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.
Indicatori e strategie
FlowTrinity — Crypto Dominance Rotation IndexFlowTrinity — Crypto Dominance Rotation Index
(Tracks BTC / Stablecoin / Altcoin dominance flows with standardized oscillators)
⚪ Overview
FlowTrinity decomposes total crypto market structure into three capital-flow regimes — BTC dominance, Stablecoin dominance, and Altcoin dominance — each normalized into oscillator form. Additionally, a fourth histogram tracks Total Market Cap expansion/contraction relative to BTC+Stable capital, revealing underlying rotation pressure not visible in raw dominance charts.
Each component is standardized through SMA/STD normalization, producing smoothed 0–100 style oscillations that highlight overbought/oversold rotation extremes, risk-on/risk-off transitions, and capital cycle inflection zones.
⚪ Flow Components
Stablecoin Dominance Oscillator —White line
Measures the combined USDT + USDC share of market dominance.
High values indicate increased hedging behavior or sidelined capital.
Low values coincide with renewed risk appetite and capital deployment into crypto assets.
Altcoin Dominance Oscillator — Orange Line
Tracks the share of liquidity rotating into altcoins (Total – BTC – Stable).
Rising values indicate broad market expansion and speculative activity.
Falling values reflect flight-to-safety or concentration back into majors.
BTC Dominance Oscillator — Purple line(off by default
Normalized BTC dominance revealing transitions between Bitcoin-led markets and altcoin-led cycles. Useful for identifying BTC absorption phases vs. altcoins dispersion regimes.
Total–BTC–Stable MarketCap Difference Histogram — histogram
A normalized histogram of total market cap change minus BTC+Stable market cap change.
• Positive → altcoin segment expanding
• Negative → capital retreating into BTC or stables
Acts as a structural layer confirming or contradicting dominance-based signals.
Normalization Logic
All flows use SMA + standard deviation scaling (lookback 7 / smoothing 7), enabling consistent comparison across unrelated dominance and market-cap metrics.
⚪ Use Cases
• Identify shifts between BTC-led and alt-led markets
• Detect early signs of liquidity rotation
• If Stablecoin OSC is oversold, liquidity may soon rotate to BTC or Altcoins, signaling potential price moves.
• If Stablecoin OSC is overbought and Altcoin OSC is oversold, it can indicate an early buying opportunity in Altcoins.
• Watching these oscillator positions helps spot early market rotations and plan entries or exits.
snapshot
Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial advice or investment guidance. Cryptocurrency trading involves significant risk; you are solely responsible for your trading decisions, based on your financial objectives and risk tolerance. The author assumes no liability for any losses arising from the use of this tool.
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.
SMC N-Gram Probability Matrix [PhenLabs]📊 SMC N-Gram Probability Matrix
Version: PineScript™ v6
📌 Description
The SMC N-Gram Probability Matrix applies computational linguistics methodology to Smart Money Concepts trading. By treating SMC patterns as a discrete “alphabet” and analyzing their sequential relationships through N-gram modeling, this indicator calculates the statistical probability of which pattern will appear next based on historical transitions.
Traditional SMC analysis is reactive—traders identify patterns after they form and then anticipate the next move. This indicator inverts that approach by building a transition probability matrix from up to 5,000 bars of pattern history, enabling traders to see which SMC formations most frequently follow their current market sequence.
The indicator detects and classifies 11 distinct SMC patterns including Fair Value Gaps, Order Blocks, Liquidity Sweeps, Break of Structure, and Change of Character in both bullish and bearish variants, then tracks how these patterns transition from one to another over time.
🚀 Points of Innovation
First indicator to apply N-gram sequence modeling from computational linguistics to SMC pattern analysis
Dynamic transition matrix rebuilds every 50 bars for adaptive probability calculations
Supports bigram (2), trigram (3), and quadgram (4) sequence lengths for varying analysis depth
Priority-based pattern classification ensures higher-significance patterns (CHoCH, BOS) take precedence
Configurable minimum occurrence threshold filters out statistically insignificant predictions
Real-time probability visualization with graphical confidence bars
🔧 Core Components
Pattern Alphabet System: 11 discrete SMC patterns encoded as integers for efficient matrix indexing and transition tracking
Swing Point Detection: Uses ta.pivothigh/pivotlow with configurable sensitivity for non-repainting structure identification
Transition Count Matrix: Flattened array storing occurrence counts for all possible pattern sequence transitions
Context Encoder: Converts N-gram pattern sequences into unique integer IDs for matrix lookup
Probability Calculator: Transforms raw transition counts into percentage probabilities for each possible next pattern
🔥 Key Features
Multi-Pattern SMC Detection: Simultaneously identifies FVGs, Order Blocks, Liquidity Sweeps, BOS, and CHoCH formations
Adjustable N-Gram Length: Choose between 2-4 pattern sequences to balance specificity against sample size
Flexible Lookback Range: Analyze anywhere from 100 to 5,000 historical bars for matrix construction
Pattern Toggle Controls: Enable or disable individual SMC pattern types to customize analysis focus
Probability Threshold Filtering: Set minimum occurrence requirements to ensure prediction reliability
Alert Integration: Built-in alert conditions trigger when high-probability predictions emerge
🎨 Visualization
Probability Table: Displays current pattern, recent sequence, sample count, and top N predicted patterns with percentage probabilities
Graphical Probability Bars: Visual bar representation (█░) showing relative probability strength at a glance
Chart Pattern Markers: Color-coded labels placed directly on price bars identifying detected SMC formations
Pattern Short Codes: Compact notation (F+, F-, O+, O-, L↑, L↓, B+, B-, C+, C-) for quick pattern identification
Customizable Table Position: Place probability display in any corner of your chart
📖 Usage Guidelines
N-Gram Configuration
N-Gram Length: Default 2, Range 2-4. Lower values provide more samples but less specificity. Higher values capture complex sequences but require more historical data.
Matrix Lookback Bars: Default 500, Range 100-5000. More bars increase statistical significance but may include outdated market behavior.
Min Occurrences for Prediction: Default 2, Range 1-10. Higher values filter noise but may reduce prediction availability.
SMC Detection Settings
Swing Detection Length: Default 5, Range 2-20. Controls pivot sensitivity for structure analysis.
FVG Minimum Size: Default 0.1%, Range 0.01-2.0%. Filters insignificant gaps.
Order Block Lookback: Default 10, Range 3-30. Bars to search for OB formations.
Liquidity Sweep Threshold: Default 0.3%, Range 0.05-1.0%. Minimum wick extension beyond swing points.
Display Settings
Show Probability Table: Toggle the probability matrix display on/off.
Show Top N Probabilities: Default 5, Range 3-10. Number of predicted patterns to display.
Show SMC Markers: Toggle on-chart pattern labels.
✅ Best Use Cases
Anticipating continuation or reversal patterns after liquidity sweeps
Identifying high-probability BOS/CHoCH sequences for trend trading
Filtering FVG and Order Block signals based on historical follow-through rates
Building confluence by comparing predicted patterns with other technical analysis
Studying how SMC patterns typically sequence on specific instruments or timeframes
⚠️ Limitations
Predictions are based solely on historical pattern frequency and do not account for fundamental factors
Low sample counts produce unreliable probabilities—always check the Samples display
Market regime changes can invalidate historical transition patterns
The indicator requires sufficient historical data to build meaningful probability matrices
Pattern detection uses standardized parameters that may not capture all institutional activity
💡 What Makes This Unique
Linguistic Modeling Applied to Markets: Treats SMC patterns like words in a language, analyzing how they “flow” together
Quantified Pattern Relationships: Transforms subjective SMC analysis into objective probability percentages
Adaptive Learning: Matrix rebuilds periodically to incorporate recent pattern behavior
Comprehensive SMC Coverage: Tracks all major Smart Money Concepts in a unified probability framework
🔬 How It Works
1. Pattern Detection Phase
Each bar is analyzed for SMC formations using configurable detection parameters
A priority hierarchy assigns the most significant pattern when multiple detections occur
2. Sequence Encoding Phase
Detected patterns are stored in a rolling history buffer of recent classifications
The current N-gram context is encoded into a unique integer identifier
3. Matrix Construction Phase
Historical pattern sequences are iterated to count transition occurrences
Each context-to-next-pattern transition increments the appropriate matrix cell
4. Probability Calculation Phase
Current context ID retrieves corresponding transition counts from the matrix
Raw counts are converted to percentages based on total context occurrences
5. Visualization Phase
Probabilities are sorted and the top N predictions are displayed in the table
Chart markers identify the current detected pattern for visual reference
💡 Note:
This indicator performs best when used as a confluence tool alongside traditional SMC analysis. The probability predictions highlight statistically common pattern sequences but should not be used as standalone trading signals. Always verify predictions against price action context, higher timeframe structure, and your overall trading plan. Monitor the sample count to ensure predictions are based on adequate historical data.
ATR ZigZag - Volatility-Filtered Market StructureDescription
This indicator draws ZigZags using an ATR based threshold for direction switching to identify major swing highs and lows. Instead of relying on fractals or fixed bar-count swings, pivots are confirmed only when price moves beyond the prior extreme by:
threshold = ATR(length) × ATR_mult
This filters noise, enforces valid swing structure (high → low → high), and adapts automatically to volatility. The ATR ZigZag is ideal for traders who want a clean, objective view of swing structure without noise. This has many uses, including mapping swing structure, drawing chart patterns, and trading around extremes.
Lag and Repainting
Pivots are confirmed only after price moves sufficiently in the opposite direction. This creates necessary lag. The ZigZag is drawn when this occurs, and will anchor to the high/low in the past. Optional detection dot plots show exactly when confirmation occurred.
What You See
ZigZag: dashed gray line, repainted to anchor at the confirmed highs and lows
Latest Pivot Levels: Dashed horizontal lines at the most recent confirmed high/low.
Optional Live Swing Leg: A real-time line from the last confirmed pivot to the current swing extreme, updating until a new pivot forms.
Optional ATR Boxes: 1×ATR shaded zones around the latest pivot for structural context.
Optional Pivot Confirmation Dots: Markers show the bar where the threshold is crossed and a swing is officially confirmed. This is to understand the lag and see when the ZigZag repainted.
ICT Order Block Identifier [Eˣ]📦 Order Block Identifier
Overview
The Order Block Identifier automatically detects and displays institutional order blocks on your charts - zones where banks, hedge funds, and market makers place their orders. This indicator helps identify where institutions are likely to defend their positions and where price often finds support or resistance, based on ICT (Inner Circle Trader) concepts.
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🎯 What This Indicator Does
Detects Order Blocks:
• 🟢 Bullish Order Blocks (OB+) - Last bearish candle before strong bullish move
• 🔴 Bearish Order Blocks (OB-) - Last bullish candle before strong bearish move
• Automatically identifies institutional buying/selling zones
• Tracks up to 30 order blocks simultaneously
• Works on all timeframes and instruments
Smart Features:
• Auto-Timeframe Adjustment - Optimizes detection for 1min to Weekly charts
• Active Block Highlighting - Shows which OB price is approaching
• Touch Tracking - Knows when blocks are tested
• ATR-Based Detection - Adapts to each instrument's volatility
• Strength Filtering - Choose Low/Medium/High to control sensitivity
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📚 Understanding Order Blocks
What Are Order Blocks?
Order blocks are the "footprints" left behind by institutional traders (banks, hedge funds, market makers) when they enter large positions. Because institutions can't fill massive orders at once without moving the market, they:
1. Place orders gradually over time
2. Leave zones where their buy/sell orders are concentrated
3. Defend these zones when price returns
4. Create reliable support and resistance levels
The ICT Concept:
Developed by Michael Huddleston (Inner Circle Trader), order block theory states that:
• The last opposite-colored candle before a strong move contains institutional orders
• Price often returns to test these zones before continuing
• These zones act as strong support (bullish OB) or resistance (bearish OB)
• Smart money defends their positions at these levels
Why Order Blocks Work:
• Unfilled Orders: Institutions may still have pending orders in the block
• Position Defense: They protect their entries by adding to positions
• Stop Placement: Retail stops cluster near these zones (liquidity for institutions)
• Market Structure: Price respects these levels due to order flow dynamics
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🟢 Bullish Order Blocks Explained
How They Form:
1. Price is consolidating or declining
2. Institutions begin accumulating (buying)
3. A strong bullish move erupts
4. The last bearish candle before this move = Bullish Order Block
5. This candle represents where institutions were buying aggressively
Why The Last Bearish Candle?
• Institutions absorbed all selling pressure at this level
• Their buy orders filled as price was declining
• When price returns, they defend this zone with more buying
• It becomes a demand zone / support level
Trading Bullish Order Blocks:
Setup:
• Wait for price to retrace back to bullish OB (green box)
• Look for rejection/reversal pattern (pin bar, engulfing, etc.)
• Enter long when price bounces from the OB zone
• Stop loss: Below the order block
• Target: Recent high or opposite order block
Best Scenarios:
• OB aligns with other support (trendline, fibonacci, round number)
• First touch of OB (unmitigated) has highest probability
• Occurs during high-volume sessions (London/NY)
• Trend is bullish on higher timeframe
Example Trade:
• Bullish OB forms at $50,000 (last red candle before rally)
• Price rallies to $52,000 then retraces
• Price drops back to $50,100 (touching OB)
• Bullish pin bar forms on the OB
• Enter long at $50,200, stop at $49,800
• Target: $52,000+ (previous high)
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🔴 Bearish Order Blocks Explained
How They Form:
1. Price is consolidating or rising
2. Institutions begin distributing (selling)
3. A strong bearish move erupts
4. The last bullish candle before this move = Bearish Order Block
5. This candle represents where institutions were selling aggressively
Why The Last Bullish Candle?
• Institutions absorbed all buying pressure at this level
• Their sell orders filled as price was rising
• When price returns, they defend this zone with more selling
• It becomes a supply zone / resistance level
Trading Bearish Order Blocks:
Setup:
• Wait for price to retrace back to bearish OB (red box)
• Look for rejection/reversal pattern (shooting star, bearish engulfing)
• Enter short when price rejects from the OB zone
• Stop loss: Above the order block
• Target: Recent low or opposite order block
Best Scenarios:
• OB aligns with other resistance (trendline, fibonacci, round number)
• First touch of OB (unmitigated) has highest probability
• Occurs during high-volume sessions (London/NY)
• Trend is bearish on higher timeframe
Example Trade:
• Bearish OB forms at $48,000 (last green candle before drop)
• Price drops to $46,000 then retraces
• Price rallies back to $47,900 (touching OB)
• Bearish engulfing forms at the OB
• Enter short at $47,800, stop at $48,200
• Target: $46,000- (previous low)
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📊 How To Use This Indicator
Strategy 1: Order Block Retest (Classic)
Best For: Swing trading, capturing reversals
Timeframes: 15min, 1H, 4H, Daily
Win Rate: 60-70% (first touch)
Entry Rules:
1. Identify unmitigated order block (bright color, not gray)
2. Wait for price to return to the OB zone
3. Look for price action confirmation:
• Bullish OB: Pin bar, bullish engulfing, hammer
• Bearish OB: Shooting star, bearish engulfing, doji
4. Enter in the direction of the OB
5. Stop loss: Beyond the opposite side of OB (20-30 pips)
6. Target: 2-3R or opposite OB
Example:
• Bullish OB at $100-$102
• Price drops to $101.50 (enters OB)
• Bullish pin bar forms with low at $100.80
• Enter long at $102 (OB high), stop at $99.50
• Risk: $2.50, Target: $107.50 (3R)
Strategy 2: Break & Retest
Best For: Trend trading, breakout confirmation
Timeframes: 5min, 15min, 1H
Win Rate: 65-75%
Entry Rules:
1. Price breaks through an order block
2. Wait for pullback to the broken OB
3. The OB now acts as support (if broken up) or resistance (if broken down)
4. Enter when price respects the flipped OB
5. Stop: Inside the OB zone
6. Target: Next OB or structure level
Why It Works: Broken OBs flip polarity - support becomes resistance and vice versa
Strategy 3: Multi-Timeframe Confirmation
Best For: High-probability setups
Timeframes: Combine 1H + 4H or 15min + 1H
Win Rate: 70-80%
Entry Rules:
1. Identify order block on higher timeframe (4H or Daily)
2. Switch to lower timeframe (1H or 15min)
3. Wait for lower TF order block to form within higher TF OB
4. Trade the lower TF OB in direction of higher TF OB
5. Stop: Below lower TF OB
6. Target: Edge of higher TF OB or beyond
Why It Works: Alignment across timeframes = institutional consensus
Strategy 4: Order Block to Order Block
Best For: Range trading, swing entries
Timeframes: 1H, 4H
Win Rate: 55-65%
Entry Rules:
1. Identify both bullish OB below and bearish OB above
2. Price is ranging between these OBs
3. Enter long at bullish OB, target bearish OB
4. Enter short at bearish OB, target bullish OB
5. Stop: Beyond the trading OB
6. Exit at opposite OB
Why It Works: Price moves from one institutional zone to another
Strategy 5: Mitigation Fade
Best For: Aggressive scalping
Timeframes: 5min, 15min
Win Rate: 50-60% (higher risk)
Entry Rules:
1. Price approaches an order block
2. Instead of bouncing, price breaks through (mitigates it)
3. Enter immediately in direction of breakout
4. Stop: Back inside the mitigated OB
5. Quick target: 1-1.5R
Why It Works: When OB fails, it often leads to strong continuation
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⚙️ Settings Explained
Core Settings
Auto-Adjust for Timeframe (Default: ON)
• Automatically optimizes detection for current chart timeframe
• 1min: 3 bars lookback
• 5min: 4 bars lookback
• 15min: 5 bars lookback
• 1H: 6 bars lookback
• 4H: 8 bars lookback
• Daily+: 10-12 bars lookback
• Recommended: Keep ON for best results
Manual Detection Length (Default: 5)
• Only used when Auto-Adjust is OFF
• Number of bars to look back for the "last opposite candle"
• Lower (2-4): More sensitive, more blocks, more noise
• Higher (6-10): Less sensitive, fewer blocks, higher quality
• Recommended: Use Auto-Adjust instead
Display Settings
Show Bullish/Bearish Order Blocks
• Toggle each type on/off independently
• Customize colors for each OB type
• Tip: Match colors to your chart theme
Max Order Blocks to Display (Default: 10)
• Limits how many OBs are shown at once
• Lower (5-8): Cleaner chart, only recent blocks
• Higher (15-30): More historical context
• Recommended: 8-12 for most trading
Show Order Block Labels (Default: ON)
• Displays "OB+" and "OB-" text on blocks
• Shows 🎯 on active (nearest) block
• Turn OFF for minimal chart appearance
• Recommended: Keep ON for clarity
Extend Blocks (bars) (Default: 50)
• How far to extend OB boxes to the right
• Lower (20-30): Shorter boxes, less clutter
• Higher (100+): Longer boxes, easier to see
• Blocks auto-extend until mitigated or limit reached
• Recommended: 40-60 bars
Filters
Block Strength Filter (Default: Medium)
• Controls how strong a move must be to create an OB
• Low: 0.5x ATR move required - Many blocks, more noise
• Medium: 1x ATR move required - Balanced quality/quantity
• High: 1.5x ATR move required - Only strongest institutional moves
• Recommended for beginners: High
• Recommended for experienced: Medium
• Recommended for scalpers: Low
Min Block Size % (Default: 0.1)
• Minimum size of OB as percentage of price
• Filters out tiny, insignificant blocks
• Crypto: 0.1-0.3%
• Forex: 0.05-0.15%
• Stocks: 0.1-0.5%
• Adjust based on instrument volatility
Advanced Settings
Show Mitigated Blocks (Default: OFF)
• When ON: Shows gray boxes for "used" order blocks
• When OFF: Blocks disappear after mitigation
• Use ON: For learning and analysis
• Use OFF: For clean, active trading
Highlight Active Block (Default: ON)
• Highlights the nearest order block to current price
• Active block shown with 🎯 emoji and brighter color
• Helps focus on most relevant trading opportunity
• Recommended: Keep ON
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📱 Info Panel Guide
Bullish OB Count
• Number of active (unmitigated) bullish order blocks
• Higher number = More support zones below price
• Multiple bullish OBs = Strong demand structure
Bearish OB Count
• Number of active (unmitigated) bearish order blocks
• Higher number = More resistance zones above price
• Multiple bearish OBs = Strong supply structure
Bias Indicator
• ⬆ Bullish: More bullish OBs than bearish (demand > supply)
• ⬇ Bearish: More bearish OBs than bullish (supply > demand)
• ↔ Neutral: Equal OBs on both sides
• Trade in direction of bias for higher probability
Near Indicator
• Shows which OB price is closest to
• Displays distance as percentage
• Example: "Bull OB 0.85%" = Bullish OB is 0.85% below current price
• Watch for "Near" alerts to time entries
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📱 Alert Setup
This indicator includes 4 alert types:
1. Price Entering Bullish OB
• Fires when price touches a bullish order block
• Action: Watch for bounce/reversal pattern
• High-probability long setup developing
2. Price Entering Bearish OB
• Fires when price touches a bearish order block
• Action: Watch for rejection/reversal pattern
• High-probability short setup developing
3. New Bullish OB Detected
• Fires when a new bullish order block forms
• Action: Mark the zone for future retest
• New demand zone identified
4. New Bearish OB Detected
• Fires when a new bearish order block forms
• Action: Mark the zone for future retest
• New supply zone identified
To Set Up Alerts:
1. Click "Alert" button (clock icon)
2. Select "Order Block Identifier"
3. Choose your alert condition
4. Configure notification method
5. Click "Create"
Pro Tip: Set "Price Entering" alerts to catch trading opportunities in real-time
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💎 Pro Tips & Best Practices
✅ DO:
• First touch is best - Unmitigated OBs have highest win rate (60-70%)
• Wait for confirmation - Don't buy/sell just because price touched OB
• Use multiple timeframes - Higher TF OBs are stronger than lower TF
• Combine with structure - OB + trendline/support = high probability
• Trade with the bias - More bullish OBs = favor longs
• Respect mitigation - Once OB is mitigated, it's less reliable
• Use proper stop loss - Always place stops beyond the OB zone
• Consider session timing - OBs work best during London/NY sessions
⚠️ DON'T:
• Don't blindly buy/sell at OBs - Wait for confirmation
• Don't ignore mitigation - Gray blocks are much weaker
• Don't trade every OB - Quality over quantity
• Don't fight strong trends - OBs can be run through in strong momentum
• Don't use alone - Combine with price action, support/resistance
• Don't expect 100% win rate - Even best OBs fail sometimes (30-40% of time)
• Don't overtrade - Wait for A+ setups with confluence
🎯 Best Timeframes By Trading Style:
• Scalpers: 1min, 5min (quick OB touches)
• Day Traders: 5min, 15min, 1H (balanced view)
• Swing Traders: 1H, 4H, Daily (major institutional zones)
• Position Traders: 4H, Daily, Weekly (strongest OBs)
🔥 Best Instruments:
• Excellent: Forex major pairs (EUR/USD, GBP/USD), BTC, ETH, ES, NQ
• Good: Gold, Oil, Major indices, Large-cap stocks
• Moderate: Altcoins, small-cap stocks (more noise)
• Avoid: Very low liquidity instruments (OBs less reliable)
⏰ Best Times To Trade OBs:
• London Session (03:00-12:00 EST): Highest OB respect rate
• NY Session (08:00-17:00 EST): Strong OB reactions
• London-NY Overlap (08:00-12:00 EST): Best probability
• Asian Session: Lower probability, wait for London
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🎓 Advanced Order Block Concepts
Order Block Flips (Polarity Change)
When price breaks through an OB and closes beyond it:
• Bullish OB that's broken becomes bearish (support becomes resistance)
• Bearish OB that's broken becomes bullish (resistance becomes support)
• Trading: Watch for retest of broken OB from opposite side
Order Block Refinement
When multiple OBs form at similar level:
• Later OB "refines" or "replaces" the earlier one
• Use the most recent OB as the active zone
• Older OBs become less relevant
Order Block Clusters
Multiple OBs stacked close together:
• Creates a "super zone" of institutional interest
• Higher probability of reversal
• Wider zone for entries (more room for confirmation)
Fair Value Gaps + Order Blocks
When OB aligns with Fair Value Gap:
• Extremely high probability setup
• Price is drawn to fill the gap AND test the OB
• Double confluence = institutional magnet
Order Block Mitigation Types
• Full Mitigation: Price fully enters and closes inside OB
• Partial Mitigation: Price wicks into OB but closes outside
• False Mitigation: Quick touch then immediate rejection
• Partial/false mitigation = OB still somewhat valid
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📈 Common Order Block Patterns
Pattern 1: The Perfect Retest
• OB forms during strong move
• Price continues 100-200+ pips
• Price retraces back to OB
• Clean bounce with confirmation candle
• Highest probability pattern
Pattern 2: The Double Tap
• Price tests OB, bounces weakly
• Price tests same OB again
• Second test produces stronger reaction
• Second touch often better entry
Pattern 3: The Fake-Out
• Price breaks through OB
• Immediately reverses back
• "Stop hunt" or liquidity grab
• Enter after price reclaims OB
Pattern 4: The Ladder
• Multiple OBs stacked like stairs
• Price steps from one OB to next
• Each OB provides support/resistance
• Trade OB-to-OB movements
Pattern 5: The Failed OB
• Price crashes through OB without pause
• OB completely invalidated
• Often signals strong momentum
• Don't fight it, trade the breakout
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🚀 What Makes This Different?
Unlike basic support/resistance indicators, Order Block Identifier:
• ICT Methodology - Based on proven institutional concepts
• Auto-Timeframe Optimization - Works perfectly on all timeframes
• ATR-Based Detection - Adapts to each instrument's volatility
• Mitigation Tracking - Knows when blocks are no longer valid
• Active Block Highlighting - Shows most relevant opportunity
• Smart Filtering - Only shows high-quality institutional zones
• Visual Clarity - Clean, professional appearance
• Real-Time Updates - Blocks update as price action develops
Based On Professional Concepts:
• ICT Smart Money Concepts (SMC)
• Institutional order flow analysis
• Market maker behavior patterns
• Supply and demand zone theory
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🙏 If You Find This Helpful
• ⭐ Leave your feedback
• 💬 Share your experience in the comments
• 🔔 Follow for updates and new tools
Questions about Order Blocks? Feel free to ask in the comments.
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Version History
• v1.0 - Initial release with auto-timeframe detection and ATR-based strength filtering
Setup Keltner Banda 3 e 5 - MMS + RSI + Distância Tabela
📊 Indicator Overview: Keltner Bands + RSI + Distance Table
This custom TradingView indicator combines three powerful tools into a single, visually intuitive setup:
Keltner Channels (Bands 3x and 5x ATR)
Relative Strength Index (RSI)
Dynamic Table Displaying RSI and Price Distance from Moving Average (MMS)
🔧 Components and Functions
1. Keltner Channels (3x and 5x ATR)
Based on a Simple Moving Average (MMS) and Average True Range (ATR).
Two sets of bands are plotted:
3x ATR Bands: Used for moderate volatility signals.
5x ATR Bands: Used for high volatility extremes.
Visual fills between bands help identify overextended price zones.
2. RSI (Relative Strength Index)
Measures momentum and potential reversal zones.
Customizable overbought (default 70) and oversold (default 30) levels.
RSI values are color-coded in the table:
Green for RSI ≤ 30 (oversold)
Blue for 30 < RSI ≤ 70 (neutral)
Red for RSI > 70 (overbought)
3. Distance Table (Price vs. MMS)
Displays the real-time distance between the current price and the MMS:
In points (absolute difference)
In percentage (relative to MMS)
Helps traders assess how far price has deviated from its mean.
📈 How to Use
Trend Reversal Signals
Look for price crossing back inside the 3x or 5x Keltner Bands.
Confirm with RSI:
RSI > 70 + price re-entering from above = potential short
RSI < 30 + price re-entering from below = potential long
Volatility Zones
Price outside the 5x band indicates extreme movement.
Use this to anticipate mean reversion or breakout continuation.
Table Insights
Monitor RSI and price distance in real time.
Use color cues to quickly assess momentum and stretch.
⚙️ Customization
Adjustable parameters for:
MMS period
ATR multipliers
RSI period and thresholds
Table position on chart
Fill colors between bands
This indicator is ideal for traders who want a clean, data-rich visual tool to track volatility, momentum, and price deviation in one place.
Candlestick Pattern Identifier (Extended + Alerts)Candlestick Pattern Identifier (Extended + Alerts)
UT Bot Pro Max (Maks Edition)Script v2.0
UT Bot Pro Max is an advanced, high-precision evolution of the well-known UT Bot indicator.
This version is fully rebuilt into a complete decision-making system that evaluates trend structure, volatility conditions, momentum signals, and entry quality.
It is designed for traders who want clear, structured signals supported by objective filters and transparent reasoning.
1. Core Engine: ATR-Based Trailing Logic
At the heart of the system is an ATR dynamic trailing stop.
It is responsible for:
detecting trend reversals
identifying breakout conditions
switching between long and short bias
determining signal strength
Unlike simple ATR lines, this engine adapts to momentum expansion and contraction, forming the backbone for every signal.
2. Three-Tier Signal Structure
Each signal is classified into one of three levels based on the number of confirmations:
Strong Signals
ATR breakout
trend filter (price relative to EMA200)
RSI filter (oversold/overbought context)
This is the highest-quality confirmation and is suitable for full-size entries.
Medium Signals
ATR breakout
trend filter
(no RSI filter)
This represents a valid trend continuation but with slightly reduced confirmation.
Weak Signals
ATR breakout only
(no trend filter, no RSI filter)
This is an early-stage impulse which can evolve into a stronger move.
The multi-level classification allows the trader to size positions rationally and avoid over-committing during uncertain market conditions.
3. Move-Since-Entry Tracking
When a new long or short position is detected, the indicator records the entry price and automatically tracks the percentage movement from that point.
This offers:
real-time monitoring of open trade performance
objective context for managing exits
clear visualization of progress since entry
4. Smart State-Change Alerts
Instead of simple “BUY” or “SELL” messages, the script sends highly structured alerts whenever the internal state changes.
Each alert includes:
the symbol and timeframe
signal direction and strength
recommended position size based on signal tier
ATR values
RSI value and its state
trend context (bullish, bearish, neutral)
distance from ATR trailing stop
movement since entry
previous state reference (optional)
This makes it ideal for automated systems, algorithmic routing, or Telegram-based signal delivery.
5. Professional On-Chart Status Table
The indicator displays a refined information panel containing:
current signal state (Strong / Medium / Weak / Hold)
ATR signal direction
trend filter result
RSI value and condition
distance to trailing stop (percentage)
current position (long / short / flat)
entry recommendation based on signal strength
ATR value and additional context in expanded mode
There is also a compact mode optimized specifically for mobile trading.
6. Optional Heikin Ashi Mode
The indicator can operate using Heikin Ashi close values for traders who prefer smooth, noise-reduced visualizations.
The internal logic is recalculated automatically.
7. Trend-Colored Candles
An optional feature allows candle coloring based on price position relative to the ATR stop line, highlighting bullish and bearish phases directly on the chart.
What This Indicator Provides
Accurate, context-aware entry signals
Scalable position sizing through multi-tier structure
Objective trend confirmation
Breakout detection with volatility adaptation
Continuous tracking of open position performance
Detailed real-time explanations through alerts
A complete visual dashboard consolidating all key metrics
UT Bot Pro Max (Maks Edition) is built as a practical tool for daily trading.
It is suitable for scalping, day trading, swing trading, automated alerts, and mobile workflows.
Dynamic Swing Anchored VWAP (Zeiierman) with alert functionoriginal script by the author, added alert function only
3 Lines RCI + Psy Signal + RSI Background📌 3 Lines RCI + Psy Signal + RSI Background
This indicator combines three RCI lines, Psychological Line signals, RSI-based background highlights, and ADX strength detection to visualize market momentum, trend strength, and potential reversal zones.
🔍 Main Features
📌 1. Triple RCI (Rank Correlation Index)
Displays Short / Mid / Long RCI
Detects momentum shifts and trend reversals
Highlight zones:
Overbought: +80 ~ +100 (Red Zone)
Oversold: -80 ~ -100 (Green Zone)
📌 2. Psychological Line Signal
Column bars appear only in extreme conditions:
Overbought → Red Bars
Oversold → Green Bars
Helps detect short-term sentiment extremes
📌 3. RSI Background Highlight
Red Background: RSI > Overbought threshold
Green Background: RSI < Oversold threshold
Provides a visual cue of underlying market pressure.
📌 4. ADX Trend Strength
ADX line color shows strength level:
Blue: Weak trend
Yellow: Moderate trend
Red: Strong trend
Useful to identify whether signals occur in a trend or range state.
🎯 Trading Usage Tips
RCI + RSI + Psy confluence can identify strong reversal timing.
Use signals only when ADX is weak or moderate to avoid counter-trading a strong trend.
Combine short/mid RCI crossovers with extreme zones for potential entry timing.
⚙️ Suitable For
Scalping, day trading, swing trading
Stocks, Forex, Crypto, Indices, Commodities
ATR ZigZag BreakoutATR ZigZag Breakout
This strategy uses my ATR ZigZag indicator (powered by the ZigZagCore library) to scalp breakouts at volatility-filtered highs and lows.
Everyone knows stops cluster around clear swing highs and lows. Breakout traders often pile in there, too. These levels are predictable areas where aggressive orders hit the tape. The idea here is simple:
→ Let ATR ZigZag define clean, volatility-filtered pivots
→ Arm a stop market order at those pivots
→ Join the breakout when the crowd hits the level
The key to greater success in this simple strategy lies in the ZigZag. Because the pivots are filtered by ATR instead of fixed bar counts or fractals, the levels tend to be more meaningful and less noisy.
This approach is especially suited for intraday trading on volatile instruments (e.g., NQ, GC, liquid crypto pairs).
How It Works
1. Pivot detection
The ATR ZigZag uses an ATR-based threshold to confirm swing highs and lows. Only when price has moved far enough in the opposite direction does a pivot become “official.”
2. Candidate breakout level
When a new swing direction is detected and the most recent high/low has not yet been broken in the current leg, the strategy arms a stop market order at that pivot.
• Long candidate → most recent swing high
• Short candidate → most recent swing low
These “candidate trades” are shown as dotted lines.
3. Entry, SL, and TP
If price breaks through the level, the stop order is filled and a bracket is placed:
• Stop loss = ATR × SL multiplier
• Take profit = SL distance × RR multiplier
Once a level has traded, it is not reused in the same swing leg.
4. Cancel & rotate
If the market reverses and forms a new swing in the opposite direction before the level is hit, the pending order is cancelled and a new candidate is considered in the new direction.
Additional Features
• Optional session filter for backtesting specific trading hours
Adaptive Risk Management [sgbpulse]1. Introduction:
Adaptive Risk Management is an advanced indicator designed to provide traders with a comprehensive risk management tool directly on the chart. Instead of relying on complex manual calculations, the indicator automates all critical steps of trade planning. It dynamically calculates the estimated Entry Price , the Stop Loss location, the required Position Size (Quantity) based on your capital and risk limits, and the three Take Profit targets based on your defined Reward/Risk ratios. The indicator displays all these essential data points clearly and visually on the chart, ensuring you always know the potential risk-reward profile of every trade.
ARM : The A daptive R isk M anagement every trader needs to ARM themselves with.
2. The Critical Importance of Risk Management
Proper risk management is the cornerstone of successful trading. Consistent profitability in the market is impossible without rigorously defining risk limits.
Risk Control: This starts by setting the maximum risk amount you are willing to lose in a single trade (Risk per Trade), and limiting the total capital allocated to the position (Max Capital per Trade).
Defining Boundaries (Stop Loss & Take Profit): It is mandatory to define a technical Stop Loss and a Take Profit target. A fundamental rule of risk management is that the Reward/Risk Ratio (R/R) must be a minimum of 1:1.
3. Core Features, Adaptivity, and Customization
The Adaptive Risk Management indicator is engineered for use across all major trading styles, including Swing Trading, Intraday Trading, and Scalping, providing consistent risk control regardless of the chosen timeframe.
Real-Time Dynamic Adaptivity: The indicator calculates all risk management parameters (Entry, Stop Loss, Quantity) dynamically with every new bar, thus adapting instantly to changing market conditions.
Trend Direction Adjustment: Define the analysis direction (Long/Uptrend or Short/Downtrend).
Intraday Session Data Control: Full control over whether lookback calculations will include data from Extended Trading Hours (ETH), or if the daily calculations will start actively only from the first bar of Regular Trading Hours (RTH).
Status Validation: The indicator performs critical status checks and displays clear Warning Messages if risk conditions are not met.
4. Intuitive Visualization and Real-Time Data
Dynamic Tracking Lines: The Entry Price and Stop Loss lines are updated with every new bar. Crucially, the length of these lines dynamically reflects the calculation's lookback range (e.g., the extent of Lookback Bars or the location of the confirmed Pivot Point), providing a visual anchor for the calculated price.
Risk and Reward Zones: The indicator creates a graphical background fill between Entry and Stop Loss (marked with the risk color) and between Entry and the Reward Targets (marked with the reward color).
Essential Information Labels: Labels are placed at the end of each line, providing critical data: Estimated Entry Price, Stock/Contract Quantity (Quantity), Total Entry Amount, Estimated Stop Loss, Risk per Share, Total Financial Risk (Risk Amount), Exit Amount, Estimated Take Profit 1/2/3, Reward/Risk Ratio 1/2/3, Total Reward 1/2/3, TP Exit Amount 1/2/3.
4.1. Data Window Metrics (16 Full Series)
The indicator displays 16 full data series in the TradingView Data Window, allowing precise tracking of every calculation parameter:
Entry Data: Estimated Entry, Quantity, Entry Amount.
Risk Data (Stop Loss): Estimated Stop Loss, Risk per Share, Risk Amount, Exit Amount.
Reward Data (Take Profit): Estimated Take Profit 1/2/3, Reward/Risk Ratio 1/2/3, Total Reward 1/2/3, TP Exit Amount 1/2/3.
4.2. Instant Tracking in the Status Line
The indicator displays 6 critical parameters continuously in the indicator's Status Line: Estimated Entry, Quantity, Estimated Stop Loss, Estimated Take Profit 1/2/3.
5. Detailed Indicator Inputs
5.1 General
Focused Trend: Defines the analysis direction (Uptrend / Downtrend).
Max Capital per Trade: The maximum amount allocated to purchasing stocks/contracts (in account currency).
Risk per Trade: The maximum amount the user is willing to risk in this single trade (in account currency).
ATR Length: The lookback period for the Average True Range (ATR) calculation.
5.2 Intraday Session Data Control
Regular Hours Limitation : If enabled, all daily lookback calculations (for Entry/Stop Loss anchor points) will begin strictly from the first Regular Trading Hours (RTH) bar. This limits the lookback range to the current RTH session, excluding preceding Extended Trading Hours (ETH) data. Only relevant for Intraday charts. Default: False (Off)
5.3 Entry Inputs
Entry Method: Selects the entry price calculation method:
Current Price: Uses the closing price of the current bar as the estimated entry point (Market Entry).
ATR Real Bodies Margin :
- Uptrend: Calculates the Maximum Real Body over the lookback period + the calculated safety margin.
- Downtrend: Calculates the Minimum Real Body over the lookback period - the calculated safety margin.
ATR Bars Margin :
- Uptrend: Calculates the Maximum High price over the lookback period + the calculated safety margin.
- Downtrend: Calculates the Minimum Low price over the lookback period - the calculated safety margin.
Lookback Bars: The number of bars used to calculate the extremes in the ATR-based entry methods (Relevant only for ATR Real Bodies Margin and ATR Bars Margin methods).
ATR Multiplier (Entry): The multiplier applied to the ATR value. The result of the multiplication is the calculated safety margin used to determine the estimated Entry Price.
5.4 Risk Inputs (Stop Loss)
Risk Method: Selects the Stop Loss price calculation method.
ATR Current Price Margin :
- Uptrend: Entry Price - the calculated safety margin.
- Downtrend: Entry Price + the calculated safety margin.
ATR Current Bar Margin :
- Uptrend: Current Bar's Low price - the calculated safety margin.
- Downtrend: Current Bar's High price + the calculated safety margin.
ATR Bars Margin :
- Uptrend: Lowest Low over lookback period - the calculated safety margin.
- Downtrend: Highest High over lookback period + the calculated safety margin.
ATR Pivot Margin :
- Uptrend: The first confirmed Pivot Low point - the calculated safety margin.
- Downtrend: The first confirmed Pivot High point + the calculated safety margin.
Lookback Bars: The lookback period for finding the extreme price used in the 'ATR Bars Margin' calculation.
ATR Multiplier (Risk): The multiplier applied to the ATR value. The result of the multiplication is the calculated safety margin used to place the estimated Stop Loss. Note: If set to 0, the Stop Loss will be placed exactly at the technical anchor point, provided the Minimum Margin Value is also 0.
Minimum Margin Value: The minimum price value (e.g., $0.01) the Stop Loss margin buffer must be.
Pivot (Left / Right): The number of bars required on either side of the pivot bar for confirmation (relevant only for the ATR Pivot Margin method).
5.5 Reward Inputs (Take Profit)
Show Take Profit 1/2/3: ON/OFF switch to control the visibility of each Take Profit target.
Reward/Risk Ratio 1/ 2/ 3: Defines the R/R ratio for the profit target. Must be ≥1.0.
6. Indicator Status/Warning Messages
In situations where the Stop Loss location cannot be calculated logically and validly, often caused by a mismatch between the configured Focused Trend (Uptrend/Downtrend) and the actual price action, the indicator will display a warning message, explaining the reason and suggesting corrective action.
Status Message 1: Pivot reference unavailable
Condition: The Stop Loss is set to the "ATR Pivot Margin" method, but the anchor point (Pivot) is missing or inaccessible.
Message Displayed: "Pivot reference unavailable. Wait for valid price action, or adjust the Regular Hours Limitation setting or Pivot Left/Right inputs."
Status Message 2: Calculated Stop Loss is unsafe
Condition: The calculated Stop Loss is placed illogically or unsafely relative to the trend direction and the Entry price.
Message Displayed: "Calculated Stop Loss is unsafe for current trend. Wait for valid price action or adjust SL Lookback/Multiplier."
7. Summary
The Adaptive Risk Management (ARM) indicator provides a seamless and systematic approach to trade execution and risk control. By dynamically automating all critical trade parameters—from Entry Price and Stop Loss placement to Position Sizing and Take Profit targets—ARM removes emotional bias and ensures every trade adheres strictly to your predefined risk profile.
Key Benefits:
Systematic Risk Control: Strict enforcement of maximum capital allocation and risk per trade limits.
Adaptivity: Dynamic calculation of prices and quantities based on real-time market data (ATR and Lookback).
Clarity and Trust: Clear on-chart visualization, precise data metrics (16 series), and unambiguous Status/Warning Messages ensure transparency and reliability.
ARM allows traders to focus on strategy and analysis, confident that their execution complies with the core principles of professional risk management.
Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
Liquidity Swings [LuxAlgo] – Intrabar More Granulara “high-resolution” version of the same script with the more-granular pivots baked in.
Alson Chew PAM EXE and Mother BarIndicators for strategies taught by Alson Chew's Price Action Manipulation (PAM) course
Two functions.
First it identifies EXE bars (Pin, Mark, Icecream bars).
Second it identifies Mother bars and draws an extension line for 6 bars.
Applicable to all time frames and can customise how many signals to show.
To be used in conjunction with trading strategies like
- 20 SMA, 50 SMA, 200 SMA FS formation
- Force Bottom, Force Top FS formation
- UR1 and DR1 using EXE Bar
VYW Stop Loss LinesA simple utility designed to visually display Stop Loss lines on the chart based on an offset from the current price (the orange dashed lines in the screenshot above).
This indicator can also draw a line from the current bar's close price to the Price axis (the dashed gray line in the screenshot above).
VOLX+ VWAP Range BandsVOLX+ plots multiple VWAP-weighted high/low channels across different lookback periods to show how price behaves relative to short-term and long-term value zones.
Instead of using a single VWAP line, this tool creates four rolling VWAP envelopes:
Short-term range (fast reaction)
Mid-term range
Mid-mid range (transitional layer)
Long-term range (macro context)
Each band is computed as:
VWAP-High = SMA(high × volume, length) ÷ SMA(volume, length)
VWAP-Low = SMA(low × volume, length) ÷ SMA(volume, length)
This produces dynamic price channels that account for both price and traded volume, offering a clearer sense of where the market is accepting or rejecting value.
What It Shows
Four VWAP-weighted high/low bands
A short-term VWAP midline
Price line
Three SMAs for trend context
Optional visibility switches for each VWAP band
The filled regions between VWAP highs and lows create a layered “value map,” helping you interpret:
Trend continuation (price hugging outer VWAP bands)
Mean reversion (price returning toward inner bands)
Volatility contraction/expansion
Shifts in short-term vs long-term balance
🧠 How to Use
Use the short-term band for day-trading context or detecting short-term excess.
Use mid-term and mid-mid bands to confirm developing structure.
Use the long-term VWAP band to understand broader value zones.
Combine VWAP bands with SMAs and structure analysis for confluence.
This indicator is intended for price interpretation and analytical support.
✔ Does Not Repaint
The script uses rolling VWAP formulas and standard MAs; everything is stable and non-repainting.
ChronoPulse MS-MACD Resonance StrategyChronoPulse MS-MACD Resonance Strategy
A systematic trading strategy that combines higher-timeframe market structure analysis with dual MACD momentum confirmation, ATR-based risk management, and real-time quality assurance monitoring.
Core Principles
The strategy operates on the principle of multi-timeframe confluence, requiring agreement between:
Market structure breaks (CHOCH/BOS) on a higher timeframe
Dual MACD momentum confirmation (classic and crypto-tuned profiles)
Trend alignment via directional EMAs
Volatility and volume filters
Quality score composite threshold
Strategy Components
Market Structure Engine : Detects Break of Structure (BOS) and Change of Character (CHOCH) events using confirmed pivots on a configurable higher timeframe. Default structure timeframe is 240 minutes (4H).
Dual MACD Fusion : Requires agreement between two MACD configurations:
Classic MACD: 12/26/9 (default)
Fusion MACD: 8/21/5 (default, optimized for crypto volatility)
Both must agree on direction before trade execution. This can be disabled to use single MACD confirmation.
Trend Alignment : Uses two EMAs for directional bias:
Directional EMA: 55 periods (default)
Execution Trend Guide: 34 periods (default)
Both must align with trade direction.
ATR Risk Management : All risk parameters are expressed in ATR multiples:
Stop Loss: 1.5 × ATR (default)
Take Profit: 3.0 × ATR (default)
Trail Activation: 1.0 × ATR profit required (default)
Trail Distance: 1.5 × ATR behind price (default)
Volume Surge Filter : Optional gate requiring current volume to exceed a multiple of the volume SMA. Default threshold is 1.4× the 20-period volume SMA.
Quality Score Gate : Composite score (0-1) combining:
Structure alignment (0.0-1.0)
Momentum strength (0.0-1.0)
Trend alignment (0.0-1.0)
ATR volatility score (0.0-1.0)
Volume intensity (0.0-1.0)
Default threshold: 0.62. Trades only execute when quality score exceeds this threshold.
Execution Discipline : Trade budgeting system:
Maximum trades per session: 6 (default)
Cooldown bars between entries: 5 (default)
Quality Assurance Console : Real-time monitoring panel displaying:
Structure status (pass/fail)
Momentum confirmation (pass/fail)
Volatility readiness (pass/fail)
Quality score (pass/fail)
Discipline compliance (pass/fail)
Performance metrics (win rate, profit factor)
Net PnL
Certification requires: Win Rate ≥ 40%, Profit Factor ≥ 1.4, Minimum 25 closed trades, and positive net profit.
Integrity Suite : Optional validation panel that audits:
Configuration sanity checks
ATR data readiness
EMA hierarchy validity
Performance realism checks
Strategy Settings
strategy(
title="ChronoPulse MS-MACD Resonance Strategy",
shorttitle="ChronPulse",
overlay=true,
max_labels_count=500,
max_lines_count=500,
initial_capital=100000,
currency=currency.USD,
pyramiding=0,
commission_type=strategy.commission.percent,
commission_value=0.015,
slippage=2,
default_qty_type=strategy.percent_of_equity,
default_qty_value=2.0,
calc_on_order_fills=true,
calc_on_every_tick=true,
process_orders_on_close=true
)
Key Input Parameters
Structure Timeframe : 240 (4H) - Higher timeframe for structure analysis
Structure Pivot Left/Right : 3/3 - Pivot confirmation periods
Structure Break Buffer : 0.15% - Buffer for structure break confirmation
MACD Fast/Slow/Signal : 12/26/9 - Classic MACD parameters
Fusion MACD Fast/Slow/Signal : 8/21/5 - Crypto-tuned MACD parameters
Directional EMA Length : 55 - Primary trend filter
Execution Trend Guide : 34 - Secondary trend filter
ATR Length : 14 - ATR calculation period
ATR Stop Multiplier : 1.5 - Stop loss in ATR units
ATR Target Multiplier : 3.0 - Take profit in ATR units
Trail Activation : 1.0 ATR - Profit required before trailing
Trail Distance : 1.5 ATR - Distance behind price
Volume Threshold : 1.4× - Volume surge multiplier
Quality Threshold : 0.62 - Minimum quality score (0-1)
Max Trades Per Session : 6 - Daily trade limit
Cooldown Bars : 5 - Bars between entries
Win-Rate Target : 40% - Minimum for QA certification
Profit Factor Target : 1.4 - Minimum for QA certification
Minimum Trades for QA : 25 - Required closed trades
Signal Generation Logic
A trade signal is generated when ALL of the following conditions are met:
Higher timeframe structure shows bullish (CHOCH/BOS) or bearish structure break
Both MACD profiles agree on direction (if fusion enabled)
Price is above both EMAs for longs (below for shorts)
ATR data is ready and above minimum threshold
Volume exceeds threshold × SMA (if volume gate enabled)
Quality score ≥ quality threshold
Trade budget available (under max trades per day)
Cooldown period satisfied
Risk Management
Stop loss and take profit are set immediately on entry
Trailing stop activates after 1.0 ATR of profit
Trailing stop maintains 1.5 ATR distance behind highest profit point
Position sizing uses 2% of equity per trade (default)
No pyramiding (single position per direction)
Limitations and Considerations
The strategy requires sufficient historical data for higher timeframe structure analysis
Quality gate may filter out many potential trades, reducing trade frequency
Performance metrics are based on historical backtesting and do not guarantee future results
Commission and slippage assumptions (0.015% + 2 ticks) may vary by broker
The strategy is optimized for trending markets with clear structure breaks
Choppy or ranging markets may produce false signals
Crypto markets may require different parameter tuning than traditional assets
Optimization Notes
The strategy includes several parameters that can be tuned for different market conditions:
Quality Threshold : Lower values (0.50-0.60) allow more trades but may reduce average quality. Higher values (0.70+) are more selective but may miss opportunities.
Structure Timeframe : Use 240 (4H) for intraday trading, Daily for swing trading, Weekly for position trading
Volume Gate : Disable for low-liquidity pairs or when volume data is unreliable
Dual MACD Fusion : Disable for mean-reverting markets where single MACD may be more responsive
Trade Discipline : Adjust max trades and cooldown based on your risk tolerance and market volatility
Non-Repainting Guarantee
All higher timeframe data requests use lookahead=barmerge.lookahead_off to prevent repainting. Pivot detection waits for full confirmation before registering structure breaks. All visual elements (tables, labels) update only on closed bars.
Alerts
Three alert conditions are available:
ChronoPulse Long Setup : Fires when all long entry conditions are met
ChronoPulse Short Setup : Fires when all short entry conditions are met
ChronoPulse QA Certification : Fires when Quality Assurance console reaches CERTIFIED status
Configure alerts with "Once Per Bar Close" delivery to match the non-repainting design.
Visual Elements
Structure Labels : CHOCH↑, CHOCH↓, BOS↑, BOS↓ markers on structure breaks
Directional EMA : Orange line showing trend bias
Trailing Stop Lines : Green (long) and red (short) trailing stop levels
Dashboard Panel : Real-time status display (structure, MACD, ATR, quality, PnL)
QA Console : Quality assurance monitoring panel
Integrity Suite Panel : Optional validation status display
Recommended Usage
Forward test with paper trading before live deployment
Monitor the QA console until it reaches CERTIFIED status
Adjust parameters based on your specific market and timeframe
Respect the trade discipline limits to avoid over-trading
Review quality scores and adjust threshold if needed
Use appropriate commission and slippage settings for your broker
Technical Implementation
The strategy uses Pine Script v6 with the following key features:
Multi-timeframe data requests with lookahead protection
Confirmed pivot detection for structure analysis
Dynamic trailing stop management
Real-time quality score calculation
Trade budgeting and cooldown enforcement
Comprehensive dashboard and monitoring panels
All source code is open and available for review and modification.
Disclaimer
This script is for educational and informational purposes only. It is not intended as financial, investment, or trading advice. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Always conduct your own research and consult with a qualified financial advisor before making any trading decisions. The author and TradingView are not responsible for any losses incurred from using this strategy.
Volume Delta + Bandas de Bollinger📊 Volume Delta + Bollinger Bands Indicator
Characteristics
• Volume Delta Histogram
• Shows the difference between buying and selling pressure.
• Green bars indicate positive delta (buyers dominating).
• Red bars indicate negative delta (sellers dominating).
• The histogram oscillates around the zero line, which represents balance between buyers and sellers.
• Bollinger Bands applied to Delta
• A moving average (basis line) of the delta is calculated.
• Upper and lower bands are plotted using standard deviation.
• These bands highlight periods when the delta moves to statistically extreme levels.
• Helps identify unusual buying or selling pressure compared to recent history.
• Zero Line Reference
• A horizontal line at zero shows equilibrium.
• Crossing above zero suggests net buying pressure.
• Crossing below zero suggests net selling pressure.
How to Use
• Identify Buyer/Seller Dominance
• Green histogram bars above zero → buyers are stronger.
• Red histogram bars below zero → sellers are stronger.
• Spot Extremes with Bollinger Bands
• When delta touches or exceeds the upper band, it signals unusually strong buying pressure.
• When delta touches or exceeds the lower band, it signals unusually strong selling pressure.
• These extremes can precede reversals or mark continuation if confirmed by price action.
• Combine with Price Analysis
• Use delta signals together with price trends and support/resistance levels.
• For example, if price is at resistance and delta spikes into the upper band, it may indicate exhaustion of buyers.
• If price is at support and delta spikes into the lower band, it may indicate exhaustion of sellers.
• Trading Strategy Ideas
• Reversal setups: Look for delta extremes against key price levels.
• Trend confirmation: Sustained delta above zero supports bullish trends; sustained delta below zero supports bearish trends.
• Volatility filter: Bollinger Bands help filter out normal fluctuations and highlight significant imbalances.
👉 In short, this indicator combines order flow pressure (delta) with volatility context (Bollinger Bands), making it useful for spotting moments when buying or selling activity becomes unusually strong compared to recent history.
Reversal WaveThis is the type of quantitative system that can get you hated on investment forums, now that the Random Walk Theory is back in fashion. The strategy has simple price action rules, zero over-optimization, and is validated by a historical record of nearly a century on both Gold and the S&P 500 index.
Recommended Markets
SPX (Weekly, Monthly)
SPY (Monthly)
Tesla (Weekly)
XAUUSD (Weekly, Monthly)
NVDA (Weekly, Monthly)
Meta (Weekly, Monthly)
GOOG (Weekly, Monthly)
MSFT (Weekly, Monthly)
AAPL (Weekly, Monthly)
System Rules and Parameters
Total capital: $10,000
We will use 10% of the total capital per trade
Commissions will be 0.1% per trade
Condition 1: Previous Bearish Candle (isPrevBearish) (the closing price was lower than the opening price).
Condition 2: Midpoint of the Body The script calculates the exact midpoint of the body of that previous bearish candle.
• Formula: (Previous Open + Previous Close) / 2.
Condition 3: 50% Recovery (longCondition) The current candle must be bullish (green) and, most importantly, its closing price must be above the midpoint calculated in the previous step.
Once these parameters are met, the system executes a long entry and calculates the exit parameters:
Stop Loss (SL): Placed at the low of the candle that generated the entry signal.
Take Profit (TP): Calculated by projecting the risk distance upward.
• Calculation: Entry Price + (Risk * 1).
Risk:Reward Ratio of 1:1.
About the Profit Factor
In my experience, TradingView calculates profits and losses based on the percentage of movement, which can cause returns to not match expectations. This doesn’t significantly affect trending systems, but it can impact systems with a high win rate and a well-defined risk-reward ratio. It only takes one large entry candle that triggers the SL to translate into a major drop in performance.
For example, you might see a system with a 60% win rate and a 1:1 risk-reward ratio generating losses, even though commissions are under control relative to the number of trades.
My recommendation is to manually calculate the performance of systems with a well-defined risk-reward ratio, assuming you will trade using a fixed amount per trade and limit losses to a fixed percentage.
Remember that, even if candles are larger or smaller in size, we can maintain a fixed loss percentage by using leverage (in cases of low volatility) or reducing the capital at risk (when volatility is high).
Implementing leverage or capital reduction based on volatility is something I haven’t been able to incorporate into the code, but it would undoubtedly improve the system’s performance dramatically, as it would fix a consistent loss percentage per trade, preventing losses from fluctuating with volatility swings.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to exit or SL
And if volatility is high and exceeds the fixed percentage we want to expose per trade (if SL is hit), we could reduce the position size.
For example, imagine we only want to risk 15% per SL on Tesla, where volatility is high and would cause a 23.57% loss. In this case, we subtract 23.57% from 15% (the loss percentage we’re willing to accept per trade), then subtract the result from our usual position size.
23.57% - 15% = 8.57%
Suppose I use $200 per trade.
To calculate 8.57% of $200, simply multiply 200 by 8.57/100. This simple calculation shows that 8.57% equals about $17.14 of the $200. Then subtract that value from $200:
$200 - $17.14 = $182.86
In summary, if we reduced the position size to $182.86 (from the usual $200, where we’re willing to lose 15%), no matter whether Tesla moves up or down 23.57%, we would still only gain or lose 15% of the $200, thus respecting our risk management.
Final Notes
The code is extremely simple, and every step of its development is detailed within it.
If you liked this strategy, which complements very well with others I’ve already published, stay tuned. Best regards.
Triple ATR Adaptive MAs + VWAP Option + Clouds + Candle Trend V2Another one of my experiences ... combining things...
📘 Indicator Description – Triple ATR Adaptive Moving Averages with VWAP Influence
This indicator plots three adaptive moving averages whose behavior changes dynamically based on market volatility (ATR) and optionally VWAP deviation.
Because they adapt in real time to both volatility and VWAP pressure, their movement, slope, and reaction speed differ significantly from traditional moving averages.
🔶 1. ATR-Adaptive Moving Averages
Each of the three MAs uses a custom adaptive formula:
ATR (Average True Range) is measured over a chosen period.
Higher ATR → more volatility → the MA becomes more reactive and moves closer to price.
Lower ATR → stable market → the MA becomes smoother and slower.
This creates a volatility-aware smoothing factor, making the MA expand, contract, and respond to market conditions in ways a classic SMA, EMA, or HMA cannot.
🔷 2. Optional VWAP Influence
Each MA has an independent toggle allowing it to be influenced by VWAP.
When enabled:
The MA is gently “pulled” toward VWAP.
The strength of this attraction is determined by the VWAP Influence parameter (0–1).
This causes the moving averages to behave differently from normal MAs:
In trending markets, the ATR and price push the MA away from VWAP.
In mean-reverting or balanced conditions, VWAP pulls the MA back toward fair value.
The result is an MA that reflects both trend pressure and fair-value pressure.
🔶 3. Visual Behavior: Non-Traditional Movement
Because each MA is simultaneously influenced by volatility, trend magnitude, and VWAP deviation, their shape is often very distinct from normal moving averages.
They may:
Respond faster during high volatility
Flatten out earlier during consolidation
Curve toward VWAP when price becomes extended
Separate or compress depending on ATR strength
This is intentional and essential, since the goal is to show:
✔ Volatility expansion
✔ Trend exhaustion
✔ Overextended price relative to VWAP
✔ Dynamic trend confirmation
Rather than simply smoothing past price.
🔷 4. Three Independent Adaptive Lines
Each of the three moving averages has:
Its own ATR length
Its own sensitivity multiplier
Its own optional VWAP influence
Its own color and trail
This allows the user to combine:
a fast volatility-adaptive trend line
a mid-range adaptive baseline
a slow adaptive long-trend MA
All adapting independently to volatility and VWAP conditions.
🔶 5. Optional Candle Coloring
The indicator can color candles according to trend strength derived from the fast/slow MAs.
Stronger trends produce more vivid colors. Neutral or conflicting trends produce softer colors.
This adds a visual layer to identify:
Trend direction
Trend strength
Volatility state
Market compression
at a glance.
📌 Summary
This indicator does not behave like standard SMAs or EMAs because each line dynamically adapts to:
🔸 ATR (volatility)
🔸 VWAP (fair value)
This makes the indicator extremely responsive to market conditions while still reducing noise during stable phases.
It provides a more realistic, context-aware, and intelligent representation of price behavior compared to traditional moving averages.
Advanced Volume Suite (24h, Pulse, Spikes, Breakout Pressure)Advanced Volume Suite transforms raw volume into a complete market-intelligence toolkit for breakout, momentum, and liquidity-driven trading.
Unlike the basic volume indicator, this tool analyzes volume in true USDT value, tracks rolling 24h exchange-style volume, measures volume strength vs historical averages, detects smart spikes, and highlights breakout pressure near support/resistance.
Core Features:
• USDT-based volume histogram
• 24h rolling volume line
• Volume Pulse (volume vs moving average)
• Smart spike detection with directional filters
• Breakout pressure system (breakouts + near-breakout conditions)
• 3 advanced volume color modes (Simple / Body / Delta-style)
• All signals and thresholds fully configurable
Perfect for traders who rely on volume confirmation for breakouts, momentum entries, scalping, or detecting institutional activity.
