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SwingScan ProSwingScan Pro is a swing trade momentum scorer that rates each bar 0–100 across five factors: 1. Momentum — size of today's price move 2. Volume Surge — today's volume vs 10-bar average 3. Trend Position — where close sits in the day's range (penalises chasing) 4. Candle Quality — body/range ratio (conviction of the move) 5. R/R Setup — workability of the stop distance Signals fire when a stock scores above the minimum threshold (default 60). High confidence signals require a score of 80+. Each signal includes: - Entry zone - Stop loss (below day low) - Target 1 (2:1 R/R) - Target 2 (4:1 R/R) - Time estimate (1-3 days / 1-3 weeks / 3-8 weeks) Designed for daily timeframe swing trading. Use with PulseWire Screener to scan across S&P 500 or NASDAQ for real-time setups.
Indicator
by samals0818
369 Vector Equilibrium [DAFE]369 Vector Equilibrium Overview 369 Vector Equilibrium (369‑VE) is a geometric probability framework that evaluates market state through angular vector dynamics, pitchfork equilibrium structure, resonance clustering, and memory‑weighted outcome statistics. It combines four orthogonal structural factors: • 369 Angular Resonance • Gann Angle Alignment • Harmonic Pitchfork Proximity • Bubble Pressure Dynamics These factors are blended using Bayesian weighting and optionally refined by a memory‑based K‑Nearest‑Neighbor engine. The model does not predict price levels. It estimates structural alignment probability under current geometric conditions. 1. Vector Geometry Core The engine computes a directional vector from: • EMA‑based displacement • ATR‑normalized momentum • Rotational offset (Base Angle) Vector angle is normalized to 0–360° and compared against: • 369 angular divisions • User‑defined Gann spokes 369 resonance checks whether the current angle falls within harmonic bins spaced across the circle. Gann alignment measures angular proximity to evenly spaced spokes. Both are continuous confidence measures, not binary triggers. 2. Equilibrium Bubble Model The equilibrium midline is defined via EMA smoothing. Bubble width expands and contracts based on entropy and ATR: • Low entropy → compressed field • High entropy → expanded field Bubble pressure is calculated as normalized displacement relative to bubble width. This captures expansion and compression dynamics. 3. Harmonic Pitchfork Engine Three Fibonacci‑length sine‑weighted moving averages (A, B, C) construct dynamic pitchfork structures. Each pitchfork includes: • Median line • Upper / lower deviation bands Distance from price to the nearest fork line (ATR‑scaled) generates pitchfork proximity confidence. Pitchfork scoring reflects structural mean‑reversion or breakout context. 4. WPK Regime Engine (Hurst Modulation) A Hurst exponent (Rescaled Range method) classifies regime: • H > Trend Threshold → Persistent (Trending) • H < Mean‑Revert Threshold → Anti‑Persistent (Reverting) • Otherwise → Neutral Regime shifts dynamically adjust the blend between: • Real‑time probability • Memory‑based probability This prevents overfitting to historical memory during strong trends and prevents overreaction during range compression. 5. Footprint Delta Integration (Optional) When enabled: • request.footprint() delta • Value Area % • Tick aggregation are incorporated as a sixth dimension in the memory vector. If footprint data is unavailable, a Wick‑Pressure Kernel (WPK) approximation substitutes delta behavior. The engine automatically detects availability and degrades gracefully. 6. Bayesian Confluence Model Final composite confidence is: confRT = w₁·369 + w₂·Gann + w₃·Pitch + w₄·Pressure User‑defined weights control each factor’s influence. Signal gating requires: • Minimum composite confidence • Minimum dominant probability • Minimum number of active factors Dynamic penalties apply in unstable regimes (angle thrashing + low Hurst). 7. Memory KNN Engine The memory system stores past feature vectors: • 369 factor • Gann factor • Pitchfork factor • Pressure factor • Directional bias • Footprint delta Each stored state includes its forward outcome over a defined horizon. At runtime: • Lorentzian similarity measures current state vs historical states • Top‑K neighbors vote • Age‑fade weighting prevents stale bias Final probability is a blend between real‑time geometric alignment and memory‑weighted outcome probability. 8. Heatmap Engine A sparse 2D grid (Angle × Pressure bins) tracks historical confluence density. Each cell accumulates decayed weight and directional bias. The grid provides: • Localized structural probability bias • Strength of prior similar conditions Heatmap is optional for performance considerations. Signal Logic A signal requires: • Sufficient composite confluence • Probability dominance • Active factor count • Cooldown clearance Signal tiers are defined: • Tier 1 – Base • Tier 2 – Strong • Tier 3 – Elite Tier thresholds are adjustable. Important Behavior Notes Some parameters do not produce immediate visual changes because they affect: • Memory accumulation (requires horizon completion) • Heatmap decay (gradual state change) • Hurst regime estimation (requires full lookback window) • KNN similarity weighting (requires sufficient stored states) These are stateful systems and require time to adapt. All parameters are active — some influence probability blending rather than immediate drawing logic. Visual Components • Multi‑ring equilibrium bubble • Gann angular rays (optional) • Fibonacci pitchforks • Probability ribbons • Heatmap grid (optional) • Professional dashboard with regime, memory, and confluence diagnostics Important Notes • Footprint features require supported exchange data. • KNN memory requires sufficient historical bars to stabilize. • No slippage or execution modeling is included. • This script does not guarantee future performance. Past performance does not guarantee future results. — Dskyz, Trade with insight. Trade with anticipation. (Keep Trying)
Indicator
by DskyzInvestments
Regime-Adaptive kNN Breakouts + Kalman Predictor [TechnicalZen]Regime-Adaptive kNN Breakout Classifier + Kalman Price Predictor Why This Indicator Exists Most breakout indicators treat every compression pattern equally. In reality, a volatility contraction forming during a high-ADX trending environment with surging volume behaves very differently from the same pattern in a choppy, low-volume consolidation. This indicator addresses that gap by combining three distinct analytical engines: Multi-Period Compression Detection — Scans across multiple bar periods to find the tightest range relative to recent history, identifying genuine volatility contraction zones where expansion is statistically likely. Regime-Adaptive kNN Classification — A machine learning gate that evaluates the market regime surrounding each compression zone using Kalman-filtered features. Only setups with sufficient similarity to historically successful breakouts are allowed through. Kalman Price Predictor — A state-space estimator tracking price position and velocity, enabling forward projection with a widening uncertainty cone. The result is an indicator that learns which market conditions produce successful breakouts and provides a probabilistic price forecast — not just pattern detection. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ HOW IT WORKS 1. Multi-Period Compression Detection The engine evaluates bar ranges across 2 to 20 periods, computing each period's range (highest high minus lowest low) and comparing it against the minimum range observed within an adaptive lookback window. When the current range is tighter than any historical range in the window, a compression zone is identified. The smallest qualifying period is selected — representing the most extreme volatility contraction. An optional Inside Bar filter adds a complementary signal when the current bar's range is entirely contained within the prior bar. 2. ADX-Adaptive Lookback Window The comparison window dynamically adjusts based on trend strength: High ADX (strong trend) — shorter lookback, more responsive to compression during momentum phases Low ADX (ranging market) — longer lookback, requiring more extreme contraction before triggering This prevents the indicator from being too sensitive in trending markets or too sluggish in ranging conditions. 3. Kalman-Filtered Feature Space Four market regime features are computed on every bar and smoothed through independent Kalman filters using a position + velocity state-space model. The Kalman filter reduces noise while tracking each feature's rate of change — achieving smoothing without the lag penalty of traditional moving averages. The kNN classifier operates entirely on these Kalman-filtered features: Relative Volume — Volume / SMA(Volume, 100) — captures participation surge or drought, Kalman-smoothed to filter out single-bar volume spikes Relative ATR — ATR(14) / SMA(ATR, 100) — captures volatility expansion vs contraction regime, Kalman-smoothed for stable regime identification ADX Normalized — ADX / 50 — measures trend strength (direction-agnostic), Kalman-smoothed to track trend momentum Distance from MA — (Close - Trend MA) / ATR — price position relative to trend, Kalman-smoothed to reduce whipsaw noise By filtering the feature space through the Kalman estimator before classification, the kNN operates on cleaner, denoised regime signals rather than raw noisy measurements. This is the critical link between the Kalman filter and the kNN — the classifier's accuracy depends on the quality of its input features. 4. kNN Breakout Classification When a compression zone triggers a breakout, the classifier: Constructs a feature vector from the four Kalman-filtered regime features Scans the history buffer using Manhattan distance to find similar past regime conditions Selects the k-nearest resolved neighbors — only TP (take-profit) and SL (stop-loss) outcomes vote; pending and time exits are excluded entirely Computes a distance-weighted classification score where closer neighbors have proportionally more influence Compares the score against the user-defined confidence threshold If the score falls below the threshold, the setup is silently skipped. The classifier has learned which combinations of volume regime, volatility regime, trend strength, and price position tend to produce winning breakouts. Key design choices: Adaptive k — k = floor(sqrt(resolved outcomes)), clamped between user-defined min/max. The number of neighbors consulted grows naturally as the classifier accumulates experience, preventing overfitting to sparse early data. Warmup phase — During the first N resolved outcomes, all setups pass through to build the training set. The classifier only begins filtering after accumulating sufficient data. Feedback loop — Every exit writes its outcome back to the history buffer. TP exits score 1.0, SL exits score 0.0. The classifier genuinely learns from the specific chart and timeframe it is applied to. Distance-weighted voting — Prevents outlier neighbors from distorting the classification. A very close TP neighbor outweighs several distant SL neighbors, producing more nuanced probability estimates. 5. Kalman Price Predictor A fifth Kalman filter runs on price itself, maintaining three estimates simultaneously: Filtered position — optimal smoothed price estimate Velocity — estimated rate of price change per bar Covariance matrix — estimation uncertainty and cross-correlations The velocity component enables forward projection: Predicted Price = Filtered Position + Velocity x Projection Bars . The uncertainty cone is scaled by ATR and widens proportionally to the square root of the projection horizon — reflecting the theoretical uncertainty growth of price over time. Projection trail: The last 5 projections are displayed with graduated transparency (50% to 90%), creating a visual history of how the forecast has evolved. A consistent, parallel trail suggests strong directional conviction; a diverging or oscillating trail signals uncertainty. 6. Trend-Aware Exit System The exit system uses four complementary mechanisms, each feeding outcomes back to the kNN: Take Profit — R-multiple target (default 2R, where R = compression zone range). Scored as 1.0 in kNN feedback. Stop Loss — Opposite side of compression zone, optionally requiring price to also be wrong-side of the Trend MA. This trend-aware condition reduces whipsaw stops in strong trends. Scored as 0.0 in kNN feedback. Trailing Stop — Activates after 1R profit, trails by ATR x multiplier. Dynamic protection that locks in gains. Time Exit — Maximum bars in trade before forced exit. Scored as 0.5 (neutral) — neither rewarding nor penalizing the kNN for inconclusive setups. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ VISUAL GUIDE Chart Elements Compression boxes — Colored zones marking detected volatility contraction (green = bullish breakout, red = bearish) Extended levels — Dotted lines projecting the high and low of each compression zone forward Entry labels — Direction and kNN confidence percentage (e.g., "Long 72.5%") Exit labels — TP / SL / T markers with R-multiple detail in tooltip Projection line — Dashed line extending forward from Kalman-filtered price Uncertainty cone — ATR-scaled filled area widening into the future Projection trail — 5 fading historical projections showing forecast evolution Kalman price line — Optional smoothed price curve (off by default) Dashboard (bottom-right) Win Rate — Percentage of resolved trades hitting TP (tinted green or red) Trades — Win / Loss count Mode — Distance-weighted classification Phase — Warmup (building data) or Active (filtering enabled) k — Current adaptive k value Score — Latest kNN confidence score History — Buffer fill level (e.g., 45/60) Projection — Predicted price with directional arrow ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SETTINGS GUIDE Detection Enable Inside Bar (default: On) — Include Inside Bar patterns alongside compression detection Adaptive kNN Enable kNN Filter (default: On) — Toggle the ML classification gate k Min / k Max (default: 2 / 10) — Bounds for adaptive k. Auto-scales with sqrt of resolved outcomes Confidence Threshold (default: 0.25) — Minimum kNN score to accept a setup. Lower values are more permissive; higher values are more selective Min Resolved to Activate (default: 15) — TP/SL outcomes needed before the classifier begins filtering History Buffer Size (default: 60) — Maximum stored breakout patterns for comparison Kalman Filter Process Noise Q (default: 0.01) — Controls how much the filter expects the underlying signal to change between bars. Higher values make the filter more responsive but noisier Measurement Noise R (default: 0.10) — Controls how much the filter distrusts each new measurement. Higher values produce smoother output with more lag Show Price Projection (default: On) — Display the forward projection line and uncertainty cone Projection Bars (default: 10) — How far forward to project price Projection Color (default: Aqua) — Color for all projection elements Show Uncertainty Cone (default: On) — Display the ATR-scaled confidence band Cone Width (default: 1.0 ATR) — Width multiplier for the uncertainty cone. Adjustable per instrument Show Kalman Price Line (default: Off) — Display the smoothed Kalman price estimate on chart Trend Filter Enable Trend Filter (default: On) — Restrict breakouts to trend-aligned direction only Trend MA Mode (default: Adaptive) — Static = fixed MA length; Adaptive = MA length scales dynamically with the compression lookback MA Type (default: EMA) — Exponential or Wilder's (RMA) moving average Adaptive Multiplier (default: 2.0) — Lookback x Multiplier = MA length in adaptive mode Static MA Length (default: 200) — Fixed MA length when in static mode Adaptive Look Back Look Back Mode (default: ADX Adaptive) — Static = fixed comparison window; ADX Adaptive = window scales with trend strength ADX Length (default: 14) — Period for ADX calculation ADX Low / High (default: 10 / 35) — ADX range mapped to lookback bounds. Higher ADX compresses the lookback LB Min / LB Max (default: 20 / 120) — Minimum and maximum lookback window size Exits TP (R-multiple target) (default: On) — Take-profit at R-multiple of compression zone range SL (opposite side) (default: On) — Stop-loss at opposite boundary of compression zone Target R (default: 2.0) — Take-profit distance as multiple of range Trend-Aware SL (default: On) — SL only triggers when price is also wrong-side of Trend MA Trailing Stop (default: On) — Trails by ATR x multiplier after 1R profit Trail ATR Multiplier (default: 1.5) — Trail distance = ATR(14) x this value Time Exit (default: On, 50 bars) — Force exit after maximum bars in trade Visual Settings Bull / Bear / Time colors — Customizable directional colors Box Fill / Border Transparency — Compression zone box appearance Extend Levels (default: 50 bars) — Forward projection distance for compression zone levels Level Width / Style — Line appearance for projected levels Max Patterns Kept (default: 120) — Maximum drawing objects maintained on chart ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ THE KALMAN-kNN PIPELINE The two ML components are not independent — they form a pipeline: Kalman filters denoise the four regime features on every bar, producing clean estimates of volume regime, volatility regime, trend strength, and price position kNN classifier operates on these Kalman-filtered features, comparing the current denoised regime against historically successful and unsuccessful breakout conditions Kalman price filter independently tracks price dynamics, projecting the estimated trajectory forward with quantified uncertainty The classifier's accuracy fundamentally depends on the quality of its input features. By feeding Kalman-filtered signals rather than raw measurements, the kNN compares regime states rather than noisy observations — producing more stable and meaningful similarity assessments. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ CREDITS AND ACKNOWLEDGMENTS This indicator builds upon concepts from two published works: Smart NR2–NR20 and Inside Bar by Zeiierman — multi-period compression detection, adaptive lookback via ADX, and breakout trigger architecture kNN Market Architecture by LuxAlgo — application of k-nearest neighbors classification to filter market signals using relative volatility and volume features Original contributions in this indicator: Kalman filter state-space estimation for feature smoothing (position + velocity model with full covariance tracking) Kalman-to-kNN pipeline — classifier operates on denoised regime features, not raw measurements Regime-adaptive kNN classification with distance-weighted voting on resolved outcomes only Real-time feedback loop where exit outcomes update the kNN training data Adaptive k scaling based on accumulated classifier experience Kalman price predictor with forward projection and ATR-scaled uncertainty cone Graduated projection trail showing forecast evolution ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ This indicator is for educational and informational purposes only. It does not constitute financial advice. All investments involve risk, and past performance does not guarantee future results. The kNN classifier learns from historical patterns on the specific chart and timeframe it is applied to — its effectiveness may vary across different instruments and market conditions. Always conduct your own analysis and risk management.
Indicator
by TechnicalZen
Absorption Structure Detector v2.3Absorption Structure Detector v2.3 A price-action based tool designed to identify absorption candles at key structural levels, helping traders spot potential reversals and continuation points with clarity and discipline. Overview The Absorption Structure Detector highlights candles where strong opposing pressure is absorbed by market participants, often signalling a shift in control between buyers and sellers. Rather than relying on lagging indicators, this tool focuses on pure price behaviour, combining wick structure, candle positioning, and contextual filters to identify high-probability zones. Core Logic The indicator detects absorption based on: Dominant wick structure (rejection of price) Controlled candle body size (inefficiency / absorption) Strong closing position (shift in control) Optional liquidity sweep detection (false breakouts) Optional trend filter (EMA) Optional pivot proximity filter (structure alignment) Optional RSI divergence filter (momentum confirmation) A built-in quality scoring system (1–5) ensures that only higher-confluence setups are considered when desired. How to Use This indicator is designed for higher timeframe trading, particularly: Daily (primary) 4H (secondary confirmation) Bullish Setup Price reaches a key support level Bullish absorption candle forms Enter on break of the candle high Stop below the candle low Target 2:1 or next structure level Bearish Setup Price reaches resistance Bearish absorption candle forms Enter on break of the candle low Stop above the candle high Target 2:1 or next structure level Key Features Clean visual identification of absorption candles Built-in trend alignment filter (EMA) Liquidity sweep detection for false breakout scenarios Pivot-based structure filtering Adjustable quality threshold to reduce noise Optional entry, stop, and 2R target plotting Alert conditions for bullish and bearish setups Important Notes This tool performs best when used at key structural levels It is not designed for low timeframe scalping Signals should be used with context and discipline, not in isolation Fewer, higher-quality setups are preferred over frequent trading Philosophy The Absorption Structure Detector is built around a simple idea: Markets turn when pressure is absorbed and control shifts. This tool helps visualise those moments — the rest is execution and discipline. Final Thought This is not a “signal generator” to follow blindly. It is a decision support tool designed to improve timing and clarity within a structured trading plan.
Indicator
by jbsquirrell
Esco Theory v4Esco Theory maps the hidden geometry of price action. It identifies swing structure, plots geometric rails between pivots, detects supply and demand zones, fair value gaps, liquidity pools, compression patterns, and confluence clusters. All signals are synthesized into a real-time dashboard so traders can read market structure and volatility conditions at a glance. Built for traders who study displacement, structure shifts, and the expansion–compression cycles that drive price. Features Market Structure (BOS / MSS) Automatically detects Break of Structure (BOS) and Market Structure Shifts (MSS) using configurable swing lookback. Bullish and bearish shifts are labeled directly on the chart with color-coded markers. Displacement candles (body greater than 1.5× ATR) are highlighted to confirm impulsive moves. Geometric Rails Trendlines (“rails”) are drawn between consecutive swing highs and swing lows and extended forward. Two tiers are available: Minor Rails Short-term pivots for intraday and swing geometry. Major Cycle Rails Higher-timeframe pivots that reveal broader structural channels. Cross-rails connect swing highs to swing lows using dotted diagonals, revealing convergence and divergence patterns. Cycle Fan A fan of rays projects from the deepest major swing low through each major swing high (and vice versa), mapping the angular geometry of the current market cycle. These angles often highlight reaction zones where time and price intersect. Supply & Demand Zones Zones are created at pivot candles confirmed by displacement on the following bar. Each zone tracks retests and gradually fades in transparency as it is touched. Mitigated zones are automatically removed to keep charts clean. Fair Value Gaps (FVG) & Inverted FVGs Three-candle imbalance gaps are detected and drawn as shaded boxes. When a gap fills to its midpoint it converts into an inverted FVG, which can act as a continuation or re-entry zone. Both gap types have independent color settings and optional auto-expiration. Premium / Discount Zones Using the most recent major swing high and low, price is divided into: Premium (upper 25%) Discount (lower 25%) Equilibrium (midpoint) A dotted equilibrium line marks fair value and helps filter entries. Support & Resistance Clustering All pivot prices are grouped by proximity. Levels with multiple touches are drawn as dashed horizontal lines labeled with touch count: S (3) R (4) Stronger clusters appear as thicker lines. Confluence Zones When three or more levels from different sources cluster together (pivots, S/R levels, supply and demand), a shaded confluence zone is drawn. These areas often produce the strongest market reactions. Liquidity — Equal Highs / Equal Lows Swing highs and lows within a defined tolerance are identified as EQH and EQL liquidity pools. These levels extend forward and often attract price before reversals or breakouts. Liquidity Sweeps When price wicks through an equal high or low and closes back inside the level, a sweep marker (✕) appears. Sweeps often signal liquidity grabs before reversals. Compression & Squeeze Detection Two compression signals identify volatility contraction. ATR Compression Occurs when fast ATR drops below 60% of slow ATR. Bollinger / Keltner Squeeze When Bollinger Bands contract inside Keltner Channels. When the squeeze releases, a triangle marker signals expansion. A wedge overlay connects compression pivots to visualize tightening ranges. Real-Time Dashboard A compact panel displays current market conditions. Bias Current structure trend (Bullish / Bearish / Neutral) Zone Premium, Discount, or Equilibrium Volatility Squeeze, Compression, or Expansion ATR Ratio Fast ATR vs Slow ATR BBW Bollinger Band Width percentage Wedge Active compression wedge detection FVG Active gap count Sweeps Recent liquidity sweep count Inputs & Customization Every module can be toggled independently. Key settings include: Swing Lookback (minor and major) Rail Extension length Max Cross-Rails Supply / Demand Pivot Length FVG Minimum Size and Max Age Support / Resistance Tolerance and Minimum Touches Confluence Width and Minimum Levels Equal High / Low Tolerance All colors are fully customizable. How to Use Identify bias Check the dashboard for current structure direction and premium/discount location. Find confluence Look for areas where rails, zones, gaps, and support/resistance overlap. Watch compression Squeeze diamonds and wedges signal volatility building. Trade displacement Highlighted candles confirm impulsive moves through key levels. Monitor liquidity sweeps EQH/EQL sweeps often precede reversals or expansions. Notes Overlay indicator designed for use directly on price charts. Compatible with all markets and timeframes. Lower timeframes with large bar counts may increase drawing load. Adjust lookback settings if needed. Best used alongside discretionary price action and market context.
Indicator
by escobrypto
A++ Signals [Scalping-Algo]This indicator is a high-probability trend-following system designed for scalping and intraday trading (3M, 5M, 15M). It combines volatility-based signals with institutional trend filters to maintain a high winrate. 1. How to Enter a Trade Long Entry: Wait for the green "Long" bubble. Price must be above both the Gold VWAP and the Blue EMA 13. Short Entry: Wait for the red "Short" bubble. Price must be below both the Gold VWAP and the Blue EMA 13. Trend Filter: Ensure the price is trading in the direction of the EMA 200 (thin gray line) for the highest probability of success. 2. Managing the Trade (TP/SL) Once a signal appears, the indicator draws two dynamic boxes: Green Zone (TP): Your target area. The trade is a "Win" when price hits the top of this box (marked by a purple "Long TP" bubble). Red Zone (SL): Your protection area. The trade is a "Loss" if price hits the bottom of this box (marked by a red "Long SL" bubble). The "76% Winrate" Secret: The indicator uses Asymmetric Risk. By setting a smaller Take Profit (1.0) and a wider Stop Loss (3.0), you allow the trade to "breathe" through market noise, significantly increasing the chance of hitting your profit target. 3. Using the Dashboard Win %: Displays the real-time accuracy of the strategy on your current chart. Multiplier/Period: Shows your active sensitivity settings. If the winrate drops below 70%, try increasing the Multiplier slightly to filter out more noise. 4. Pro Tips for Maximum Success Trade the "Session": The best signals occur during the London/New York crossover (active by default in the settings). Volume is King: Only take signals where the volume is high (the indicator filters this automatically, but always look for "strong" candles). Avoid Flat Markets: If the Gold VWAP and Blue EMA 13 are crossing each other frequently (moving sideways), stay out of the market until a clear trend emerges.
Indicator
by A1TradingHub
(AboBassil) Crash Radar indexCrash Radar Index its is a market risk indicator designed to monitor shifts in volatility structure, credit stress, internal market weakness, trend damage, and price pressure. The script is built to help highlight transitions from lower-risk to higher-risk market conditions through a clean visual framework. Yellow markers indicate early warning conditions. Orange markers indicate risk build-up. Red markers indicate stronger risk confirmation. This indicator is intended to be used as a market condition filter, not as a standalone trading system. It is best used together with price action, trend analysis, and risk management. ===== Crash Radar Index هو مؤشر لقياس مخاطر السوق، تم تصميمه لمراقبة تغيرات هيكل التقلب، ضغط الائتمان، ضعف السوق الداخلي، ضرر الاتجاه، والضغط السعري. يهدف المؤشر إلى المساعدة في رصد انتقال السوق من حالة أقل خطورة إلى حالة أعلى خطورة من خلال إطار بصري واضح ومباشر. العلامات الصفراء تمثل إنذارًا مبكرًا. العلامات البرتقالية تمثل تصاعد الخطر. العلامات الحمراء تمثل تأكيدًا أقوى على ارتفاع مستوى الخطر.
Indicator
by AboBassil
FED Liquidity DashboardA Macro Liquidity Dashboard of a comprehensive "Risk-On / Risk-Off" engine designed to provide a high-level view of the global financial system. Instead of focusing on lagging price action, this indicator tracks the "plumbing" of the economy—monitoring the Yield Curve, Bank Liquidity, Bond Market Volatility, and the Fed’s actual behavior in real-time. This is an "SIMPLE" system for traders who want to know if the wind is at their back or if they are trading into a systemic storm. Key Components The Yield Curve (Visual): A real-time plot of the US Treasury Curve from 3-Month to 30-Year maturities. It automatically highlights whether the curve is Steepening (Teal) or Flattening (Red). Economy (10Y-3M Spread): Monitors the "Gold Standard" recession indicator. It identifies the current state of the Treasury spread. An INVERTED reading warns of an upcoming recession, while a move back to STABLE (Positive) after a long inversion often signals that the economic "contraction" has officially begun. Bank Plumbing (Repo Stress): Tracks the spread between SOFR and the Effective Federal Funds Rate. This tells you if the internal bank pipes are CLEAR or BLOCKED. Bond Volatility (MOVE Index): Incorporates the "VIX for Bonds." It categorizes market fear as CALM, UNCERTAIN, ELEVATED, or CRISIS. Corporate Stress (HY Spreads): Monitors High Yield credit spreads to see if "Real World" companies are struggling to pay their debts. Fed Action Gauge: A proprietary logic row that determines if the Federal Reserve is currently VACUUMING (Removing cash), PATCHING (Emergency liquidity), or FLOODING (Printing money/Stimulus). How to Read the Final Signal The indicator produces a single Final Signal based on the confluence of all macro factors: 🚀 BUY: The "All-Clear." Triggered only when the Curve is Steepening, Plumbing is Clear, Bond Vol is stable, and Corporate Stress is low. ✋ WAIT: The "Safety First" signal. Triggered if any single part of the financial plumbing is blocked or showing signs of systemic stress. Usage This dashboard is best used on a Daily (D) timeframe for long-term bias. It is not a scalping tool, but a Liquidity Filter. Before entering a long position on S&P 500, Nasdaq, or Bitcoin, check the Dashboard. If the signal is WAIT, reduce your position size or stay in cash. If the signal is BUY, the macro "tide" is rising.
Indicator
by supruzr
Analogue Matcher | GainzAlgoAnalogue Matcher: Dual-Path Regression Projection What It Is The Analogue Matcher is a high-performance pattern recognition engine designed to find historical "price twins." Unlike standard fractals that look for raw shape similarity, this tool utilizes Linear Regression Analysis to identify periods in the past where market velocity (slope) and trend consistency ($R^2$) were near-identical to current conditions. It then projects those historical outcomes forward as "Ghost Candles," providing a probabilistic roadmap of where price might go. How It Works The indicator operates by scanning a user defined amount of lookback bars of history in real-time (Default 500). • The Scan: It calculates the current regression slope over a user-defined window. • The Match: It iterates through the lookback period to find the closest matches based on a strict Slope Tolerance . • Dual-Path Intelligence: In "Dual Mode," the script identifies the single best Bullish outcome and the single best Bearish outcome simultaneously. This prevents "bias-blindness" by showing you the best-case scenarios for both directions. Understanding Confidence & R2 The "Conf (R²)" column in your dashboard is the heart of the script's decision-making. • Slope Similarity: Measures how closely the historical angle matches the current angle. • R2 (Coefficient of Determination) : Measures the "cleanliness" of the trend. An R2 of 100.0 is a perfect straight line; 0.0 is pure noise. • The Percentage: Our algorithm combines these two factors. A 90%+ Confidence rating means you have found a historical twin that moved at the same speed and with the same level of trend maturity as the current bar. How to Use: A Risk Management Approach This is not a "magic signal" generator—it is a Risk Management and Bias Tool . • Identify Convergence: If both the Bullish and Bearish paths show high confidence (>80%) and both point in the same direction, you have high-probability confluence. • Divergence Warning: If the Bullish path has 95% confidence but the Bearish path has only 10%, the historical precedent for a trend reversal is mathematically weak. Your bias in this case would lean bullish. Inverse if it’s flipped with a high bearish confidence and a low bullish confidence. • Filtering Noise: Use the R2 percentage to ignore "messy" matches. If the confidence is below 50%, the analogue is likely too "noisy" to be used for a high-conviction trade entry. • Single Mode for Speed: Switch to Single Mode on lower timeframes (1m, 5m) to find the absolute "Best Fit" twin for quick scalping targets. Master the Engine: Key Inputs To get the most out of the Analogue Matcher , it’s essential to understand the "knobs" you are turning. Tuning these correctly is the difference between finding a perfect twin and seeing random noise. • Mode Selection (Single vs. Dual): Single Mode: Focuses the processing power on finding the absolute "Best Fit" regardless of direction. Ideal for high-speed scalping or very large lookbacks. Dual Mode: The full "Risk Management" suite. It forces the script to find both a Bullish and a Bearish path to show you the two most likely outcomes. • Projection Window: This determines the size of the "Ghost." If set to 50, the script analyzes a 50-bar trend and projects a 50-bar future. • Lookback Period: This is how far into the past the engine scans. While the script is optimized for performance, keeping this within a reasonable range (500–2000) ensures fast UI response. • Slope Tolerance: This is your "Sensitivity" setting. Lower Values (0.001 - 0.004): Very strict. The script will only show matches that have a nearly identical angle of attack. Higher Values (>0.01): More lenient. Use this in highly volatile markets (like Crypto) where trends are aggressive and vary in steepness. Examples In this image, we can see BTCUSD on the daily. The confidence favours a bullish move, both Bearish and Bullish possible paths are plotted. Let’s see what happens. The outcome was an initial bullish move though with a bit of a neutral tilt, as it ended relatively flat. Now let us look at ES1!: In this case, the indicator is showing 2 possible paths (Dual Mode), with a bullish tilt. Let’s see what happened next: The move was indeed bullish, and volatility remained intact through the move. Important Considerations The indicators true strength stems from its ability to act as a risk management tool and compare the degree of “fit” of each respective path (i.e. bullish vs. bearish). If you are looking to take a bearish position on a ticker, but you see that the R2 skew slightly favours a move to the upside, you may want to hold off on pulling the short trigger until you have a skew that fits your bias. While the paths are likely not going to be a perfect, identical match, the power comes from understanding the confidence skew of the bullish vs bearish path. This is your saving grace for managing risk in your positions. Though the matches are not likely to be perfect, they are scaled to the ticker’s ATR and thus can be used to help you gauge potential entries, exits and positioning areas. For example, if we look at SPY on the hourly timeframe: We see we have a bearish skew. The bearish path has sizeable upside. We can use this forecasted range to identify potential entry/resistance areas like so: Now let’s see how it plays out: You can see that the key forecast areas provided actual levels for support and resistance! Concluding Remarks In a market driven by algorithmic repetition, the Analogue Matcher gives you the power to see the "scripts" the market has run before. By quantifying the similarity of price action through regression, traders can move away from "gut feelings" and toward data-driven forecasts.
Indicator
by GainzAlgo
144
Business Cycle Composite [v6]The Business Cycle Composite is a macro oscillator that aggregates ten independently scored economic signals into a single weighted composite, designed to identify where the U.S. economy currently stands within the four classical cycle phases: Expansion, Late Cycle, Contraction, and Trough. Each signal is normalized to a −1 to +1 scale before being weighted and combined. The yield curve (10Y−2Y spread) carries the highest weight at 18%, reflecting its historically reliable recession-forecasting track record. Credit market health is captured through the HYG/LQD ratio (15%), while Fed Funds trend, CPI momentum, consumer sentiment, risk appetite (XLY/XLP), and housing permits each contribute between 8–10%. The Copper/Gold ratio and the Sahm Rule unemployment trigger round out the composite at lower weights, serving as real-economy confirmation signals. The final score is smoothed with a configurable EMA and requires a minimum number of consecutive bars before a phase transition is confirmed, reducing noise-driven whipsaws. The resulting oscillator crosses four threshold zones. A score above +0.35 signals Expansion — broad macro conditions are supportive of risk assets. Between zero and +0.35 the indicator reads Late Cycle, characterized by tightening conditions and fading momentum. Below zero but above −0.30 marks Contraction, where recessionary pressure is building. Below −0.30 the indicator enters the Trough phase, historically the zone where forward-looking assets begin to bottom ahead of the real economy. The indicator plots both the smoothed composite and the underlying raw score, with color-coded phase backgrounds for instant visual context. A dashboard table in the top-right corner shows the current phase label, composite score, Sahm Rule status, and individual signal readings with a simple bar-style strength display. Five built-in alert conditions notify on every phase transition, including a dedicated Sahm Rule trigger alert. All data is pulled automatically from FRED and standard U.S. equity ETFs. The indicator is best used on the weekly chart. All weights and thresholds are fully adjustable via the settings panel. For educational purposes only — not financial advice.
Indicator
by Phillipklh
ICT / SMC XAUUSD M5 PRO FINAL + END MOVE# ICT / SMC Smart Money Toolkit – XAUUSD Scalping ## Overview This indicator is based on **ICT (Inner Circle Trader)** and **Smart Money Concepts (SMC)**. It is designed to help traders identify institutional activity, market structure shifts, and high-probability trading setups. The tool combines several advanced market structure concepts into one indicator to simplify chart reading and decision making. It works particularly well for **XAUUSD** and is highly effective on **lower timeframes such as M1**, making it suitable for scalping strategies. --- # Key Features ### Market Structure Detection The indicator automatically identifies important structural events: * **BOS – Break Of Structure** * **CHoCH – Change Of Character** * **MSS – Market Structure Shift** These signals help traders understand when the market trend is changing or continuing. --- ### Smart Money Zones The indicator automatically displays key institutional areas: * **Fair Value Gap (FVG)** * **Inverse Fair Value Gap (IFVG)** * **Order Blocks** * **OTE Zones (Optimal Trade Entry)** * **Buy Zones and Sell Zones** These zones highlight areas where institutional liquidity and imbalance are likely present. --- ### Setup Detection Trade signals appear when multiple Smart Money confirmations align, such as: * Liquidity sweep * Break of structure * Formation of a Fair Value Gap * MSS or CHoCH confirmation * Price returning to a high-interest zone The **number of confirmations required can be customized in the settings**, allowing traders to adjust the aggressiveness of the strategy. --- ### Automatic Risk Management The indicator automatically calculates: * **Entry** * **Stop Loss** * **TP1** * **TP2** * **TP3** Targets are based on **configurable Risk/Reward ratios** to maintain consistent risk management. --- ### Setup Rating System Each setup is scored with a **star rating** based on the number of confirmations. Example: ★★★★★ = Very strong setup ★★★★☆ = Strong setup ★★★☆☆ = Medium probability setup This helps traders focus on the highest-quality opportunities. --- ### Smart Dashboard The dashboard provides real-time information including: * Current trading session * Market structure bias * Active confirmations * Setup score * Entry / SL / TP levels * Market status (BUY READY / SELL READY) --- ### End-of-Move Signal The indicator also provides an **End of Move signal** when: * The final target is reached * Or an opposite market structure appears This can help identify potential market reversals. --- # How to Use 1. Wait for a **market structure shift** 2. Identify a **Smart Money zone (FVG / OB / OTE)** 3. Wait for price to **return to the zone** 4. Check the **setup score** 5. Enter using the suggested **Entry / SL / TP levels** --- # Recommended Timeframes This indicator can be used on multiple timeframes but performs especially well on: * **M1** * **M5** * **M15** It is particularly optimized for **XAUUSD scalping**. --- # Customizable Settings Users can configure: * Number of confirmations required * Risk management parameters * Risk/Reward targets * Zone visibility * Dashboard display * Trading sessions * Colors and visual settings --- # Disclaimer This indicator is designed as a **trading analysis tool** and should not be considered financial advice. Always apply proper risk management when trading.
Indicator
by ogtraging
3
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