ابدأ الآن

Signals

Structural SVM Ranker [LuxAlgo]The Structural SVM Ranker indicator is a market structure tool that utilizes a linear Support Vector Machine (SVM) algorithm to classify and rank structural breaks based on volume, momentum, and price magnitude. By assigning a score from 0 to 100 to every Break of Structure (BOS) and Change of Character (CHoCH), it aims to help traders differentiate between high-conviction structural shifts and low-probability price action. 🔶 USAGE The indicator identifies key pivot highs and lows to map out the market structure. When price closes beyond these levels, a structural break is identified and assigned a score based on the quality of the move. BOS (Break of Structure): Represented by solid lines, these indicate a continuation of the current local trend. CHoCH (Change of Character): Represented by dashed lines, these indicate a potential reversal in the trend direction. SVM Score: Displayed on labels and the dashboard. A higher score suggests the break occurred with significant relative volume, strong RSI momentum, and a meaningful price distance beyond the pivot level. Traders can use the SVM score to filter trade quality. For example, a "CHoCH" with a score above 70 indicates a high-conviction reversal backed by volume and momentum, whereas a score below 30 might suggest a "fakeout" or a weak structural shift. 🔶 DETAILS The core of the script is a linear classification logic inspired by Support Vector Machines. It takes three primary features into account to determine the "strength" of a break: Relative Volume: Compares current volume to its 20-period average to ensure the break is supported by market participation. RSI Momentum: Measures the distance of the RSI from its midpoint (50) to confirm trend strength. Break Distance: Measures how far the price closed beyond the structural level, normalized by the Average True Range (ATR). These features are multiplied by user-defined weights and then passed through a Sigmoid function to produce a normalized score between 0 and 100. 🔶 SETTINGS 🔹 Market Structure Pivot Lookback: Determines the number of bars required to confirm a pivot high or low. Show BOS/CHoCH: Toggles the visibility of structural break lines and labels. 🔹 SVM Ranking Parameters Relative Volume Weight: Adjusts the influence of volume on the final score. RSI Momentum Weight: Adjusts the influence of RSI deviation from 50 on the final score. Break Distance Weight: Adjusts the influence of the price distance beyond the pivot (relative to ATR). ATR Length: The period used for the ATR normalization of the break distance. 🔹 Dashboard Dashboard: Toggles the visibility of the real-time ranking table. Position: Moves the dashboard to different corners of the chart (Top Right, Bottom Right, Bottom Left). Size: Adjusts the scale of the dashboard text.
مؤشر Pine Script®
من ‎LuxAlgo‎
8
HTF Reversal Divergences [LuxAlgo]The HTF Reversal Divergences indicator is a multi-timeframe analysis tool that integrates higher timeframe (HTF) price action patterns, RSI divergences, and advanced candle projections (PO3) to identify potential market reversals. 🔶 USAGE The indicator is designed to provide traders with a comprehensive view of market exhaustion and trend shifts by combining momentum oscillators with structural price patterns. Users can monitor HTF candles (e.g., 1H, 4H) while trading on lower timeframes (e.g., 5m, 15m). When a reversal pattern like an Engulfing candle or a Pin Bar forms on the higher timeframe, the script highlights the specific area on the chart using styled boxes and labels. 🔹 RSI Divergences The script calculates the Relative Strength Index (RSI) and automatically detects regular divergences. These are visualized with connecting lines on both the indicator pane and the main price chart: Bullish Divergence : Occurs when price makes a lower low but the RSI makes a higher low, suggesting waning downward momentum. Bearish Divergence : Occurs when price makes a higher high but the RSI makes a lower high, suggesting waning upward momentum. 🔹 Advanced HTF PO3 (Power of 3) A unique feature of this tool is the projection of Higher Timeframe candles to the right of the current price action. This allows traders to see how the current lower-timeframe bars are contributing to the formation of the larger HTF candle (Open, High, Low, Close). The PO3 projection includes a "Running Delta" which tracks volume-based buying and selling pressure within the current HTF period. Dashed lines connect the projected candle's OHLC levels back to the specific bars where those levels were established on the current timeframe. 🔶 DETAILS The indicator uses request.security() to fetch data from the user-specified higher timeframe. The reversal patterns are defined as follows: Engulfing : A candle that completely overlaps the body of the previous candle in the opposite direction. Pin Bars : Hammers and Shooting Stars, defined by a long wick representing at least 60% of the total candle range. The PO3 (Accumulation, Manipulation, Distribution) logic is reflected in the live candle projection, helping traders visualize where the "open" of the session is relative to current price, and whether the high or low of the HTF bar has likely been set. 🔶 SETTINGS 🔹 HTF Reversal Patterns High Timeframe : Sets the timeframe used for pattern detection and candle projections. Show Engulfing Patterns : Toggles the detection of bullish and bearish engulfing candles. Show Pin Bars : Toggles the detection of Hammers and Shooting Stars. Colors : Customize the visual representation of bullish and bearish structural patterns. 🔹 RSI Divergence Show RSI Divergences : Toggles the calculation and display of momentum divergences. RSI Length : The lookback period for the RSI calculation. Pivot Lookbacks : Determines the sensitivity of the pivot detection used for finding divergence points. 🔹 Advanced: HTF PO3 Show HTF PO3 : Toggles the projected candle interface on the right side of the chart. Candles to Show : The number of historical HTF candles to project alongside the live one. Right Offset : How many bars to the right the projection is rendered. Show PO3 Price Labels/Delta : Toggles specific data points on the projection UI.
مؤشر Pine Script®
من ‎LuxAlgo‎
3
Support & Resistance Pro Toolkit [LuxAlgo]The Support & Resistance Pro Toolkit indicator is the ultimate professional structural analysis engine for TradingView, meticulously engineered to provide the definitive solution for modern structural analysis by integrating four sophisticated detection algorithms—Pivots, Donchian Alternating, CSID, and ZigZag—marked by directional triangle signals to identify high-conviction swing points. This powerhouse tool allows traders to seamlessly toggle between precise level plotting and dynamic ATR-based zones, both featuring a revolutionary security breakout buffer and 25-bar future projections, alongside advanced filtering based on traded volume, liquidity sweeps (marked by prominent dot signals), re-test frequency, and survival duration. 🔶 USAGE The toolkit identifies significant price structures using one of four sophisticated detection methods. Once a level is identified, it can be displayed as a precise line or a dynamic zone with depth determined by the Average True Range (ATR). Traders can use this toolkit to filter out market noise by setting minimum requirements for volume, re-tests, or liquidity sweeps. This ensures that only the most significant institutional structures are displayed on the chart. 🔹 Advanced Detection Engines The foundation of any structural analysis is detection. This toolkit offers four unique methodologies to suit any trading style: Pivots : The industry-standard approach using left/right strength lookbacks to find peak highs and valley lows. Donchian (Alternating) : A high-performance state-machine detector. It identifies alternating swings without fixed lag, confirming a previous extreme precisely when price shifts to a new directional state (e.g., a new Higher High confirms the previous Lower Low). CSID : A momentum-based detector that identifies structural extremes based on a consecutive sequence of N bullish or bearish candles, highlighting areas of strong trend initiation. ZigZag : A volatility-adjusted method that identifies swings based on a percentage deviation from price, filtering out minor fluctuations and focusing on significant market moves. 🔹 Zone Sizing & The Security Buffer Structural areas are rarely single prices. This toolkit treats S&R as dynamic regions of interest: Zone Depth (ATR Mult) : Zones are calculated using the Average True Range (ATR) to ensure they adapt to current market volatility. This sets the thickness from the swing point inwards towards price. Breakout Buffer (ATR Mult) : A revolutionary "Security Buffer" that extends the zone outwards on the breakout side. This requires price to clear an additional layer of volatility before a breakout is confirmed, significantly reducing "fakeouts" and noise-triggered mitigations. 🔹 Overlap & Structural Hygiene Keep your charts actionable and clean with institutional-grade overlap management: Merge Overlapping : When two zones interact, the older zone expands its boundaries to encompass the newer one, creating a "Super Zone" that respects the combined historical context. Hide Oldest First : Prioritizes the most recent market context by hiding older levels that are overlapped by newer ones. Hide Youngest First : Respects established, historical structures by ignoring newer, smaller levels that form within the range of existing unmitigated zones. 🔹 Institutional Filtering Eliminate minor "noise" levels by showing only structures that meet high-conviction criteria: Price Entries (E) : Shows zones only after they have been re-tested a specific number of times. Strength (S) : Tracks the number of additional swing points that occur within the zone range during its lifetime. Sweeps (SW) : Filters for zones that have successfully trapped liquidity through wick-only violations. Traded Volume (V) : Sums every tick of volume that occurs while price is within the zone, identifying areas of massive institutional participation. Duration (D) : Requires a level to survive for a minimum number of bars before it is considered a valid structure. 🔶 DETAILS 🔹 Symbols & Analytic Feedback ▲/▼ Triangles : Pinpoint markers at the exact bar of every detected swing high and low. ● Large Dots : Marked at the exact location of "Sweeps"—where price wicks past a boundary but closes back inside, signaling a potential reversal or liquidity grab. Future Projections : Active, unmitigated levels extend 25 bars beyond the current price action for immediate visual guidance. Dynamic Shorthand Labels : Positioned at the end of the extension and centered on the zone average, providing a real-time data readout: E:Entries | S:Strength | SW:Sweeps | V:Volume | D:Duration 🔹 The Performance Dashboard A 4-column command center providing a side-by-side comparison of structural performance across Support, Resistance, and Totals: Active / Total : Real-time count of currently valid versus historically detected structures. Mitigation % : The structural "break rate" of your current settings. Avg Duration : The average number of bars a level survives before being violated—critical for timing trades. Avg Volume : The typical "weight" of institutional activity accumulated within zones before they break. Total Sweeps : A macro-view of liquidity hunting activity on both sides of the market. 🔶 SETTINGS 🔹 Detection Settings Detection Method : Choose between Pivots, Donchian, CSID, or ZigZag logic. Swing Sensitivity : Adjusts the lookback or deviation required to confirm a new swing point. 🔹 Zone & Level Sizing Display Style : Toggles between horizontal levels and ATR-based zones. ATR Period : Period used for the volatility calculations. Zone Depth (ATR Mult) : Sets the vertical thickness of the S&R zones. Breakout Buffer (ATR Mult) : Adds a buffer to the breakout side to filter out false breaks. 🔹 Filtering & Visibility Overlap Handling : Manages how overlapping zones are displayed (Merge, Hide Oldest, or Hide Youngest). Max Active (Unmitigated) : Limits the number of unmitigated levels shown on the chart. Show Broken S&R : Toggles the visibility of levels that have already been mitigated. Extend Active S&R : Extends active levels into the future for better visibility. 🔹 Minimum Requirements Min Price Entries : Minimum re-tests required for a level to be visible. Min Overall Strength : Minimum strength score required based on internal swing points. Min Sweeps : Minimum liquidity sweeps required. Min Traded Volume : Minimum accumulated volume required within the zone. Min Duration (Bars) : Minimum age of the level in bars before display.
مؤشر Pine Script®
من ‎LuxAlgo‎
13
Viprasol Volume Weighted Trend Engine## Overview The Volume Weighted Trend Engine uses a Volume Weighted Moving Average (VWMA) as a central trend baseline with ATR-based volatility bands that expand and contract dynamically. When price closes above the upper band the trend turns bullish; below the lower band it turns bearish. The indicator holds the last confirmed direction until the opposite band is breached, keeping signals clean and avoiding constant flip-flopping. Built for traders who want volume-aware trend detection with squeeze identification and configurable signal filtering. ## What Is Original (Viprasol Additions) This is an original Viprasol indicator. The following features were added in this enhanced version: 1. **Signal Cooldown** — A configurable minimum bar gap (default 0 = off) between consecutive signals. Prevents rapid-fire noise in choppy or ranging markets while allowing the core band-breach logic to remain responsive. 2. **Volume Confirmation Filter** — When enabled, signals only fire if current volume exceeds the 20-bar simple moving average. This filters out low-conviction band breaches that occur on thin volume, which are more likely to fail. 3. **Trend Strength Meter** — Calculates where price sits within the bands as a percentage (-100 to +100). At the VWMA = 0%, at the upper band = +100%, at the lower band = -100%. Displayed in the dashboard and optionally as a background tint that intensifies as price moves further from the VWMA. 4. **ATR Squeeze Detection** — Measures band width as a percentage of the VWMA, then compares it to its own 50-bar SMA. When band width falls below the SMA multiplied by a threshold factor (default 0.8), a squeeze is flagged. Diamond markers appear on the VWMA line during squeeze periods. Squeezes indicate periods of compression that often precede strong directional moves. 5. **Info Dashboard** — An 8-row real-time table showing: trend direction, trend strength percentage, VWMA value, ATR value, band width percentage, squeeze status, and volume status. Configurable position (4 locations) and font size (4 sizes). 6. **5 Additional Alert Conditions** — Squeeze started, volume-confirmed bullish/bearish signals, trend strength extreme (>90%), and band touch alerts. Total: 8 alert conditions (up from 3). 7. **Tooltips on All Inputs** — Every input parameter (15+) has a descriptive tooltip explaining its function and effect on behavior. 8. **Organized Input Groups** — Inputs organized into 4 clear groups: Core Settings, Signal Filters, Visual Settings, and Dashboard. ## How It Works **VWMA Baseline:** A Volume Weighted Moving Average of the configured source (default: close) over the specified period (default: 34). Unlike a regular SMA, VWMA gives more weight to bars with higher volume, making the baseline naturally responsive to institutional activity. **ATR Volatility Bands:** The Average True Range over the same period is multiplied by a configurable factor (default: 1.5) and added/subtracted from the VWMA to create dynamic upper and lower bands. The bands widen during volatile conditions and narrow during compression. **Trend Detection:** When price closes above the upper band, the trend flips to bullish. When price closes below the lower band, it flips to bearish. The direction is held (latched) until the opposite band is breached. This prevents the constant signal noise that occurs when price oscillates near a single moving average. **Glow Effect:** Three overlapping plots of the VWMA at decreasing opacity create a soft glow behind the main line, providing enhanced visual clarity of the trend direction. ## Key Features - Volume Weighted Moving Average (VWMA) baseline with dynamic ATR bands - Latching trend detection — direction holds until opposite band is breached - Signal cooldown to prevent noise in choppy markets - Optional volume confirmation filter for higher-quality signals - Trend strength meter (-100% to +100%) with optional background gradient - ATR squeeze detection with diamond markers - Glow effect on VWMA line (3-layer opacity stack) - Gradient band fills (inner and outer zones) - Candlestick bar coloring by trend direction - Signal labels with entry price - 8-row info dashboard with trend, strength, VWMA, ATR, band width, squeeze, volume - 8 alert conditions with dynamic messages - All visual elements individually toggleable - Custom bullish and bearish colors ## How to Use **Reading the Chart:** - **VWMA line** (solid, colored) shows the volume-weighted trend center - **Bands** show volatility envelope — price between bands = no new signal - **Glow color** indicates current trend direction at a glance - **Diamond markers** on the VWMA flag squeeze periods (potential breakout setup) - **Triangle signals** mark confirmed trend changes **Trading Ideas:** - Enter on trend change signals, especially those confirmed by above-average volume - Use squeeze periods to prepare for directional moves — the first band breach after a squeeze often produces strong trends - Trend strength > 70% suggests extended price action — consider taking profits or tightening stops - Use the VWMA as dynamic support (bull) or resistance (bear) for trailing stops **Recommended Settings:** - Scalping (1m-5m): VWMA 21, ATR Mult 1.2, Cooldown 3 - Day Trading (15m-1H): VWMA 34, ATR Mult 1.5, Cooldown 0 - Swing (4H-1D): VWMA 55, ATR Mult 2.0, Cooldown 0 ## Settings | Group | Description | |---|---| | Core Settings | VWMA period, ATR multiplier, price source | | Signal Filters | Signal cooldown bars, volume confirmation toggle, squeeze threshold | | Visual Settings | Bull/bear colors, band fills, glow effect, bar coloring, signal labels, trend strength background | | Dashboard | Show/hide, position (4 options), font size (4 options) | ## Alerts 1. **Bullish Signal** — Trend flipped bullish (price closed above upper band) 2. **Bearish Signal** — Trend flipped bearish (price closed below lower band) 3. **Trend Change** — Any trend direction change 4. **Squeeze Started** — Band width dropped below compression threshold 5. **Volume Confirmed Bull** — Bullish signal with above-average volume 6. **Volume Confirmed Bear** — Bearish signal with above-average volume 7. **Trend Strength Extreme** — Trend strength exceeded 90% in either direction 8. **Band Touch** — Price touched or exceeded a band boundary All alerts include {{ticker}}, {{close}}, and {{interval}} for dynamic notification messages. ## Limitations & Disclaimer - VWMA requires volume data — on instruments without real volume (some forex pairs), the indicator will use tick volume which may behave differently. - The latching trend mechanism means signals are inherently late — the trend only changes after a confirmed band breach, not at the start of a move. - Squeeze detection identifies compression but does not predict breakout direction. - Trend strength is normalized to the current band width — during very narrow bands, small price moves can cause large strength readings. - Signal cooldown and volume filter are independent — both must pass for a signal to fire when both are configured. - This indicator is for educational and analytical purposes only — it is not financial advice. Always use proper risk management. ## Credits & Attribution Original concept and implementation by Viprasol. Enhanced with signal filtering, squeeze detection, trend strength meter, dashboard, and expanded alert system.
مؤشر Pine Script®
من ‎viprasol‎
Structural Pivot Mapper [JOAT]Structural Pivot Mapper Introduction The Structural Pivot Mapper (SPM) is an advanced open-source structural analysis indicator that combines W/M pattern detection, dynamic support/resistance level mapping, pivot point analysis, volume profile integration, and break-retest detection to identify institutional structural pivots and key price levels. This indicator reveals market structure through systematic detection of swing highs/lows, classical chart patterns, and volume-based price levels, providing traders with a comprehensive structural framework for identifying high-probability entry and exit zones. Unlike basic pivot indicators that simply mark swing points, SPM employs sophisticated pattern recognition algorithms to detect W patterns (bullish reversal), M patterns (bearish reversal), Head & Shoulders formations, and tracks level strength through touch counting and volume analysis. The indicator automatically manages support/resistance levels, removes outdated levels, and highlights Point of Control (POC) from volume profile analysis to show where institutional activity is concentrated. Why This Indicator Exists This indicator addresses the challenge of identifying key structural levels where institutional players are likely to defend positions or initiate new trades. Market structure provides the framework for understanding price behavior, and SPM systematically reveals: W/M Pattern Detection: Identifies classical reversal patterns with strict validation rules Dynamic Support/Resistance: Tracks pivot-based levels with automatic strength scoring Level Touch Counting: Quantifies level importance through historical price interaction Volume Profile Integration: Identifies Point of Control (POC) where maximum volume traded Break & Retest Detection: Monitors level breaks and subsequent retests for confirmation Head & Shoulders Patterns: Detects both regular and inverse H&S formations Smart Level Management: Automatically removes weak levels and maintains only strongest Each component provides unique intelligence. W/M patterns show reversal zones, pivots show swing structure, touch counting shows level strength, volume profile shows institutional interest, break-retest confirms level validity, and H&S patterns show major reversals. Core Components Explained 1. W Pattern Detection (Bullish Reversal) SPM detects W patterns through systematic analysis of 5 pivot points (A-B-C-D-E): f_detect_w_pattern(float src, int lookback, int offset, bool strict) => // Find 5 pivot points forming W shape // E = current, D = first low, C = middle high, B = second low, A = left high // Validation: E > C, D < E, D < C, B <= D (strict), B < A found := a > 0 and a != b and c != 0 and d != 0 and src > src and src < src and src < src and (src <= src or not strict) and src < src W patterns indicate bullish reversal when: - Price forms double bottom (D and B) - Middle high (C) is lower than current price (E) - Second low (B) is higher than or equal to first low (D) in strict mode - Pattern completes with breakout above middle high (C) Entry level is at middle high (C), stop loss at second low (B). 2. M Pattern Detection (Bearish Reversal) M patterns are detected through inverted W logic: f_detect_m_pattern(float src, int lookback, int offset, bool strict) => // Find 5 pivot points forming M shape // E = current, D = first high, C = middle low, B = second high, A = left low // Validation: E < C, D > E, D > C, B >= D (strict), B > A found := a > 0 and a != b and c != 0 and d != 0 and src < src and src > src and src > src and (src >= src or not strict) and src > src M patterns indicate bearish reversal when: - Price forms double top (D and B) - Middle low (C) is higher than current price (E) - Second high (B) is lower than or equal to first high (D) in strict mode - Pattern completes with breakdown below middle low (C) Entry level is at middle low (C), stop loss at second high (B). 3. Dynamic Support/Resistance Level Management SPM tracks pivot-based support and resistance levels with automatic management: float pivot_high = ta.pivothigh(high, pivot_left, pivot_right) float pivot_low = ta.pivotlow(low, pivot_left, pivot_right) // Store levels in arrays if not na(pivot_high) and barstate.isconfirmed if array.size(resistance_levels) < max_levels array.push(resistance_levels, pivot_high) array.push(resistance_touches, 1) else if auto_cleanup array.shift(resistance_levels) // Remove oldest array.push(resistance_levels, pivot_high) Level strength is calculated through touch counting: 1 touch: New level (weak) 2 touches: Confirmed level (moderate) 3+ touches: Strong level (high importance) Levels are automatically removed when max_levels is reached and auto_cleanup is enabled. 4. Level Touch Counting & Strength Scoring SPM tracks how many times price interacts with each level: float zone_size = atr_value * zone_width if high >= level - zone_size and high <= level + zone_size array.set(resistance_touches, i, array.get(resistance_touches, i) + 1) Strength score (0-100) is calculated based on: Touch Count (0-40 points): More touches = stronger level (8 points per touch, max 40) Age Factor (0-30 points): Older levels = more established (based on level_strength_period) Volume Factor (0-30 points): Higher volume at level = more institutional interest Only levels with 2+ touches and strength >60 are displayed to reduce clutter. 5. Volume Profile & Point of Control (POC) SPM calculates volume profile to identify price levels with maximum trading activity: f_volume_profile(int bins, int lookback) => float price_range = price_high - price_low float bin_size = price_range / bins // Accumulate volume in 20 price bins for i = 0 to lookback - 1 float bar_price = hlc3 int bin = math.floor((bar_price - price_low) / bin_size) array.set(vp_volumes, bin, current_vol + bar_vol) // Find POC (highest volume bin) float poc_price = array.get(vp_prices, poc_bin) POC represents the price level where most volume traded - typically where institutions have significant positions. Value Area High (VAH) and Value Area Low (VAL) define the range containing 70% of volume. 6. Break & Retest Detection SPM monitors when price breaks through resistance levels and subsequently retests: // Detect break (close above resistance) if not was_broken and close > level and close <= level array.set(level_broken, i, true) array.set(break_bar_index, i, bar_index) // Detect retest (price returns to broken level within 3-20 bars) if was_broken int break_bar = array.get(break_bar_index, i) bool is_retest = bar_index - break_bar >= 3 and bar_index - break_bar <= 20 bool touching_level = math.abs(close - level) < atr_value * 0.5 if is_retest and touching_level label.new(bar_index, level, "RT", color=c_support_strong) Successful retests confirm level validity and often provide high-probability entry opportunities. 7. Head & Shoulders Pattern Detection SPM detects both regular and inverse Head & Shoulders formations: f_detect_head_shoulders(float src, int lookback) => // Find 3 pivot highs: left shoulder, head, right shoulder float ph1 = ta.pivothigh(src, lookback, lookback) float ph2 = ta.pivothigh(src, lookback, lookback) float ph3 = ta.pivothigh(src, lookback, lookback) // Validate: head higher than shoulders, shoulders roughly equal if ph2 > ph1 and ph2 > ph3 and math.abs(ph1 - ph3) < (ph2 - ph1) * 0.3 found := true neckline := math.min(low , low ) H&S patterns are major reversal formations indicating trend exhaustion and potential reversal. Visual Elements Support Lines: Blue horizontal lines with strength-based width (2-3px) Resistance Lines: Pink horizontal lines with strength-based width (2-3px) Level Labels: "S: price " for support, "R: price " for resistance (N = touch count) Pivot Markers: Small circles at swing highs (pink) and lows (blue) POC Line: Yellow dotted line showing Point of Control from volume profile Retest Markers: "RT" labels when price retests broken levels Pattern Lines: Optional dashed lines showing W/M pattern structure (disabled by default) Dashboard: Real-time metrics showing resistance count, support count, pattern status, POC price Input Parameters Pattern Detection: Pattern Range: Lookback period for W/M detection (default: 9) Pattern Offset: Additional bars to check (default: 0) Strict Pattern Validation: Enforce stricter pattern rules (default: false) Pivot Settings: Pivot Left Bars: Bars to left of pivot (default: 6) Pivot Right Bars: Bars to right of pivot (default: 1) Show Pivot Labels: Toggle pivot markers (default: true) Level Management: Maximum Levels: Max support/resistance levels to track (default: 3) Level Strength Period: Lookback for strength calculation (default: 50) Auto-Cleanup Old Levels: Remove oldest when max reached (default: true) Visualization: Show Support/Resistance Zones: Toggle level display (default: true) Zone Width (ATR %): Width of level zones (default: 0.5) Show Pattern Lines: Toggle W/M pattern visualization (default: false) How to Use This Indicator Step 1: Identify Key Structural Levels Look for blue (support) and pink (resistance) lines. Thicker lines with higher touch counts are strongest. Step 2: Monitor Pattern Formations Watch dashboard for "W Pattern" (bullish) or "M Pattern" (bearish) status. These indicate potential reversal zones. Step 3: Check POC Proximity Yellow POC line shows where maximum volume traded. Price often gravitates toward POC or bounces from it. Step 4: Wait for Break & Retest When price breaks resistance and retests (RT label), it confirms level as new support. High-probability long entry. Step 5: Use Level Strength for Confidence Levels with 3+ touches are most reliable. Dashboard shows total support/resistance count. Step 6: Combine with Higher Timeframe Structure Use SPM on multiple timeframes. Daily/weekly levels are stronger than intraday levels. Best Practices Focus on levels with 3+ touches - these have proven institutional interest W/M patterns work best at major support/resistance levels POC acts as magnet - price often returns to POC after deviating Break-retest setups have highest win rate when combined with volume confirmation Disable pattern lines to reduce chart clutter - use dashboard for pattern status Adjust zone width based on instrument volatility (higher ATR = wider zones) Auto-cleanup keeps chart clean but may remove valid older levels H&S patterns are most reliable on higher timeframes (4H+) Level strength score >70 indicates institutional-grade level Smart spacing prevents overlapping levels - only strongest levels shown Indicator Limitations Pattern detection requires sufficient historical data and clear pivot formation W/M patterns can produce false signals during strong trends Level touch counting is historical - doesn't predict future touches Volume profile requires consistent volume data - may not work on illiquid instruments Break-retest detection has time window (3-20 bars) - may miss delayed retests Maximum level limit means some valid levels may be removed Pivot detection lags by pivot_right bars - not real-time H&S patterns are rare and require specific market conditions Level strength scoring is multi-factor but still subjective Smart spacing may hide valid levels that are too close to stronger levels Technical Implementation Built with Pine Script v6 using: Custom W/M pattern detection with 5-point validation Pivot-based support/resistance tracking with arrays Touch counting system with ATR-based zone detection Multi-factor level strength scoring (touches + age + volume) Volume profile calculation with 20-bin price distribution POC detection through maximum volume identification Break-retest monitoring with time window validation Head & Shoulders pattern detection (regular and inverse) Smart level spacing to prevent overlapping (1.5 ATR minimum) Automatic level cleanup when maximum reached Dynamic line and label management to prevent memory issues Real-time dashboard with 4 key metrics The code is fully open-source and can be modified to suit individual trading styles. Originality Statement This indicator is original in its comprehensive structural analysis approach. While pivot detection and pattern recognition are established concepts, this indicator is justified because: It combines W/M pattern detection with dynamic support/resistance management in a unified system The multi-factor level strength scoring (touches + age + volume) provides quantitative level assessment Volume profile integration with POC detection adds institutional perspective to structural analysis Break-retest detection with time window validation automates a manual trading technique Smart level spacing prevents chart clutter while maintaining strongest levels Head & Shoulders detection (both regular and inverse) adds major reversal pattern recognition Automatic level cleanup maintains chart readability without manual intervention Integration of classical patterns (W/M, H&S) with modern volume analysis creates layered confirmation Each component contributes unique information: W/M patterns show reversals, pivots show structure, touch counting shows strength, volume profile shows institutional interest, break-retest confirms validity, H&S shows major reversals, and strength scoring quantifies importance. The indicator's value lies in presenting these complementary perspectives simultaneously with intelligent level management. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Structural levels and patterns do not guarantee price behavior. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose. -Made with passion by officialjackofalltrades
مؤشر Pine Script®
من ‎officialjackofalltrades‎
Quant Reversal Index [AlgoPoint]Overview The AlgoPoint Quant Reversal Index is a normalized (0-100) oscillator designed to measure mean-reverting tendencies in financial time series. By combining the Hurst Exponent, an Autoregressive AR(1) Half-Life model, and Ornstein-Uhlenbeck (OU) boundaries, this indicator evaluates whether an asset is in a trending or ranging regime and calculates its proportional deviation from a dynamic historical mean. Mathematical Core & Components This indicator relies on three primary quantitative concepts: 1. Hurst Exponent ( H ) : Approximated using the log variance ratio of price differences over distinct time lags. It determines the current market regime: - H < 0.5: Indicates a Mean Reverting (ranging) regime. - H > 0.5: Indicates a Trending (momentum) regime. 2. AR(1) Half-Life : Calculates the estimated time (in bars) it takes for the price to revert to its mean. This is derived from the linear regression slope (covariance/variance) of price changes against previous prices. This dynamic half-life dictates the lookback length for the oscillator's mean and standard deviation. 3. Ornstein-Uhlenbeck (OU) Conversion : Calculates the mean ($\mu$) and standard deviation ($\sigma$) over the dynamic half-life period to establish upper and lower OU boundaries. The current price is then normalized into a 0 to 100 index based on its position relative to these boundaries. Visual Elements & Interpretation - The 0-100 Scale : * A value of 50 represents the dynamic mean ($\mu$). - A value of 0 represents the Lower OU boundary (Standard Deviation limit). - A value of 100 represents the Upper OU boundary. - Values extending beyond 0 or 100 highlight statistical extremes. - Dynamic Regime Background : When the Hurst Exponent is strictly below the user-defined threshold (default 0.5), the oscillator's background is highlighted. This visually confirms that the asset exhibits stationary, mean-reverting properties. If the background is not highlighted, the asset is considered to be trending, and mean-reversion logic is disabled. - Signal Generation : The indicator plots "Buy" and "Sell" labels strictly when the market is in a confirmed mean-reverting regime ($H < 0.5$) AND the oscillator crosses back into the 0-100 range from an extreme (e.g., crossing above 0 or crossing below 100). All signals use barstate.isconfirmed to prevent repainting. - Quant Dashboard : Displays real-time data for the current market regime, exact Hurst Exponent value, and the estimated Half-Life in bars. How to Use - Wait for the background to highlight, confirming a mean-reverting regime. - Monitor the index as it reaches extreme values (< 0 or > 100). - A statistical reversion is indicated when the index crosses back inside the core 0-100 range. - Signals should be combined with broader macro analysis and strict risk management protocols. Alerts The indicator includes standard alert conditions and dynamic JSON webhook strings for automated trading systems, providing variables such as asset name, price, hurst value, and half-life duration on signal generation.
مؤشر Pine Script®
من ‎Iamalala‎
Trend filter [Jamallo](2025) This is a trend qualification and filtering tool. Breakdown: Signal Line — Vervoort ATR Trailing Stop The signal line is an implementation of the ATR Trailing Stop developed by Sylvain Vervoort, first published in Technical Analysis of Stocks & Commodities, Volume 27, Issue 6 (June 2009), in his article "Average True Range Trailing Stops" . The stop uses a modified ATR calculated on the average price (O+H+L+C)/4 rather than the plain close. Baseline — Kalman Filter The baseline is derived from the Kalman Filter, a recursive algorithm developed in 1960 by Rudolf E. Kálmán, a Hungarian-American engineer and mathematician. Originally developed for aerospace applications in the early 1960s — including guidance of the Apollo spacecraft. In this indicator, the Kalman Filter acts as a smooth, low-lag trend estimate. Rather than applying fixed weights to historical data like conventional moving averages, it dynamically adjusts its trust between the predicted trend and observed prices. Bands — Volatility Channels Two pairs of bands (inner and outer) are built around the Kalman baseline using a 200-bar WMA.
مؤشر Pine Script®
من ‎Jamallo22‎
J - Trend Sniper v2(2024) A trend-following indicator that combines an ATR trailing stop with a smoothed price line to detect trend shifts and generate long/short signals. Calculates a slow ATR trailing stop (main trend boundary) and a fast ATR trailing stop, then plots a midpoint "Fast Line" between the two A smoothed signal line (a) tracks price using a volatility-weighted EMA — more reactive during high-volatility candles, smoother during low-volatility ones Long signal fires when the signal line crosses above the ATR trailing stop; Short when it crosses below
مؤشر Pine Script®
من ‎Jamallo22‎
Viprasol Multi-Timeframe Trend Signal Engine## Overview The Multi-Timeframe Trend Signal Engine is a comprehensive trading system that combines SuperTrend-based signals with a 6-timeframe ADX trend dashboard, EMA trend ribbon, chaos trend line, order blocks, and risk management — all in one overlay. It scans 5m through Daily timeframes using ADX-based trend detection and calculates a confluence score (0-6) showing how many timeframes agree on direction. Built for traders who want multi-timeframe confirmation before entering trades. ## What Is Original (Viprasol Additions) The following features were designed and implemented by Viprasol and do not exist in the original script: 1. **MTF Confluence Score (0-6)** — Counts how many of the 6 monitored timeframes (5m, 15m, 1H, 4H, 12H, Daily) currently show a bullish ADX trend. Displayed in the dashboard as "X/6 Bullish" with color coding: green (5-6), yellow (3-4), red (0-2). A separate bear confluence count is also tracked. This gives traders an instant read on multi-timeframe alignment strength. 2. **Enhanced Dashboard Rows** — The original dashboard only showed 6 timeframe trend readings with volatility and RSI. Viprasol added three additional rows: (a) MTF Confluence Score alongside Ribbon trend status, (b) Last Signal direction (Buy/Sell) alongside Chaos Trend status (Bullish/Bearish), and (c) a branded footer row. The dashboard now shows 10 rows of information instead of 8. 3. **MTF Alignment Alerts** — Two new alert conditions that fire when 5 or more of the 6 timeframes agree on direction (Strong Bullish Alignment and Strong Bearish Alignment). These did not exist in the original and provide automated notification of high-confluence multi-timeframe setups. 4. **Ribbon Trend Change Alerts** — Two alert conditions for when the EMA ribbon crosses from bullish to bearish or vice versa. The original had trend change alerts but they were tied to the ribbon state variable directly — the Viprasol version uses edge detection (`ribbonBullish and not ribbonBullish `) for precise single-bar firing. 5. **Tooltips on All Inputs** — Every input parameter (25+) has a descriptive tooltip explaining its function, recommended values, and behavior. The original had tooltips on only 3 inputs (sensitivity, signal type, and EMA length). 6. **Reorganized Input Groups** — Inputs reorganized from 4 groups (Main, Trend, Advanced, Dashboard) into 5 semantically clearer groups (Main Settings, Trend Settings, Signal Settings, Dashboard Settings, Risk Management) with consistent naming and inline layouts. 7. **Viprasol Dashboard Styling** — Branded header ("Viprasol - MTF Trend Signal Engine"), dark theme color scheme (#111725 background, #18233a header), and branded footer with version number. ## How It Works **SuperTrend Signals:** A custom SuperTrend calculation generates buy/sell signals using ATR-based dynamic bands. All signals require bar-close confirmation to prevent repainting. Two modes are available: "All Signals" shows every crossover, while "Filtered Signals" adds an EMA filter requiring price to be above/below the main EMA for additional confirmation. **Multi-Timeframe ADX Dashboard:** The indicator fetches ADX trend quality from 6 timeframes (5m, 15m, 1H, 4H, 12H, Daily) using an anti-repaint security function (`src ` with `lookahead_on` — confirmed previous bar only). Each timeframe is classified as Bullish (ADX above adaptive threshold), Bearish (below threshold), or Neutral. The confluence score counts how many timeframes are bullish (0-6), providing an at-a-glance alignment reading. **Trend Ribbon:** Five EMAs (20, 25, 35, 45, 55) form a color-coded ribbon that shifts between bullish and bearish states on crossover. The ribbon provides visual trend context independent of the signal system. **EMA Cloud:** The 150/250 EMA cloud identifies longer-term structural trend direction. Green fill indicates bullish structure, red indicates bearish. **Chaos Trend Line:** An adaptive trend line using pivot-based detection with ATR channels. It tracks the trend using highest/lowest pivot levels and changes color on confirmed reversals. **Order Blocks:** Structural order blocks based on pivot break of structure. Bullish OBs form at swing lows when higher highs break structure; bearish OBs form at swing highs when lower lows break structure. Boxes fade when tested and are removed when fully invalidated. **RSI Take Profit System:** A sequential TP system using RSI crossovers at 70/85/100 (bullish) and 30/15/5 (bearish). Each TP level only fires after the previous one has triggered within the current signal, creating a staged exit approach. **Reversal Signals:** A 25-period RSI-based reversal detector that fires when RSI crosses above oversold (25) or below overbought (75) levels, using bar-close confirmation. ## Key Features - Custom SuperTrend signals with bar-close confirmation (no repainting on confirmed bars) - Two signal modes: All Signals and EMA-Filtered Signals - 6-timeframe ADX trend dashboard (5m, 15m, 1H, 4H, 12H, Daily) - MTF Confluence Score (0-6) — count of bullish timeframes - 5-EMA trend ribbon with color-coded direction - EMA 150/250 cloud for structural trend - Adaptive chaos trend line with pivot detection - Structural order blocks with auto-invalidation - RSI-based sequential take profit system (TP1/TP2/TP3) - Visual-only TP/SL risk management lines - RSI reversal signals at extreme levels - Channel breakout levels from pivot highs/lows - 3 candle coloring modes (Scalper RSI, Trend Ribbon, EMA Direction) - RSI background zones for overbought/oversold - Configurable dashboard position (3 locations) and font size (4 sizes) - All visual elements individually toggleable - 10 alert conditions with dynamic messages ## How to Use **Reading the Dashboard:** - Check the MTF Confluence Score first — 5-6/6 Bullish = strong alignment for longs, 0-1/6 = strong alignment for shorts - Individual timeframe trends show where agreement and disagreement exist - Ribbon and Chaos Trend rows provide additional trend context **Signal Interpretation:** - Use "Filtered Signals" mode for higher-quality entries aligned with the main EMA - Use "All Signals" mode for more frequent entries in ranging markets - Reversal signals (purple labels) indicate potential exhaustion at RSI extremes - TP1/TP2/TP3 markers provide staged exit targets based on RSI momentum **Recommended Settings:** - Scalping (1m-5m): Sensitivity 2.0, ATR Factor 8, Filtered mode - Intraday (15m-1H): Sensitivity 2.5, ATR Factor 11, All Signals mode - Swing (4H-1D): Sensitivity 3.0, ATR Factor 14, Filtered mode ## Settings | Group | Description | |---|---| | Main Settings | Sensitivity (signal frequency), Signal Mode (All/Filtered), ATR Factor (band width) | | Trend Settings | Toggle trend ribbon, EMA cloud, chaos trend line, order blocks, main EMA (with custom period) | | Signal Settings | Show/hide signals, candle coloring mode, RSI background zones, channel breakouts | | Dashboard Settings | Show/hide dashboard, position (3 options), font size (4 options) | | Risk Management | Visual-only TP/SL lines with adjustable TP strength, individual TP level toggles | ## Alerts 1. **Buy Signal** — SuperTrend crossover buy confirmed at bar close 2. **Sell Signal** — SuperTrend crossover sell confirmed at bar close 3. **Filtered Buy** — Buy signal with price above main EMA 4. **Filtered Sell** — Sell signal with price below main EMA 5. **Reversal Up** — RSI crosses above oversold level 6. **Reversal Down** — RSI crosses below overbought level 7. **Ribbon Turned Bullish** — EMA ribbon crosses to bullish state 8. **Ribbon Turned Bearish** — EMA ribbon crosses to bearish state 9. **Strong Bullish MTF Alignment** — 5+ of 6 timeframes showing bullish trend 10. **Strong Bearish MTF Alignment** — 5+ of 6 timeframes showing bearish trend All alerts include {{ticker}}, {{close}}, and {{interval}} for dynamic notification messages. ## Limitations & Disclaimer - MTF data uses the anti-repaint pattern (previous bar + lookahead) to avoid repainting on confirmed bars. However, the current bar's data updates in real-time until confirmed. - ADX trend classification uses an adaptive threshold (median ADX x multiplier), which means "Neutral" readings are relative to recent volatility, not fixed levels. - The RSI TP system is sequential — TP2 only fires after TP1, and TP3 after TP2. If TP1 never triggers, later levels will not fire. - Order blocks are based on a simplified break-of-structure method using 3-bar pivots. They are not equivalent to institutional order flow. - The Risk Management TP/SL lines are VISUAL ONLY — they do not execute trades. - Candle coloring modes use different data sources — ensure you understand which mode is active. - This indicator is for educational and analytical purposes only — it is not financial advice. Always use proper risk management and test on a demo account first. ## Credits & Attribution The original script provides the SuperTrend signal engine, EMA trend ribbon, EMA cloud, chaos trend line, MTF ADX dashboard (6 timeframes), order block detection, RSI take profit system, risk management TP/SL lines, reversal signals, channel breakouts, candle coloring modes, volatility measurement, and 8 alert conditions. All enhancements listed in the "What Is Original" section above were designed and implemented by Viprasol. Published open-source per TradingView's open-source reuse guidelines.
مؤشر Pine Script®
من ‎viprasol‎
1
CUSUM Trend [AlgoPoint]The CUSUM Trend by AlgoPoint brings hedge-fund-level quantitative analysis directly to your charts. While standard moving averages suffer from lag and fakeouts, this script utilizes an advanced Cumulative Sum (CUSUM) algorithm, deeply re-engineered with adaptive volatility and volume-weighted metrics to identify true market regimes. It is designed to protect traders from choppy markets and explicitly capture high-probability, volume-backed trend breakouts before they become obvious to the retail crowd. 🧠 Under the Hood: The Quant Mechanics Instead of a basic price deviation model, the CUSUM Trend operates on four advanced pillars: - Zero-Lag Kernel (Ehlers SuperSmoother): We replaced traditional MAs with John Ehlers' SuperSmoother filter to establish a mathematically zero-lag baseline. - Volume-Weighted Residuals: Price deviations (residuals) only build up the CUSUM pressure pools if they are backed by institutional volume. Low-volume spikes are treated as noise and explicitly filtered out. - Fractal Dimension (Adaptive Thresholds): By using a proxy for the Hurst Exponent, the engine "reads" the market state. In choppy conditions, the bands expand defensively to prevent fakeouts. In trending conditions, they tighten aggressively. - Asymmetric Volatility: The algorithm calculates upside and downside variance independently, recognizing that market drops are often much sharper than rallies. 📊 How to Read the Chart - The Dynamic Trend Cloud: The asymmetric bands represent the institutional pressure thresholds. When price breaks and confirms outside this zone, a regime change (Bull/Bear trend) is triggered. - Gradient Candles: Candle colors dynamically shift based on the built-up CUSUM pressure. Bright green/red indicates extreme breakout momentum, while faded colors represent a stable trend or a ranging market. - Trailing Stop: Once a trend is established, the opposite side of the threshold acts as a dynamic trailing stop line, allowing you to ride the trend to its mathematical exhaustion. - Hybrid Dashboard: Monitor the internal breakout pressure, fractal regime, and exact trailing stop value in real-time without cluttering your main view. ⚙️ How to Use It - Sensitivity Profiles: Choose between Fast (Day Trade), Balanced (Swing), or Slow (Trend) in the settings. The engine automatically recalculates all internal variance and fractal thresholds based on your choice. - Automation Ready: Fully compatible with webhook automation (3Commas, PineConnector, etc.) via dynamic JSON alerts triggering on confirmed regime breakouts. Disclaimer: This indicator is for educational and analytical purposes only. Past performance is not indicative of future results.
مؤشر Pine Script®
من ‎Iamalala‎
5
Money Flow Divergence Zones [AlgoAlpha]🟠 OVERVIEW This script identifies key price levels where volume and momentum show significant disagreement, visualizing these areas as Money Flow Liquidity Zones. By tracking the Money Flow Index (MFI) and its relationship to price action, the tool detects regular divergences that often precede market reversals. When a divergence is confirmed, the script projects a horizontal zone onto the chart based on the recent price extreme. These zones act as "liquidity pockets" that remain active until price successfully mitigates them through a wick or body cross, providing a clear map of potential support and resistance derived from volume-weighted momentum. 🟠 CONCEPTS The core logic relies on the interaction between a smoothed MFI and pivot-based price extremes. While price might make a lower low, the MFI—calculated from $hlc3$ and volume—might make a higher low, signaling that selling pressure is exhausting despite the price drop. This script uses these divergences to set the initial context for a zone. The zones are then refined using a "Body vs Wick" logic, where the zone's depth is defined by the distance between the absolute high/low and the candle body. The MFI smoothing via a Hull Moving Average (HMA) ensures that the momentum signals are responsive yet filtered for high-frequency noise. 🟠 FEATURES Dynamic Liquidity Zones : Automatically draws and extends support/resistance zones based on MFI divergence. Divergence Engine : Detects regular bullish and bearish divergences with adjustable pivot lookbacks. Visual Momentum Oscillator : Features a color-coded, smoothed MFI with a gradient midline to show volume strength. Touch Signals : Small triangles appear when price interacts with an active zone while momentum aligns. 🟠 USAGE Setup : Add the script to your chart. It is effective on most timeframes, but for intraday trading, the default 14-period MFI works well on 5m to 15m charts. Adjust the "Pivot Lookback" to fine-tune how sensitive the divergence detection is to local peaks. Read the chart : Green zones represent bullish liquidity (potential support), while red zones represent bearish liquidity (potential resistance). Look for "▲" or "▼" symbols on the bars; these indicate price is currently touching a zone and might be ready for a reversal. The oscillator at the bottom confirms the trend: green for rising money flow and red for falling. Settings that matter : The Sweep Type is critical—switching to "wick" will make zones disappear more easily (conservative), while "body" keeps zones active until a candle closes through them (aggressive). The Max Zone Age prevents old, irrelevant levels from cluttering your chart by removing them after a set number of bars.
مؤشر Pine Script®
من ‎AlgoAlpha‎
Hidden Markov Reversal Finder [UAlgo]Hidden Markov Reversal Finder is a regime aware reversal detection indicator that uses a compact 3 state Hidden Markov style filter with online adaptation to classify market conditions and highlight potential top and bottom rotations. The script models price behavior as transitions between three regimes: - Bull Expansion - Balance - Bear Stress Instead of running a heavy Baum Welch retraining loop, this version is designed as a lightweight real time filter. It updates regime probabilities using a transition matrix plus a two dimensional Gaussian emission model built from two normalized observations: Return observation as a smoothed log return z score Volatility observation as a realized volatility z score The indicator runs in its own pane ( overlay=false ) but can optionally paint chart bars and place reversal labels on price using force overlay. It also includes a clean dashboard panel showing the current state, confidence, observation values, score, posterior probabilities, stretch, and the current setup classification. The reversal engine is built around a top rotation and bottom rotation concept. It looks for a probability peak in a regime, then a fade from that peak, combined with momentum flip conditions and a stretch filter measured in ATR units relative to a baseline EMA. Signals are gated by a confidence threshold and a cooldown period to reduce repetitive prints. This makes the indicator useful as a regime driven reversal framework that integrates: State probabilities and confidence Regime score and momentum flip ATR based stretch extremes Peak fade rotation logic Clean visual markers and dashboard transparency 🔹 Features 🔸 1) Three Regime Model The script uses three explicit regimes with distinct roles: Bull Expansion, intended to represent positive drift conditions Balance, intended to represent neutral or mixed drift Bear Stress, intended to represent negative drift and higher stress conditions Each regime has its own mean and variance assumptions for return and volatility, which are then adapted online. 🔸 2) Two Dimensional Observation System (Return and Volatility) The model does not rely on only returns. It uses both: A normalized return feature A normalized volatility feature This helps distinguish clean bullish trends from choppy balance periods, and balance periods from bearish stress regimes. 🔸 3) Transition Matrix with Persistence Controls Users can control how sticky each regime is through persistence settings: Bull persistence Balance persistence Bear persistence The transition matrix is constructed so that most probability remains in the same regime, while the remainder flows into other regimes using asymmetric weights that reflect realistic behavior. 🔸 4) Real Time Bayesian Filter Update Each bar, the model performs: Prediction step using the transition matrix Update step using Gaussian emissions Posterior normalization Active state selection by arg max This produces a smooth probability based regime tracker suitable for live use. 🔸 5) Adaptation After filtering, the model adapts its internal means and variances using a learning rate scaled by posterior responsibility. This allows the state distributions to slowly adjust to changing market conditions without full retraining. This keeps the indicator responsive while still stable. 🔸 6) Regime Score Output The main score line is: Bull posterior minus Bear posterior This produces a continuous signal that ranges between negative and positive values and functions as a regime tilt meter. A confidence ribbon is also plotted as an area band derived from the dominant posterior. 🔸 7) Confidence Gating and Visual Strength Confidence is defined as the largest posterior probability among the three regimes. The script uses confidence to: Gate reversal signals Determine bar tint transparency when bar coloring is enabled Decide whether state shift tags should be printed This reduces noise during low clarity periods. 🔸 8) Rotation Style Reversal Engine The reversal finder is built on rotation logic: A top rotation occurs after a Bull probability peak fades while Bear probability begins to rise A bottom rotation occurs after a Bear probability peak fades while Bull probability begins to rise This is a probabilistic rotation concept rather than a simple oscillator crossover. 🔸 9) Momentum Flip Confirmation Signals require momentum confirmation through: Regime score change direction Return observation crossing a flip threshold This is designed to reduce premature top and bottom calls when the regime probabilities shift but price momentum has not actually flipped. 🔸 10) ATR Based Stretch Filter The script computes stretch as distance from an EMA baseline measured in ATR units. Signals require: Top signals only when stretch is above a positive threshold Bottom signals only when stretch is below a negative threshold This ensures reversal signals occur when price is extended, not when it is near equilibrium. 🔸 11) Cooldown Control A cooldown setting prevents consecutive buy or sell reversal signals from printing too frequently. This is especially useful when the market chops around an extreme and repeatedly triggers partial rotation conditions. 🔸 12) Dashboard Panel A table dashboard displays key information on the last bar: Active state name Confidence Return z score and volatility z score Regime score Posterior probabilities Stretch in ATR units Current setup text such as BUY REVERSAL, SELL REVERSAL, TOP WATCH, BOTTOM WATCH, WAIT This makes the indicator transparent and easy to interpret. 🔸 13) State Tags and Reversal Labels on Chart When enabled, the script prints: State tags such as BULL, BASE, BEAR with arrows Reversal markers with a vertical guide line and bold letter B or S Tooltips include confidence, peak probability, stretch, and current posterior probabilities. 🔸 14) Optional Probability Curves and Bar Coloring Users can toggle: State probability plots Signal markers and dots Dashboard visibility State tag visibility Bar coloring by regime with confidence adjusted transparency This makes the indicator adaptable for minimalist or fully informational workflows. 🔹 Calculations 1) Return Observation Construction The script uses log returns: float logReturn = math.log(close / nz(close , close)) It smooths return with an EMA: float smoothedReturn = ta.ema(logReturn, returnSmoothLength) Then normalizes by the return standard deviation: float returnStdev = math.max(nz(ta.stdev(logReturn, returnZLength), EPS), EPS) float returnObs = clampFloat(smoothedReturn / returnStdev, -obsClamp, obsClamp) Interpretation: Return observation is a clamped z score like feature, where positive values represent bullish return pressure and negative values represent bearish return pressure. 2) Volatility Observation Construction Realized volatility is measured as the standard deviation of log returns: float realizedVol = nz(ta.stdev(logReturn, volLength), EPS) Then it is normalized relative to a baseline EMA and baseline standard deviation: float volMean = nz(ta.ema(realizedVol, volBaselineLength), realizedVol) float volStdev = math.max(nz(ta.stdev(realizedVol, volBaselineLength), EPS), EPS) float volObs = clampFloat((realizedVol - volMean) / volStdev, -obsClamp, obsClamp) Interpretation: Volatility observation is a clamped z score like feature, where higher values indicate volatility expansion relative to baseline. 3) Warmup Logic The model waits for enough history to compute stable normalized observations: int warmupBars = math.max(returnZLength, volBaselineLength) + volLength bool ready = bar_index > warmupBars and not na(returnObs) and not na(volObs) Before ready, the script avoids producing live signals and uses the initial posterior distribution. 4) Transition Matrix Configuration The transition matrix uses persistence values and asymmetric drift splits: From Bull, most drift flows to Balance and a smaller portion to Bear From Bear, most drift flows to Balance and a smaller portion to Bull From Balance, drift splits evenly between Bull and Bear Core setup: this.setTransition(STATE_BULL, STATE_BALANCE, bullDrift * 0.78) this.setTransition(STATE_BULL, STATE_BEAR, bullDrift * 0.22) ... this.setTransition(STATE_BEAR, STATE_BALANCE, bearDrift * 0.78) this.setTransition(STATE_BEAR, STATE_BULL, bearDrift * 0.22) This design makes Balance act like a bridge regime and reduces unrealistic direct flip frequency. 5) Emission Model: 2D Gaussian Density Each state computes an emission probability from return and volatility observations using a 2D Gaussian likelihood: float exponent = -0.5 * ((retDeviation * retDeviation) / retVariance + (volDeviation * volDeviation) / volVariance) float normalizer = 1.0 / (2.0 * math.pi * math.sqrt(retVariance * volVariance)) math.max(normalizer * math.exp(math.max(exponent, -24.0)), EPS) Variances are floored at 0.12 to prevent collapse. 6) Prediction Step The model predicts next probabilities using the transition matrix: predictedProbability += posterior * transition(fromState, toState) Then normalizes the predicted vector so it sums to 1. 7) Filter Update Step The posterior is updated by multiplying predicted probabilities by emission likelihoods: nextPosterior = predicted * emission(state, retObs, volObs) Then normalized. The active state is the arg max of the posterior. 8) Online Adaptation The model updates state means and variances using posterior responsibility times learning rate: float responsibility = posterior * learningRate Means update by moving toward the current observation: nextMuRet = oldMuRet + responsibility * retError nextMuVol = oldMuVol + responsibility * volError Variances update toward squared error: nextVarRet = oldVarRet + responsibility * (retError * retError - oldVarRet) nextVarVol = oldVarVol + responsibility * (volError * volError - oldVarVol) All parameters are clamped to stability ranges so the model does not explode. 9) Regime Score and Confidence Score is defined as: posterior - posterior Confidence is the maximum posterior: posterior These values drive visuals and signal gating. 10) Stretch Calculation in ATR Units Stretch uses an EMA basis of price and measures distance in ATR units: float basis = ta.ema(close, stretchLength) float atrValue = math.max(ta.atr(14), syminfo.mintick) float stretch = (close - basis) / atrValue Top stretch requires: stretch >= stretchThreshold Bottom stretch requires: stretch <= -stretchThreshold This ensures reversals occur when price is statistically extended relative to recent volatility. 11) Probability Peak and Fade Logic The script measures recent peaks for bull and bear probabilities: float bullPeak = ta.highest(bullProb , peakLookback) float bearPeak = ta.highest(bearProb , peakLookback) Fade is peak minus current: bullFade = bullPeak - bullProb bearFade = bearPeak - bearProb Top rotation condition requires: Bull peak above threshold Bull fade above minimum Bear probability rising Bottom rotation requires the mirrored conditions. This captures the idea of regime dominance peaking, then fading as the opposite side begins to regain influence. 12) Momentum Flip Confirmation Momentum down requires: Regime score decreasing Return observation strongly negative below a flip threshold Momentum up requires: Regime score increasing Return observation strongly positive above the flip threshold This prevents signals when probabilities fade but momentum remains neutral. 13) Signal Gating and Cooldown Signals require confidence above the threshold and a cooldown to avoid repeated triggers: confidenceValue >= confidenceThreshold bar_index - lastSignalBar > cooldownBars 14) Buy and Sell Reversal Signals Buy reversal: Bottom rotation Momentum up Bottom stretch Confidence filter Cooldown filter Sell reversal: Top rotation Momentum down Top stretch Confidence filter Cooldown filter A Balance signal is also triggered when the state changes to Balance with sufficient confidence. 15) Visual Outputs The indicator plots: Regime score line with area fill around zero Confidence ribbon as an area band Optional posterior curves for Bull, Balance, Bear Normalized stretch line scaled by the stretch threshold Optional dots on the chart for reversal events Optional bar coloring on the main chart It also prints: Reversal labels B and S with stretch, confidence, and peak probability tooltips State tags on regime shifts A dashboard panel summarizing live state and setup context
مؤشر Pine Script®
من ‎UAlgo‎
2
Volatility-Adjusted Rate of Change [QuantAlgo]🟢 Overview The Volatility-Adjusted Rate of Change (VA-ROC) is a momentum oscillator that normalizes price changes against current market volatility, helping traders identify meaningful momentum shifts, spot overbought/oversold extremes, and filter out noise caused by changing volatility regimes. By measuring how large a price move is relative to what's normal for the instrument, this indicator reveals genuine directional pressure that raw momentum readings often obscure. 🟢 How It Works The indicator begins by calculating the single-bar price change and dividing it by the Average True Range over a configurable lookback period. This normalization step ensures that the same oscillator reading carries equal significance whether applied to a low-volatility blue chip or a highly volatile cryptocurrency, a concept absent from traditional rate of change indicators. price_momentum = ta.change(close) / ta.atr(atr_length) When price rises by an amount that is large relative to recent volatility, the normalized momentum produces a strong positive reading. Conversely, a decline that is modest in absolute terms but significant relative to the current ATR environment will register appropriately. This volatility-adjustment prevents the oscillator from generating inflated signals during high-volatility regimes or muted signals during quiet markets. A sensitivity multiplier then scales the normalized value, allowing traders to compress or amplify the oscillator's range to suit their instrument and timeframe: va_roc = calc_ma(price_momentum * sensitivity, ma_length, ma_type) The scaled momentum is then smoothed using a configurable moving average (supporting SMA, EMA, WMA, RMA, HMA, VWMA, DEMA, and TEMA), which filters bar-to-bar noise while preserving the shape of genuine momentum waves. The smoothed output is the final VA-ROC value, plotted against a system of four threshold levels that define bullish, bearish, neutral, and extreme zones. Momentum state is determined by the oscillator's position relative to these thresholds: is_bullish = va_roc > upper_threshold is_bearish = va_roc < lower_threshold Crossings into bullish or bearish territory, zero-line crosses, and entries into extreme zones each generate distinct signals and corresponding alerts. 🟢 Key Features The indicator is built around a threshold-based momentum framework with gradient-colored visualization, preset configurations, and a full alert system, all designed to give traders immediate clarity on momentum conditions without manual tuning. 1. Volatility Normalization: Unlike traditional ROC or momentum oscillators that produce raw price differences, VA-ROC divides every price change by the ATR, creating a dimensionless reading that remains consistent across instruments, timeframes, and volatility regimes. A reading of +1.0 always means "price moved one ATR's worth in a single bar", whether you're trading forex, equities, or crypto. This eliminates the need to recalibrate threshold levels when switching between assets. 2. Adaptive Threshold Zones: Four configurable levels (Upper Extreme, Upper Threshold, Lower Threshold, and Lower Extreme) divide the oscillator into five distinct momentum zones. The neutral zone between the upper and lower thresholds represents normal market fluctuation. Crossings above the upper threshold confirm bullish momentum, while crossings below the lower threshold confirm bearish momentum. The extreme levels mark climactic conditions where momentum is unusually powerful, often coinciding with exhaustion points or the early stages of a strong trend continuation. 3. Preset Configurations: Three built-in presets automatically optimize the sensitivity, ATR lookback, MA type, and smoothing length for different trading styles. Default provides balanced readings suited for swing trading on 4H and daily charts. Fast Response amplifies small moves with minimal smoothing for intraday scalping. Smooth Trend compresses the oscillator and applies heavier smoothing to highlight only significant directional moves for position trading. 4. Built-in Alert System: Comprehensive alerts covering all key momentum events, including bullish and bearish momentum confirmation, zero-line crossovers in both directions, and entries into upper and lower extreme zones. A combined momentum direction change alert is also included. All alerts carry exchange, ticker, and interval placeholders for seamless integration with notification workflows. 5. Visual Customization: Choose from 5 color presets (Classic, Aqua, Cosmic, Cyber, Neon) or create a fully custom color scheme using individual bullish, bearish, and neutral color pickers. Optional price bar coloring overlays the oscillator's momentum colors directly onto your main chart candles, tinting bars bullish or bearish based on the current threshold state while leaving neutral bars uncolored, providing instant trend confirmation without switching panels.
مؤشر Pine Script®
من ‎QuantAlgo‎
2
NEXOUS_cl UNIVERSAL PRO TRADERTechnical Overview: Universal 8-EMA Ribbon: This indicator utilises a sophisticated ribbon of 8 Exponential Moving Averages ( NYSE:EMA $) ranging from 20 to 55 periods. It creates a dynamic trend corridor. Green ribbon indicates bullish momentum; Red ribbon indicates bearish momentum. Institutional Kill Zones: Automated high-visibility highlighting of the most liquid trading hours (London & New York Opens). These zones are plotted in bold Yellow (#FFD700) to signal when major banks and institutions are active. Signal Logic: Precision BUY/SELL signals are generated based on the cross-over of the 20 EMA and 55 EMA, filtered by session liquidity.Audio Alerts: Integrated alert system for Session Entry and Trend Reversals. 📖 Trading Strategy Guide How to use the NEXOUS_cl indicator like a Pro. Step 1: Wait for the Yellow Kill Zone to appear. Avoid high-risk trades during low-liquidity hours. Step 2: Check the NEXOUS_cl Ribbon colour. If Green and price are above: Look for Longs. If Red and price are below: Look for Shorts. Step 3: Execution. Long Entry: Enter when the NEXOUS_cl BUY shape appears inside the Yellow zone. Short Entry: Enter when the NEXOUS_cl SELL shape appears inside the Yellow zone. Step 4: Risk Management. Place your Stop Loss below the thickest line of the ribbon (EMA 55).
مؤشر Pine Script®
من ‎NEXOUS_cl‎
Adaptive Momentum Classifier [WillyAlgoTrader]📡 Adaptive Momentum Classifier is an overlay indicator that evaluates four independent market dimensions — momentum, trend, volatility position, and money flow — ranks each one against its own historical distribution using percentile scoring, and combines them into a single composite score (0–100%) that drives signal generation. Signals fire only when the composite score crosses a threshold with minimum feature agreement across axes, passes through five independent filters, and is confirmed on bar close. The core idea: instead of using one indicator to generate signals, this tool treats four market dimensions as independent measurement axes, normalizes each to a uniform 0–1 scale via percentile ranking, weights and combines them into a consensus score, and then requires both the score threshold AND a minimum number of agreeing axes before allowing a signal. This multi-axis + agreement gate architecture filters out situations where a single strong reading (e.g., RSI spike) would trigger a false signal while the other dimensions disagree. 🧩 WHY THESE COMPONENTS WORK TOGETHER Traditional signal generators face a fundamental problem: a single indicator measures one market dimension. RSI measures momentum speed but is blind to trend direction. MACD measures trend but ignores where price sits within its volatility envelope. Volume-based indicators measure flow but know nothing about price momentum. Using any one of these alone produces signals that ignore critical market context. Simply combining indicators with AND/OR logic (e.g., "buy when RSI > 50 AND MACD > 0") doesn't solve the deeper problem: the indicators are on different scales, have different distributions, and their raw values aren't comparable. RSI = 55 and MACD histogram = 0.002 both "lean bullish" but you can't meaningfully average them. This indicator solves both problems: Step 1 — Orthogonal axis design: Each axis measures a genuinely different market dimension. Momentum (how fast), Trend (which direction), Volatility Position (where within the range), Flow (where is money going). They are deliberately chosen to be as independent as possible. Step 2 — Percentile normalization: Each axis's raw value is ranked against its own recent history. "Is this RSI-ROC blend reading higher than 75% of the last 89 readings?" This converts every axis to a uniform 0–1 scale where 0.5 = median. Now all four axes are directly comparable and combinable. Step 3 — Weighted consensus: The four normalized scores are combined with weights (Trend 1.2×, Momentum 1.0×, Flow 1.0×, Volatility 0.8×) into a single composite score. The weighting reflects that trend conviction is slightly more predictive than raw momentum. Step 4 — Agreement gate: Even with a high composite score, the signal is blocked unless at least half the axes independently agree (each reading > 0.6 for bullish or < 0.4 for bearish). This prevents one extreme axis from dominating the composite and producing a false consensus. Step 5 — Filter stack: Five independent filters (trend alignment, volatility regime, volume, score acceleration, HTF bias) provide additional context gates. The signal only fires when all enabled filters pass simultaneously. No single component is useful alone. Percentile ranking without multiple axes just normalizes one indicator. Multiple axes without percentile ranking can't be meaningfully combined. A combined score without the agreement gate can be dominated by one outlier. And all of this without filters would still fire in unsuitable market conditions. The full pipeline is required. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Four-axis percentile scoring engine. Each axis is built from two sub-components blended together, then converted to a 0–1 percentile rank against the scoring lookback window (default 89 bars). The percentile function counts what fraction of historical values are below the current value — producing a uniform distribution with no dead zones (unlike z-score normalization which compresses values near the mean). Axis 1 — Momentum (weight 1.0): Sub-components: RSI(13) centered at 50, and ROC(9). Each is percentile-ranked independently, then blended 60% RSI + 40% ROC. RSI provides stable momentum reading, ROC provides faster reaction to price acceleration. The blend captures both speed (ROC) and sustained momentum (RSI) in a single axis. Axis 2 — Trend (weight 1.2): Sub-components: MACD histogram (12/26/9), and EMA slope normalized by ATR. EMA slope = (EMA − EMA ) / (ATR × 5), making it scale-independent across instruments. Each percentile-ranked, blended 60% MACD + 40% slope. MACD histogram captures momentum of the trend itself (acceleration), while EMA slope captures sustained directional movement. This axis receives the highest weight (1.2) because directional conviction is the strongest single predictor of continuation. Axis 3 — Volatility Position (weight 0.8): Sub-components: Bollinger %B (21-period, showing where price sits within the band envelope, 0 = lower band, 1 = upper band), and ATR expansion ratio (current ATR / SMA of ATR over lookback). Combined as: (BB%B − 0.5) × min(ATR_ratio, 2.5), then percentile-ranked. This creates a directional volatility signal: price at upper band during volatility expansion scores high (strong bullish breakout), price at upper band during contraction scores lower (potential mean-reversion). The ATR ratio is capped at 2.5 to prevent extreme volatility spikes from distorting the axis. Lower weight (0.8) reflects that volatility position is a confirming factor, not a primary driver. Axis 4 — Flow (weight 1.0, auto-disabled without volume): Sub-components: MFI(13) centered at 50, and OBV slope (smoothed OBV EMA(21), slope = (OBV_EMA − OBV_EMA ) / |OBV_EMA|). Each percentile-ranked, blended 50/50. MFI combines price and volume into a single money flow reading, OBV slope shows whether accumulation is accelerating or decelerating. On instruments without volume data (forex), this axis returns 0.5 (neutral) and its weight drops to 0, so the composite score is calculated from three axes only. 2️⃣ Composite score with symmetric thresholds. The four axes are combined: composite = (1.0 × momentum + 1.2 × trend + 0.8 × volatility_position + 1.0 × flow) / total_weight. Result is 0–1 where 0 = maximum bearish consensus, 0.5 = neutral, 1 = maximum bullish consensus. A buy signal fires when the composite crosses above the threshold (default 0.618). A sell signal fires when it crosses below (1 − threshold = 0.382). This creates symmetric entry conditions: the same strength of consensus is required for both directions. 3️⃣ Feature agreement gate. Independent of the composite score, each axis is evaluated for directional agreement: > 0.6 = bullish vote, < 0.4 = bearish vote, 0.4–0.6 = abstain. The agreement ratio = max(bull_votes, bear_votes) / active_axes. Signals require agreement ≥ 0.5 (at least half the axes independently confirming the same direction). This prevents false signals from composite score averaging: if momentum = 0.95 but trend = 0.3 and volatility = 0.4, the composite might cross the threshold but only 1/4 axes agree — signal is blocked. 4️⃣ Score acceleration filter. The rate of change of the composite score: acceleration = score − score . Signals require |acceleration| ≥ Min Score Acceleration (default 0.02). This filters out slow-drift crossovers where the score gradually creeps past the threshold without any decisive move — these typically represent noise, not genuine momentum shifts. Only fast, decisive threshold crosses produce signals. 5️⃣ Five-filter stack. Each filter is independently toggleable: — Trend Alignment (default On): price must be above EMA(50) for longs, below for shorts — prevents counter-trend entries — Volatility Regime (default On): ATR ratio must be between 0.4 and 3.0 — suppresses signals during dead markets (ATR < 40% of average) and crash conditions (ATR > 300% of average) — Volume Confirmation (default On): volume must exceed 80% of its 20-period SMA — confirms market participation. Auto-disabled on instruments without volume data — Score Acceleration (default 0.02): described above. Set to 0 to disable — Higher TF Bias (default disabled): when a timeframe is selected, price must be above/below EMA(21) on the higher timeframe for longs/shorts. Uses + lookahead_on for non-repainting HTF data 6️⃣ Direction lock — no consecutive same-direction signals. After a buy signal fires, the next signal can only be a sell (and vice versa). This prevents signal clustering where multiple buy signals fire in sequence during a strong trend — you get one entry per direction until the trend reverses. 7️⃣ Four sensitivity presets. Each preset overrides two parameters simultaneously: — Conservative : threshold 0.80, lookback 150 — requires very strong consensus over a long history, fewer but higher-conviction signals — Default : uses your manual settings (threshold 0.618, lookback 89) — Aggressive : threshold 0.60, lookback 60 — lower bar for signals, shorter history, faster adaptation — Scalping : threshold 0.55, lookback 40 — minimum consensus required, very short history, designed for 1–5M charts The lookback affects all four axes simultaneously (percentile ranking window), so the entire scoring engine adapts as a unit. 8️⃣ Dynamic trend band. A visual EMA ± 0.5× ATR band colored by the composite score: green (score > 55%), red (< 45%), yellow (neutral). This provides an at-a-glance trend context without needing to read the dashboard. The band width adapts to volatility automatically. 9️⃣ Signal strength classification. Each signal is classified based on the composite score at the moment of firing: Strong (score ≥ 85%), Medium (≥ 75%), Weak (< 75%). Displayed in the dashboard and available in alert messages. This helps you size positions or filter setups based on conviction level. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Raw feature calculation: RSI(13), ROC(9), MACD(12/26/9) histogram, EMA slope (normalized by ATR), BB%B(21), ATR ratio, MFI(13), OBV slope — eight raw values computed from price and volume. Step 2 — Percentile ranking: Each raw value is ranked against its own history over the scoring lookback (default 89 bars). The pctRank function iterates through the lookback window and counts what fraction of past values are below the current value. Result: 0.0 (lower than all history) to 1.0 (higher than all history). This normalization is performed for each of the eight sub-components independently. Step 3 — Axis blending: Each pair of sub-components is blended into one axis score: momentum = 0.6 × pctRSI + 0.4 × pctROC, trend = 0.6 × pctMACD + 0.4 × pctSlope, volatility = pctVolPosition (single combined raw), flow = 0.5 × pctMFI + 0.5 × pctOBV. Step 4 — Weighted composite: composite = (1.0 × momentum + 1.2 × trend + 0.8 × volatility + 1.0 × flow) / total_weight. On instruments without volume: flow weight = 0, total_weight = 3.0 instead of 4.0. Step 5 — Threshold crossing: Buy triggers when composite crosses above the threshold (default 0.618) from below. Sell triggers when composite crosses below (1 − 0.618 = 0.382) from above. Both require barstate.isconfirmed. Step 6 — Agreement check: Each axis is independently classified as bullish (> 0.6), bearish (< 0.4), or neutral. At least 50% of active axes must agree with the signal direction. Step 7 — Filter stack: All five enabled filters must pass. Any failure blocks the signal. Step 8 — Direction lock: Signal must be opposite to the last confirmed signal. Step 9 — Emission: Buy (▲) or Sell (▼) label placed on the confirmed bar. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator to your chart 2. Select a sensitivity preset matching your style (or use Default) 3. The trend band immediately shows the current momentum bias (green/red/yellow) 4. Wait for a ▲ (buy) or ▼ (sell) label — check the dashboard for score and strength 5. Use the agreement ratio (e.g., 3/4) to confirm multi-axis consensus 👁️ Reading the chart: — 🟢 Green trend band = bullish momentum (score > 55%) — 🟡 Yellow trend band = neutral / transition zone — 🔴 Red trend band = bearish momentum (score < 45%) — 🟢 ▲ label below bar = confirmed buy signal — 🔴 ▼ label above bar = confirmed sell signal — Band width = current volatility (wider = more volatile) 📊 Dashboard fields: — Trend: current composite direction (Bullish / Bearish / Neutral) — Last Signal: most recent signal with bars elapsed — Strength: signal quality (Strong / Medium / Weak) — Score: current composite as percentage — Agreement: how many axes confirm (e.g., 3/4) — Volatility: ATR regime (High / Normal / Low) — TF and version 🔧 Tuning guide: — Too many signals: increase threshold (0.70–0.85), enable more filters, use Conservative preset — Too few signals: decrease threshold (0.55–0.60), reduce lookback (50–70), use Aggressive preset — Signals too late: shorten RSI/ROC/MACD lengths, reduce lookback — Too many false signals in ranging markets: enable ADX-aware Volatility Regime filter, increase Min Score Acceleration to 0.03–0.05 — Scalping 1–5M: use Scalping preset (threshold 0.55, lookback 40), lower filter aggressiveness — Swing 4H–1D: use Conservative preset (threshold 0.80, lookback 150), enable HTF bias filter ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Sensitivity Preset (default Default): Conservative / Default / Aggressive / Scalping — Scoring Lookback (default 89): percentile ranking window — higher = more stable, lower = faster adaptation — Signal Threshold (default 0.618): minimum composite score for buy signals (sell = 1 − threshold) 📊 Feature Engine: — RSI Length (default 13) / ROC Length (default 9): momentum axis sub-components — MACD Fast/Slow/Signal (default 12/26/9): trend axis MACD — Bollinger Length (default 21): volatility position axis — MFI Length (default 13) / OBV Smooth (default 21): flow axis 🔍 Filters: — Trend Alignment (default On): EMA(34) trend direction gate — Volatility Regime (default On): ATR ratio 0.4–3.0 range gate — Volume Confirmation (default On): volume > 80% of 20-SMA — Min Score Acceleration (default 0.02): minimum speed of score change — Higher TF Bias (default Off): optional HTF EMA(21) alignment 🎨 Visual: — Trend band (EMA ± 0.5× ATR, scored coloring) — Background tint / Dynamic bar coloring (optional) — Auto / Dark / Light theme 🔔 Alerts — 🟢 BUY — ticker, price, timeframe, composite score — 🔴 SELL — same fields Both support plain text and JSON webhook format. Bar-close confirmed, direction-locked (no consecutive same-direction alerts). ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed. HTF bias uses + lookahead_on. A warmup period (max of lookback, MACD slow period, and trend EMA length, minimum 50 bars) prevents signals during insufficient data. — 📐 The composite score is not a probability . A score of 80% means four market dimensions, percentile-ranked against recent history, strongly agree on bullish conditions. It measures consensus quality, not prediction accuracy. — ⚖️ Percentile ranking is relative to the lookback window . A score of 0.9 means "higher than 90% of the last N bars" — it does not mean the same thing on different instruments or timeframes. Each chart creates its own distribution. — 📊 The Flow axis (MFI + OBV) auto-disables on instruments without volume data (many forex pairs). The composite then runs on three axes with adjusted total weight. Signal quality is slightly lower without flow data but the other three axes remain fully functional. — 🔒 Direction lock means you get one signal per trend leg . After a buy, only a sell can fire next. This prevents clustering but means you won't get "add to position" signals — the tool provides one entry per direction. — 🔄 The agreement gate requires ≥ 50% of axes to independently confirm. On 4-axis instruments, this means ≥ 2. On 3-axis (no volume), ≥ 2. This is a deliberately moderate threshold — raising it to 75%+ would make signals extremely rare. — 🛠️ This is a signal and analysis tool , not an automated trading bot. It classifies momentum consensus and generates signals — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume-dependent features auto-adapt to available data.
مؤشر Pine Script®
من ‎WillyAlgoTrader‎
Ornstein-Uhlenbeck Mean Reversion Probability Bands [UAlgo]Ornstein-Uhlenbeck Mean Reversion Probability Bands is a statistical mean reversion indicator that models price as a mean reverting process and projects dynamic probability style zones around an estimated equilibrium mean. The script uses a rolling lookback of closing prices, fits an Ornstein-Uhlenbeck inspired parameter set from recent behavior, and then converts that estimate into inner and outer deviation bands around the current mean. The indicator runs directly on price ( overlay=true ) and is built to help traders identify when price is stretched away from its estimated equilibrium. Instead of using a fixed moving average and static standard deviation, the script attempts to infer a mean reverting structure from the data itself. It estimates the long term mean, the speed of reversion, and an equilibrium style dispersion measure, then plots two upside and two downside mean reversion zones. When price pushes into the upper or lower band regions, the script calculates a standardized distance from the estimated mean and displays a probability style label with both the percentage score and the current z score. This gives the user a quick visual read of how statistically extended price is relative to the model. A key strength of this script is that it combines: A rolling Ornstein-Uhlenbeck style parameter estimation Adaptive mean reversion zones Probability style stretch labels at band events A clean overlay presentation with visible upper and lower probability regions Important note: The percentage label in this script is a normal distribution coverage style score derived from the current z score. It is best understood as a probabilistic stretch measure, not a literal exact OU first passage probability. 🔹 Features 🔸 1) Ornstein-Uhlenbeck Inspired Mean Reversion Model The script estimates a mean reverting process from recent closing prices instead of relying only on a moving average. It uses a rolling regression style approach on consecutive price observations, then converts those estimates into Ornstein-Uhlenbeck style parameters. This makes the indicator more model driven than a standard band tool. 🔸 2) Rolling Adaptive Mean Line The central mean line is not a fixed average only. It is the estimated equilibrium level ( mu ) of the fitted process. As the rolling price sample changes, the model updates and the mean shifts with changing market structure. The mean line also changes color depending on whether current price is above or below that estimated equilibrium. 🔸 3) Dual Mean Reversion Zones (Inner and Outer) The script builds two sets of reversion bands around the mean: Inner bands using the inner multiplier Outer bands using the outer multiplier This creates a layered framework where the inner zone marks an early stretch area and the outer zone marks a more extreme statistical extension. 🔸 4) Probability Style Stretch Labels When price crosses into the upper or lower band regions, the script calculates a z score based on current distance from the estimated mean and converts it into a percentage style probability score. The label shows: A directional marker The probability style percentage The current z score This gives the user both a visual event trigger and a numeric measure of extension. 🔸 5) Visual Zone Based Design The indicator uses filled upper and lower zones rather than emphasizing the band lines themselves. This creates a cleaner chart display where the mean line stays visible and the stretch regions are highlighted as colored areas above and below it. This makes the indicator easy to read during fast chart scanning. 🔸 6) Configurable Lookback, Time Step, and Band Width Users can customize: The rolling lookback period used for model estimation The time step parameter ( dt ) used in OU conversion The inner band multiplier The outer band multiplier This makes the script adaptable to different timeframes, instruments, and preferred sensitivity levels. 🔸 7) Built In Estimation Safeguards The parameter estimation logic includes fallback protections. If the inferred model parameters are unstable or unrealistic, the script falls back to simpler sample statistics. This helps prevent unusable outputs during difficult market regimes or low quality fits. 🔸 8) Directional Touch Event Logic The script tracks both upper side and lower side band interaction: Upper side events can signal statistically stretched bullish price movement Lower side events can signal statistically stretched bearish price movement Labels are only created on crossing events, which helps reduce repeated prints while price remains outside the band. 🔹 Calculations 1) Rolling Price Queue Management The script stores recent closing prices in an array with a fixed maximum length: price_array.update_queue(close, length_input) The queue update method behaves differently depending on bar state: On a new bar, it pushes the latest value On an updating live bar, it overwrites the last stored value This keeps the rolling sample aligned with the current chart state without duplicating the active bar. 2) Fallback Mean and Dispersion Estimates Before attempting the OU style fit, the script calculates simple fallback values: float fallback_mu = src_array.avg() float fallback_sigma = src_array.stdev() These act as safety defaults if the regression based OU estimate is not reliable. Important note: In this script, fallback_sigma is a simple sample standard deviation of price levels, not return volatility. 3) AR(1) Style Regression on Consecutive Prices The model estimation is built from consecutive price pairs: x = price y = price The script computes: Mean of x Mean of y Covariance between x and y Variance of x Then it estimates: float b = sum_cov / sum_var_x This creates an AR(1) style coefficient that is later translated into OU style parameters. 4) Conversion from AR(1) Form to OU Style Parameters If the estimated b is within a valid range: if b > 0.05 and b < 0.95 the script computes: float a = mean_y - b * mean_x float mu_exact = a / (1.0 - b) float theta_exact = -math.log(b) / dt Interpretation: mu_exact is the estimated long run mean. theta_exact is the implied mean reversion speed. The conversion assumes the AR(1) relation is a discrete time representation of a mean reverting process. 5) Residual Variance and Equilibrium Dispersion The script next measures residual error from the AR(1) fit: float err = y_i - (a + b * x_i) float var_err = sum_err_sq / (n - 1) Then it converts that residual variance into an equilibrium variance estimate: float var_eq = var_err / (1.0 - b * b) Finally: float calc_sigma = math.sqrt(var_eq) Important implementation note: The variable named sigma in this script is used as an equilibrium style standard deviation around the mean, not as the continuous time OU diffusion coefficient from the SDE form. 6) Stability Filter for the Estimated Sigma Even if the AR(1) fit is mathematically valid, the script only accepts the calculated sigma when it is reasonably close to the fallback sample standard deviation: if calc_sigma < fallback_sigma * 1.5 and calc_sigma > fallback_sigma * 0.5 If this test fails, the script keeps the fallback values instead. This helps avoid unstable band widths caused by bad short term fits. 7) Final Parameter Output The estimation method returns: OU_Params.new(theta, mu, sigma_eq) Where: theta is the estimated reversion speed mu is the estimated equilibrium mean sigma_eq is the accepted equilibrium dispersion measure These parameters are then used to build the bands. 8) Band Construction The script computes four band levels around the estimated mean: float up_out = mean_val + (dev_val * mult_outer) float up_in = mean_val + (dev_val * mult_inner) float dn_in = mean_val - (dev_val * mult_inner) float dn_out = mean_val - (dev_val * mult_outer) Interpretation: Inner bands represent a milder deviation from the mean. Outer bands represent a more extreme deviation from the mean. 9) Mean and Zone Visualization The mean line is explicitly plotted: p_mean = plot(ou_bands.mean, color=color_mean, linewidth=2, title="Mean") The inner and outer band plots are also created, but their colors are fully transparent: color color_inner_up = color.new(#ffb74d, 100) color color_outer_up = color.new(#ef5350, 100) ... This means the visible structure mainly comes from the zone fills: fill(p_ui, p_uo, ...) fill(p_li, p_lo, ...) So the user sees clean upper and lower probability zones rather than several bright boundary lines. 10) Touch and Crossing Logic The script first checks whether price is currently inside a stretch area: bool touch_upper = close >= ou_bands.upper_inner bool touch_lower = close <= ou_bands.lower_inner Then it checks for fresh crossings: bool cross_up_in = ta.crossover(close, ou_bands.upper_inner) bool cross_up_out = ta.crossover(close, ou_bands.upper_outer) bool cross_dn_in = ta.crossunder(close, ou_bands.lower_inner) bool cross_dn_out = ta.crossunder(close, ou_bands.lower_outer) Labels are only created when price is touching the region and a fresh crossing occurs. This avoids creating labels on every bar that remains outside the band. 11) Z Score Calculation When an event occurs, the script calculates the standardized distance from the mean: float current_z_score = dev_val != 0 ? math.abs(close - mean_val) / dev_val : 0.0 Interpretation: A z score of 1 means price is one equilibrium standard deviation away from the estimated mean. Higher values indicate a more statistically stretched condition. 12) Probability Style Score Calculation The script converts the z score into a percentage style score using an approximation of the error function: float x = math.abs(z_score) / math.sqrt(2.0) ... float prob = erf_approx * 100.0 Because erf(|z| / sqrt(2)) corresponds to the probability mass within plus or minus that z distance under a normal distribution, the output behaves like a confidence or coverage score. Important note: This is not a direct OU mean reversion probability in the strict stochastic process sense. It is a normal distribution style stretch score based on the current z distance. 13) Upper Event Label Logic When price crosses into the upper band region: if (touch_upper and cross_up_in) or (touch_upper and cross_up_out) the script prints a bearish styled label above the bar: "▼ %" + str.tostring(probability, "#.##") + " (Z:" + str.tostring(current_z_score, "#.##") + ")" This reflects the idea that price is statistically extended above the mean and may be vulnerable to reversion. 14) Lower Event Label Logic When price crosses into the lower band region: if (touch_lower and cross_dn_in) or (touch_lower and cross_dn_out) the script prints a bullish styled label below the bar: "▲ %" + str.tostring(probability, "#.##") + " (Z:" + str.tostring(current_z_score, "#.##") + ")" This reflects the idea that price is statistically extended below the mean and may be vulnerable to reversion. 15) Role of the Time Step Input The dt_input parameter affects the conversion from the AR(1) coefficient into the OU reversion speed: float theta_exact = -math.log(b) / dt A larger dt lowers the inferred theta for the same b . A smaller dt raises the inferred theta for the same b .
مؤشر Pine Script®
من ‎UAlgo‎
1
Volume Divergence Reversal Signals [AlgoAlpha]🟠 OVERVIEW This script identifies potential trend reversals by analyzing divergences between price action and normalized volume. It transforms raw volume into a 0–100 scale to make activity levels comparable across different market regimes. By detecting instances where price reaches new extremes but volume fails to follow, the script highlights "exhaustion" or "effort without result" scenarios. It also integrates Volume Delta data to provide granular details on net buying or selling pressure at the exact moment a divergence is confirmed, offering a deeper look into the internal mechanics of a reversal. 🟠 CONCEPTS The core logic relies on the relationship between price discovery and participation. First, volume is normalized against a long-term lookback to create a standardized baseline. The script then monitors "pivots" in this normalized volume. A Bullish Divergence occurs when price makes a Lower Low while volume creates a Higher Low, suggesting that selling pressure is drying up despite the price drop. A Bearish Divergence occurs when price makes a Higher High while volume makes a Lower High, indicating a lack of buying conviction at new peaks. While price defines the trend structure , the volume pivots provide the momentum context required to signal a change in direction. 🟠 FEATURES Automatic detection of bullish and bearish volume divergences. Integrated Volume Delta (CVD or per-bar) displayed directly on signal labels. Real-time alerts for confirmed divergence patterns. 🟠 USAGE Setup : Add the script to your chart and ensure the Normalization Length is large enough (default 1000) to capture a representative sample of volume. For higher precision, the Volume Delta Lower Timeframe should be set to a lower interval than your current chart. Read the chart : Look for the "▲" (Bullish) and "▼" (Bearish) labels. When a signal appears, check the label text; it shows the total volume and the net delta (buy vs. sell) for that specific pivot. A bullish divergence with a positive (+) delta suggests aggressive buyers are stepping in at the low. Settings that matter : The Pivot Lookback Right determines the confirmation delay; a higher value makes signals more reliable but "lags" the entry. The Max Bars Between Pivots controls how far apart the two price/volume points can be; decreasing this focuses the script on immediate, sharp reversals rather than broad cycles.
مؤشر Pine Script®
من ‎AlgoAlpha‎
7
Strong Breakouts MTF | ProjectSyndicateStrong Breakouts MTF automatically identifies and power-ranks high-probability breakout opportunities by analyzing historical pivot structures. It filters for quality, calculates a 0-10 strength score for every breakout based on zone tightness, candle momentum, and proximity to the breakout level, and presents all data on the chart and in a comprehensive multi-timeframe dashboard to eliminate noise and focus on breakouts that matter. • 🎯 Power-Ranking System (0-10) — every breakout is given a strength score based on a weighted algorithm that assesses zone structure, breakout candle characteristics, and ATR-based volatility, providing an instant quality assessment. • 🎨 Strength-Based Color Scheme — breakout zones are colored by their power rank; stronger breakouts get darker, more prominent colors for immediate visual hierarchy. • 🧠 Smart Pivot Structure Detection — automatically identifies the underlying pivot high/low structure that creates the breakout zone, ensuring the detected levels are based on significant market turning points. • 📊 On-Chart Statistics — each breakout zone displays its direction (Bullish/Bearish) and its calculated strength score directly on the chart. NQ • 🧭 Full MTF Dashboard Display — provides a complete market overview across 7 timeframes (M1, M5, M15, M30, H1, H4, D1), showing the latest breakout signal, its strength, entry/SL/TP levels, and how many bars ago it occurred on that timeframe. The dashboard is stable and consistent regardless of the chart you are viewing. • 🔔 Comprehensive Alerts — get notified the moment a new breakout occurs, with the alert message containing the full details: strength, entry, SL, and TP levels. • ✅ Quality Control Filters — a user-configurable minimum strength score allows you to filter out weak, low-probability breakouts and focus only on high-quality signals. • 🔧 Fully Customizable — control everything from the breakout lookback period and ATR multipliers for SL/TP to the visibility of the dashboard and on-chart visuals. BTCUSD • 🎯 Why this algo is unique: Standard breakout indicators often generate excessive false signals or repaint. This algorithm uses a multi-factor scoring system to quantify the quality of a breakout in real-time. It doesn’t just show you a breakout; it tells you how strong it is. The MTF dashboard provides a complete, stable cross-timeframe perspective that is impossible to achieve with standard indicators. • 🚀 Apply to Gold (XAUUSD), Forex, Crypto, and Indices on any timeframe. The breakout lookback and minimum score settings allow it to adapt to anything from scalping to swing trading. USDJPY • 🎯 How to use this? Focus on trading opportunities from high-strength breakouts rated 7/10 or higher, as these have the highest probability of a significant follow-through. Use the dashboard to quickly identify which timeframes have active signals and use the on-chart visuals to analyze the breakout structure in detail. • ⚠️ IMPORTANT NOTICE: This indicator is designed to identify high-probability breakout opportunities. It should NOT be used as a standalone signal for entering trades. Always use it in conjunction with your own trading strategy, price action analysis, and other technical indicators to confirm trade setups and manage risk. Alerts Setup To receive the detailed breakout alerts, follow these steps: This single alert will trigger for any new Bullish or Bearish breakout detected by the script. 1.Click the "Alert" button in the top toolbar of TradingView. 2.In the "Condition" dropdown, select "Strong Breakouts MTF". 3.In the second dropdown, choose "Any alert() function call". 4.Set "Expiration" to your desired time. 5.Click "Create". Alerts Format BULLISH BREAKOUT Symbol : XAUUSD Timeframe: 5 Strength : 7.4 / 10 Entry : 3185.50 SL : 3181.20 TP1 : 3189.80 TP2 : 3194.10 Bearish Breakout: BEARISH BREAKOUT Symbol : XAUUSD Timeframe: 5 Strength : 6.1 / 10 Entry : 3178.30 SL : 3182.60 TP1 : 3174.00 TP2 : 3169.70
مؤشر Pine Script®
من ‎ProjectSyndicate‎
3
StO Price Action - Trend HeatmapShort Summary - Displays multi-timeframe market bias as a color heatmap table - Aggregates bullish and bearish candles per timeframe - Visual intensity reflects directional dominance Full Description Overview - Analyzes up to 10 selectable timeframes simultaneously - Counts bullish and bearish candles per timeframe - Evaluates a configurable number of historical candles - More bullish candles increase green intensity - More bearish candles increase red intensity - Neutral or mixed conditions appear visually balanced - Outputs results in a compact on-chart table Method - Designed to visualize multi-timeframe alignment - Provides instant directional context across intraday to macro levels - Uses candle color logic as momentum proxy - Helps identify trend stacking or timeframe divergence - Clean table layout with adjustable screen position Timeframe Structure - Supports custom selection of up to 10 timeframes - Intraday and higher timeframes can be mixed freely - Each timeframe can be enabled or disabled individually - Works with built-in available timeframes Usage - Select which timeframes to include - Set how many candles to evaluate per timeframe - Position the table on the chart as preferred - Use strong color clustering as confirmation tool - Watch for mixed colors as early warning of conflict Notes - Does not predict reversals, only shows directional dominance - Particularly useful for top-down analysis - Designed as bias confirmation, not as entry trigger
مؤشر Pine Script®
من ‎sto_svc‎
Volatility-Gated Trend Oscillator [QuantAlgo]🟢 Overview The Volatility-Gated Trend Oscillator identifies statistically significant trend conditions by measuring price deviation from a dynamic baseline and filtering out normal market noise through an adaptive volatility floor. It calculates a moving average of the chosen type as a baseline, then measures how far price has deviated from it relative to average absolute deviation to define a noise threshold. Only when price breaks decisively beyond this threshold is a trend state confirmed, helping traders distinguish genuine momentum from random noise across different timeframes and markets. 🟢 How It Works The indicator's core methodology lies in its dual-layer approach combining deviation measurement with volatility-gated filtering, where trend confirmation requires price movement to exceed statistically meaningful thresholds. First, a configurable moving average is calculated to establish a dynamic baseline reflecting the underlying trend at the chosen sensitivity level: baseline = get_ma(src, sensitivity, ma_type) raw_diff = src - baseline Then, the average absolute deviation from the baseline is measured over the same period and scaled by a user-defined multiplier to construct an adaptive noise floor, which is the minimum price deviation required to confirm a trend signal: noise_floor = ta.sma(math.abs(raw_diff), sensitivity) * noise_mult The trend state is then determined by comparing raw deviation against this noise floor, with a decay mechanism applied when price re-enters the neutral zone to avoid abrupt reversals: if raw_diff > noise_floor trend_state := 1 locked_val := raw_diff else if raw_diff < -noise_floor trend_state := -1 locked_val := raw_diff else locked_val := locked_val * 0.9 The locked deviation value is then normalized by ATR to make the oscillator comparable across instruments and volatility regimes, and smoothed with a short WMA to reduce micro-fluctuations in the final output: normalized_val = locked_val / ta.atr(sensitivity) final_osc = ta.wma(normalized_val, 5) This creates a robust momentum oscillator that only registers trend conditions when price makes structurally significant moves beyond typical noise, while the ATR normalization ensures readings remain meaningful and consistent regardless of the underlying instrument's price scale or volatility level. 🟢 Signal Interpretation ▶ Bullish Trend (Oscillator Rising Above Zero with Bullish Color): When price deviation breaks above the positive noise floor, the oscillator enters bullish mode with green/bullish coloring across all visual elements = Confirmed upward momentum signal for trend-following long positions. The trend remains bullish until price deviation falls below the negative noise floor, allowing traders to stay positioned through normal consolidations without premature exits on minor pullbacks that remain within the noise boundary. ▶ Bearish Trend (Oscillator Falling Below Zero with Bearish Color): When price deviation breaks below the negative noise floor, the oscillator enters bearish mode with red/bearish coloring across all visual elements = Confirmed downward momentum signal for short positions or long exit signals. The trend remains bearish until deviation exceeds the positive noise floor, enabling traders to maintain directional bias through corrective bounces that stay within the threshold boundaries. 🟢 Features ▶ Preconfigured Presets: Three optimized parameter sets tailored for different trading styles and timeframes. "Default" delivers balanced trend detection for swing trading on 4-hour and daily charts, filtering minor noise while remaining responsive to meaningful momentum shifts. "Fast Response" uses a reactive EMA baseline with a tighter noise floor for intraday and scalping timeframes, generating earlier signals suited to active traders on 5-minute to 1-hour charts. "Smooth Trend" applies a smooth, lag-reduced HMA baseline with a demanding noise threshold for position trading on daily and weekly charts, confirming only major directional shifts with minimal false positives. ▶ Built-in Alerts: Three alert conditions enable automated monitoring of trend transitions without constant chart observation. "Bullish Trend Signal" triggers when the oscillator first enters a confirmed bullish state, alerting for potential long entries. "Bearish Trend Signal" activates when the oscillator first enters a confirmed bearish state, signaling potential short entries or long exits. "Trend Direction Changed" provides a combined alert for any trend transition regardless of direction, allowing traders to monitor both bullish and bearish opportunities through a single alert setup. ▶ Visual Customization: Six color presets (Classic, Aqua, Cosmic, Cyber, Neon, plus Custom) accommodate different chart themes and aesthetic preferences, with coordinated bullish and bearish color schemes applied consistently across all indicator elements. A layered luminance fill system creates graduated visual depth around the main oscillator line using four fill zones at progressively increasing transparency, making trend strength and direction immediately readable at a glance. Optional bar coloring tints price bars with the active trend color during confirmed bullish and bearish periods, providing instant overhead visual confirmation of trend state without requiring direct reference to the oscillator panel below.
مؤشر Pine Script®
من ‎QuantAlgo‎
4
Supreme BUY/SELL Signal Indicator By Chaitu50cSupreme Buy/Sell Signals Indicator By Chaitu50c Overview The Supreme Buy/Sell Signals Indicator is a structured price-action based breakout system designed to detect strong consecutive momentum moves within the same trading session. The indicator focuses on clean candle structure and breakout confirmation rather than oscillators or lagging calculations. It is built to identify continuation strength after two consecutive candles in the same direction, followed by a confirmed breakout beyond the previous candle’s extreme. The logic is simple, rule-based, and non-repainting because signals are confirmed only after candle close. This tool is ideal for intraday traders who prefer structure-based entries and want clear, controlled signal behavior without noise. Core Signal Logic The indicator detects bullish signals when two consecutive bullish candles form and the current candle closes above the previous candle’s high. This confirms bullish continuation strength and prints a Buy signal. Similarly, a bearish signal is generated when two consecutive bearish candles form and the current candle closes below the previous candle’s low, confirming downside continuation strength. Signals are only generated after the candle closes, ensuring no repainting during live bars. Additionally, signals are restricted within the same trading day. At the start of a new session, the internal state resets to prevent carryover signals from the previous day. Single Signal Mode The “Single Signal Until Opposite Forms” option controls whether the indicator allows consecutive signals in the same direction. When enabled, once a Buy signal is generated, no additional Buy signals will appear until a valid Sell signal forms. This prevents repetitive entries in strong trends and keeps the chart clean. When disabled, the indicator will generate every valid breakout signal, even if multiple signals occur in the same direction. This setting is particularly useful for traders who prefer one clean setup per move rather than multiple re-entries. Body Breakout Unlock Mode The “Require Body Breakout to Unlock” option introduces a structured reset mechanism. After a signal is generated, the direction becomes temporarily locked. A new signal of the same direction cannot form unless price proves invalidation by closing its body beyond the extreme of the previous signal candle. For example, after a Buy signal, if a bearish candle closes below the low of the signal candle, the system unlocks. Only then can another Buy signal form later. This ensures that repeated signals only occur after meaningful structural invalidation. If disabled, signals can occur again without requiring this structural reset. This mode is designed to improve discipline and reduce signal clustering. Stop Loss Line Logic When enabled, the indicator automatically draws a dynamic Stop Loss line at the extreme of the signal candle. For Buy signals, the stop loss is placed at the signal candle’s low. For Sell signals, it is placed at the signal candle’s high. The Stop Loss line extends forward bar by bar until a candle closes beyond it. Once price closes past the stop level, the line stops extending, indicating that the stop has been hit. Users can customize the stop loss line’s color, style (solid, dashed, dotted), and width. This feature helps traders visually track trade risk and understand when a setup becomes invalid. Display Options The “Show Buy/Sell Signals” toggle controls whether Buy and Sell labels appear on the chart. These labels can be customized in color for both bullish and bearish signals, as well as text color for better chart visibility. The “Show Bar Colors” option highlights the signal candle itself using user-defined bullish or bearish paint colors. This visually emphasizes the exact breakout candle responsible for the signal. Both display options are fully optional and allow traders to keep the chart either minimal or visually descriptive. Session Behavior The indicator resets automatically at the beginning of each new trading day. This ensures that signals, locks, and stop loss tracking do not carry over into the next session. The logic is designed specifically for intraday use where daily session separation is important. Alerts Built-in alert conditions are included for both Buy and Sell signals. Traders can create TradingView alerts directly from the indicator to receive notifications whenever a valid consecutive breakout occurs. Practical Use Cases This indicator is particularly effective in trending intraday environments where momentum continuation setups perform well. It can be used for breakout trading, pullback continuation entries, and structured momentum strategies. Traders may combine it with higher timeframe bias, support and resistance levels, or volume confirmation to filter trades further. It works especially well when aligned with broader market structure. Testing & Optimization This indicator has been personally tested on the NIFTY chart using the 5-minute timeframe. The logic performed effectively in capturing structured intraday continuation moves within active market sessions. However, traders are encouraged to test and optimize it according to their own strategy and risk management rules before live deployment.
مؤشر Pine Script®
من ‎chaitu50c‎
4
Trend Freeway MTF | ProjectSyndicateTrend Freeway MTF provides a complete multi-timeframe market overview in a single, clean panel. It visualizes trend and momentum confluence across 5 user-defined timeframes by simultaneously tracking Supertrend, RSI, and MACD status. This eliminates the need to switch between charts, providing an instant, high-conviction view of whether the market is aligned for a strong move or is consolidating with conflicting signals. • 🚦 15-Lane Confluence Panel — each of the 5 timeframe groups is split into 3 sub-lanes SUPER, RSI, MACD, giving you a 15-point real-time market audit. • 🧠 Triple-Indicator Logic — cross-validates a trend-following indicator Supertrend, a momentum oscillator RSI, and a trend/momentum hybrid MACD for robust signal filtering. • 🔭 Full Multi-Timeframe Support — instantly see the bigger picture by monitoring 5 timeframes at once defaults: M5, M15, M30, H1, H4, all fully configurable to any TF. • 📊 Master Trend Signal Header — a dynamic header at the top of the panel scores all 15 lanes and displays the master signal BUY, STRONG BUY, SUPER STRONG BUY with a color-coded background for an immediate, top-down market bias reading. • 🎨 Clear Visual Hierarchy — uses a distinct, high-contrast color scheme dark teal for bull, dark crimson for bear, near-black for neutral so you can assess market alignment in a fraction of a second. • 🔔 Comprehensive Alerts — get notified when a specific signal strength is reached e.g., STRONG BUY or when all 15 lanes achieve full bullish or bearish confluence, ensuring you never miss a major market shift. • ✅ RSI Neutral Zone Filter — the RSI lane turns a neutral color when momentum is weak between 40-60 by default, effectively filtering out choppy, low-probability conditions. • 🔧 Fully Customizable — control everything from the 5 timeframes and all indicator settings ATR, RSI, MACD to the colors, lane widths, and table position. • 🎯 Why this algo is unique: Standard indicators only give you one piece of the puzzle on a single timeframe. This algorithm forces three independent concepts—trend, momentum, and relative strength—to agree across five separate timeframes. It doesn't just show you a signal; it shows you the quality of the signal. When all 15 lanes light up with the same color, you are looking at institutional-grade trend alignment. When colors are mixed, it instantly warns you to stay out. • 🚀 Apply to Gold (XAUUSD), Forex (EURUSD, GBPJPY), Crypto (BTCUSD, ETHUSD), and Indices (NASDAQ/NQ, S&P500/ES) on any timeframe. The fully configurable indicator settings allow it to adapt to anything from scalping to swing trading. • 🎯 How to use this? Focus on trading opportunities when you see full alignment all 3 sub-lanes are the same color on your primary trading timeframe. For the highest-probability setups, wait for the Master Trend Signal to show STRONG or SUPER STRONG status, indicating that the majority of all 15 lanes are in agreement. Use moments of conflicting colors as a clear signal to stay out of the market and avoid chop. • ⚠️ IMPORTANT NOTICE: This indicator is a powerful decision-support tool designed to provide a high-level overview of market confluence. It should NOT be used as a standalone signal for entering or exiting trades. Always use it in conjunction with your own trading strategy, price action analysis, and proper risk management to confirm trade setups.
مؤشر Pine Script®
من ‎ProjectSyndicate‎
2
Adaptive Entropy Trend [QuantAlgo]🟢 Overview Adaptive Entropy Trend is a trend-following indicator built on Shannon information theory rather than conventional price averaging. It quantifies the statistical disorder of recent log returns to determine whether the market is in a directional regime or a random one, then feeds this entropy reading into every layer of the system simultaneously, helping traders identify directional shifts that are validated by both low-entropy momentum conditions and genuine volatility expansion across different timeframes and markets. 🟢 How It Works The foundation of the indicator is a per-bar entropy calculation built from the distribution of log returns over the lookback window. Log returns are computed and their range is divided into equal-width histogram bins: logReturn = math.log(close / close ) minReturn = ta.lowest(logReturn, lookbackLen) maxReturn = ta.highest(logReturn, lookbackLen) returnRange = maxReturn - minReturn Each historical return within the lookback is assigned to a bin, building a frequency distribution. Shannon entropy is then calculated from the probability of each bin, measuring how uniformly returns are spread across the range: probability = array.get(binCounts, i) / lookbackLen if probability > 0 entropy := entropy - probability * math.log(probability) / math.log(2) A uniform distribution produces maximum entropy, reflecting a chaotic, non-directional market. A concentrated distribution produces low entropy, reflecting a market where returns are clustering in a consistent direction. The raw entropy is normalized against the theoretical maximum for the bin count to produce a stable 0-1 score: normalizedEntropy = maxEntropy > 0 ? entropy / maxEntropy : 0.5 This score is then wired directly into the EMA smoothing factor. Higher entropy lengthens the effective period of the EMA, insulating it from noise. Lower entropy shortens it, allowing the EMA to track price closely during genuine trends: adaptiveAlpha = 2.0 / (lookbackLen * (0.3 + normalizedEntropy * 1.4) + 1.0) adaptiveEma := na(adaptiveEma) ? close : adaptiveEma + adaptiveAlpha * (close - adaptiveEma) The same entropy reading drives band width through an inverted trend strength factor. Unlike volatility-based bands that widen during noise, these bands widen specifically during trending conditions and tighten during choppy ones: trendStrength = 1.0 - normalizedEntropy fastBandWidth = atr * fastMultiplier * (0.5 + trendStrength) slowBandWidth = atr * slowMultiplier * (0.5 + trendStrength) Finally, trend state is determined when price breaks beyond the inner bands, and transitions are tracked for alert conditions: if close > innerUpper trendDirection := 1 else if close < innerLower trendDirection := -1 trendTurnedBullish = trendDirection == 1 and trendDirection != 1 trendTurnedBearish = trendDirection == -1 and trendDirection != -1 This creates a self-regulating trend system where the EMA baseline, the trigger threshold, and the visual envelope all adapt together from the same entropy source, rather than using a fixed center with adaptive edges or vice versa. 🟢 Signal Interpretation ▶ Bullish Trend (Price Above Inner Upper Band, Green): When price closes above the inner upper band, the indicator switches to bullish mode with bullish coloring across all visual elements = Confirmed uptrend signal for trend-following long positions. Because the inner band expands in low-entropy trending conditions, a bullish confirmation in a genuinely directional market requires a more meaningful breakout than in a noisy one. The trend remains bullish until price breaks below the inner lower band, allowing traders to stay positioned through normal pullbacks that remain within the band range. ▶ Bearish Trend (Price Below Inner Lower Band, Red): When price closes below the inner lower band, the indicator switches to bearish mode with bearish coloring throughout all visual elements = Confirmed downtrend signal for short positions or long exit signals. The adaptive band floor ensures the trigger threshold in choppy, high-entropy markets is tighter, reducing the risk of false breakdowns on thin directional moves. The trend remains bearish until price breaks above the inner upper band. ▶ Neutral Zone (Price Between Inner Bands): When price trades between the inner upper and lower bands, the indicator holds its previous trend direction = Continuation of existing trend during consolidation or normal volatility retracements. This prevents whipsaws during sideways action by requiring price to make a statistically meaningful move beyond the entropy-scaled band boundaries rather than reacting to minor crosses of the adaptive EMA centerline. 🟢 Features ▶ Preconfigured Presets: Three optimized parameter sets for different trading approaches and timeframes. "Default" provides balanced trend detection for swing trading on 4-hour and daily charts, "Fast Response" delivers quicker trend signals for intraday trading on 1-minute to 1-hour charts, and "Smooth Trend" focuses on major trend changes for position trading on daily to weekly timeframes. ▶ Built-in Alerts: Three alert conditions enable automated monitoring of trend changes without constant chart watching. "Bullish Trend Signal" triggers when the indicator switches to bullish mode after price breaks above the inner upper band, alerting for potential long entries. "Bearish Trend Signal" activates when the indicator switches to bearish mode after price breaks below the inner lower band, signaling potential short entries or long exits. "Trend Direction Changed" provides a combined alert for any trend transition regardless of direction, allowing traders to monitor both bullish and bearish opportunities with a single alert setup. ▶ Visual Customization: Six color presets (Classic, Aqua, Cosmic, Cyber, Neon, plus Custom) accommodate different chart backgrounds and aesthetic preferences, with coordinated bullish, bearish, and neutral color schemes applied across all indicator elements. Inner and outer band fills create a two-layer gradient envelope around the adaptive EMA, with the inner zone between the two bands rendered slightly more transparent than the outer zone to preserve natural depth, both controlled by a single fill transparency input (0-100%) so the visual weight of the envelope can be adjusted without disrupting the gradient relationship. Optional bar coloring tints price bars with trend-appropriate colors during bullish and bearish periods, enabling instant visual confirmation of trend state across multiple timeframes without switching between chart and indicator panels.
مؤشر Pine Script®
من ‎QuantAlgo‎
2