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Breakout Josip strategy is focused on analyzing price movements during specific time intervals (from 9:00 AM to 12:00 PM) each day. It tracks the highest and lowest prices in that period and uses them to set targets for potential trades, placing horizontal lines based on these levels. Additionally, you're interested in tracking the success and failure of trades based on whether price breaks certain levels during this time range. The strategy also calculates various metrics like the percentage of successful trades, failed trades, and total trades during a selected time range.
Pine Script® indicator
by fluoclipwow
Breakout Candles + RSIHello! This is my firt script :) This indicator looks for candles that are significantly larger than the previous X candle. It is possible to set the following: Multiplier: deviation from the size of the previous X candle (if set to 3 the size of the actual candle's body /abs(open - close)/ must be larger than the size of the bigger candle from the prevous X candles) Previous candles: the number of previous candles to size check Upper RSI limit: if the RSI14 close higher than the specified number, the candle will ignore Lower RSI limit: if the RSI14 close lower than the specified number, the candle will ignore Without dojis: if checked, watches candles only that do not have a bottom spike (bullish) or top spike (bearish). Useful for Heikin-Ashi candles Feel free to left any suggestion! Thank You!
Pine Script® indicator
by mildZebra14333
4
Breakout Volume Can Help Confirm Other SignalsVolume can help confirm signals we might discover using other methods of technical analysis. This indicator tracks volume intelligently. Its logic spots above-average turnover and then tests against the price change. BrkVol highlights sessions with heavy volume and directional moves. This can help take out the noise and help confirm the trend. Tesla is a classic example of this, with the stock rallying after showing heavy-volume gains on October 24- 25, December 16 and January 8.
Pine Script® indicator
by TradeStation
6
TTM Squeeze [ST]**TTM Squeeze ** is a streamlined volatility indicator designed to identify periods of consolidation before potential price breakouts. This version focuses exclusively on the "Squeeze Dots" component, making it a lightweight and minimalist tool for traders who want to filter low-volatility environments without the clutter of a momentum histogram. ### 🛠 Key Concepts The indicator compares **Bollinger Bands** (Standard Deviation) with **Keltner Channels** (Average True Range): 1. **🔴 Red Dots (Squeeze ON):** * Occurs when Bollinger Bands contract *inside* the Keltner Channels. * **Meaning:** Volatility is extremely low. The market is "coiling" or building up energy. * **Action:** Prepare for a potential breakout. Do not trade the chop; wait for expansion. 2. **⚫ Dark Gray Dots (Squeeze OFF):** * Occurs when Bollinger Bands expand *outside* the Keltner Channels. * **Meaning:** The squeeze has "fired." Volatility is expanding. * **Action:** The move has likely started. ### ⚙️ Standardization * **Part of the Suite:** Standardized inputs and optimized performance. * **English Native:** Codebase and settings translated to English. * **Version Control:** Internal version tracking included. ### 📋 How to Use Use this tool as a "Go / No-Go" filter for your trades. * If the dot is **Red**, avoid entering new trend-following positions, as the price is likely chopping sideways. * Wait for the first **Gray** dot after a series of Red dots to signal the start of a new volatility expansion phase. --- *Disclaimer: This tool is for educational purposes and technical analysis assistance only. Always manage your risk.*
Pine Script® indicator
by impressive_Storkj9gr3
Liquidity Depth Indicator [BigBeluga]🔵 OVERVIEW Liquidity Depth Indicator visualizes the distribution, balance, and depth of liquidity within a selected lookback window. It builds a full liquidity profile by scanning how often price interacted with each price level, generating cumulative buy-side and sell-side curves, heatmap intensity zones, and a clear Point of Control (PoC). This provides a deep structural view of where liquidity sits, how it’s stacked, and which side of the market dominates. 🔵 CONCEPTS Liquidity Binning — The full range (High → Low) over the lookback window is divided into 100 micro-price zones. Each candle contributes its volume into the bin closest to its close. Buy/Sell Side Split — • Zones above the midpoint = potential sell-side liquidity concentration. • Zones below midpoint = potential buy-side liquidity concentration. Cumulative Liquidity Curves — Each side builds a flowing curve showing how liquidity stacks from mid toward extremes. Liquidity Heatmap — Highlights volume density at each price level using color intensity for easy visual analysis. Point of Control — The price level with the highest liquidity accumulation (max volume bin). 🔵 FEATURES 100-Level Volume Distribution — Scans all candles inside the lookback period and assigns each close to the nearest bin. Sell-Side Depth Curve — Plotted above the midpoint, showing how sell liquidity increases as price moves toward the top of the range. Buy-Side Depth Curve — Plotted below the midpoint, showing how buy liquidity builds toward the bottom of the range. Volume Labels — Displays total buy-side and sell-side volume at curve peaks. Mid-Range Liquidity Split — Calculates: • Buy-side liquidity % • Sell-side liquidity % Displayed in two vertical boxes next to the profile. Liquidity Heatmap Overlay — Color-coded price strips showing where largest clusters sit: • Above midpoint → Sell zones • Below midpoint → Buy zones PoC Detection — Draws the strongest liquidity level with a bold line and prints its relative volume. Range Frame Lines — High, Low, and Mid lines are plotted to define the liquidity environment. Auto-Cleanup & Rebuild — All curves, boxes, and heatmap segments are refreshed each bar using barstate.islast. 🔵 HOW IT WORKS 1. Determines High, Low, and Mid over the lookback window. 2. Divides the range into 100 bins based on linear spacing. 3. Accumulates volume per bin depending on where each candle’s close lands. 4. Builds total, buy-side, and sell-side cumulative curves . 5. Colors the heatmap based on normalized volume per bin. 6. Locates PoC — the bin with maximum volume. 7. Creates buy/sell percentage distribution boxes . 🔵 HOW TO USE Identify Liquidity Imbalance — Compare the buy vs sell percentage boxes to see which side dominates. Spot Strong Liquidity Walls — Thick portions of cumulative curves represent areas price may reject. Read PoC as a Magnet — Price often gravitates toward the PoC or reacts strongly once reached. Evaluate Breakout Strength — If liquidity is concentrated at extremes, a breakout may face strong absorption. Use Heatmap as Hidden S/R — The brightest zones frequently act as hidden support/resistance. Detect Exhaustion Areas — If a curve sharply thins near highs or lows, the trend may weaken. 🔵 CONCLUSION Liquidity Depth Indicator is a powerful microstructure tool that reveals where liquidity is stacked within a price range. By combining cumulative curves, heat mapping, and PoC identification, it exposes both visible and hidden liquidity layers — helping traders spot absorption zones, reversal clusters, liquidity pools, and trend exhaustion areas with high clarity.
Pine Script® indicator
by BigBeluga
ORB Fusion🎯 CORE INNOVATION: INSTITUTIONAL ORB FRAMEWORK WITH FAILED BREAKOUT INTELLIGENCE ORB Fusion represents a complete institutional-grade Opening Range Breakout system combining classic Market Profile concepts (Initial Balance, day type classification) with modern algorithmic breakout detection, failed breakout reversal logic, and comprehensive statistical tracking. Rather than simply drawing lines at opening range extremes, this system implements the full trading methodology used by professional floor traders and market makers—including the critical concept that failed breakouts are often higher-probability setups than successful breakouts . The Opening Range Hypothesis: The first 30-60 minutes of trading establishes the day's value area —the price range where the majority of participants agree on fair value. This range is formed during peak information flow (overnight news digestion, gap reactions, early institutional positioning). Breakouts from this range signal directional conviction; failures to hold breakouts signal trapped participants and create exploitable reversals. Why Opening Range Matters: 1. Information Aggregation : Opening range reflects overnight news, pre-market sentiment, and early institutional orders. It's the market's initial "consensus" on value. 2. Liquidity Concentration : Stop losses cluster just outside opening range. Breakouts trigger these stops, creating momentum. Failed breakouts trap traders, forcing reversals. 3. Statistical Persistence : Markets exhibit range expansion tendency —when price accepts above/below opening range with volume, it often extends 1.0-2.0x the opening range size before mean reversion. 4. Institutional Behavior : Large players (market makers, institutions) use opening range as reference for the day's trading plan. They fade extremes in rotation days and follow breakouts in trend days. Historical Context: Opening Range Breakout methodology originated in commodity futures pits (1970s-80s) where floor traders noticed consistent patterns: the first 30-60 minutes established a "fair value zone," and directional moves occurred when this zone was violated with conviction. J. Peter Steidlmayer formalized this observation in Market Profile theory, introducing the "Initial Balance" concept—the first hour (two 30-minute periods) defining market structure. 📊 OPENING RANGE CONSTRUCTION Four ORB Timeframe Options: 1. 5-Minute ORB (0930-0935 ET): Captures immediate market direction during "opening drive"—the explosive first few minutes when overnight orders hit the tape. Use Case: • Scalping strategies • High-frequency breakout trading • Extremely liquid instruments (ES, NQ, SPY) Characteristics: • Very tight range (often 0.2-0.5% of price) • Early breakouts common (7 of 10 days break within first hour) • Higher false breakout rate (50-60%) • Requires sub-minute chart monitoring Psychology: Captures panic buyers/sellers reacting to overnight news. Range is small because sample size is minimal—only 5 minutes of price discovery. Early breakouts often fail because they're driven by retail FOMO rather than institutional conviction. 2. 15-Minute ORB (0930-0945 ET): Balances responsiveness with statistical validity. Captures opening drive plus initial reaction to that drive. Use Case: • Day trading strategies • Balanced scalping/swing hybrid • Most liquid instruments Characteristics: • Moderate range (0.4-0.8% of price typically) • Breakout rate ~60% of days • False breakout rate ~40-45% • Good balance of opportunity and reliability Psychology: Includes opening panic AND the first retest/consolidation. Sophisticated traders (institutions, algos) start expressing directional bias. This is the "Goldilocks" timeframe—not too reactive, not too slow. 3. 30-Minute ORB (0930-1000 ET): Classic ORB timeframe. Default for most professional implementations. Use Case: • Standard intraday trading • Position sizing for full-day trades • All liquid instruments (equities, indices, futures) Characteristics: • Substantial range (0.6-1.2% of price) • Breakout rate ~55% of days • False breakout rate ~35-40% • Statistical sweet spot for extensions Psychology: Full opening auction + first institutional repositioning complete. By 10:00 AM ET, headlines are digested, early stops are hit, and "real" directional players reveal themselves. This is when institutional programs typically finish their opening positioning. Statistical Advantage: 30-minute ORB shows highest correlation with daily range. When price breaks and holds outside 30m ORB, probability of reaching 1.0x extension (doubling the opening range) exceeds 60% historically. 4. 60-Minute ORB (0930-1030 ET) - Initial Balance: Steidlmayer's "Initial Balance"—the foundation of Market Profile theory. Use Case: • Swing trading entries • Day type classification • Low-frequency institutional setups Characteristics: • Wide range (0.8-1.5% of price) • Breakout rate ~45% of days • False breakout rate ~25-30% (lowest) • Best for trend day identification Psychology: Full first hour captures A-period (0930-1000) and B-period (1000-1030). By 10:30 AM ET, all early positioning is complete. Market has "voted" on value. Subsequent price action confirms (trend day) or rejects (rotation day) this value assessment. Initial Balance Theory: IB represents the market's accepted value area . When price extends significantly beyond IB (>1.5x IB range), it signals a Trend Day —strong directional conviction. When price remains within 1.0x IB, it signals a Rotation Day —mean reversion environment. This classification completely changes trading strategy. 🔬 LTF PRECISION TECHNOLOGY The Chart Timeframe Problem: Traditional ORB indicators calculate range using the chart's current timeframe. This creates critical inaccuracies: Example: • You're on a 5-minute chart • ORB period is 30 minutes (0930-1000 ET) • Indicator sees only 6 bars (30min ÷ 5min/bar = 6 bars) • If any 5-minute bar has extreme wick, entire ORB is distorted The Problem Amplifies: • On 15-minute chart with 30-minute ORB: Only 2 bars sampled • On 30-minute chart with 30-minute ORB: Only 1 bar sampled • Opening spike or single large wick defines entire range (invalid) Solution: Lower Timeframe (LTF) Precision: ORB Fusion uses `request.security_lower_tf()` to sample 1-minute bars regardless of chart timeframe: ``` For 30-minute ORB on 15-minute chart: - Traditional method: Uses 2 bars (15min × 2 = 30min) - LTF Precision: Requests thirty 1-minute bars, calculates true high/low ``` Why This Matters: Scenario: ES futures, 15-minute chart, 30-minute ORB • Traditional ORB: High = 5850.00, Low = 5842.00 (range = 8 points) • LTF Precision ORB: High = 5848.50, Low = 5843.25 (range = 5.25 points) Difference: 2.75 points distortion from single 15-minute wick hitting 5850.00 at 9:31 AM then immediately reversing. LTF precision filters this out by seeing it was a fleeting wick, not a sustained high. Impact on Extensions: With inflated range (8 points vs 5.25 points): • 1.5x extension projects +12 points instead of +7.875 points • Difference: 4.125 points (nearly $200 per ES contract) • Breakout signals trigger late; extension targets unreachable Implementation: ```pinescript getLtfHighLow() => float ha = request.security_lower_tf(syminfo.tickerid, "1", high) float la = request.security_lower_tf(syminfo.tickerid, "1", low) ``` Function returns arrays of 1-minute high/low values, then finds true maximum and minimum across all samples. When LTF Precision Activates: Only when chart timeframe exceeds ORB session window: • 5-minute chart + 30-minute ORB: LTF used (chart TF > session bars needed) • 1-minute chart + 30-minute ORB: LTF not needed (direct sampling sufficient) Recommendation: Always enable LTF Precision unless you're on 1-minute charts. The computational overhead is negligible, and accuracy improvement is substantial. ⚖️ INITIAL BALANCE (IB) FRAMEWORK Steidlmayer's Market Profile Innovation: J. Peter Steidlmayer developed Market Profile in the 1980s for the Chicago Board of Trade. His key insight: market structure is best understood through time-at-price (value area) rather than just price-over-time (traditional charts). Initial Balance Definition: IB is the price range established during the first hour of trading, subdivided into: • A-Period : First 30 minutes (0930-1000 ET for US equities) • B-Period : Second 30 minutes (1000-1030 ET) A-Period vs B-Period Comparison: The relationship between A and B periods forecasts the day: B-Period Expansion (Bullish): • B-period high > A-period high • B-period low ≥ A-period low • Interpretation: Buyers stepping in after opening assessed • Implication: Bullish continuation likely • Strategy: Buy pullbacks to A-period high (now support) B-Period Expansion (Bearish): • B-period low < A-period low • B-period high ≤ A-period high • Interpretation: Sellers stepping in after opening assessed • Implication: Bearish continuation likely • Strategy: Sell rallies to A-period low (now resistance) B-Period Contraction: • B-period stays within A-period range • Interpretation: Market indecisive, digesting A-period information • Implication: Rotation day likely, stay range-bound • Strategy: Fade extremes, sell high/buy low within IB IB Extensions: Professional traders use IB as a ruler to project price targets: Extension Levels: • 0.5x IB : Initial probe outside value (minor target) • 1.0x IB : Full extension (major target for normal days) • 1.5x IB : Trend day threshold (classifies as trending) • 2.0x IB : Strong trend day (rare, ~10-15% of days) Calculation: ``` IB Range = IB High - IB Low Bull Extension 1.0x = IB High + (IB Range × 1.0) Bear Extension 1.0x = IB Low - (IB Range × 1.0) ``` Example: ES futures: • IB High: 5850.00 • IB Low: 5842.00 • IB Range: 8.00 points Extensions: • 1.0x Bull Target: 5850 + 8 = 5858.00 • 1.5x Bull Target: 5850 + 12 = 5862.00 • 2.0x Bull Target: 5850 + 16 = 5866.00 If price reaches 5862.00 (1.5x), day is classified as Trend Day —strategy shifts from mean reversion to trend following. 📈 DAY TYPE CLASSIFICATION SYSTEM Four Day Types (Market Profile Framework): 1. TREND DAY: Definition: Price extends ≥1.5x IB range in one direction and stays there. Characteristics: • Opens and never returns to IB • Persistent directional movement • Volume increases as day progresses (conviction building) • News-driven or strong institutional flow Frequency: ~20-25% of trading days Trading Strategy: • DO: Follow the trend, trail stops, let winners run • DON'T: Fade extremes, take early profits • Key: Add to position on pullbacks to previous extension level • Risk: Getting chopped in false trend (see Failed Breakout section) Example: FOMC decision, payroll report, earnings surprise—anything creating one-sided conviction. 2. NORMAL DAY: Definition: Price extends 0.5-1.5x IB, tests both sides, returns to IB. Characteristics: • Two-sided trading • Extensions occur but don't persist • Volume balanced throughout day • Most common day type Frequency: ~45-50% of trading days Trading Strategy: • DO: Take profits at extension levels, expect reversals • DON'T: Hold for massive moves • Key: Treat each extension as a profit-taking opportunity • Risk: Holding too long when momentum shifts Example: Typical day with no major catalysts—market balancing supply and demand. 3. ROTATION DAY: Definition: Price stays within IB all day, rotating between high and low. Characteristics: • Never accepts outside IB • Multiple tests of IB high/low • Decreasing volume (no conviction) • Classic range-bound action Frequency: ~25-30% of trading days Trading Strategy: • DO: Fade extremes (sell IB high, buy IB low) • DON'T: Chase breakouts • Key: Enter at extremes with tight stops just outside IB • Risk: Breakout finally occurs after multiple failures Example: [/b> Pre-holiday trading, summer doldrums, consolidation after big move. 4. DEVELOPING: Definition: Day type not yet determined (early in session). Usage: Classification before 12:00 PM ET when IB extension pattern unclear. ORB Fusion's Classification Algorithm: ```pinescript if close > ibHigh: ibExtension = (close - ibHigh) / ibRange direction = "BULLISH" else if close < ibLow: ibExtension = (ibLow - close) / ibRange direction = "BEARISH" if ibExtension >= 1.5: dayType = "TREND DAY" else if ibExtension >= 0.5: dayType = "NORMAL DAY" else if close within IB: dayType = "ROTATION DAY" ``` Why Classification Matters: Same setup (bullish ORB breakout) has opposite implications: • Trend Day : Hold for 2.0x extension, trail stops aggressively • Normal Day : Take profits at 1.0x extension, watch for reversal • Rotation Day : Fade the breakout immediately (likely false) Knowing day type prevents catastrophic errors like fading a trend day or holding through rotation. 🚀 BREAKOUT DETECTION & CONFIRMATION Three Confirmation Methods: 1. Close Beyond Level (Recommended): Logic: Candle must close above ORB high (bull) or below ORB low (bear). Why: • Filters out wicks (temporary liquidity grabs) • Ensures sustained acceptance above/below range • Reduces false breakout rate by ~20-30% Example: • ORB High: 5850.00 • Bar high touches 5850.50 (wick above) • Bar closes at 5848.00 (inside range) • Result: NO breakout signal vs. • Bar high touches 5850.50 • Bar closes at 5851.00 (outside range) • Result: BREAKOUT signal confirmed Trade-off: Slightly delayed entry (wait for close) but much higher reliability. 2. Wick Beyond Level: Logic: [/b> Any touch of ORB high/low triggers breakout. Why: • Earliest possible entry • Captures aggressive momentum moves Risk: • High false breakout rate (60-70%) • Stop runs trigger signals • Requires very tight stops (difficult to manage) Use Case: Scalping with 1-2 point profit targets where any penetration = trade. 3. Body Beyond Level: Logic: [/b> Candle body (close vs open) must be entirely outside range. Why: • Strictest confirmation • Ensures directional conviction (not just momentum) • Lowest false breakout rate Example: Trade-off: [/b> Very conservative—misses some valid breakouts but rarely triggers on false ones. Volume Confirmation Layer: All confirmation methods can require volume validation: Volume Multiplier Logic: Rationale: [/b> True breakouts are driven by institutional activity (large size). Volume spike confirms real conviction vs. stop-run manipulation. Statistical Impact: [/b> • Breakouts with volume confirmation: ~65% success rate • Breakouts without volume: ~45% success rate • Difference: 20 percentage points edge Implementation Note: [/b> Volume confirmation adds complexity—you'll miss breakouts that work but lack volume. However, when targeting 1.5x+ extensions (ambitious goals), volume confirmation becomes critical because those moves require sustained institutional participation. Recommended Settings by Strategy: [/b> Scalping (1-2 point targets): [/b> • Method: Close • Volume: OFF • Rationale: Quick in/out doesn't need perfection Intraday Swing (5-10 point targets): [/b> • Method: Close • Volume: ON (1.5x multiplier) • Rationale: Balance reliability and opportunity Position Trading (full-day holds): [/b> • Method: Body • Volume: ON (2.0x multiplier) • Rationale: Must be certain—large stops require high win rate 🔥 FAILED BREAKOUT SYSTEM The Core Insight: [/b> Failed breakouts are often more profitable [/b> than successful breakouts because they create trapped traders with predictable behavior. Failed Breakout Definition: [/b> A breakout that: 1. Initially penetrates ORB level with confirmation 2. Attracts participants (volume spike, momentum) 3. Fails to extend (stalls or immediately reverses) 4. Returns inside ORB range within N bars Psychology of Failure: [/b> When breakout fails: • Breakout buyers are trapped [/b>: Bought at ORB high, now underwater • Early longs reduce: Take profit, fearful of reversal • Shorts smell blood: See failed breakout as reversal signal • Result: Cascade of selling as trapped bulls exit + new shorts enter Mirror image for failed bearish breakouts (trapped shorts cover + new longs enter). Failure Detection Parameters: [/b> 1. Failure Confirmation Bars (default: 3): [/b> How many bars after breakout to confirm failure? Logic: Settings: [/b> • 2 bars: Aggressive failure detection (more signals, more false failures) • 3 bars Balanced (default) • 5-10 bars: Conservative (wait for clear reversal) Why This Matters: Too few bars: You call "failed breakout" when price is just consolidating before next leg. Too many bars: You miss the reversal entry (price already back in range). 2. Failure Buffer (default: 0.1 ATR): [/b> How far inside ORB must price return to confirm failure? Formula: Why Buffer Matters: clear rejection [/b> (not just hovering at level). Settings: [/b> • 0.0 ATR: No buffer, immediate failure signal • 0.1 ATR: Small buffer (default) - filters noise • [b>0.2-0.3 ATR: Large buffer - only dramatic failures count Example: Reversal Entry System: [/b> When failure confirmed, system generates complete reversal trade: For Failed Bull Breakout (Short Reversal): [/b> Entry: [/b> Current close when failure confirmed Stop Loss: [/b> Extreme high since breakout + 0.10 ATR padding Target 1: [/b> ORB High - (ORB Range × 0.5) Target 2: Target 3: [/b> ORB High - (ORB Range × 1.5) Example: • ORB High: 5850, ORB Low: 5842, Range: 8 points • Breakout to 5853, fails, reverses to 5848 (entry) • Stop: 5853 + 1 = 5854 (6 point risk) • T1: 5850 - 4 = 5846 (-2 points, 1:3 R:R) • T2: 5850 - 8 = 5842 (-6 points, 1:1 R:R) • T3: 5850 - 12 = 5838 (-10 points, 1.67:1 R:R) [b>Why These Targets? [/b> • T1 (0.5x ORB below high): Trapped bulls start panic • T2 (1.0x ORB = ORB Mid): Major retracement, momentum fully reversed • T3 (1.5x ORB): Reversal extended, now targeting opposite side Historical Performance: [/b> Failed breakout reversals in ORB Fusion's tracking system show: • Win Rate: 65-75% (significantly higher than initial breakouts) • Average Winner: 1.2x ORB range • Average Loser: 0.5x ORB range (protected by stop at extreme) • Expectancy: Strongly positive even with <70% win rate Why Failed Breakouts Outperform: [/b> 1. Information Advantage: You now know what price did (failed to extend). Initial breakout trades are speculative; reversal trades are reactive to confirmed failure. 2. Trapped Participant Pressure: Every trapped bull becomes a seller. This creates sustained pressure. 3. Stop Loss Clarity: Extreme high is obvious stop (just beyond recent high). Breakout trades have ambiguous stops (ORB mid? Recent low? Too wide or too tight). 4. Mean Reversion Edge: Failed breakouts return to value (ORB mid). Initial breakouts try to escape value (harder to sustain). Critical Insight: [/b> "The best trade is often the one that trapped everyone else." Failed breakouts create asymmetric opportunity because you're trading against [/b> trapped participants rather than with [/b> them. When you see a failed breakout signal, you're seeing real-time evidence that the market rejected directional conviction—that's exploitable. 📐 FIBONACCI EXTENSION SYSTEM Six Extension Levels: [/b> Extensions project how far price will travel after ORB breakout. Based on Fibonacci ratios + empirical market behavior. 1. 1.272x (27.2% Extension): [/b> Formula: [/b> ORB High/Low + (ORB Range × 0.272) Psychology: [/b> Initial probe beyond ORB. Early momentum + trapped shorts (on bull side) covering. Probability of Reach: [/b> ~75-80% after confirmed breakout Trading: [/b> • First resistance/support after breakout • Partial profit target (take 30-50% off) • Watch for rejection here (could signal failure in progress) Why 1.272? [/b> Related to harmonic patterns (1.272 is √1.618). Empirically, markets often stall at 25-30% extension before deciding whether to continue or fail. 2. 1.5x (50% Extension): Formula: [/b> ORB High/Low + (ORB Range × 0.5) Psychology: [/b> Breakout gaining conviction. Requires sustained buying/selling (not just momentum spike). Probability of Reach: [/b> ~60-65% after confirmed breakout Trading: [/b> • Major partial profit (take 50-70% off) • Move stops to breakeven • Trail remaining position Why 1.5x? [/b> Classic halfway point to 2.0x. Markets often consolidate here before final push. If day type is "Normal," this is likely the high/low for the day. 3. 1.618x (Golden Ratio Extension): [/b> Formula: [/b> ORB High/Low + (ORB Range × 0.618) Psychology: [/b> Strong directional day. Institutional conviction + retail FOMO. Probability of Reach: [/b> ~45-50% after confirmed breakout Trading: [/b> • Final partial profit (close 80-90%) • Trail remainder with wide stop (allow breathing room) Why 1.618? [/b> Fibonacci golden ratio. Appears consistently in market geometry. When price reaches 1.618x extension, move is "mature" and reversal risk increases. 4. 2.0x (100% Extension): [/b> Formula: ORB High/Low + (ORB Range × 1.0) Psychology: [/b> Trend day confirmed. Opening range completely duplicated. Probability of Reach: [/b> ~30-35% after confirmed breakout Trading: Why 2.0x? [/b> Psychological level—range doubled. Also corresponds to typical daily ATR in many instruments (opening range ~ 0.5 ATR, daily range ~ 1.0 ATR). 5. 2.618x (Super Extension): Formula: [/b> ORB High/Low + (ORB Range × 1.618) Psychology: [/b> Parabolic move. News-driven or squeeze. Probability of Reach: [/b> ~10-15% after confirmed breakout [b>Trading: Why 2.618? [/b> Fibonacci ratio (1.618²). Rare to reach—when it does, move is extreme. Often precedes multi-day consolidation or reversal. 6. 3.0x (Extreme Extension): [/b> Formula: [/b> ORB High/Low + (ORB Range × 2.0) Psychology: [/b> Market melt-up/crash. Only in extreme events. [b>Probability of Reach: [/b> <5% after confirmed breakout Trading: [/b> • Close immediately if reached • These are outlier events (black swans, flash crashes, squeeze-outs) • Holding for more is greed—take windfall profit Why 3.0x? [/b> Triple opening range. So rare it's statistical noise. When it happens, it's headline news. Visual Example: ES futures, ORB 5842-5850 (8 point range), Bullish breakout: • ORB High : 5850.00 (entry zone) • 1.272x : 5850 + 2.18 = 5852.18 (first resistance) • 1.5x : 5850 + 4.00 = 5854.00 (major target) • 1.618x : 5850 + 4.94 = 5854.94 (strong target) • 2.0x : 5850 + 8.00 = 5858.00 (trend day) • 2.618x : 5850 + 12.94 = 5862.94 (extreme) • 3.0x : 5850 + 16.00 = 5866.00 (parabolic) Profit-Taking Strategy: Optimal scaling out at extensions: • Breakout entry at 5850.50 • 30% off at 1.272x (5852.18) → +1.68 points • 40% off at 1.5x (5854.00) → +3.50 points • 20% off at 1.618x (5854.94) → +4.44 points • 10% off at 2.0x (5858.00) → +7.50 points [b>Average Exit: Conclusion: [/b> Scaling out at extensions produces 40% higher expectancy than holding for home runs. 📊 GAP ANALYSIS & FILL PSYCHOLOGY [b>Gap Definition: [/b> Price discontinuity between previous close and current open: • Gap Up : Open > Previous Close + noise threshold (0.1 ATR) • Gap Down : Open < Previous Close - noise threshold Why Gaps Matter: [/b> Gaps represent unfilled orders [/b>. When market gaps up, all limit buy orders between yesterday's close and today's open are never filled. Those buyers are "left behind." Psychology: they wait for price to return ("fill the gap") so they can enter. This creates magnetic pull [/b> toward gap level. Gap Fill Statistics (Empirical): [/b> • Gaps <0.5% [/b>: 85-90% fill within same day • Gaps 0.5-1.0% [/b>: 70-75% fill within same day, 90%+ within week • Gaps >1.0% [/b>: 50-60% fill within same day (major news often prevents fill) Gap Fill Strategy: [/b> Setup 1: Gap-and-Go Gap opens, extends away from gap (doesn't fill). • ORB confirms direction away from gap • Trade WITH ORB breakout direction • Expectation: Gap won't fill today (momentum too strong) Setup 2: Gap-Fill Fade Gap opens, but fails to extend. Price drifts back toward gap. • ORB breakout TOWARD gap (not away) • Trade toward gap fill level • Target: Previous close (gap fill complete) Setup 3: Gap-Fill Rejection Gap fills (touches previous close) then rejects. • ORB breakout AWAY from gap after fill • Trade away from gap direction • Thesis: Gap filled (orders executed), now resume original direction [b>Example: Scenario A (Gap-and-Go): • ORB breaks upward to $454 (away from gap) • Trade: LONG breakout, expect continued rally • Gap becomes support ($452) Scenario B (Gap-Fill): • ORB breaks downward through $452.50 (toward gap) • Trade: SHORT toward gap fill at $450.00 • Target: $450.00 (gap filled), close position Scenario C (Gap-Fill Rejection): • Price drifts to $450.00 (gap filled) early in session • ORB establishes $450-$451 after gap fill • ORB breaks upward to $451.50 • Trade: LONG breakout (gap is filled, now resume rally) ORB Fusion Integration: [/b> Dashboard shows: • Gap type (Up/Down/None) • Gap size (percentage) • Gap fill status (Filled ✓ / Open) This informs setup confidence: • ORB breakout AWAY from unfilled gap: +10% confidence (gap becomes support/resistance) • ORB breakout TOWARD unfilled gap: -10% confidence (gap fill may override ORB) [b>📈 VWAP & INSTITUTIONAL BIAS [/b> [b>Volume-Weighted Average Price (VWAP): [/b> Average price weighted by volume at each price level. Represents true "average" cost for the day. [b>Calculation: Institutional Benchmark [/b>: Institutions (mutual funds, pension funds) use VWAP as performance benchmark. If they buy above VWAP, they underperformed; below VWAP, they outperformed. 2. [b>Algorithmic Target [/b>: Many algos are programmed to buy below VWAP and sell above VWAP to achieve "fair" execution. 3. [b>Support/Resistance [/b>: VWAP acts as dynamic support (price above) or resistance (price below). [b>VWAP Bands (Standard Deviations): [/b> • [b>1σ Band [/b>: VWAP ± 1 standard deviation - Contains ~68% of volume - Normal trading range - Bounces common • [b>2σ Band [/b>: VWAP ± 2 standard deviations - Contains ~95% of volume - Extreme extension - Mean reversion likely ORB + VWAP Confluence: [/b> Highest-probability setups occur when ORB and VWAP align: Bullish Confluence: [/b> • ORB breakout upward (bullish signal) • Price above VWAP (institutional buying) • Confidence boost: +15% Bearish Confluence: [/b> • ORB breakout downward (bearish signal) • Price below VWAP (institutional selling) • Confidence boost: +15% [b>Divergence Warning: • ORB breakout upward BUT price below VWAP • Conflict: Breakout says "buy," VWAP says "sell" • Confidence penalty: -10% • Interpretation: Retail buying but institutions not participating (lower quality breakout) 📊 MOMENTUM CONTEXT SYSTEM [b>Innovation: Candle Coloring by Position Rather than fixed support/resistance lines, ORB Fusion colors candles based on their [b>relationship to ORB : [b>Three Zones: [/b> 1. Inside ORB (Blue Boxes): [/b> [b>Calculation: • Darker blue: Near extremes of ORB (potential breakout imminent) • Lighter blue: Near ORB mid (consolidation) [b>Trading: [/b> Coiled spring—await breakout. [b>2. Above ORB (Green Boxes): [b>Calculation: 3. Below ORB (Red Boxes): Mirror of above ORB logic. [b>Special Contexts: [/b> [b>Breakout Bar (Darkest Green/Red): [/b> The specific bar where breakout occurs gets maximum color intensity regardless of distance. This highlights the pivotal moment. [b>Failed Breakout Bar (Orange/Warning): [/b> When failed breakout is confirmed, that bar gets orange/warning color. Visual alert: "reversal opportunity here." [b>Near Extension (Cyan/Magenta Tint): [/b> When price is within 0.5 ATR of an extension level, candle gets tinted cyan (bull) or magenta (bear). Indicates "target approaching—prepare to take profit." [b>Why Visual Context? [/b> Traditional indicators show lines. ORB Fusion shows [b>context-aware momentum [/b>. Glance at chart: • Lots of blue? Consolidation day (fade extremes). • Progressive green? Trend day (follow). • Green then orange? Failed breakout (reversal setup). This visual language communicates market state instantly—no interpretation needed. 🎯 TRADE SETUP GENERATION & GRADING [/b> [b>Algorithmic Setup Detection: [/b> ORB Fusion continuously evaluates market state and generates current best trade setup with: • Action (LONG / SHORT / FADE HIGH / FADE LOW / WAIT) • Entry price • Stop loss • Three targets • Risk:Reward ratio • Confidence score (0-100) • Grade (A+ to D) [b>Setup Types: [/b> [b>1. ORB LONG (Bullish Breakout): [/b> [b>Trigger: [/b> • Bullish ORB breakout confirmed • Not failed [b>Parameters: • Entry: Current close • Stop: ORB mid (protects against failure) • T1: ORB High + 0.5x range (1.5x extension) • T2: ORB High + 1.0x range (2.0x extension) • T3: ORB High + 1.618x range (2.618x extension) [b>Confidence Scoring: [b>Trigger: [/b> • Bearish breakout occurred • Failed (returned inside ORB) [b>Parameters: [/b> • Entry: Close when failure confirmed • Stop: Extreme low since breakout + 0.10 ATR • T1: ORB Low + 0.5x range • T2: ORB Low + 1.0x range (ORB mid) • T3: ORB Low + 1.5x range [b>Confidence Scoring: [b>Trigger: • Inside ORB • Close > ORB mid (near high) [b>Parameters: [/b> • Entry: ORB High (limit order) • Stop: ORB High + 0.2x range • T1: ORB Mid • T2: ORB Low [b>Confidence Scoring: [/b> Base: 40 points (lower base—range fading is lower probability than breakout/reversal) [b>Use Case: [/b> Rotation days. Not recommended on normal/trend days. [b>6. FADE LOW (Range Trade): Mirror of FADE HIGH. [b>7. WAIT: [b>Trigger: [/b> • ORB not complete yet OR • No clear setup (price in no-man's-land) [b>Action: [/b> Observe, don't trade. [b>Confidence: [/b> 0 points [b>Grading System: ``` Confidence → Grade 85-100 → A+ 75-84 → A 65-74 → B+ 55-64 → B 45-54 → C 0-44 → D ``` [b>Grade Interpretation: [/b> • [b>A+ / A: High probability setup. Take these trades. • [b>B+ / B [/b>: Decent setup. Trade if fits system rules. • [b>C [/b>: Marginal setup. Only if very experienced. • [b>D [/b>: Poor setup or no setup. Don't trade. [b>Example Scenario: [/b> ES futures: • ORB: 5842-5850 (8 point range) • Bullish breakout to 5851 confirmed • Volume: 2.0x average (confirmed) • VWAP: 5845 (price above VWAP ✓) • Day type: Developing (too early, no bonus) • Gap: None [b>Setup: [/b> • Action: LONG • Entry: 5851 • Stop: 5846 (ORB mid, -5 point risk) • T1: 5854 (+3 points, 1:0.6 R:R) • T2: 5858 (+7 points, 1:1.4 R:R) • T3: 5862.94 (+11.94 points, 1:2.4 R:R) [b>Confidence: LONG with 55% confidence. Interpretation: Solid setup, not perfect. Trade it if your system allows B-grade signals. [b>📊 STATISTICS TRACKING & PERFORMANCE ANALYSIS [/b> [b>Real-Time Performance Metrics: [/b> ORB Fusion tracks comprehensive statistics over user-defined lookback (default 50 days): [b>Breakout Performance: [/b> • [b>Bull Breakouts: [/b> Total count, wins, losses, win rate • [b>Bear Breakouts: [/b> Total count, wins, losses, win rate [b>Win Definition: [/b> Breakout reaches ≥1.0x extension (doubles the opening range) before end of day. [b>Example: [/b> • ORB: 5842-5850 (8 points) • Bull breakout at 5851 • Reaches 5858 (1.0x extension) by close • Result: WIN [b>Failed Breakout Performance: [/b> • [b>Total Failed Breakouts [/b>: Count of breakouts that failed • [b>Reversal Wins [/b>: Count where reversal trade reached target • [b>Failed Reversal Win Rate [/b>: Wins / Total Failed [b>Win Definition for Reversals: [/b> • Failed bull → reversal short reaches ORB mid • Failed bear → reversal long reaches ORB mid [b>Extension Tracking: [/b> • [b>Average Extension Reached [/b>: Mean of maximum extension achieved across all breakout days • [b>Max Extension Overall [/b>: Largest extension ever achieved in lookback period [b>Example: 🎨 THREE DISPLAY MODES [b>Design Philosophy: [/b> Not all traders need all features. Beginners want simplicity. Professionals want everything. ORB Fusion adapts. [b>SIMPLE MODE: [/b> [b>Shows: [/b> • Primary ORB levels (High, Mid, Low) • ORB box • Breakout signals (triangles) • Failed breakout signals (crosses) • Basic dashboard (ORB status, breakout status, setup) • VWAP [b>Hides: [/b> • Session ORBs (Asian, London, NY) • IB levels and extensions • ORB extensions beyond basic levels • Gap analysis visuals • Statistics dashboard • Momentum candle coloring • Narrative dashboard [b>Use Case: [/b> • Traders who want clean chart • Focus on core ORB concept only • Mobile trading (less screen space) [b>STANDARD MODE: [b>Shows Everything in Simple Plus: [/b> • Session ORBs (Asian, London, NY) • IB levels (high, low, mid) • IB extensions • ORB extensions (1.272x, 1.5x, 1.618x, 2.0x) • Gap analysis and fill targets • VWAP bands (1σ and 2σ) • Momentum candle coloring • Context section in dashboard • Narrative dashboard [b>Hides: [/b> • Advanced extensions (2.618x, 3.0x) • Detailed statistics dashboard [b>Use Case: [/b> • Most traders • Balance between information and clarity • Covers 90% of use cases [b>ADVANCED MODE: [b>Shows Everything: • All session ORBs • All IB levels and extensions • All ORB extensions (including 2.618x and 3.0x) • Full gap analysis • VWAP with both 1σ and 2σ bands • Momentum candle coloring • Complete statistics dashboard • Narrative dashboard • All context metrics [b>Use Case: [/b> • Professional traders • System developers • Those who want maximum information density [b>Switching Modes: [/b> Single dropdown input: "Display Mode" → Simple / Standard / Advanced Entire indicator adapts instantly. No need to toggle 20 individual settings. 📖 NARRATIVE DASHBOARD [b>Innovation: Plain-English Market State [/b> Most indicators show data. ORB Fusion explains what the data [b>means [/b>. [b>Narrative Components: [/b> [b>1. Phase: [/b> • "📍 Building ORB..." (during ORB session) • "📊 Trading Phase" (after ORB complete) • "⏳ Pre-Market" (before ORB session) [b>2. Status (Current Observation): [/b> • "⚠️ Failed breakout - reversal likely" • "🚀 Bullish momentum in play" • "📉 Bearish momentum in play" • "⚖️ Consolidating in range" • "👀 Monitoring for setup" [b>3. Next Level: Tells you what to watch for: • "🎯 1.5x @ 5854.00" (next extension target) • "Watch ORB levels" (inside range, await breakout) [b>4. Setup: [/b> Current trade setup + grade: • "LONG " (bullish breakout, A-grade) • "🔥 SHORT REVERSAL " (failed bull breakout, A+-grade) • "WAIT " (no setup) [b>5. Reason: [/b> Why this setup exists: • "ORB Bullish Breakout" • "Failed Bear Breakout - High Probability Reversal" • "Range Fade - Near High" [b>6. Tip (Market Insight): Contextual advice: • "🔥 TREND DAY - Trail stops" (day type is trending) • "🔄 ROTATION - Fade extremes" (day type is rotating) • "📊 Gap unfilled - magnet level" (gap creates target) • "📈 Normal conditions" (no special context) [b>Example Narrative: ``` 📖 ORB Narrative ━━━━━━━━━━━━━━━━ Phase | 📊 Trading Phase Status | 🚀 Bullish momentum in play Next | 🎯 1.5x @ 5854.00 📈 Setup | LONG Reason | ORB Bullish Breakout 💡 Tip | 🔥 TREND DAY - Trail stops ``` [b>Glance Interpretation: [/b> "We're in trading phase. Bullish breakout happened (momentum in play). Next target is 1.5x extension at 5854. Current setup is LONG with A-grade. It's a trend day, so trail stops (don't take early profits)." Complete market state communicated in 6 lines. No interpretation needed. [b>Why This Matters: Beginner traders struggle with "So what?" question. Indicators show lines and signals, but what does it mean [/b>? Narrative dashboard bridges this gap. Professional traders benefit too—rapid context assessment during fast-moving markets. No time to analyze; glance at narrative, get action plan. 🔔 INTELLIGENT ALERT SYSTEM [b>Four Alert Types: [/b> [b>1. Breakout Alert: [/b> [b>Trigger: [/b> ORB breakout confirmed (bull or bear) [b>Message: [/b> ``` 🚀 ORB BULLISH BREAKOUT Price: 5851.00 Volume Confirmed Grade: A ``` [b>Frequency: [/b> Once per bar (prevents spam) [b>2. Failed Breakout Alert: [/b> [b>Trigger: [/b> Breakout fails, reversal setup generated [b>Message: [/b> ``` 🔥 FAILED BULLISH BREAKOUT! HIGH PROBABILITY SHORT REVERSAL Entry: 5848.00 Stop: 5854.00 T1: 5846.00 T2: 5842.00 Historical Win Rate: 73% ``` [b>Why Comprehensive? [/b> Failed breakout alerts include complete trade plan. You can execute immediately from alert—no need to check chart. [b>3. Extension Alert: [b>Trigger: [/b> Price reaches extension level for first time [b>Message: [/b> ``` 🎯 Bull Extension 1.5x reached @ 5854.00 ``` [b>Use: [/b> Profit-taking reminder. When extension hit, consider scaling out. [b>4. IB Break Alert: [/b> [b>Trigger: [/b> Price breaks above IB high or below IB low [b>Message: [/b> ``` 📊 IB HIGH BROKEN - Potential Trend Day ``` [b>Use: [/b> Day type classification. IB break suggests trend day developing—adjust strategy to trend-following mode. [b>Alert Management: [/b> Each alert type can be enabled/disabled independently. Prevents notification overload. [b>Cooldown Logic: [/b> Alerts won't fire if same alert type triggered within last bar. Prevents: • "Breakout" alert every tick during choppy breakout • Multiple "extension" alerts if price oscillates at level Ensures: One clean alert per event. ⚙️ KEY PARAMETERS EXPLAINED [b>Opening Range Settings: [/b> • [b>ORB Timeframe [/b> (5/15/30/60 min): Duration of opening range window - 30 min recommended for most traders • [b>Use RTH Only [/b> (ON/OFF): Only trade during regular trading hours - ON recommended (avoids thin overnight markets) • [b>Use LTF Precision [/b> (ON/OFF): Sample 1-minute bars for accuracy - ON recommended (critical for charts >1 minute) • [b>Precision TF [/b> (1/5 min): Timeframe for LTF sampling - 1 min recommended (most accurate) [b>Session ORBs: [/b> • [b>Show Asian/London/NY ORB [/b> (ON/OFF): Display multi-session ranges - OFF in Simple mode - ON in Standard/Advanced if trading 24hr markets • [b>Session Windows [/b>: Time ranges for each session ORB - Defaults align with major session opens [b>Initial Balance: [/b> • [b>Show IB [/b> (ON/OFF): Display Initial Balance levels - ON recommended for day type classification • [b>IB Session Window [/b> (0930-1030): First hour of trading - Default is standard for US equities • [b>Show IB Extensions [/b> (ON/OFF): Project IB extension targets - ON recommended (identifies trend days) • [b>IB Extensions 1-4 [/b> (0.5x, 1.0x, 1.5x, 2.0x): Extension multipliers - Defaults are Market Profile standard [b>ORB Extensions: [/b> • [b>Show Extensions [/b> (ON/OFF): Project ORB extension targets - ON recommended (defines profit targets) • [b>Enable Individual Extensions [/b> (1.272x, 1.5x, 1.618x, 2.0x, 2.618x, 3.0x) - Enable 1.272x, 1.5x, 1.618x, 2.0x minimum - Disable 2.618x and 3.0x unless trading very volatile instruments [b>Breakout Detection: • [b>Confirmation Method [/b> (Close/Wick/Body): - Close recommended (best balance) - Wick for scalping - Body for conservative • [b>Require Volume Confirmation [/b> (ON/OFF): - ON recommended (increases reliability) • [b>Volume Multiplier [/b> (1.0-3.0): - 1.5x recommended - Lower for thin instruments - Higher for heavy volume instruments [b>Failed Breakout System: [/b> • [b>Enable Failed Breakouts [/b> (ON/OFF): - ON strongly recommended (highest edge) • [b>Bars to Confirm Failure [/b> (2-10): - 3 bars recommended - 2 for aggressive (more signals, more false failures) - 5+ for conservative (fewer signals, higher quality) • [b>Failure Buffer [/b> (0.0-0.5 ATR): - 0.1 ATR recommended - Filters noise during consolidation near ORB level • [b>Show Reversal Targets [/b> (ON/OFF): - ON recommended (visualizes trade plan) • [b>Reversal Target Mults [/b> (0.5x, 1.0x, 1.5x): - Defaults are tested values - Adjust based on average daily range [b>Gap Analysis: • [b>Show Gap Analysis [/b> (ON/OFF): - ON if trading instruments that gap frequently - OFF for 24hr markets (forex, crypto—no gaps) • [b>Gap Fill Target [/b> (ON/OFF): - ON to visualize previous close (gap fill level) [b>VWAP: • [b>Show VWAP [/b> (ON/OFF): - ON recommended (key institutional level) • [b>Show VWAP Bands [/b> (ON/OFF): - ON in Standard/Advanced - OFF in Simple • [b>Band Multipliers (1.0σ, 2.0σ): - Defaults are standard - 1σ = normal range, 2σ = extreme [b>Day Type: [/b> • [b>Show Day Type Analysis [/b> (ON/OFF): - ON recommended (critical for strategy adaptation) • [b>Trend Day Threshold [/b> (1.0-2.5 IB mult): - 1.5x recommended - When price extends >1.5x IB, classifies as Trend Day [b>Enhanced Visuals: • [b>Show Momentum Candles [/b> (ON/OFF): - ON for visual context - OFF if chart gets too colorful • [b>Show Gradient Zone Fills [/b> (ON/OFF): - ON for professional look - OFF for minimalist chart • [b>Label Display Mode [/b> (All/Adaptive/Minimal): - Adaptive recommended (shows nearby labels only) - All for information density - Minimal for clean chart • [b>Label Proximity [/b> (1.0-5.0 ATR): - 3.0 ATR recommended - Labels beyond this distance are hidden (Adaptive mode) [b>🎓 PROFESSIONAL USAGE PROTOCOL [/b> [b>Phase 1: Learning the System (Week 1) [/b> [b>Goal: [/b> Understand ORB concepts and dashboard interpretation [b>Setup: [/b> • Display Mode: STANDARD • ORB Timeframe: 30 minutes • Enable ALL features (IB, extensions, failed breakouts, VWAP, gap analysis) • Enable statistics tracking [b>Actions: [/b> • Paper trade ONLY—no real money • Observe ORB formation every day (9:30-10:00 AM ET for US markets) • Note when ORB breakouts occur and if they extend • Note when breakouts fail and reversals happen • Watch day type classification evolve during session • Track statistics—which setups are working? [b>Key Learning: [/b> • How often do breakouts reach 1.5x extension? (typically 50-60% of confirmed breakouts) • How often do breakouts fail? (typically 30-40%) • Which setup grade (A/B/C) actually performs best? (should see A-grade outperforming) • What day type produces best results? (trend days favor breakouts, rotation days favor fades) [b>Phase 2: Parameter Optimization (Week 2) [/b> [b>Goal: [/b> Tune system to your instrument and timeframe [b>ORB Timeframe Selection: • Run 5 days with 15-minute ORB • Run 5 days with 30-minute ORB • Compare: Which captures better breakouts on your instrument? • Typically: 30-minute optimal for most, 15-minute for very liquid (ES, SPY) [b>Volume Confirmation Testing: • Run 5 days WITH volume confirmation • Run 5 days WITHOUT volume confirmation • Compare: Does volume confirmation increase win rate? • If win rate improves by >5%: Keep volume confirmation ON • If no improvement: Turn OFF (avoid missing valid breakouts) [b>Failed Breakout Bars: [b>Goal: [/b> Develop personal trading rules based on system signals [b>Setup Selection Rules: [/b> Define which setups you'll trade: • [b>Conservative: [/b> Only A+ and A grades • [b>Balanced: [/b> A+, A, B+ grades • [b>Aggressive: [/b> All grades B and above Test each approach for 5-10 trades, compare results. [b>Position Sizing by Grade: [/b> Consider risk-weighting by setup quality: • A+ grade: 100% position size • A grade: 75% position size • B+ grade: 50% position size • B grade: 25% position size Example: If max risk is $1000/trade: • A+ setup: Risk $1000 • A setup: Risk $750 • B+ setup: Risk $500 This matches bet sizing to edge. [b>Day Type Adaptation: [/b> Create rules for different day types: Trend Days: • Take ALL breakout signals (A/B/C grades) • Hold for 2.0x extension minimum • Trail stops aggressively (1.0 ATR trail) • DON'T fade—reversals unlikely Rotation Days: • ONLY take failed breakout reversals • Ignore initial breakout signals (likely to fail) • Take profits quickly (0.5x extension) • Focus on fade setups (Fade High/Fade Low) Normal Days: • Take A/A+ breakout signals only • Take ALL failed breakout reversals (high probability) • Target 1.0-1.5x extensions • Partial profit-taking at extensions Time-of-Day Rules: [/b> Breakouts at different times have different probabilities: 10:00-10:30 AM (Early Breakout): • ORB just completed • Fresh breakout • Probability: Moderate (50-55% reach 1.0x) • Strategy: Conservative position sizing 10:30-12:00 PM (Mid-Morning): • Momentum established • Volume still healthy • Probability: High (60-65% reach 1.0x) • Strategy: Standard position sizing 12:00-2:00 PM (Lunch Doldrums): • Volume dries up • Whipsaw risk increases • Probability: Low (40-45% reach 1.0x) • Strategy: Avoid new entries OR reduce size 50% 2:00-4:00 PM (Afternoon Session): • Late-day positioning • EOD squeezes possible • Probability: Moderate-High (55-60%) • Strategy: Watch for IB break—if trending all day, follow [b>Phase 4: Live Micro-Sizing (Month 2) [/b> [b>Goal: [/b> Validate paper trading results with minimal risk [b>Setup: [/b> • 10-20% of intended full position size • Take ONLY A+ and A grade setups • Follow stop loss and targets religiously [b>Execution: [/b> • Execute from alerts OR from dashboard setup box • Entry: Close of signal bar OR next bar market order • Stop: Use exact stop from setup (don't widen) • Targets: Scale out at T1/T2/T3 as indicated [b>Tracking: [/b> • Log every trade: Entry, Exit, Grade, Outcome, Day Type • Calculate: Win rate, Average R-multiple, Max consecutive losses • Compare to paper trading results (should be within 15%) [b>Red Flags: [/b> • Win rate <45%: System not suitable for this instrument/timeframe • Major divergence from paper trading: Execution issues (slippage, late entries, emotional exits) • Max consecutive losses >8: Hitting rough patch OR market regime changed [b>Phase 5: Scaling Up (Months 3-6) [b>Goal: [/b> Gradually increase to full position size [b>Progression: [/b> • Month 3: 25-40% size (if micro-sizing profitable) • Month 4: 40-60% size • Month 5: 60-80% size • Month 6: 80-100% size [b>Milestones Required to Scale Up: [/b> • Minimum 30 trades at current size • Win rate ≥48% • Profit factor ≥1.2 • Max drawdown <20% • Emotional control (no revenge trading, no FOMO) [b>Advanced Techniques: [b>Multi-Timeframe ORB: Assumes first 30-60 minutes establish value. Violation: Market opens after major news, price discovery continues for hours (opening range meaningless). 2. [b>Volume Indicates Conviction: ES, NQ, RTY, SPY, QQQ—high liquidity, clean ORB formation, reliable extensions • [b>Large-Cap Stocks: AAPL, MSFT, TSLA, NVDA (>$5B market cap, >5M daily volume) • [b>Liquid Futures: CL (crude oil), GC (gold), 6E (EUR/USD), ZB (bonds)—24hr markets benefit from session ORBs • [b>Major Forex Pairs: [/b> EUR/USD, GBP/USD, USD/JPY—London/NY session ORBs work well [b>Performs Poorly On: [/b> • [b>Illiquid Stocks: <$1M daily volume, wide spreads, gappy price action • [b>Penny Stocks: [/b> Manipulated, pump-and-dump, no real price discovery • [b>Low-Volume ETFs: Exotic sector ETFs, leveraged products with thin volume • [b>Crypto on Sketchy Exchanges: Wash trading, spoofing invalidates volume analysis • [b>Earnings Days: [/b> ORB completes before earnings release, then completely resets (useless) • Binary Event Days: FDA approvals, court rulings—discontinuous price action [b>Known Weaknesses: [/b> • [b>Slow Starts: ORB doesn't complete until 10:00 AM (30-min ORB). Early morning traders have no signals for 30 minutes. Consider using 15-minute ORB if this is problematic. • [b>Failure Detection Lag: [/b> Failed breakout requires 3+ bars to confirm. By the time system signals reversal, price may have already moved significantly back inside range. Manual traders watching in real-time can enter earlier. • [b>Extension Overshoot: [/b> System projects extensions mathematically (1.5x, 2.0x, etc.). Actual moves may stop short (1.3x) or overshoot (2.2x). Extensions are targets, not magnets. • [b>Day Type Misclassification: [/b> Early in session, day type is "Developing." By the time it's classified definitively (often 11:00 AM+), half the day is over. Strategy adjustments happen late. • [b>Gap Assumptions: [/b> System assumes gaps want to fill. Strong trend days never fill gaps (gap becomes support/resistance forever). Blindly trading toward gaps can backfire on trend days. • [b>Volume Data Quality: Forex doesn't have centralized volume (uses tick volume as proxy—less reliable). Crypto volume is often fake (wash trading). Volume confirmation less effective on these instruments. • [b>Multi-Session Complexity: [/b> When using Asian/London/NY ORBs simultaneously, chart becomes cluttered. Requires discipline to focus on relevant session for current time. [b>Risk Factors: [/b> • [b>Opening Gaps: Large gaps (>2%) can create distorted ORBs. Opening range might be unusually wide or narrow, making extensions unreliable. • [b>Low Volatility Environments:[/b> When VIX <12, opening ranges can be tiny (0.2-0.3%). Extensions are equally tiny. Profit targets don't justify commission/slippage. • [b>High Volatility Environments:[/b> When VIX >30, opening ranges are huge (2-3%+). Extensions project unrealistic targets. Failed breakouts happen faster (volatility whipsaw). • [b>Algorithm Dominance:[/b> In heavily algorithmic markets (ES during overnight session), ORB levels can be manipulated—algos pin price to ORB high/low intentionally. Breakouts become stop-runs rather than genuine directional moves. [b>⚠️ RISK DISCLOSURE[/b> Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Opening Range Breakout strategies, while based on sound market structure principles, do not guarantee profits and can result in significant losses. The ORB Fusion indicator implements professional trading concepts including Opening Range theory, Market Profile Initial Balance analysis, Fibonacci extensions, and failed breakout reversal logic. These methodologies have theoretical foundations but past performance—whether backtested or live—is not indicative of future results. Opening Range theory assumes the first 30-60 minutes of trading establish a meaningful value area and that breakouts from this range signal directional conviction. This assumption may not hold during: • Major news events (FOMC, NFP, earnings surprises) • Market structure changes (circuit breakers, trading halts) • Low liquidity periods (holidays, early closures) • Algorithmic manipulation or spoofing Failed breakout detection relies on patterns of trapped participant behavior. While historically these patterns have shown statistical edges, market conditions change. Institutional algorithms, changing market structure, or regime shifts can reduce or eliminate edges that existed historically. Initial Balance classification (trend day vs rotation day vs normal day) is a heuristic framework, not a deterministic prediction. Day type can change mid-session. Early classification may prove incorrect as the day develops. Extension projections (1.272x, 1.5x, 1.618x, 2.0x, etc.) are probabilistic targets derived from Fibonacci ratios and empirical market behavior. They are not "support and resistance levels" that price must reach or respect. Markets can stop short of extensions, overshoot them, or ignore them entirely. Volume confirmation assumes high volume indicates institutional participation and conviction. In algorithmic markets, volume can be artificially high (HFT activity) or artificially low (dark pools, internalization). Volume is a proxy, not a guarantee of conviction. LTF precision sampling improves ORB accuracy by using 1-minute bars but introduces additional data dependencies. If 1-minute data is unavailable, inaccurate, or delayed, ORB calculations will be incorrect. The grading system (A+/A/B+/B/C/D) and confidence scores aggregate multiple factors (volume, VWAP, day type, IB expansion, gap context) into a single assessment. This is a mechanical calculation, not artificial intelligence. The system cannot adapt to unprecedented market conditions or events outside its programmed logic. Real trading involves slippage, commissions, latency, partial fills, and rejected orders not present in indicator calculations. ORB Fusion generates signals at bar close; actual fills occur with delay. Opening range forms during highest volatility (first 30 minutes)—spreads widen, slippage increases. Execution quality significantly impacts realized results. Statistics tracking (win rates, extension levels reached, day type distribution) is based on historical bars in your lookback window. If lookback is small (<50 bars) or market regime changed, statistics may not represent future probabilities. Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively (100+ trades minimum) before risking capital. Start with micro position sizing (5-10% of intended size) for 50+ trades to validate execution quality matches expectations. Never risk more than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every single trade without exception. Understand that most retail traders lose money—sophisticated indicators do not change this fundamental reality. They systematize analysis but cannot eliminate risk. The developer makes no warranties regarding profitability, suitability, accuracy, reliability, or fitness for any purpose. Users assume full responsibility for all trading decisions, parameter selections, risk management, and outcomes. By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses. [b>═══════════════════════════════════════════════════════════════════════════════[/b> [b>CLOSING STATEMENT[/b> [b>═══════════════════════════════════════════════════════════════════════════════[/b> Opening Range Breakout is not a trick. It's a framework. The first 30-60 minutes reveal where participants believe value lies. Breakouts signal directional conviction. Failures signal trapped participants. Extensions define profit targets. Day types dictate strategy. Failed breakouts create the highest-probability reversals. ORB Fusion doesn't predict the future—it identifies [b>structure[/b>, detects [b>breakouts[/b>, recognizes [b>failures[/b>, and generates [b>probabilistic trade plans[/b> with defined risk and reward. The edge is not in the opening range itself. The edge is in recognizing when the market respects structure (follow breakouts) versus when it violates structure (fade breakouts). The edge is in detecting failures faster than discretionary traders. The edge is in systematic classification that prevents catastrophic errors—like fading a trend day or holding through rotation. Most indicators draw lines. ORB Fusion implements a complete institutional trading methodology: Opening Range theory, Market Profile classification, failed breakout intelligence, Fibonacci projections, volume confirmation, gap psychology, and real-time performance tracking. Whether you're a beginner learning market structure or a professional seeking systematic ORB implementation, this system provides the framework. "The market's first word is its opening range. Everything after is commentary." — ORB Fusion
Pine Script® indicator
by DskyzInvestments
10
Volumetric Supply and Demand Zones [BOSWaves]Volumetric Supply and Demand Zones - Impulse-Based Zone Detection with Embedded Volume Profile Analysis Overview Volumetric Supply and Demand Zones is an impulse-driven zone identification system that marks significant reversal areas through swing detection and volume accumulation patterns, where zone boundaries dynamically reflect actual trading activity concentration rather than arbitrary price levels. Instead of relying on traditional horizontal support/resistance lines or fixed pivot structures, zone placement, thickness, and volumetric composition are determined through ATR-normalized impulse detection, volume profile distribution analysis, and delta decomposition within base formation periods. This creates adaptive supply and demand boundaries that reflect actual volume accumulation patterns rather than simple price extremes - contracting zones around high-volume concentration areas when profile shows tight distribution, expanding zones during dispersed volume activity, and incorporating positive/negative delta breakdowns to reveal whether zones formed under buying or selling pressure dominance. Price interactions are therefore evaluated relative to volume-weighted zone structures and point-of-control levels rather than conventional naked price zones. Conceptual Framework Volumetric Supply and Demand Zones is founded on the principle that meaningful reversal zones emerge where significant volume accumulated during consolidation before impulse moves rather than at simple swing high/low pivot points. Traditional supply and demand methods identify zones using price structure alone through swing detection or candlestick patterns, which often ignores the underlying volume distribution and buying/selling pressure that validates institutional accumulation or distribution. This framework replaces price-only logic with volume-weighted zone construction informed by actual trading activity concentration and delta composition. Three core principles guide the design: Zone boundaries should encompass base formation periods preceding impulse moves, not isolated pivot candles alone. Volume profile distribution within zones must reveal where actual trading activity concentrated, identifying true points of control. Delta decomposition exposes whether zones formed under buying pressure (demand accumulation) or selling pressure (supply distribution). This shifts supply and demand analysis from naked price levels into volume-validated, delta-aware institutional footprint zones. Theoretical Foundation The indicator combines swing pivot detection, ATR-based impulse measurement, volume profile construction, and delta decomposition analysis. A pivot detection system identifies local swing highs and lows using configurable left/right bar parameters. Impulse validation measures the subsequent price move magnitude relative to ATR, confirming whether the swing preceded a significant directional thrust. Zone boundaries encompass a lookback period of candles forming the base, with maximum height capped by ATR multiplier to prevent excessively large zones. Volume profile divides each zone into horizontal rows, distributing volume proportionally based on price overlap and identifying the point of control (highest volume row). Delta profile separates volume into buying versus selling components using close-open relationships, revealing net directional pressure within each profile row. Five internal systems operate in tandem: Swing Detection Engine : Identifies pivot highs and lows using symmetrical left/right bar confirmation for potential zone anchor points. Impulse Validation System : Measures price movement magnitude following pivot formation, requiring ATR-multiple threshold breach to confirm zone significance. Volume Profile Constructor : Divides zone height into configurable rows, allocates volume proportionally based on bar price range overlap with each row, identifies POC as highest-volume row. Delta Decomposition Engine : Separates volume into buying (up-close bars) versus selling (down-close bars) components within each profile row, calculates net delta and dominant pressure direction. Zone Merge Logic : Detects overlapping zones of same type (supply/supply or demand/demand), combines boundaries and recalculates volume/delta statistics with weighted blending. This design allows supply and demand zones to reflect actual volume accumulation reality rather than reacting mechanically to price pivots alone. How It Works Volumetric Supply and Demand Zones evaluates price through a sequence of volume-aware zone construction processes: Pivot Identification : Swing detection algorithm identifies local highs and lows using configurable left/right bar symmetry, marking potential reversal zone anchors. Impulse Magnitude Validation : Following pivot formation, price movement measured relative to ATR over lookback period - move must exceed ATR multiplier threshold to confirm zone validity. Base Period Boundary Definition : Zone encompasses pivot bar plus configurable lookback candles forming the consolidation base preceding impulse move. Height Normalization : Raw zone height (high to low of base period) capped at maximum ATR multiplier to prevent zones becoming unreasonably large during extended consolidations. Volume Profile Row Allocation : Zone divided into configurable number of horizontal rows, each bar's volume distributed proportionally based on price range overlap with row boundaries. Point of Control Identification : Row with highest accumulated volume marked as POC, representing price level with maximum trading activity concentration within zone. Delta Component Separation : Each bar's volume classified as buying (close > open) or selling (close < open), allocated to respective delta buckets within overlapping profile rows. Delta Profile Construction : Net delta (buy volume minus sell volume) calculated per row, rendered as horizontal bars extending from zone right edge inward with green (positive) or red (negative) coloring. Overlap Detection and Merging : New zones checked against existing zones of same type, overlapping zones within merge gap threshold combined with boundary expansion and volume/delta statistics aggregation. Mitigation Detection : Price interaction monitoring using configurable method (wick or close) determines when zones violated, triggering zone deletion and cleanup of all visual elements. Together, these elements form a continuously updating supply and demand framework anchored in volume accumulation reality and delta pressure composition. Interpretation Volumetric Supply and Demand Zones should be interpreted as volume-validated institutional footprint zones: Demand Zones (Green) : Form at swing lows preceding upward impulse moves exceeding ATR threshold - represent areas where buyers accumulated positions before markup phase, volume profile shows where bids concentrated. Supply Zones (Red) : Establish at swing highs preceding downward impulse moves exceeding ATR threshold - identify areas where sellers distributed positions before markdown phase, volume profile shows where offers concentrated. Volume Profile Bars : Horizontal bars extending from zone left edge show relative volume distribution across price levels - longer bars indicate higher trading activity, revealing true institutional accumulation/distribution levels versus arbitrary zone edges. Point of Control Line (White) : Horizontal line within zone marks price level with maximum volume concentration - represents the most significant institutional activity level, often acts as magnetic price level during retests. Delta Profile Bars : Horizontal bars extending from zone right edge inward display net buying/selling pressure per price level - green bars show buy volume dominance (accumulation), red bars show sell volume dominance (distribution). Zone Info Box : Text panel on right edge displays zone type (SUPPLY/DEMAND), status (Fresh/Tested), total volume, net delta, and touch count - provides quantitative validation of zone significance. Fresh Status : Newly created zones not yet tested by price - highest probability reversal zones as institutional orders likely remain unfilled. Tested Status : Zones where price returned and interacted with boundaries - touch count reveals how many times zone provided support/resistance, excessive touches suggest weakening. Merged Zones : Wider zones with higher volume/delta values formed by combining multiple overlapping base periods - represent extended institutional accumulation/distribution areas with greater significance. POC Brightness : Brightest (white) volume profile bar marks point of control - visual emphasis highlights the most critical price level within zone structure. Volume distribution shape, POC placement, delta composition, and touch count outweigh simple zone boundary reactions. Signal Logic & Visual Cues Volumetric Supply and Demand Zones presents zone interaction insights rather than discrete directional signals: Fresh Zone Formation : New supply or demand zone created when swing pivot followed by ATR-threshold impulse - suggests institutional footprint left behind, high-probability reversal area established. First Retest (Fresh → Tested) : Price returning to previously untouched zone triggers status change and touch increment - historically highest-probability reaction level as unfilled orders likely remain. POC Magnetic Behavior : Price gravitating toward white POC line during zone interaction - suggests institutional activity concentration level acting as support/resistance within broader zone. Volume Profile Asymmetry : Profile showing volume concentrated at zone edge versus center reveals base formation character - edge concentration suggests quick accumulation before impulse, center concentration indicates prolonged consolidation. Delta Divergence Patterns : Demand zones showing negative delta profile (red bars dominant) or supply zones showing positive delta (green bars) reveal weak zone formation - pressure composition conflicted with expected direction. Delta Confirmation Patterns : Demand zones with strong positive delta (green bars) or supply zones with strong negative delta (red bars) validate institutional conviction - pressure aligned with expected reversal direction. Excessive Touch Degradation : Touch count exceeding 3-4 interactions suggests zone weakening - repeated tests consume institutional orders, reducing reversal probability. Mitigation Events : Price closing beyond zone boundaries (or wicking through, based on settings) triggers zone deletion - invalidation confirms institutional levels failed, trend continuation likely. The primary value lies in volume-validated zone structure and delta composition analysis rather than simple boundary touches. Strategy Integration Volumetric Supply and Demand Zones fits within institutional footprint and order flow-aware trading approaches: Fresh Zone Reversal Entries : Enter counter-trend positions at first retest of fresh zones with strong delta confirmation - unfilled institutional orders provide high-probability reaction levels. POC-Precise Limit Orders : Place entries at POC line rather than zone edges - point of control represents maximum volume concentration, offering tighter stop placement and better risk/reward. Delta-Filtered Zone Selection : Prioritize demand zones showing positive net delta and supply zones showing negative net delta-aligned pressure composition validates institutional conviction. Volume Profile Distribution Analysis : Favor zones with tight volume concentration (profile bars clustered) over dispersed distribution - concentrated profiles suggest decisive institutional accumulation/distribution. Merge-Enhanced Conviction : Treat merged zones with higher volume/delta totals as stronger reversal candidates - combined statistics represent extended institutional activity periods. Touch Count Degradation Filtering : Reduce position sizing or avoid zones with 3+ touches - excessive interaction depletes institutional orders, weakening reversal probability. Trend Continuation via Mitigation : Enter breakout positions when price closes beyond supply zones (uptrend) or demand zones (downtrend) - mitigation confirms trend strength overwhelming institutional levels. Multi-Timeframe Zone Confluence : Apply higher-timeframe zones for macro structure, use lower-timeframe volume profile to identify precise entry levels within larger zones. Technical Implementation Details Core Engine : Pivot detection with symmetrical left/right confirmation, ATR-normalized impulse validation Zone Construction : Base period lookback with ATR-capped height normalization and time-based extension Volume Profile System : Proportional volume allocation across configurable rows with overlap percentage calculation Delta Engine : Close-open relationship classification separating buy/sell volume with net delta calculation per row POC Identification : Maximum volume row detection with visual emphasis rendering Merge Logic : Overlap detection with gap threshold, boundary expansion, and weighted statistic aggregation Visualization : Multi-element rendering (zone boxes, profile bars, delta bars, POC lines, info panels) with proportional sizing Performance Profile : Custom type system for zone/profile/delta management, efficient array-based storage with configurable zone limits Optimal Application Parameters Timeframe Guidance: 1 - 5 min : Micro-structure supply/demand for scalping with tight ATR multipliers and reduced lookback 15 - 60 min : Intraday institutional footprint zones with balanced profile row count and merge sensitivity 4H - Daily : Swing-level accumulation/distribution areas with extended lookback periods and wider merge gaps Weekly - Monthly : Macro institutional zones with maximum profile detail and extended zone persistence Suggested Baseline Configuration: Swing Length : 8 Impulse Size (ATR) : 1.2 Base Lookback Candles : 3 ATR Length : 14 Maximum Zone Height (ATR) : 4.0 Maximum Zones : 10 Extend Zones (bars) : 60 Merge Overlapping Zones : Enabled Merge Gap (ATR) : 0.3 Mitigation Type : Wick Profile Rows : 10 Profile Width (%) : 0.5 Show POC Line : Enabled Show Delta Profile : Enabled Delta Profile Width (%) : 0.35 Show Zone Info Box : Enabled These suggested parameters should be used as a baseline; their effectiveness depends on the asset's volatility profile, volume characteristics, and preferred zone sensitivity, so fine-tuning is expected for optimal performance. Parameter Calibration Notes Use the following adjustments to refine behavior without altering the core logic: Too many zones cluttering chart : Increase Swing Length (10 - 12) to demand stronger pivots, or increase Impulse Size multiplier (1.5 - 2.0) to require larger moves for zone validation. Missing significant reversal levels : Decrease Swing Length (5-6) for earlier pivot detection, or reduce Impulse Size (0.8 - 1.0) to capture smaller but valid base formations. Zones too large/tall : Reduce Maximum Zone Height ATR multiplier (2.5 - 3.0) to cap vertical size, or decrease Base Lookback Candles (1 - 2) for tighter base periods. Zones too small to be useful : Increase Base Lookback Candles (4 - 6) to encompass longer consolidation periods, or raise Maximum Zone Height (5.0 - 7.0) for taller zones. Profile bars too granular : Decrease Profile Rows (6 - 8) for coarser distribution showing major volume clusters only. Profile lacking detail : Increase Profile Rows (15 - 20) for finer resolution revealing subtle volume distribution nuances. Zones merging too aggressively : Decrease Merge Gap ATR multiplier (0.1 - 0.2) to require tighter overlap for merge qualification, or disable merging entirely. Related zones not combining : Increase Merge Gap (0.5 - 0.8) to allow merging of zones with larger separation distances. Zones invalidating prematurely : Switch Mitigation Type from "Wick" to "Close" to require closing violation rather than intrabar penetration. Zones persisting too long after breach : Switch Mitigation Type from "Close" to "Wick" for faster invalidation on initial penetration. Profile bars invisible : Increase Profile Width percentage (0.6 - 0.8) for longer bars, improving visibility on cluttered charts. Delta profile obscuring volume profile : Reduce Delta Profile Width (0.2 - 0.3) to prevent overlap, or disable delta display temporarily. Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions. Performance Characteristics High Effectiveness: Range-bound and mean-reverting markets where institutional zones provide reliable turning points Instruments with consistent volume characteristics where profile distribution reveals true accumulation/distribution Swing trading approaches targeting zone-to-zone reactions with defined risk parameters Reversal strategies seeking volume-validated entry levels rather than blind counter-trend positions Markets where delta proxy correlates well with actual order flow (trending volume instruments) Position trading benefiting from macro supply/demand structure with embedded volume context Reduced Effectiveness: Extremely low volume environments where profile distribution becomes unreliable and sparse News-driven or gapped markets where zones form/invalidate without normal volume accumulation patterns Highly trending markets where zones consistently mitigate without providing reversal opportunities Instruments with erratic volume patterns making delta decomposition and profile interpretation misleading Very high-frequency timeframes (seconds) where base formation periods too short for meaningful volume accumulation Integration Guidelines Confluence : Combine with BOSWaves structure, market profile, or traditional technical analysis for zone validation within broader context Volume Profile Respect : Trust POC levels and high-volume profile bars over arbitrary zone edges for entry/exit precision Delta Confirmation Priority : Favor zones where delta composition aligns with expected direction - positive delta in demand, negative delta in supply Fresh Zone Preference : Prioritize first retests of untouched zones over repeatedly tested areas with high touch counts Merge Recognition : Treat merged zones with elevated volume/delta statistics as higher-conviction institutional footprint areas Touch Count Filtering : Reduce position sizing or avoid zones after 3+ touches as institutional order depletion reduces effectiveness Mitigation Discipline : Exit zone-based positions decisively when price closes beyond boundaries, respecting invalidation signals Multi-Timeframe Structure : Apply higher-timeframe zones for swing structure, use lower-timeframe profiles for tactical entry refinement Disclaimer Volumetric Supply and Demand Zones is a professional-grade supply/demand zone and volume profile analysis tool. It uses volume-based delta proxy to estimate directional pressure but does not access true order book data or institutional trade information. Results depend on market conditions, volume reliability, ATR characteristics, parameter selection, and disciplined execution. Volume profile and delta calculations represent approximations based on close-open relationships and price overlap formulas, not actual bid/ask transactions. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates price structure, order flow context, and comprehensive risk management.
Pine Script® indicator
by BOSWaves
Multi Basis Bollinger Bands ProMulti Basis Bollinger Bands Pro is a volatility and trend-focused indicator using multiple Bollinger Bands with customizable moving average types (SMA, EMA, WMA) and sources. Trend bias is determined by the SMA 20 on higher timeframes (H1, H4, Daily). High-source bands (BB1 & BB2) are used for BUY signals when price touches their lower gap. Low-source bands (BB3 & BB4) are used for SELL signals when price touches their upper gap. Both upper and lower band gaps are highlighted with configurable green/red fills for clear visual zones. Includes a standard Bollinger Band reference for context. This strategy helps traders align entries with higher timeframe trends, filter trades, and visually spot volatility extremes and breakout zones.
Pine Script® indicator
by Williamhwl
Turtle Soup vs Previous CandleThis indicator highlights **Turtle Soup (TS)** setups by comparing **the current candle to the previous one**—and it only triggers **once the candle is fully closed**, so it doesn’t “paint and disappear” while the bar is still forming. **What it detects** * **TS Bear (bearish):** Price *breaks above the previous candle’s high* (liquidity grab), then closes **bearish**, returning back below that prior high. → Concept: “fake breakout up, then reversal.” * **TS Bull (bullish):** Price *breaks below the previous candle’s low* (liquidity grab), then closes **bullish**, back above that prior low. → Concept: “fake breakdown down, then rebound.” **Strict vs Flexible mode (the indicator switch)** * ✅ **Allow close outside the previous range (ON):** more flexible. The close can finish outside the prior candle’s range. Useful in fast, impulsive moves. * ❌ **Allow close outside the previous range (OFF):** stricter. The close must finish **inside** the previous candle’s range (cleaner signals, usually fewer of them). **The key feature** * Signals are plotted **only after the candle closes on your current timeframe**. If you’re on M15, it confirms at the M15 close. If you’re on H1, at the H1 close. Result: more reliable signals and less “indicator drama.” **What it’s good for** * Spotting potential **quick reversals** right after a sweep of highs/lows. * Identifying areas where price often reacts due to **liquidity runs**. **Practical note** This isn’t a magic button—signals work best with context (trend, key levels, range/session timing, market structure). Fine-tune strict vs flexible per asset/timeframe and you’ll go from “random dots” to “useful tells.”
Pine Script® indicator
by Fran_Pineda
Double Relative Strength Index - DRSI🎯 Overview This is the Double Relative Strength Index (DRSI) indicator for TradingView - an advanced momentum oscillator that applies a unique mathematical transformation to traditional RSI, creating amplified signals with reduced lag while maintaining trend awareness ⚡ 🧩 Core Components ⚙️ Indicator Settings 🎛️ Input Parameters A. 🎨 Color Settings: 6 different color themes: 🎨 Classic, ✨ Neon, 🚀 Modern, 💪 Robust, 🌈 Accented, ⚫⚪ Monochrome Each theme provides distinct bullish/bearish color pairs B. 📊 DRSI Configuration: 📏 Length: Default 14 periods 📈 Source: Default close price (customizable) 📈 Long Threshold: Default 57 (asymmetric upper level) 📉 Short Threshold: Default 56 (asymmetric lower level) 🧮 Technical Calculations A. 📈 Double RSI Formula: DRSI = 2 × RSI - RSI(RSI) First: Standard RSI calculation Second: RSI applied to first RSI values Mathematical transformation amplifies momentum changes B. 🔄 State Tracking System: State persists until opposite threshold is crossed Reduces whipsaws through state memory C. 🔔 Signal Detection: 🟢 isBull_D_RSI: (bullish condition) 🔴 isBear_D_RSI: (bearish condition) 🟢 Bull_D_RSI: Crossover signal (DRSI crosses above Long Threshold) 🔴 Bear_D_RSI: Crossunder signal (DRSI crosses below Short Threshold) 👁️ Visual Elements A. 📉 Main Plots: 📊 DRSI Line: Thick line (width 2) colored conditionally based on position relative to thresholds 🎯 Long Threshold Line: Upper boundary with thematic bullish color 🎯 Short Threshold Line: Lower boundary with thematic bearish color B. 🎨 Fill Areas: 🟢 Overbought Zone: Filled between DRSI and Long Threshold 🔴 Oversold Zone: Filled between DRSI and Short Threshold 🌈 Dynamic Middle Fill: Adaptive area that shifts based on market state C. 📊 Enhanced Visualization: 🎨 Colored Candles: Price bars colored based on DRSI signal state 🔺 Signal Markers: Triangle indicators above/below bars for entry signals 📝 Current Value Label: Real-time DRSI value displayed on last bar D. 📋 Table Display: Shows "⬆️ Bullish", "⬇️ Bearish", or "🔀 Reversion" with appropriate coloring 🔔 Alert System 🟢 LONG Alert: Triggers when DRSI crosses above Long Threshold 🔴 SHORT Alert: Triggers when DRSI crosses below Short Threshold Includes ticker symbol in alert message 🏁 Trading Logic 🎯 Primary Signals: 🟢 Bullish Setup: 📈 DRSI crosses above Long Threshold (57) 📊 Bullish state persists while DRSI > Short Threshold 🎨 Visual: Theme bull colors, bullish fills, up triangles 🔴 Bearish Setup: 📉 DRSI crosses below Short Threshold (56) 📊 Bearish state persists while DRSI < Long Threshold 🎨 Visual: Theme bear colors, bearish fills, down triangles ✨ Key Features: ⚡ Amplified Momentum: Double calculation provides faster response than standard RSI 🛡️ State Persistence: Reduces whipsaws by maintaining signal until opposite threshold crossed 🎯 Asymmetric Thresholds: 57/56 levels account for market bias vs traditional 70/30 👁️ Multi-Layer Visualization: Candles, fills, markers, and table provide comprehensive view 🛠️ Customizability: Six color themes adapt to different preferences and trading styles 💻 Code Structure The script is well-organized with clear sections: ⚙️ Input settings 🧮 DRSI calculations 🔄 State tracking logic 🎨 Color definitions 📊 Multi-layer plotting 📋 Table display 🔔 Alert conditions 🎯 Best Use Cases 📈 Momentum Trading: Detects accelerating/decelerating momentum with reduced lag 🔄 Swing Trading: Asymmetric thresholds work well for swing entry/exit points ⚡ Responsive Signals: Faster than traditional RSI for timely entries 📊 Multi-Timeframe Analysis: Works across various timeframes for confirmation ✅ Signal Filtering: State persistence filters out noise and false breakouts 🏆 Unique Advantages 🎯 Mathematical Innovation: DRSI formula transforms traditional oscillator behavior 🛡️ Reduced Whipsaws: State tracking prevents premature signal reversals 👁️ Comprehensive Display: Four visual layers (candles, fills, markers, table) communicate clearly ⚡ Balanced Responsiveness: Faster than traditional RSI but more stable than raw momentum 💼 Professional Presentation: Clean, modern interface suitable for serious trading analysis
Pine Script® indicator
by Tiagorocha1989
TA Confluence Scanner v2.9 | Mint_Algo📘 TA Confluence Scanner Introduction The TA Confluence Scanner is a multi-factor trend system designed to filter market noise and identify high-probability trade setups. By combining adaptive algorithms (KAMA) with Price Action methodologies (SMC, Breakouts, Fractals), this indicator operates on the principle of Confluence : a signal is only valid when multiple independent tools agree on the direction. Instead of relying on a single lagging indicator (like just MA fast and slow crossover), this script acts as a "Scanner," evaluating the market state through Volatility, Trend Structure, and Equilibrium. ─────────────────────────────────────────────────── Important Note To make this "Plug & Play," I have included optimized presets in the settings for different timeframes (1m/15m-1h/4h-1D) and trading styles (Scalper, Intraday, Swing, Investor) tested on symbols: FX:EURUSD IG:NASDAQ BITSTAMP:BTCUSD BINANCE:ETHUSD CAPITALCOM:US500 OANDA:XAUUSD NASDAQ:AAPL NASDAQ:TSLA BUT default settings already include a good preset which excludes most of the noise and grabs the trend better (fewer entries, but quality is higher). Check the presets at the bottom 👇 ─────────────────────────────────────────────────── Core Features Adaptive Trend Filter (KAMA): Adjusts to market volatility to distinguish between chop and true trends. SMC Equilibrium (EQ) Fans: A three-tiered dynamic structure (Fast, Medium, Slow) for trailing stops and targets. Confluence Counter: Visually displays the strength of a signal (e.g., "Strong 4/6") based on how many factors align. Re-Entry Logic: Identifies low-risk entry points within an existing trend. Automated S/R & Breakouts: Detects key pivot levels and structural breaks. ─────────────────────────────────────────────────── Settings & Components Breakdown 1. KAMA (Primary Trend Filter) The backbone of the system. It calculates the Efficiency Ratio (ER) of price movement. How it works: If the ER is high (strong trend), KAMA follows price closely. If ER is low (ranging), KAMA flattens out to prevent false signals. Tuning: Fast (ER ~100/5/60): For Scalping. Smooth: Default settings are optimized for a balance between lag and noise reduction. 2. SMC Equilibrium (EQ Structure) Based on the HL2 formula (High+Low / 2), this creates a "fan" of three lines: EQ1 (Fast): The aggressive line. Used for early exits or scalping stops. EQ2 (Medium): The baseline trend structure. EQ3 (Slow): The major trend container. Used for position trading. Usage: Use these lines to gauge how far price has deviated from its "fair value." 3. Breakout & Internal Trend Lookback Period: Defines the range for a valid breakout. A lower lookback (e.g., 10) gives earlier signals but more noise; a higher lookback (e.g., 20-30) confirms significant structural breaks. Internal Trend: A simplified SMA check to ensure immediate momentum aligns with the macro trend. 4. Signal Strength (The Confluence Meter) The indicator counts active signals from: KAMA, Internal Trend, S/R, FVG, Breakout, and EQ. Strong Signal: When the count hits your threshold (e.g., 4/6 ). This suggests a high-probability reversal or breakout. Medium Signal (Triangles): These appear when the trend is active but not all filters align. These are excellent continuation/re-entry points. ─────────────────────────────────────────────────── How to Trade (Strategy Guide) 🎯 The Entry Wait for a Strong Signal (Large Label). This confirms that volatility, structure, and momentum have aligned. Conservative: Wait for the candle to close. Aggressive: Enter on the breakout of the KAMA line. 🔄 Re-Entry & Continuation Markets rarely move in a straight line. Scenario: You missed the initial "Strong" entry, or you took profit and want to re-enter. The Signal: Look for the small Triangles (Medium signals). These often appear after a pullback when price resumes the main trend. Logic: If the main KAMA trend is still green/red, but the "Strong" signal isn't firing, a Triangle indicates a safe place to add to a position. ⚠️ Pyramiding & Risk Management (Advanced) The EQ Lines (Fast/Medium/Slow) are designed for a tiered position management strategy: Entry: Open position (e.g., 0.03 lots). First Take Profit: When price extends far beyond EQ1 (Fast) , lock in partial profits. Trailing Stop: Move your Stop Loss to trace the EQ2 (Medium) line. Trend Riding: Hold the "Runner" portion of your position until price closes back under EQ3 (Slow) or the KAMA line. Tip: Use William Fractals (Period 2) to pinpoint exact swing highs/lows for tightening stops. ─────────────────────────────────────────────────── Presets & Optimized Settings To make this "Plug & Play," I have included optimized presets in the settings for different trading styles. (If you don't see some parameters, that means they are turned off in trading mode) ⚡ SCALPER (1m - 5m) KAMA: ER: 100 Fast Length: 15 Slow Length: 30 FVG: Size %: 0.01 Trend Detection: Length: 20 Breakout: Lookback Period: 10 S/R Detection: Pivot Length: 10 Tolerance: 0.3 SMC EQ: Default: 10 EQ1: 10 EQ2 (Main): 30 EQ3: 120 Signal Strength: Strong: 4 Medium: 3 📊 INTRADAY (15m - 1H) KAMA: ER: 100 Fast Length: 5 Slow Length: 30 Trend Detection: Length: 100 Breakout: Lookback Period: 30 S/R Detection: Pivot Length: 20 Tolerance: 0.5 SMC EQ: Default: 10 EQ1: 10 EQ2 (Main): 40 EQ3: 80 Signal Strength: Strong: 4 Medium: 3 📈 SWING (4H - 1D) KAMA: ER: 30 Fast Length: 4 Slow Length: 30 Trend Detection: Length: 50 Breakout: Lookback Period: 20 S/R Detection: Pivot Length: 30 Tolerance: 0.7 SMC EQ: Default: 10 EQ1: 10 EQ2: 50 EQ3 (Main): 60 Signal Strength: Strong: 4 Medium: 3 💼 INVESTOR (4H - 1D+) KAMA: ER: 30 Fast Length: 5 Slow Length: 10 Trend Detection: Length: 100 Breakout: Lookback Period: 50 S/R Detection: Pivot Length: 30 Tolerance: 0.7 SMC EQ: Default: 10 EQ1: 10 EQ2: 50 EQ3 (Main): 100 Signal Strength: Strong: 4 Medium: 3 ─────────────────────────────────────────────────── Notes FVG (Fair Value Gaps): Optional. Enable if you trade volatile assets like Crypto/Gold where imbalances are common. Support/Resistance: The built-in Pivot system is optional. Disable it if you prefer drawing your own levels to keep the chart clean. Recommended Pairing: For best results, pair this with a momentum oscillator like RSI to detect the range regime of a trend. Or DI+ and DI- (when it crosses over each other, that means the "range of possible" regime change of a trend). ─────────────────────────────────────────────────── Disclaimer: This tool is for informational purposes only. "Confluence" increases probability but does not guarantee results. Always manage your risk.
Pine Script® indicator
by Mint_Algo
3
CYCLE BY RiotWolftradingDescription of the "CYCLE" Indicator The "CYCLE" indicator is a custom Pine Script v5 script for TradingView that visualizes cyclic patterns in price action, dividing the trading day into specific sessions and 90-minute quarters (Q1-Q4). It is designed to identify and display market phases (Accumulation, Manipulation, Distribution, and Continuation/Reversal) along with key support and resistance levels within those sessions. Additionally, it allows customization of boxes, lines, labels, and colors to suit user preferences. Main Features Cycle Phases: Accumulation (1900-0100): Represents the phase where large operators accumulate positions. Manipulation (0100-0700): Identifies potential manipulative moves to mislead retail traders. Distribution (0700-1300): The phase where large operators distribute their positions. Continuation/Reversal (1300-1900): Indicates whether the price continues the trend or reverses. 90-Minute Quarters (Q1-Q4): Divides each 6-hour cycle (360 minutes) into four 90-minute quarters (Q1: 00:00-01:30, Q2: 01:30-03:00, Q3: 03:00-04:30, Q4: 04:30-06:00 UTC). Each quarter is displayed with a colored box (Q1: light purple, Q2: light blue, Q3: light gray, Q4: light pink) and labels (defaulted to black). Support and Resistance Visualization: Draws boxes or lines (based on settings) showing the high and low levels of each session. Optionally displays accumulated volume at the highs and lows within the boxes. Daily Lines and Last 3 Boxes: How to Use the Indicator Step 1: Add the Indicator to TradingView Open TradingView and select the chart where you want to apply the indicator (e.g., UMG9OOR on a 5-minute timeframe, as shown in the screenshot). Go to the Pine Editor (at the bottom of the TradingView interface). Copy and paste the provided code. Click Compile and then Add to Chart. Step 2: Configure the Indicator Click on the indicator name on the chart ("CYCLE") and select Settings (or double-click the name). Adjust the options based on your needs: Cycle Phases: Enable/disable phases (Accumulation, Manipulation, Distribution, Continuation/Reversal) and adjust their time slots if needed. 90-Minute Quarters: Enable/disable quarters (Q1-Q4). Step 3: Interpret the Indicator Identify Cycle Phases: Observe the red boxes indicating the phases (Accumulation, Manipulation, etc.). The high and low levels within each phase are potential support/resistance zones. If volume is enabled, pay attention to the accumulated volume at highs and lows, as it may indicate the strength of those levels. Use the 90-Minute Quarters (Q1-Q4): The colored boxes (Q1-Q4) divide the day into 90-minute segments. Each quarter shows the price range (high and low) during that period. Use these boxes to identify price patterns within each quarter, such as breakouts or consolidations. The labels (Q1, Q2, etc.) help you track time and anticipate potential moves in the next quarter. Analyze Support and Resistance: The high and low levels of each phase/quarter act as support and resistance. Daily lines (if enabled) show key levels from the previous day, useful for planning entries/exits. The "last 3 boxes below price" (if enabled) highlight potential support levels the price might target. Avoid Manipulation: During the Manipulation phase (0100-0700), be cautious of sharp moves or false breakouts. Use the high/low levels of this phase to identify potential traps (as explained in your first question about manipulation candles). Step 4: Trading Strategy Entries and Exits: Support/Resistance: Use the high/low levels of phases and quarters to set entry or exit points. For example, if the price bounces off a Q1 support level, consider a buy. Breakouts: If the price breaks a high/low of a quarter (e.g., Q2), wait for confirmation to enter in the direction of the breakout. Volume: If accumulated volume is high near a key level, that level may be more significant. Risk Management: Place stop-loss orders below lows (for buys) or above highs (for sells) identified by the indicator. Avoid trading during the Manipulation phase unless you have a specific strategy to handle false breakouts. Time Context: Use the quarters (Q1-Q4) to plan your trades based on time. For example, if Q3 is typically volatile in your market, prepare for larger moves between 03:00-04:30 UTC. Step 5: Adjustments and Testing Test on Different Timeframes: The indicator is set for a 5-minute timeframe (as in the screenshot), but you can test it on other timeframes (e.g., 1-minute, 15-minute) by adjusting the time slots if needed. Adjust Colors and Styles: If the default colors are not visible on your chart, change them for better clarity. --- 📌 1. **Accumulation: Strong Institutional Activity** - During the **accumulation phase, we see **high volume: 82.773K, which suggests strong buying interest**, likely from institutional players. - This sets the base for the following upward move in price. --- 📌 2. **Manipulation: False Breakout with Lower Volume** - Later, there's a manipulation phase where price breaks above previous highs, but the volume (71.814K) is **lower than during accumulation**. - This implies that buyers are not as aggressive as before—no real demandbehind the breakout. - It’s likely a bull trap, where smart money is selling into the breakout to exit their positions. --- ### 📌 3. Distribution: Weakness and Lack of Demand - The market enters a distribution phase, and volume drops even further (only 7.914K). - Price struggles to go higher, and you start seeing rejections at the top. - This shows that demand is drying up, and smart money is offloading positions**—not accumulating anymore. --- ### 💡 Why Take the Short Here? - Volume is not increasing with new highs—showing weak demand**. - The manipulation volume is weaker than the accumulation volume, confirming the breakout was likely false. - Structure starts to break down (Q levels falling), which confirms weakness. - This creates a high-probability short setup: - **Entry:** after confirmation of distribution and structural breakdown. - **Stop loss:** above the manipulation high. - **Target:** down toward previous lows or value zones. --- ### ✅ Conclusion Since the manipulation volume failed to exceed the accumulation volume, the breakout lacked real strength. Combined with decreasing volume in the distribution phase, this indicates fading demand and supply taking control—which justifies entering a short position.
Pine Script® indicator
by anarkiacapital
1
Swing IA Cockpit [v2]//@version=5 indicator("Swing IA Cockpit ", overlay=true, max_bars_back=500) // === INPUTS === mode = input.string("Pullback", title="Entry Mode", options= ) corrLen = input.int(60, "Correlation Window Length") scoreWeightBias = input.float(0.6, title="Weight: Bias", minval=0, maxval=1) scoreWeightTiming = 1.0 - scoreWeightBias // === INDICATEURS H1 === ema200_H1 = ta.ema(close, 200) ema50_H1 = ta.ema(close, 50) rsi_H1 = ta.rsi(close, 14) donchianHigh = ta.highest(high, 20) donchianLow = ta.lowest(low, 20) atr_H1 = ta.atr(14) avgATR_H1 = ta.sma(atr_H1, 50) body = math.abs(close - open) avgBody = ta.sma(body, 20) // === H4 / D1 === close_H4 = request.security(syminfo.tickerid, "240", close) ema200_H4 = request.security(syminfo.tickerid, "240", ta.ema(close, 200)) rsi_H4 = request.security(syminfo.tickerid, "240", ta.rsi(close, 14)) atr_H4 = request.security(syminfo.tickerid, "240", ta.atr(14)) avgATR_H4 = request.security(syminfo.tickerid, "240", ta.sma(ta.atr(14), 50)) close_D1 = request.security(syminfo.tickerid, "D", close) ema200_D1 = request.security(syminfo.tickerid, "D", ta.ema(close, 200)) // === CORRÉLATIONS === dxy = request.security("TVC:DXY", "60", close) spx = request.security("SP:SPX", "60", close) gold = request.security("OANDA:XAUUSD", "60", close) corrDXY = ta.correlation(close, dxy, corrLen) corrSPX = ta.correlation(close, spx, corrLen) corrGold = ta.correlation(close, gold, corrLen) // === LOGIQUE BIAIS === biasLong = close_D1 > ema200_D1 and close_H4 > ema200_H4 and rsi_H4 >= 55 biasShort = close_D1 < ema200_D1 and close_H4 < ema200_H4 and rsi_H4 <= 45 bias = biasLong ? "LONG" : biasShort ? "SHORT" : "NEUTRAL" // === LOGIQUE TIMING === isBreakoutLong = mode == "Breakout" and high > donchianHigh and close > ema200_H1 and rsi_H1 > 50 isBreakoutShort = mode == "Breakout" and low < donchianLow and close < ema200_H1 and rsi_H1 < 50 var float breakoutPrice = na var int breakoutBar = na if isBreakoutLong or isBreakoutShort breakoutPrice := close breakoutBar := bar_index validPullbackLong = mode == "Pullback" and not na(breakoutBar) and bar_index <= breakoutBar + 3 and close > ema50_H1 and low <= ema50_H1 validPullbackShort = mode == "Pullback" and not na(breakoutBar) and bar_index <= breakoutBar + 3 and close < ema50_H1 and high >= ema50_H1 timingLong = isBreakoutLong or validPullbackLong timingShort = isBreakoutShort or validPullbackShort // === SCORES === scoreTrend = (close_D1 > ema200_D1 ? 20 : 0) + (close_H4 > ema200_H4 ? 20 : 0) scoreMomentumBias = (rsi_H4 >= 55 or rsi_H4 <= 45) ? 20 : 10 scoreCorr = 0 scoreCorr += biasLong and corrDXY < 0 ? 10 : 0 scoreCorr += biasLong and corrSPX > 0 ? 10 : 0 scoreCorr += biasLong and corrGold >= 0 ? 10 : 0 scoreCorr += biasShort and corrDXY > 0 ? 10 : 0 scoreCorr += biasShort and corrSPX < 0 ? 10 : 0 scoreCorr += biasShort and corrGold <= 0 ? 10 : 0 scoreCorr := math.min(scoreCorr, 30) scoreVolBias = atr_H4 > avgATR_H4 ? 10 : 0 scoreBias = scoreTrend + scoreMomentumBias + scoreCorr + scoreVolBias scoreStruct = (timingLong or timingShort) ? 40 : 0 scoreMomentumTiming = rsi_H1 > 50 or rsi_H1 < 50 ? 25 : 10 scoreTrendH1 = (close > ema50_H1 and ema50_H1 > ema200_H1) or (close < ema50_H1 and ema50_H1 < ema200_H1) ? 20 : 10 scoreVolTiming = atr_H1 > avgATR_H1 ? 15 : 5 scoreTiming = scoreStruct + scoreMomentumTiming + scoreTrendH1 + scoreVolTiming scoreTotal = scoreBias * scoreWeightBias + scoreTiming * scoreWeightTiming scoreLong = biasLong ? scoreTotal : 0 scoreShort = biasShort ? scoreTotal : 0 delta = scoreLong - scoreShort scoreExtMomentum = (rsi_H4 > 55 ? 10 : 0) scoreExtVol = atr_H4 > avgATR_H4 ? 10 : 0 scoreExtStructure = body > avgBody ? 10 : 5 scoreExtCorr = (scoreCorr > 15 ? 10 : 5) scoreExtension = scoreExtMomentum + scoreExtVol + scoreExtStructure + scoreExtCorr // === VERDICT FINAL === verdict = "NO TRADE" verdict := bias == "NEUTRAL" or math.abs(delta) < 10 or scoreTotal < 70 ? "NO TRADE" : scoreTotal < 80 ? "WAIT" : scoreTotal >= 85 and math.abs(delta) >= 20 and scoreExtension >= 60 ? "TRADE A+" : "TRADE" // === TABLE COCKPIT === var table cockpit = table.new(position.top_right, 2, 9, border_width=1) if bar_index % 5 == 0 table.cell(cockpit, 0, 0, "Bias", bgcolor=color.gray) table.cell(cockpit, 1, 0, bias) table.cell(cockpit, 0, 1, "ScoreBias", bgcolor=color.gray) table.cell(cockpit, 1, 1, str.tostring(scoreBias)) table.cell(cockpit, 0, 2, "ScoreTiming", bgcolor=color.gray) table.cell(cockpit, 1, 2, str.tostring(scoreTiming)) table.cell(cockpit, 0, 3, "ScoreTotal", bgcolor=color.gray) table.cell(cockpit, 1, 3, str.tostring(scoreTotal)) table.cell(cockpit, 0, 4, "ScoreLong", bgcolor=color.gray) table.cell(cockpit, 1, 4, str.tostring(scoreLong)) table.cell(cockpit, 0, 5, "ScoreShort", bgcolor=color.gray) table.cell(cockpit, 1, 5, str.tostring(scoreShort)) table.cell(cockpit, 0, 6, "Delta", bgcolor=color.gray) table.cell(cockpit, 1, 6, str.tostring(delta)) table.cell(cockpit, 0, 7, "Extension", bgcolor=color.gray) table.cell(cockpit, 1, 7, str.tostring(scoreExtension)) table.cell(cockpit, 0, 8, "Verdict", bgcolor=color.gray) table.cell(cockpit, 1, 8, verdict, bgcolor=verdict == "TRADE A+" ? color.green : verdict == "TRADE" ? color.lime : verdict == "WAIT" ? color.orange : color.red) // === ALERTS === alertcondition(verdict == "TRADE A+" and bias == "LONG", title="TRADE A+ LONG", message="TRADE A+ signal long") alertcondition(verdict == "TRADE A+" and bias == "SHORT", title="TRADE A+ SHORT", message="TRADE A+ signal short") alertcondition(verdict == "NO TRADE", title="NO TRADE / RANGE", message="Marché confus ou neutre — pas de trade")
Pine Script® indicator
by matpi2278
Trend Gauge [BullByte]Trend Gauge Summary A multi-factor trend detection indicator that aggregates EMA alignment, VWMA momentum scaling, volume spikes, ATR breakout strength, higher-timeframe confirmation, ADX-based regime filtering, and RSI pivot-divergence penalty into one normalized trend score. It also provides a confidence meter, a Δ Score momentum histogram, divergence highlights, and a compact, scalable dashboard for at-a-glance status. ________________________________________ ## 1. Purpose of the Indicator Why this was built Traders often monitor several indicators in parallel - EMAs, volume signals, volatility breakouts, higher-timeframe trends, ADX readings, divergence alerts, etc., which can be cumbersome and sometimes contradictory. The “Trend Gauge” indicator was created to consolidate these complementary checks into a single, normalized score that reflects the prevailing market bias (bullish, bearish, or neutral) and its strength. By combining multiple inputs with an adaptive regime filter, scaling contributions by magnitude, and penalizing weakening signals (divergence), this tool aims to reduce noise, highlight genuine trend opportunities, and warn when momentum fades. Key Design Goals Signal Aggregation Merged trend-following signals (EMA crossover, ATR breakout, higher-timeframe confirmation) and momentum signals (VWMA thrust, volume spikes) into a unified score that reflects directional bias more holistically. Market Regime Awareness Implemented an ADX-style filter to distinguish between trending and ranging markets, reducing the influence of trend signals during sideways phases to avoid false breakouts. Magnitude-Based Scaling Replaced binary contributions with scaled inputs: VWMA thrust and ATR breakout are weighted relative to recent averages, allowing for more nuanced score adjustments based on signal strength. Momentum Divergence Penalty Integrated pivot-based RSI divergence detection to slightly reduce the overall score when early signs of momentum weakening are detected, improving risk-awareness in entries. Confidence Transparency Added a live confidence metric that shows what percentage of enabled sub-indicators currently agree with the overall bias, making the scoring system more interpretable. Momentum Acceleration Visualization Plotted the change in score (Δ Score) as a histogram bar-to-bar, highlighting whether momentum is increasing, flattening, or reversing, aiding in more timely decision-making. Compact Informational Dashboard Presented a clean, scalable dashboard that displays each component’s status, the final score, confidence %, detected regime (Trending/Ranging), and a labeled strength gauge for quick visual assessment. ________________________________________ ## 2. Why a Trader Should Use It Main benefits and use cases 1. Unified View: Rather than juggling multiple windows or panels, this indicator delivers a single score synthesizing diverse signals. 2. Regime Filtering: In ranging markets, trend signals often generate false entries. The ADX-based regime filter automatically down-weights trend-following components, helping you avoid chasing false breakouts. 3. Nuanced Momentum & Volatility: VWMA and ATR breakout contributions are normalized by recent averages, so strong moves register strongly while smaller fluctuations are de-emphasized. 4. Early Warning of Weakening: Pivot-based RSI divergence is detected and used to slightly reduce the score when price/momentum diverges, giving a cautionary signal before a full reversal. 5. Confidence Meter: See at a glance how many sub-indicators align with the aggregated bias (e.g., “80% confidence” means 4 out of 5 components agree ). This transparency avoids black-box decisions. 6. Trend Acceleration/Deceleration View: The Δ Score histogram visualizes whether the aggregated score is rising (accelerating trend) or falling (momentum fading), supplementing the main oscillator. 7. Compact Dashboard: A corner table lists each check’s status (“Bull”, “Bear”, “Flat” or “Disabled”), plus overall Score, Confidence %, Regime, Trend Strength label, and a gauge bar. Users can scale text size (Normal, Small, Tiny) without removing elements, so the full picture remains visible even in compact layouts. 8. Customizable & Transparent: All components can be enabled/disabled and parameterized (lengths, thresholds, weights). The full Pine code is open and well-commented, letting users inspect or adapt the logic. 9. Alert-ready: Built-in alert conditions fire when the score crosses weak thresholds to bullish/bearish or returns to neutral, enabling timely notifications. ________________________________________ ## 3. Component Rationale (“Why These Specific Indicators?”) Each sub-component was chosen because it adds complementary information about trend or momentum: 1. EMA Cross o Basic trend measure: compares a faster EMA vs. a slower EMA. Quickly reflects trend shifts but by itself can whipsaw in sideways markets. 2. VWMA Momentum o Volume-weighted moving average change indicates momentum with volume context. By normalizing (dividing by a recent average absolute change), we capture the strength of momentum relative to recent history. This scaling prevents tiny moves from dominating and highlights genuinely strong momentum. 3. Volume Spikes o Sudden jumps in volume combined with price movement often accompany stronger moves or reversals. A binary detection (+1 for bullish spike, -1 for bearish spike) flags high-conviction bars. 4. ATR Breakout o Detects price breaking beyond recent highs/lows by a multiple of ATR. Measures breakout strength by how far beyond the threshold price moves relative to ATR, capped to avoid extreme outliers. This gives a volatility-contextual trend signal. 5. Higher-Timeframe EMA Alignment o Confirms whether the shorter-term trend aligns with a higher timeframe trend. Uses request.security with lookahead_off to avoid future data. When multiple timeframes agree, confidence in direction increases. 6. ADX Regime Filter (Manual Calculation) o Computes directional movement (+DM/–DM), smoothes via RMA, computes DI+ and DI–, then a DX and ADX-like value. If ADX ≥ threshold, market is “Trending” and trend components carry full weight; if ADX < threshold, “Ranging” mode applies a configurable weight multiplier (e.g., 0.5) to trend-based contributions, reducing false signals in sideways conditions. Volume spikes remain binary (optional behavior; can be adjusted if desired). 7. RSI Pivot-Divergence Penalty o Uses ta.pivothigh / ta.pivotlow with a lookback to detect pivot highs/lows on price and corresponding RSI values. When price makes a higher high but RSI makes a lower high (bearish divergence), or price makes a lower low but RSI makes a higher low (bullish divergence), a divergence signal is set. Rather than flipping the trend outright, the indicator subtracts (or adds) a small penalty (configurable) from the aggregated score if it would weaken the current bias. This subtle adjustment warns of weakening momentum without overreacting to noise. 8. Confidence Meter o Counts how many enabled components currently agree in direction with the aggregated score (i.e., component sign × score sign > 0). Displays this as a percentage. A high percentage indicates strong corroboration; a low percentage warns of mixed signals. 9. Δ Score Momentum View o Plots the bar-to-bar change in the aggregated score (delta_score = score - score ) as a histogram. When positive, bars are drawn in green above zero; when negative, bars are drawn in red below zero. This reveals acceleration (rising Δ) or deceleration (falling Δ), supplementing the main oscillator. 10. Dashboard • A table in the indicator pane’s top-right with 11 rows: 1. EMA Cross status 2. VWMA Momentum status 3. Volume Spike status 4. ATR Breakout status 5. Higher-Timeframe Trend status 6. Score (numeric) 7. Confidence % 8. Regime (“Trending” or “Ranging”) 9. Trend Strength label (e.g., “Weak Bullish Trend”, “Strong Bearish Trend”) 10. Gauge bar visually representing score magnitude • All rows always present; size_opt (Normal, Small, Tiny) only changes text size via text_size, not which elements appear. This ensures full transparency. ________________________________________ ## 4. What Makes This Indicator Stand Out • Regime-Weighted Multi-Factor Score: Trend and momentum signals are adaptively weighted by market regime (trending vs. ranging) , reducing false signals. • Magnitude Scaling: VWMA and ATR breakout contributions are normalized by recent average momentum or ATR, giving finer gradation compared to simple ±1. • Integrated Divergence Penalty: Divergence directly adjusts the aggregated score rather than appearing as a separate subplot; this influences alerts and trend labeling in real time. • Confidence Meter: Shows the percentage of sub-signals in agreement, providing transparency and preventing blind trust in a single metric. • Δ Score Histogram Momentum View: A histogram highlights acceleration or deceleration of the aggregated trend score, helping detect shifts early. • Flexible Dashboard: Always-visible component statuses and summary metrics in one place; text size scaling keeps the full picture available in cramped layouts. • Lookahead-Safe HTF Confirmation: Uses lookahead_off so no future data is accessed from higher timeframes, avoiding repaint bias. • Repaint Transparency: Divergence detection uses pivot functions that inherently confirm only after lookback bars; description documents this lag so users understand how and when divergence labels appear. • Open-Source & Educational: Full, well-commented Pine v6 code is provided; users can learn from its structure: manual ADX computation, conditional plotting with series = show ? value : na, efficient use of table.new in barstate.islast, and grouped inputs with tooltips. • Compliance-Conscious: All plots have descriptive titles; inputs use clear names; no unnamed generic “Plot” entries; manual ADX uses RMA; all request.security calls use lookahead_off. Code comments mention repaint behavior and limitations. ________________________________________ ## 5. Recommended Timeframes & Tuning • Any Timeframe: The indicator works on small (e.g., 1m) to large (daily, weekly) timeframes. However: o On very low timeframes (<1m or tick charts), noise may produce frequent whipsaws. Consider increasing smoothing lengths, disabling certain components (e.g., volume spike if volume data noisy), or using a larger pivot lookback for divergence. o On higher timeframes (daily, weekly), consider longer lookbacks for ATR breakout or divergence, and set Higher-Timeframe trend appropriately (e.g., 4H HTF when on 5 Min chart). • Defaults & Experimentation: Default input values are chosen to be balanced for many liquid markets. Users should test with replay or historical analysis on their symbol/timeframe and adjust: o ADX threshold (e.g., 20–30) based on instrument volatility. o VWMA and ATR scaling lengths to match average volatility cycles. o Pivot lookback for divergence: shorter for faster markets, longer for slower ones. • Combining with Other Analysis: Use in conjunction with price action, support/resistance, candlestick patterns, order flow, or other tools as desired. The aggregated score and alerts can guide attention but should not be the sole decision-factor. ________________________________________ ## 6. How Scoring and Logic Works (Step-by-Step) 1. Compute Sub-Scores o EMA Cross: Evaluate fast EMA > slow EMA ? +1 : fast EMA < slow EMA ? -1 : 0. o VWMA Momentum: Calculate vwma = ta.vwma(close, length), then vwma_mom = vwma - vwma . Normalize: divide by recent average absolute momentum (e.g., ta.sma(abs(vwma_mom), lookback)), clip to . o Volume Spike: Compute vol_SMA = ta.sma(volume, len). If volume > vol_SMA * multiplier AND price moved up ≥ threshold%, assign +1; if moved down ≥ threshold%, assign -1; else 0. o ATR Breakout: Determine recent high/low over lookback. If close > high + ATR*mult, compute distance = close - (high + ATR*mult), normalize by ATR, cap at a configured maximum. Assign positive contribution. Similarly for bearish breakout below low. o Higher-Timeframe Trend: Use request.security(..., lookahead=barmerge.lookahead_off) to fetch HTF EMAs; assign +1 or -1 based on alignment. 2. ADX Regime Weighting o Compute manual ADX: directional movements (+DM, –DM), smoothed via RMA, DI+ and DI–, then DX and ADX via RMA. If ADX ≥ threshold, market is considered “Trending”; otherwise “Ranging.” o If trending, trend-based contributions (EMA, VWMA, ATR, HTF) use full weight = 1.0. If ranging, use weight = ranging_weight (e.g., 0.5) to down-weight them. Volume spike stays binary ±1 (optional to change if desired). 3. Aggregate Raw Score o Sum weighted contributions of all enabled components. Count the number of enabled components; if zero, default count = 1 to avoid division by zero. 4. Divergence Penalty o Detect pivot highs/lows on price and corresponding RSI values, using a lookback. When price and RSI diverge (bearish or bullish divergence), check if current raw score is in the opposing direction:  If bearish divergence (price higher high, RSI lower high) and raw score currently positive, subtract a penalty (e.g., 0.5).  If bullish divergence (price lower low, RSI higher low) and raw score currently negative, add a penalty. o This reduces score magnitude to reflect weakening momentum, without flipping the trend outright. 5. Normalize and Smooth o Normalized score = (raw_score / number_of_enabled_components) * 100. This yields a roughly range. o Optional EMA smoothing of this normalized score to reduce noise. 6. Interpretation o Sign: >0 = net bullish bias; <0 = net bearish bias; near zero = neutral. o Magnitude Zones: Compare |score| to thresholds (Weak, Medium, Strong) to label trend strength (e.g., “Weak Bullish Trend”, “Medium Bearish Trend”, “Strong Bullish Trend”). o Δ Score Histogram: The histogram bars from zero show change from previous bar’s score; positive bars indicate acceleration, negative bars indicate deceleration. o Confidence: Percentage of sub-indicators aligned with the score’s sign. o Regime: Indicates whether trend-based signals are fully weighted or down-weighted. ________________________________________ ## 7. Oscillator Plot & Visualization: How to Read It Main Score Line & Area The oscillator plots the aggregated score as a line, with colored fill: green above zero for bullish area, red below zero for bearish area. Horizontal reference lines at ±Weak, ±Medium, and ±Strong thresholds mark zones: crossing above +Weak suggests beginning of bullish bias, above +Medium for moderate strength, above +Strong for strong trend; similarly for bearish below negative thresholds. Δ Score Histogram If enabled, a histogram shows score - score . When positive, bars appear in green above zero, indicating accelerating bullish momentum; when negative, bars appear in red below zero, indicating decelerating or reversing momentum. The height of each bar reflects the magnitude of change in the aggregated score from the prior bar. Divergence Highlight Fill If enabled, when a pivot-based divergence is confirmed: • Bullish Divergence : fill the area below zero down to –Weak threshold in green, signaling potential reversal from bearish to bullish. • Bearish Divergence : fill the area above zero up to +Weak threshold in red, signaling potential reversal from bullish to bearish. These fills appear with a lag equal to pivot lookback (the number of bars needed to confirm the pivot). They do not repaint after confirmation, but users must understand this lag. Trend Direction Label When score crosses above or below the Weak threshold, a small label appears near the score line reading “Bullish” or “Bearish.” If the score returns within ±Weak, the label “Neutral” appears. This helps quickly identify shifts at the moment they occur. Dashboard Panel In the indicator pane’s top-right, a table shows: 1. EMA Cross status: “Bull”, “Bear”, “Flat”, or “Disabled” 2. VWMA Momentum status: similarly 3. Volume Spike status: “Bull”, “Bear”, “No”, or “Disabled” 4. ATR Breakout status: “Bull”, “Bear”, “No”, or “Disabled” 5. Higher-Timeframe Trend status: “Bull”, “Bear”, “Flat”, or “Disabled” 6. Score: numeric value (rounded) 7. Confidence: e.g., “80%” (colored: green for high, amber for medium, red for low) 8. Regime: “Trending” or “Ranging” (colored accordingly) 9. Trend Strength: textual label based on magnitude (e.g., “Medium Bullish Trend”) 10. Gauge: a bar of blocks representing |score|/100 All rows remain visible at all times; changing Dashboard Size only scales text size (Normal, Small, Tiny). ________________________________________ ## 8. Example Usage (Illustrative Scenario) Example: BTCUSD 5 Min 1. Setup: Add “Trend Gauge ” to your BTCUSD 5 Min chart. Defaults: EMAs (8/21), VWMA 14 with lookback 3, volume spike settings, ATR breakout 14/5, HTF = 5m (or adjust to 4H if preferred), ADX threshold 25, ranging weight 0.5, divergence RSI length 14 pivot lookback 5, penalty 0.5, smoothing length 3, thresholds Weak=20, Medium=50, Strong=80. Dashboard Size = Small. 2. Trend Onset: At some point, price breaks above recent high by ATR multiple, volume spikes upward, faster EMA crosses above slower EMA, HTF EMA also bullish, and ADX (manual) ≥ threshold → aggregated score rises above +20 (Weak threshold) into +Medium zone. Dashboard shows “Bull” for EMA, VWMA, Vol Spike, ATR, HTF; Score ~+60–+70; Confidence ~100%; Regime “Trending”; Trend Strength “Medium Bullish Trend”; Gauge ~6–7 blocks. Δ Score histogram bars are green and rising, indicating accelerating bullish momentum. Trader notes the alignment. 3. Divergence Warning: Later, price makes a slightly higher high but RSI fails to confirm (lower RSI high). Pivot lookback completes; the indicator highlights a bearish divergence fill above zero and subtracts a small penalty from the score, causing score to stall or retrace slightly. Dashboard still bullish but score dips toward +Weak. This warns the trader to tighten stops or take partial profits. 4. Trend Weakens: Score eventually crosses below +Weak back into neutral; a “Neutral” label appears, and a “Neutral Trend” alert fires if enabled. Trader exits or avoids new long entries. If score subsequently crosses below –Weak, a “Bearish” label and alert occur. 5. Customization: If the trader finds VWMA noise too frequent on this instrument, they may disable VWMA or increase lookback. If ATR breakouts are too rare, adjust ATR length or multiplier. If ADX threshold seems off, tune threshold. All these adjustments are explained in Inputs section. 6. Visualization: The screenshot shows the main score oscillator with colored areas, reference lines at ±20/50/80, Δ Score histogram bars below/above zero, divergence fill highlighting potential reversal, and the dashboard table in the top-right. ________________________________________ ## 9. Inputs Explanation A concise yet clear summary of inputs helps users understand and adjust: 1. General Settings • Theme (Dark/Light): Choose background-appropriate colors for the indicator pane. • Dashboard Size (Normal/Small/Tiny): Scales text size only; all dashboard elements remain visible. 2. Indicator Settings • Enable EMA Cross: Toggle on/off basic EMA alignment check. o Fast EMA Length and Slow EMA Length: Periods for EMAs. • Enable VWMA Momentum: Toggle VWMA momentum check. o VWMA Length: Period for VWMA. o VWMA Momentum Lookback: Bars to compare VWMA to measure momentum. • Enable Volume Spike: Toggle volume spike detection. o Volume SMA Length: Period to compute average volume. o Volume Spike Multiplier: How many times above average volume qualifies as spike. o Min Price Move (%): Minimum percent change in price during spike to qualify as bullish or bearish. • Enable ATR Breakout: Toggle ATR breakout detection. o ATR Length: Period for ATR. o Breakout Lookback: Bars to look back for recent highs/lows. o ATR Multiplier: Multiplier for breakout threshold. • Enable Higher Timeframe Trend: Toggle HTF EMA alignment. o Higher Timeframe: E.g., “5” for 5-minute when on 1-minute chart, or “60” for 5 Min when on 15m, etc. Uses lookahead_off. • Enable ADX Regime Filter: Toggles regime-based weighting. o ADX Length: Period for manual ADX calculation. o ADX Threshold: Value above which market considered trending. o Ranging Weight Multiplier: Weight applied to trend components when ADX < threshold (e.g., 0.5). • Scale VWMA Momentum: Toggle normalization of VWMA momentum magnitude. o VWMA Mom Scale Lookback: Period for average absolute VWMA momentum. • Scale ATR Breakout Strength: Toggle normalization of breakout distance by ATR. o ATR Scale Cap: Maximum multiple of ATR used for breakout strength. • Enable Price-RSI Divergence: Toggle divergence detection. o RSI Length for Divergence: Period for RSI. o Pivot Lookback for Divergence: Bars on each side to identify pivot high/low. o Divergence Penalty: Amount to subtract/add to score when divergence detected (e.g., 0.5). 3. Score Settings • Smooth Score: Toggle EMA smoothing of normalized score. • Score Smoothing Length: Period for smoothing EMA. • Weak Threshold: Absolute score value under which trend is considered weak or neutral. • Medium Threshold: Score above Weak but below Medium is moderate. • Strong Threshold: Score above this indicates strong trend. 4. Visualization Settings • Show Δ Score Histogram: Toggle display of the bar-to-bar change in score as a histogram. Default true. • Show Divergence Fill: Toggle background fill highlighting confirmed divergences. Default true. Each input has a tooltip in the code. ________________________________________ ## 10. Limitations, Repaint Notes, and Disclaimers 10.1. Repaint & Lag Considerations • Pivot-Based Divergence Lag: The divergence detection uses ta.pivothigh / ta.pivotlow with a specified lookback. By design, a pivot is only confirmed after the lookback number of bars. As a result: o Divergence labels or fills appear with a delay equal to the pivot lookback. o Once the pivot is confirmed and the divergence is detected, the fill/label does not repaint thereafter, but you must understand and accept this lag. o Users should not treat divergence highlights as predictive signals without additional confirmation, because they appear after the pivot has fully formed. • Higher-Timeframe EMA Alignment: Uses request.security(..., lookahead=barmerge.lookahead_off), so no future data from the higher timeframe is used. This avoids lookahead bias and ensures signals are based only on completed higher-timeframe bars. • No Future Data: All calculations are designed to avoid using future information. For example, manual ADX uses RMA on past data; security calls use lookahead_off. 10.2. Market & Noise Considerations • In very choppy or low-liquidity markets, some components (e.g., volume spikes or VWMA momentum) may be noisy. Users can disable or adjust those components’ parameters. • On extremely low timeframes, noise may dominate; consider smoothing lengths or disabling certain features. • On very high timeframes, pivots and breakouts occur less frequently; adjust lookbacks accordingly to avoid sparse signals. 10.3. Not a Standalone Trading System • This is an indicator, not a complete trading strategy. It provides signals and context but does not manage entries, exits, position sizing, or risk management. • Users must combine it with their own analysis, money management, and confirmations (e.g., price patterns, support/resistance, fundamental context). • No guarantees: past behavior does not guarantee future performance. 10.4. Disclaimers • Educational Purposes Only: The script is provided as-is for educational and informational purposes. It does not constitute financial, investment, or trading advice. • Use at Your Own Risk: Trading involves risk of loss. Users should thoroughly test and use proper risk management. • No Guarantees: The author is not responsible for trading outcomes based on this indicator. • License: Published under Mozilla Public License 2.0; code is open for viewing and modification under MPL terms. ________________________________________ ## 11. Alerts • The indicator defines three alert conditions: 1. Bullish Trend: when the aggregated score crosses above the Weak threshold. 2. Bearish Trend: when the score crosses below the negative Weak threshold. 3. Neutral Trend: when the score returns within ±Weak after being outside. Good luck – BullByte
Pine Script® indicator
by BullByte
3