volume.
- 3/10: Local Grab against the trend (risky).
📊 ANALYTICAL DASHBOARD
In the lower right corner, you'll find the "Command Center":
- Trend Status (Distribution/Accumulation)
- Whale's Last Move (Price and Direction)
- Current Tactics (e.g., "Ignore Longs, Search for Shorts")
- Filter Status (RSI, Volume, Reclaim)
🚀 HOW TO USE IT?
1. Set the H4 timeframe.
2. Wait for a signal with a rating > 7/10.
3. Ignore "Fish/Local" signals (small icons) if they contradict the Dashboard color.
4. Entry occurs only after the candle closes (Reclaim).
BLACK SWAN SWEEP (DANIELPEREZ)Crt de velas especificas después del sweep buscar la confirmación del order block para tomar una operacio .
Check specific candlesticks after the sweep to find order block confirmation before taking a trade.
NoProcess PivotsNoProcess Pivots
Visualize the structural framework of price action with NoProcess Pivots, a precision tool for multi-timeframe confluence trading.
Pivots are mathematically derived levels where price statistically finds support, resistance, or equilibrium. Institutional order flow respects these levels as key decision points where liquidity pools form and inefficiencies seek rebalancing.
NoProcess Pivots displays historical pivot ranges as period-bounded zones across Daily, Weekly, and Quarterly timeframes—allowing you to observe how price has respected or violated these levels over time. By projecting ±33% extensions beyond R1/S1, traders can identify targets, retracement levels, and key reversal points.
Cross-reference pivots across multiple timeframes to find confluence zones where Daily, Weekly, and Quarterly levels stack. These high-conviction areas offer the clearest setups for entries and exits.
Features:
Multi-timeframe pivots: Daily, Weekly, Quarterly
Historical levels with adjustable depth
Period-bounded zones
±33% extensions
Adaptive light/dark mode table
Real-time Δ PP percentage
Pivot cross alerts
Built for traders who respect the math behind the markets.
Support & Resistance Auto-Detector by Rakesh Sharma📊 SUPPORT & RESISTANCE AUTO-DETECTOR
Automatically identifies and displays key price levels where traders make decisions. No more manual drawing - let the algorithm do the work!
✨ KEY FEATURES:
- Auto-detects Swing High/Low levels with strength rating
- Previous Day High/Low (PDH/PDL) - Most important intraday levels
- Previous Week High/Low (PWH/PWL) - Strong swing levels
- Previous Month High/Low (PMH/PML) - Major turning points
- Round Number levels (Psychological barriers)
- S/R Zones (Better than exact lines)
- Breakout/Breakdown alerts
- Live Dashboard with trade bias
🎯 PERFECT FOR:
Nifty, Bank Nifty, Stocks, Forex, Crypto - All markets, all timeframes
⚡ SMART FEATURES:
- Strength Rating: Very Strong/Strong/Medium/Weak
- Distance Calculator: Shows points to next S/R
- Trade Bias: "Buy Dips" / "Sell Rallies" / "Breakout"
- Break Alerts: Get notified on PDH/PDL breaks
- Clean Chart: Shows only most important levels
💡 TRADING EDGE:
Trade bounces at support, rejections at resistance, or breakouts through key levels. Combines perfectly with price action and other indicators.
Created by: Rakesh Sharma
Setup Keltner BandS MMS + RSI SIGNALS
📊 Keltner Bands with RSI Confirmation – TradingView Script
Introduction
This script combines Keltner Channel logic with Relative Strength Index (RSI) confirmation to provide traders with visual signals and alerts for potential reversals. It is designed for scalping and short-term trading strategies, where precision and quick decision-making are essential.
🔧 How It Works
• Keltner Bands (ATR-based):
• Two sets of bands are plotted around a moving average:
• Band 3 (ATR × 3) – more sensitive, suitable for aggressive entries.
• Band 5 (ATR × 5) – wider, used as a filter or confirmation zone.
• Signals are generated when the price crosses back inside the bands from outside.
• RSI Confirmation:
• RSI is calculated with a customizable period (default: 14).
• Overbought and oversold levels (default: 70/30) are used to filter signals.
• A bearish reversal is confirmed only if RSI is above the overbought level.
• A bullish reversal is confirmed only if RSI is below the oversold level.
📌 Functions and Features
• Visual Signals:
• Triangles plotted above/below candles for Keltner-only signals.
• Additional colored triangles for Keltner + RSI confirmed signals.
• Alerts:
• Configurable alerts for both Keltner-only and RSI-confirmed conditions.
• Messages include the type of reversal and the band level.
• Customizable Parameters:
• Moving average length.
• ATR multipliers (3 and 5).
• RSI length and thresholds.
• Colors for band fills and signals.
🎯 Usage
1. Apply the script to your chart in TradingView.
2. Adjust parameters to fit your trading style (scalping, intraday, swing).
3. Watch for signals:
• Red/green/orange/teal triangles → Keltner-only reversals.
• Maroon/lime/purple/blue triangles → RSI-confirmed reversals.
4. Set alerts to receive notifications when conditions are met.
5. Use RSI confirmation to filter out false signals and increase accuracy.
✅ Benefits
• Clear visualization of reversal zones.
• Dual-layer confirmation (Keltner + RSI).
• Flexible for different timeframes and trading styles.
• Ready-to-use alerts for automation or manual trading.
RVOL + Volume Z-Score (Textbook)This indicator is a relative-volume and “volume anomaly” dashboard designed to help you quickly spot when a ticker is actually in-play versus simply drifting on normal activity. It plots standard volume bars (colored by up/down candles) and overlays multiple optional smoothers of volume (SMA, LSMA/linear-regression MA, HMA, ALMA) so you can see whether participation is expanding or fading across different smoothing styles. It also calculates RVOL (current bar volume divided by the average volume over a user-defined lookback) and displays RVOL (and Z) in a small table for quick reference.
The core feature is a textbook volume z-score: Z=(V−SMA(V,N))/StDev(V,N)
This measures how far the current bar’s volume is from its recent average in standard-deviation units, making it easy to filter for genuinely unusual volume. The script plots mean + 1σ and mean + 2σ threshold bands and can highlight “anomaly” volume bars when Z exceeds your chosen σ thresholds (default 1σ for broader detection, with alerts available for 1σ/2σ). Use it as a participation filter: combine high RVOL / high Z with your price structure (key levels, VWAP, trend) to validate breakouts or identify high-conviction reversal/flush events.
IMPORTANT Levels by SBImportant levels by SB based on gann levels.One can plot these levels once on the chart and can work on these levels .When ever market market come at any of these levels .User can wait for the price action and accordingly user can get inside the trade
Indian Scalper 2025 – PSAR + SMA50 + RSI≤50 + High Volume (75%)Best 1-min / 2-min scalping strategy for NIFTY, BANKNIFTY, FINNIFTY & liquid stocks in 2025
✓ PSAR flip + SMA-50 trend filter
✓ RSI ≤50 (avoids chasing)
✓ Only high-volume candles (bright colour)
✓ Loud mobile alerts with price & SL
✓ 1:2+ RR with PSAR trailing
Works like magic 9:15–11:30 AM and 2–3:20 PM
Made with love for the Indian trading community ♥
Absorption RatioThe Hidden Connections Between Markets
Financial markets are not isolated islands. When panic spreads, seemingly unrelated assets suddenly begin moving in lockstep. Stocks, bonds, commodities, and currencies that normally provide diversification benefits start falling together. This phenomenon, where correlations spike during crises, has devastated portfolios throughout history. The Absorption Ratio provides a quantitative measure of this hidden fragility.
The concept emerged from research at State Street Associates, where Mark Kritzman, Yuanzhen Li, Sebastien Page, and Roberto Rigobon developed a novel application of principal component analysis to measure systemic risk. Their 2011 paper in the Journal of Portfolio Management demonstrated that when markets become tightly coupled, the variance explained by the first few principal components increases dramatically. This concentration of variance signals elevated systemic risk.
What the Absorption Ratio Measures
Principal component analysis, or PCA, is a statistical technique that identifies the underlying factors driving a set of variables. When applied to asset returns, the first principal component typically captures broad market movements. The second might capture sector rotations or risk-on/risk-off dynamics. Additional components capture increasingly idiosyncratic patterns.
The Absorption Ratio measures the fraction of total variance absorbed or explained by a fixed number of principal components. In the original research, Kritzman and colleagues used the first fifth of the eigenvectors. When this fraction is high, it means a small number of factors are driving most of the market movements. Assets are moving together, and diversification provides less protection than usual.
Consider an analogy: imagine a room full of people having independent conversations. Each person speaks at different times about different topics. The total "variance" of sound in the room comes from many independent sources. Now imagine a fire alarm goes off. Suddenly everyone is talking about the same thing, moving in the same direction. The variance is now dominated by a single factor. The Absorption Ratio captures this transition from diverse, independent behavior to unified, correlated movement.
The Implementation Approach
TradingView does not support matrix algebra required for true principal component analysis. This implementation uses a closely related proxy: the average absolute correlation across a universe of major asset classes. This approach captures the same underlying phenomenon because when assets are highly correlated, the first principal component explains more variance by mathematical necessity.
The asset universe includes eight ETFs representing major investable categories: SPY and QQQ for large cap US equities, IWM for small caps, EFA for developed international markets, EEM for emerging markets, TLT for long-term treasuries, GLD for gold, and USO for oil. This selection provides exposure to equities across geographies and market caps, plus traditional diversifying assets.
From eight assets, there are twenty-eight unique pairwise correlations. The indicator calculates each using a rolling window, takes the absolute value to measure coupling strength regardless of direction, and averages across all pairs. This average correlation is then transformed to match the typical range of published Absorption Ratio values.
The transformation maps zero average correlation to an AR of 0.50 and perfect correlation to an AR of 1.00. This scaling aligns with empirical observations that the AR typically fluctuates between 0.60 and 0.95 in practice.
Interpreting the Regimes
The indicator classifies systemic risk into four regimes based on AR levels.
The Extreme regime occurs when the AR exceeds 0.90. At this level, nearly all asset classes are moving together. Diversification has largely failed. Historically, this regime has coincided with major market dislocations: the 2008 financial crisis, the 2020 COVID crash, and significant correction periods. Portfolios constructed under normal correlation assumptions will experience larger drawdowns than expected.
The High regime, between 0.80 and 0.90, indicates elevated systemic risk. Correlations across asset classes are above normal. This often occurs during the build-up to stress events or during volatile periods where fear is spreading but has not reached panic levels. Risk management should be more conservative.
The Normal regime covers AR values between 0.60 and 0.80. This represents typical market conditions where some correlation exists between assets but diversification still provides meaningful benefits. Standard portfolio construction assumptions are reasonable.
The Low regime, below 0.60, indicates that assets are behaving relatively independently. Diversification is working well. Idiosyncratic factors dominate returns rather than systematic risk. This environment is favorable for active management and security selection strategies.
The Relationship to Portfolio Construction
The implications for portfolio management are significant. Modern portfolio theory assumes correlations are stable and uses historical estimates to construct efficient portfolios. The Absorption Ratio reveals that this assumption is violated precisely when it matters most.
When AR is elevated, the effective number of independent bets in a diversified portfolio shrinks. A portfolio holding stocks, bonds, commodities, and real estate might behave as if it holds only one or two positions during high AR periods. Position sizing based on normal correlation estimates will underestimate portfolio risk.
Conversely, when AR is low, true diversification opportunities expand. The same nominal portfolio provides more independent return streams. Risk can be deployed more aggressively while maintaining the same effective exposure.
Component Analysis
The indicator separately tracks equity correlations and cross-asset correlations. These components tell different stories about market structure.
Equity correlations measure coupling within the stock market. High equity correlation indicates broad risk-on or risk-off behavior where all stocks move together. This is common during both rallies and selloffs driven by macroeconomic factors. Stock pickers face headwinds when equity correlations are elevated because individual company fundamentals matter less than market beta.
Cross-asset correlations measure coupling between different asset classes. When stocks, bonds, and commodities start moving together, traditional hedges fail. The classic 60/40 stock/bond portfolio, for example, assumes negative or low correlation between equities and treasuries. When cross-asset correlation spikes, this assumption breaks down.
During the 2022 market environment, for instance, both stocks and bonds fell significantly as inflation and rate hikes affected all assets simultaneously. High cross-asset correlation warned that the usual defensive allocations would not provide their expected protection.
Mean Reversion Characteristics
Like most risk metrics, the Absorption Ratio tends to mean-revert over time. Extremely high AR readings eventually normalize as panic subsides and assets return to more independent behavior. Extremely low readings tend to rise as some level of systematic risk always reasserts itself.
The indicator tracks AR in statistical terms by calculating its Z-score relative to the trailing distribution. When AR reaches extreme Z-scores, the probability of normalization increases. This creates potential opportunities for strategies that bet on mean reversion in systemic risk.
A buy signal triggers when AR recovers from extremely elevated levels, suggesting the worst of the correlation spike may be over. A sell signal triggers when AR rises from unusually low levels, warning that complacency about diversification benefits may be excessive.
Momentum and Trend
The rate of change in AR carries information beyond the absolute level. Rapidly rising AR suggests correlations are increasing and systemic risk is building. Even if AR has not yet reached the high regime, acceleration in coupling should prompt increased vigilance.
Falling AR momentum indicates normalizing conditions. Correlations are decreasing and assets are returning to more independent behavior. This often occurs in the recovery phase following stress events.
Practical Application
For asset allocators, the AR provides guidance on how much diversification benefit to expect from a given allocation. During high AR periods, reducing overall portfolio risk makes sense because the usual diversifiers provide less protection. During low AR periods, standard or even aggressive allocations are more appropriate.
For risk managers, the AR serves as an early warning indicator. Rising AR often precedes large market moves and volatility spikes. Tightening risk limits before correlations reach extreme levels can protect capital.
For systematic traders, the AR provides a regime filter. Mean reversion strategies may work better during high AR periods when panics create overshooting. Momentum strategies may work better during low AR periods when trends can develop independently across assets.
Limitations and Considerations
The proxy methodology introduces some approximation error relative to true PCA-based AR calculations. The asset universe, while representative, does not include all possible diversifiers. Correlation estimates are inherently backward-looking and can change rapidly.
The transformation from average correlation to AR scale is calibrated to match typical published ranges but is not mathematically equivalent to the eigenvalue ratio. Users should interpret levels directionally rather than as precise measurements.
Correlation regimes can persist longer than expected. Mean reversion signals indicate elevated probability of normalization but do not guarantee timing. High AR can remain elevated throughout extended crisis periods.
References
Kritzman, M., Li, Y., Page, S., and Rigobon, R. (2011). Principal Components as a Measure of Systemic Risk. Journal of Portfolio Management, 37(4), 112-126.
Kritzman, M., and Li, Y. (2010). Skulls, Financial Turbulence, and Risk Management. Financial Analysts Journal, 66(5), 30-41.
Billio, M., Getmansky, M., Lo, A., and Pelizzon, L. (2012). Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors. Journal of Financial Economics, 104(3), 535-559.
Credit Spread RegimeThe Credit Market as Economic Barometer
Credit spreads are among the most reliable leading indicators of economic stress. When corporations borrow money by issuing bonds, investors demand a premium above the risk-free Treasury rate to compensate for the possibility of default. This premium, known as the credit spread, fluctuates based on perceptions of economic health, corporate profitability, and systemic risk.
The relationship between credit spreads and economic activity has been studied extensively. Two papers form the foundation of this indicator. Pierre Collin-Dufresne, Robert Goldstein, and Spencer Martin published their influential 2001 paper in the Journal of Finance, documenting that credit spread changes are driven by factors beyond firm-specific credit quality. They found that a substantial portion of spread variation is explained by market-wide factors, suggesting credit spreads contain information about aggregate economic conditions.
Simon Gilchrist and Egon Zakrajsek extended this research in their 2012 American Economic Review paper, introducing the concept of the Excess Bond Premium. They demonstrated that the component of credit spreads not explained by default risk alone is a powerful predictor of future economic activity. Elevated excess spreads precede recessions with remarkable consistency.
What Credit Spreads Reveal
Credit spreads measure the difference in yield between corporate bonds and Treasury securities of similar maturity. High yield bonds, also called junk bonds, carry ratings below investment grade and offer higher yields to compensate for greater default risk. Investment grade bonds have lower yields because the probability of default is smaller.
The spread between high yield and investment grade bonds is particularly informative. When this spread widens, investors are demanding significantly more compensation for taking on credit risk. This typically indicates deteriorating economic expectations, tighter financial conditions, or increasing risk aversion. When the spread narrows, investors are comfortable accepting lower premiums, signaling confidence in corporate health.
The Gilchrist-Zakrajsek research showed that credit spreads contain two distinct components. The first is the expected default component, which reflects the probability-weighted cost of potential defaults based on corporate fundamentals. The second is the excess bond premium, which captures additional compensation demanded beyond expected defaults. This excess premium rises when investor risk appetite declines and financial conditions tighten.
The Implementation Approach
This indicator uses actual option-adjusted spread data from the Federal Reserve Economic Database (FRED), available directly in TradingView. The ICE BofA indices represent the industry standard for measuring corporate bond spreads.
The primary data sources are FRED:BAMLH0A0HYM2, the ICE BofA US High Yield Index Option-Adjusted Spread, and FRED:BAMLC0A0CM, the ICE BofA US Corporate Index Option-Adjusted Spread for investment grade bonds. These indices measure the spread of corporate bonds over Treasury securities of similar duration, expressed in basis points.
Option-adjusted spreads account for embedded options in corporate bonds, providing a cleaner measure of credit risk than simple yield spreads. The methodology developed by ICE BofA is widely used by institutional investors and central banks for monitoring credit conditions.
The indicator offers two modes. The HY-IG excess spread mode calculates the difference between high yield and investment grade spreads, isolating the pure compensation for below-investment-grade credit risk. This measure is less affected by broad interest rate movements. The HY-only mode tracks the absolute high yield spread, capturing both credit risk and the overall level of risk premiums in the market.
Interpreting the Regimes
Credit conditions are classified into four regimes based on Z-scores calculated from the spread proxy.
The Stress regime occurs when spreads reach extreme levels, typically above a Z-score of 2.0. At this point, credit markets are pricing in significant default risk and economic deterioration. Historically, stress regimes have coincided with recessions, financial crises, and major market dislocations. The 2008 financial crisis, the 2011 European debt crisis, the 2016 commodity collapse, and the 2020 pandemic all triggered credit stress regimes.
The Elevated regime, between Z-scores of 1.0 and 2.0, indicates above-normal risk premiums. Credit conditions are tightening. This often occurs in the build-up to stress events or during periods of uncertainty. Risk management should be heightened, and exposure to credit-sensitive assets may be reduced.
The Normal regime covers Z-scores between -1.0 and 1.0. This represents typical credit conditions where spreads fluctuate around historical averages. Standard investment approaches are appropriate.
The Low regime occurs when spreads are compressed below a Z-score of -1.0. Investors are accepting below-average compensation for credit risk. This can indicate complacency, strong economic confidence, or excessive risk-taking. While often associated with favorable conditions, extremely tight spreads sometimes precede sudden reversals.
Credit Cycle Dynamics
Beyond static regime classification, the indicator tracks the direction and acceleration of spread movements. This reveals where credit markets stand in the credit cycle.
The Deteriorating phase occurs when spreads are elevated and continuing to widen. Credit conditions are actively worsening. This phase often precedes or coincides with economic downturns.
The Recovering phase occurs when spreads are elevated but beginning to narrow. The worst may be over. Credit conditions are improving from stressed levels. This phase often accompanies the early stages of economic recovery.
The Tightening phase occurs when spreads are low and continuing to compress. Credit conditions are very favorable and improving further. This typically occurs during strong economic expansions but may signal building complacency.
The Loosening phase occurs when spreads are low but beginning to widen from compressed levels. The extremely favorable conditions may be normalizing. This can be an early warning of changing sentiment.
Relationship to Economic Activity
The predictive power of credit spreads for economic activity is well-documented. Gilchrist and Zakrajsek found that the excess bond premium predicts GDP growth, industrial production, and unemployment rates over horizons of one to four quarters.
When credit spreads spike, the cost of corporate borrowing increases. Companies may delay or cancel investment projects. Reduced investment leads to slower growth and eventually higher unemployment. The transmission mechanism runs from financial conditions to real economic activity.
Conversely, tight credit spreads lower borrowing costs and encourage investment. Easy credit conditions support economic expansion. However, excessively tight spreads may encourage over-leveraging, planting seeds for future stress.
Practical Application
For equity investors, credit spreads provide context for market risk. Equities and credit often move together because both reflect corporate health. Rising credit spreads typically accompany falling stock prices. Extremely wide spreads historically have coincided with equity market bottoms, though timing the reversal remains challenging.
For fixed income investors, spread regimes guide sector allocation decisions. During stress regimes, flight to quality favors Treasuries over corporates. During low regimes, spread compression may offer limited additional return for credit risk, suggesting caution on high yield.
For macro traders, credit spreads complement other indicators of financial conditions. Credit stress often leads equity volatility, providing an early warning signal. Cross-asset strategies may use credit regime as a filter for position sizing.
Limitations and Considerations
FRED data updates with a lag, typically one business day for the ICE BofA indices. For intraday trading decisions, more current proxies may be necessary. The data is most reliable on daily timeframes.
Credit spreads can remain at extreme levels for extended periods. Mean reversion signals indicate elevated probability of normalization but do not guarantee timing. The 2008 crisis saw spreads remain elevated for many months before normalizing.
The indicator is calibrated for US credit markets. Application to other regions would require different data sources such as European or Asian credit indices. The relationship between spreads and subsequent economic activity may vary across market cycles and structural regimes.
References
Collin-Dufresne, P., Goldstein, R.S., and Martin, J.S. (2001). The Determinants of Credit Spread Changes. Journal of Finance, 56(6), 2177-2207.
Gilchrist, S., and Zakrajsek, E. (2012). Credit Spreads and Business Cycle Fluctuations. American Economic Review, 102(4), 1692-1720.
Krishnamurthy, A., and Muir, T. (2017). How Credit Cycles across a Financial Crisis. Working Paper, Stanford University.
CRR Birgua HUD (HH-HL / LL-LH)CRR Birgua HUD (HH-HL / LL-LH) essentially does three things:
Detects price structure using pivots.
Marks highs as:
HH = Higher High
LH = Lower High
Marks lows as:
HL = Higher Low
LL = Lower Low
It uses a pivot length (pivotLen, default 3) to find these turning points.
Measures the “Birgua” (impulse correction).
In a downtrend:
When an LH appears, it measures how much the retracement rose from the last low to that LH.
In an uptrend:
When an HL appears, it measures how much the retracement fell from the last high to that HL.
It calculates two things:
% correction (birgua_lastPct)
ATR multiples (birgua_lastAtrMult)
It only considers it “valid” if:
% correction ≥ birgua_minBirguaPc (e.g., 25%)
ATR multiple ≥ birgua_minAtrMult (e.g., 0.5)
If valid: it labels it with OK; otherwise: SMALL.
Creates a HUD and a “Birgua Score.”
Calculates a Birgua Score (0–100):
Starts at 50.
If the last Birgua was at an HL (strong bullish), it increases from 50.
If it was at an LH (strong bearish), it decreases from 50.
It can draw a line at the bottom with this score if you enable Show Birgua Score.
At the top of the screen, it displays a HUD with:
Direction: BULL (HL), BEAR (LH), or NEUTRAL.
B: XX.X% (Birgua percentage).
ATR: X.XX (ATR multiples).
Strength: Strong / Weak / N/A based on the minimums you defined.
🧠 Quick Use:
HL + strong Birgua → probable bullish continuation.
LH + strong Birgua → probable bearish continuation.
The HUD summarizes whether the last correction was strong or weak and on which side (bull or bear).
The Rumer's Box Theory“The Rumer's Box Theory” is a visual trading indicator designed to help traders quickly identify the previous daily candle’s high and low ranges across all timeframes. The indicator draws a purple box spanning the previous day’s high to low, with a blue horizontal line at the 50% midpoint for easy reference.
Equal Highs & Lows Strategy // ------------------------------------------------------------------------------
// 🧠 THE MARKET PSYCHOLOGY (WHY THIS WORKS):
// ------------------------------------------------------------------------------
// 1. THE MAGNET THEORY:
// "Equal Highs" (EQH) and "Equal Lows" (EQL) are not random. They represent
// Retail Support and Resistance. Retail traders are taught to put Stop Losses
// just above Double Tops or just below Double Bottoms.
// - Therefore, these lines represent massive pools of LIQUIDITY (Money).
// - Price is often engineered to move toward these lines to "unlock" that money.
//
// 2. THE INSTITUTIONAL TRAP (STOP HUNTS):
// Institutions need liquidity to fill large orders without slippage.
// - To Buy massive amounts, they need many Sellers -> They push price BELOW EQL
// to trigger retail Sell Stops.
// - To Sell massive amounts, they need many Buyers -> They push price ABOVE EQH
// to trigger retail Buy Stops.
//
// 3. THE STRATEGY (TURTLE SOUP):
// We do not trade the initial touch. We wait for the "Sweep & Reclaim".
// - Bullish Signal (GRAB ⬆): Price drops below the Green Line (EQL), grabs the
// stops, but buyers step in and force the candle to CLOSE back above the line.
// - Bearish Signal (GRAB ⬇): Price spikes above the Red Line (EQH), grabs the
// stops, but sellers step in and force the candle to CLOSE back below the line.
// ------------------------------------------------------------------------------
5% Move Counter (Up vs Down)5% Move Counter (Up vs Down)
This indicator tracks how many times a stock has made a 5% or larger move in a single session, and shows the count separately for up days and down days. It’s meant for traders who want quick context on whether a stock has a history of making large moves, instead of manually scrolling through years of price action.
Most tools only tell you what’s happening right now. This one helps you understand what the stock is capable of.
What it shows
Number of 5%+ up days
Number of 5%+ down days
Optional display modes:
All
Up Only
Down Only
Why it’s useful
Different stocks behave differently. Some give clean, powerful bursts when they break out, while others rarely move big even when the setup looks perfect. This tool helps you gauge a stock’s historical “explosiveness” so you can decide whether your strategy fits its behavior.
If your setups depend on volatility or momentum, it helps to know whether the stock has produced big moves before. This gives you that information instantly.
Customization
You can place the stats box anywhere on the chart using a simple 1–9 selector.
You can hide the rows you don’t need through a dropdown.
When a row is hidden, its background becomes fully transparent so the chart stays clean.
Who it’s for
Short-term traders, breakout traders, swing traders, and anyone who wants a quick read on whether a stock moves enough to justify certain types of trades.
