Volatility Regime Compass [JOAT]Volatility Regime Compass
Introduction
Volatility Regime Compass is an open-source volatility state classifier that continuously measures where current ATR stands relative to its own historical distribution and maps it to one of four named regimes: Compressed, Normal, Elevated, and Extreme. The classification is not binary (high or low) — it uses a rolling percentile ranking against configurable lookback windows so the regime reflects where current volatility stands within its recent history, not against a fixed absolute threshold that becomes stale as market conditions evolve.
The practical value is in strategy switching: mean-reversion techniques tend to work in compressed regimes, breakout and momentum techniques in elevated ones. Knowing which regime is active before selecting a technique reduces category errors that produce losses.
Core Concepts
1. ATR Percentile Ranking
Rather than comparing ATR to a static multiplier, the indicator ranks the current ATR value within a rolling distribution of historical ATR values. This produces a percentile score from 0 to 100 that is self-normalizing across different instruments and timeframes:
float atrHi = ta.highest(atrVal, i_rankLen)
float atrLo = ta.lowest (atrVal, i_rankLen)
float atrPct = (atrHi - atrLo) > 0 ?
(atrVal - atrLo) / (atrHi - atrLo) * 100.0 : 50.0
A reading of 80 means current ATR is in the 80th percentile of its recent range — clearly elevated. A reading of 15 means ATR is near multi-period lows — compressed.
2. Four-State Regime Classification
The percentile score maps to four regimes with configurable boundary thresholds. Defaults are: Compressed (below 25th percentile), Normal (25th to 60th), Elevated (60th to 85th), Extreme (above 85th). Crossing a regime boundary triggers a transition event labeled on the chart.
3. Multi-Band Visualization
Five ATR bands project above and below close at configurable multiples (0.5×, 1×, 1.5×, 2×, 2.5× ATR). Each band is color-coded by regime — tighter bands in compressed regimes shade cooler, wider bands in extreme regimes shade hotter using a 5-stop gradient. This gives instant visual calibration of price's relationship to current volatility structure.
4. Volatility Trend
The rate of change of ATR is computed and smoothed. Positive volatility trend (ATR rising) is labeled differently from negative trend (ATR contracting). This distinguishes a currently-elevated but contracting regime from one that is expanding — the former is more likely to produce consolidation, the latter continuation.
Features
ATR percentile ranking: Self-normalizing volatility score relative to recent history
Four volatility regimes: Compressed, Normal, Elevated, Extreme with configurable boundaries
Regime transition labels: On-chart labels at every regime change event
Five ATR expansion bands: Projected above and below close, gradient-colored by regime
Volatility trend direction: Rising vs contracting ATR tracked independently of level
Candle coloring: Candles reflect current volatility regime in real time
Regime background shading: Chart background tint corresponds to current regime
Dashboard: Current ATR, percentile, regime, trend direction, and band levels
Input Parameters
ATR Settings:
ATR Period: ATR calculation length (default: 14)
Percentile Lookback: Rolling window for ATR percentile ranking (default: 100)
Regime Thresholds:
Compressed Below: Percentile below which regime is Compressed (default: 25)
Elevated Above: Percentile above which regime is Elevated (default: 60)
Extreme Above: Percentile above which regime is Extreme (default: 85)
How to Use This Indicator
Step 1: Check the Current Regime
Read the REGIME row in the dashboard. This tells you whether to expect range-bound or trending behavior in the near term.
Step 2: Watch for Regime Transitions
A transition from Compressed to Elevated is the setup for breakout strategies. A transition from Extreme back toward Normal may signal trend exhaustion.
Step 3: Use Bands as Structural Reference
The ATR bands define statistically reasonable price excursion limits for the current volatility state. Closes beyond the 2× or 2.5× band while in a Compressed regime are structurally significant events.
Step 4: Combine with Directional Indicators
This indicator classifies volatility magnitude, not direction. Pair it with a trend or momentum tool to apply regime context to directional decisions.
Indicator Limitations
Percentile ranking depends on lookback length; very short lookbacks can produce unstable regime classifications during sudden volatility spikes
The four-state classification is a simplification; volatility is continuous and regime boundaries are heuristic
Volatility expansion does not indicate direction — it only measures magnitude of movement
Originality Statement
The combination of a self-normalizing ATR percentile ranking, a four-state regime classifier with configurable percentile boundaries, gradient-coded multi-band projection, and a simultaneous volatility trend tracker in a single Pine Script v6 publication constitutes the original contribution. Standard ATR indicators display the raw value or a fixed-multiple band without regime classification or percentile normalization.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Volatility regime classifications are statistical summaries of historical data and do not predict future price movement. Trading involves substantial risk of loss.
-Made with passion by jackofalltrades
Indicador
Kalman Trend Filter [JOAT]Kalman Trend Filter
Introduction
Kalman Trend Filter is an open-source trend detection indicator that applies a two-state Kalman filter to price, tracking both the filtered price level and its velocity simultaneously. Unlike exponential moving averages — which apply a fixed exponential decay to past data — the Kalman filter dynamically adjusts its responsiveness based on the ratio of process noise to measurement noise. When price is moving consistently in one direction, the filter trusts new measurements more heavily. When price is noisy, it trusts its own model more heavily.
The practical result is a trend line that responds faster than an equivalent EMA during genuine trends while remaining smoother during chop. The velocity state is the direct indicator of trend direction and strength — it is what drives signal generation and candle coloring.
Core Concepts
1. Two-State Kalman Filter
The filter tracks two quantities: price (position state) and the rate at which price is changing (velocity state). The prediction step projects both states forward using simple kinematic equations. The correction step updates them based on how much the current close deviates from prediction:
// Prediction
float xPred = xEst + vEst
float pPred = pEst + qNoise
// Kalman gain
float kGain = pPred / (pPred + rNoise)
// Correction
float xEst = xPred + kGain * (close - xPred)
float vEst = vEst + kGain * (close - xPred)
The process noise (qNoise) and measurement noise (rNoise) parameters control how much the filter trusts its own momentum model versus new price data.
2. Velocity as Trend Proxy
The velocity state is the most analytically useful output. Positive velocity means the filtered price is accelerating upward; negative means downward. The magnitude of velocity indicates trend strength. Velocity crossing zero is a higher-quality trend reversal signal than a moving average crossover because it reflects the momentum of the filtered series, not the level.
3. Gradient Candle Coloring
Candles are painted using a two-sided gradient driven by the velocity state. Strongly positive velocity produces bright cyan candles; strongly negative produces bright magenta. Near-zero velocity transitions to neutral. The gradient intensity scales with velocity magnitude rather than applying a binary color switch.
4. Velocity Oscillator
The velocity state is plotted as a separate sub-indicator below the main chart, providing a visual oscillator that crosses zero at trend reversals. Unlike momentum oscillators derived from price differences, this oscillator represents the Kalman filter's internal estimate of trend rate — it is inherently smooth without additional EMA smoothing.
Features
Two-state Kalman filter: Tracks price level and velocity simultaneously
Configurable noise parameters: Process and measurement noise control filter responsiveness
Filtered price line overlay: Smooth trend line drawn on the price chart
Velocity oscillator: Kalman velocity state as a zero-line oscillator
Velocity zero-cross signals: Bull and bear signals when velocity crosses zero
Gradient candle coloring: Cyan for upward velocity, magenta for downward, scaled by magnitude
Dashboard: Current filtered price, velocity, trend state, and noise parameters
Alerts: Velocity zero-cross and extreme velocity alerts
Input Parameters
Kalman Engine:
Process Noise (Q): How much the filter trusts its own velocity model (default: 0.01)
Measurement Noise (R): How much the filter trusts new price measurements (default: 1.0)
Initial Velocity: Starting velocity state (default: 0.0)
Display:
Show Filter Line toggle
Show Velocity Oscillator toggle
Show Candle Color toggle
How to Use This Indicator
Step 1: Read Velocity Direction
Positive velocity (oscillator above zero, cyan candles) indicates the filter is trending upward. Negative velocity (below zero, magenta candles) indicates downward trend. The magnitude tells you how strong.
Step 2: Use Velocity Zero-Cross as Trend Change Signal
When velocity crosses from negative to positive, the filter's internal momentum model has flipped bullish. This is more reliable than a price crossover because it reflects the rate of change of the filtered series.
Step 3: Tune Noise Parameters to Timeframe
On faster timeframes, increase Q slightly (0.02–0.05) to make the filter more responsive. On weekly charts, reduce Q (0.001–0.005) for a smoother, slower-adjusting filter.
Step 4: Combine with Regime Context
The Kalman filter performs best in trending regimes. Combine with Fractal Dimension Oscillator: when FDO shows a trending regime, Kalman velocity direction provides the trend bias.
Indicator Limitations
The Kalman filter assumes a linear motion model; non-linear price dynamics (sudden gaps, news events) produce temporary distortion in the filter state
Optimal Q and R values are instrument and timeframe dependent; no universal setting works everywhere
Velocity zero-crosses during low-volatility consolidation can produce frequent false signals
Originality Statement
The two-state Kalman filter implementation combined with a velocity-driven gradient candle coloring system, a dedicated velocity oscillator, and dual-input noise parameter configuration in a single publication is the original contribution here. Most published Kalman filter scripts on TradingView implement a single-state position filter with no velocity tracking and no gradient visualization.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Kalman filter outputs are mathematical estimates based on prior observations and do not predict future price. Trading involves substantial risk of loss.
-Made with passion by jackofalltrades
Indicador
Entropic Structure Bands [JOAT]Entropic Structure Bands
Introduction
Entropic Structure Bands is an open-source overlay indicator that dynamically selects the best-fitting Ordinary Least Squares regression window from recent structural pivots and surrounds that regression channel with entropy-adjusted deviation bands. The key innovation over standard regression channel indicators is twofold: the window length is selected optimally each bar by searching through available pivot anchors for the highest R² × log(N) quality score, and the band width is modulated by the current Shannon entropy of log returns — widening during chaotic periods and tightening during orderly ones.
Core Concepts
1. Optimal Regression Window Search
Rather than using a fixed lookback, the indicator records the bar index of every confirmed pivot high and low. Each bar, it tests several candidate windows anchored at recent pivots and selects the one that maximizes a performance score: R² multiplied by the natural log of the window length. This rewards both fit quality and window depth simultaneously:
float score = r2 * math.log(float(N))
// highest score wins; window updates every bar
if trial.perfScore > bestScore
bestScore := trial.perfScore
bestMdl := trial
The regression channel therefore adapts to where significant price structure has occurred, not to an arbitrary fixed period.
2. Shannon Entropy Modulation
Shannon entropy of the log return distribution is computed using a histogram-binning approach. Low entropy means returns are concentrated — price is moving in an organized, directional way. High entropy means returns are evenly distributed — chaotic, noisy conditions. Band width scales with entropy:
float entAdjDev = bestMdl.stdErr * (1.0 + entNorm * 0.8)
When entropy is low (below the configurable threshold), the market is classified as orderly and signals are enabled. This prevents signals from firing into chaotic conditions where regression bands have less predictive value.
3. Trend-Confluence Signal Logic
Signals require simultaneous alignment of six conditions: regression slope direction, price position relative to midline, recent pullback to the inner band, momentum confirmation, optional HTF slope alignment, optional ADX trending gate, and optional RSI gate. Each condition is individually toggleable. This multi-factor gate replaces simple band-crossover logic with a structured confluence requirement.
4. Forward Projection
The regression channel extends forward by a configurable number of bars beyond the right edge of the chart. A projection target label marks the estimated price at the end of the projection window based on the current slope and intercept. This gives visual context for where the regression model expects price to be if the current trend continues.
5. Z-Score Candle Coloring
Each candle's position within the channel is expressed as a Z-score (standard deviations from the regression midline). Candles far above the midline (overbought extension) are tinted bear-color; candles far below (oversold extension) are tinted bull-color. This provides immediate visual context for where price stands within its current regression structure.
Features
Dynamic regression window: Optimal window selected each bar from pivot anchor scan
R² quality gate: Configurable minimum R² prevents low-fit windows from being used
Entropy-adjusted bands: Band width scales with Shannon entropy of log returns
Multi-factor signal gate: Six independently configurable confluence conditions
Forward projection: Channel extended beyond right edge with target label
Z-score candle coloring: Candles painted by standard deviation position in channel
Inner and outer bands (±1σ, ±2σ): Gradient-filled channel layers
Glow-effect midline: Double-drawn center line with transparency for depth
10-row dashboard: R², entropy, Z-score, duration, HTF alignment, ADX, RSI, signal state
JSON webhook alerts: Alert messages formatted as JSON with EP, TP, SL, and R²
Input Parameters
Regression Engine:
Pivot Scan Horizon: Number of pivots to evaluate as regression anchors (default: 20)
Pivot Sensitivity: Left/right bars for pivot confirmation (default: 5)
Min R² Quality Gate: Minimum fit quality to use a window (default: 0.50)
Band Multiplier 1/2: Inner and outer band standard deviation multiples (default: 1.0, 2.0)
Entropy System:
Entropy Lookback: Bars for entropy calculation (default: 20)
Entropy Bins: Histogram bins for return distribution (default: 10)
Low Entropy Threshold: Threshold below which market is classified as orderly (default: 2.5)
How to Use This Indicator
Step 1: Read the Slope Bias
Check the dashboard's Slope Bias row. BULLISH or BEARISH indicates the current regression direction. This is the primary directional input.
Step 2: Check Entropy State
LOW (orderly) entropy is the condition under which signals are most reliable. HIGH entropy warns that the regression model is operating in a chaotic environment.
Step 3: Wait for Signal Labels
LONG and SHORT labels appear only when the full confluence gate is satisfied. Each label shows entry price, TP1, TP2, stop loss, and R² quality.
Indicator Limitations
Regression channels repaint historically when the optimal window shifts to a new anchor; use the confirmed-bar signals for non-repainting entry logic
In markets with very few pivots, the scan horizon may find suboptimal windows with low R²
Shannon entropy requires sufficient lookback to produce stable estimates
Originality Statement
The dynamic pivot-anchored regression window search using R² × log(N) scoring, combined with Shannon entropy-modulated band width and a six-condition confluence signal gate, is the original analytical architecture of this publication. No existing published Pine Script regression channel indicator implements adaptive window selection from pivot anchors with entropy modulation in this manner.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Regression channels are mathematical models of past price behavior and do not predict future price. Trading involves substantial risk of loss.
-Made with passion by jackofalltrades
Indicador
Machine Learning: Volume-Weighted Mean Reversion [Dots3Red]█ MACHINE LEARNING: VOLUME-WEIGHTED MEARN REVERSION KERNEL REGRESSION
Nadaraya-Watson kernel regression is a non-parametric machine learning method. Unlike moving averages which apply fixed, predefined weights to historical bars, kernel regression derives each bar's weight from a mathematical function — the kernel — that measures how relevant that bar is to the current estimate. No hardcoded coefficients. No assumed shape. The model adapts purely from the data.
This script introduces a fundamental extension to the standard method: volume as a second weighting dimension . The result is a regression curve that gravitates toward price levels where real market participation occurred — not toward price levels where a clock happened to tick.
█ WHY KERNEL REGRESSION IS MACHINE LEARNING
The term machine learning describes algorithms that derive structure from data rather than from manually specified rules. Kernel regression satisfies this definition formally. The estimator computes:
ŷ = Σ [ w(i) × close ] / Σ
where each weight w(i) is determined by a kernel function — not by the programmer. The model decides, from the data, how much each historical bar should influence the current estimate. This is the same mathematical family as K-Nearest Neighbors, which weights neighbors by proximity. It is cited as a foundational non-parametric ML method in Bishop (2006) and Hastie et al. (2009), and is described as an attention mechanism in deep learning literature — the same concept behind transformer models. The claim is accurate, not cosmetic.
█ THE CORE INNOVATION — VOLUME WEIGHTING
Every existing Nadaraya-Watson implementation on TradingView uses a pure time kernel:
• Standard NW: w(i) = K(i/h)
This means a bar with 10,000 shares traded and a bar with 10,000,000 shares traded receive identical weight if they are the same number of bars away. A thin overnight drift and a high-volume institutional session influence the regression equally. That is statistically incorrect — volume is a direct measure of how much informational content a price bar carries.
This script uses a volume-weighted kernel:
• This script: w(i) = vol_norm(i) × K(i/h)
where vol_norm(i) is the bar's volume normalized against the peak volume in the lookback window, raised to a configurable power exponent. The regression estimate is therefore:
ŷ = Σ [ vol_norm(i) × K(i/h) × close ] / Σ
High-volume bars anchor the curve. Low-volume bars — thin sessions, overnight drift, holiday trading — contribute minimally. The regression finds where the market actually agreed on price, not just where the clock recorded a tick.
█ THREE KERNEL FUNCTIONS
All three apply the same volume weighting. The choice controls how rapidly influence decays with time distance:
• Rational Quadratic (default) — heavier tail than Gaussian. Bars from 40–60 periods ago still contribute meaningfully if they had high volume. Best for daily and weekly charts where old high-volume levels remain structurally relevant.
• Gaussian — standard bell curve decay. Weight drops sharply with distance. Best for intraday charts where recency matters more than historical anchors.
• Epanechnikov — hard cutoff at the bandwidth boundary. Anything beyond h periods receives zero weight. Produces the most locally sensitive regression. Best for fast charts requiring tight responsiveness.
█ SIGNAL LOGIC
The envelope bands are placed at a configurable multiple of ATR, standard deviation, or a fixed percentage above and below the regression line. Three band width methods are available to match different volatility contexts.
Two signal modes are available:
• Reversion mode (default) — a signal fires when price crosses back through the band after an extension. The ▲ label appears on the bar where price returns inside the lower band. The ▼ label appears on the bar where price returns inside the upper band. This confirms reversion has begun rather than anticipating it.
• Extension mode — enable Signal on extension close to fire a signal the moment price closes outside a band. This is an early warning — useful for alerts before the reversion bar arrives.
Additional signal filters: minimum bars between signals to prevent repeat firing, optional slope direction gate so signals only fire when the regression slope agrees with the signal direction.
█ WHAT YOU SEE ON THE CHART
Regression line
The volume-weighted fair value curve. Cyan when slope is rising, magenta when falling. This is where the model estimates price should be given the recent history of high-participation price levels.
Envelope bands
Upper and lower boundaries built from ATR, standard deviation, or a fixed percentage. The upper band is tinted red — resistance zone. The lower band is tinted green — support zone.
Bar coloring — 4 states
• Bright red — price closed above the upper band. Extended, statistically stretched above fair value.
• Bright green — price closed below the lower band. Extended, statistically stretched below fair value.
• Dim silver — price inside bands, regression rising or falling, i.e normal bullish or bearish context.
The contrast between fully saturated outside-band bars and dimmed inside-band bars makes overextension immediately visible without reading the scale.
Signal labels
▲ REVERT or ▼ REVERT with VW=XX% showing the volume weight of the signal bar. A signal at VW=85% fired on a high-participation bar. A signal at VW=9% fired on a thin bar — lower confidence.
Signal bar highlighting
Two additional layers available: a background flash on the signal bar and a thick vertical line through the bar's full range. Both are independently toggleable. The vertical line uses width=4 — the maximum Pine Script allows — making the signal bar visually distinct even when zoomed out.
Dashboard
Displays: current regression value, slope direction, band width, Bar Vol Weight meter (▰▰▰▱▱▱) showing how much influence the current bar has on the regression, active kernel type, volume weighting status, percentage distance from the regression midline, and non-repainting mode status.
█ NON-REPAINTING
When Non-Repainting Mode is enabled (default), all calculations use a bar offset. The current bar's close does not enter its own regression estimate. Historical signals visible on closed bars will not change as new bars form. Disable this to see a predictive (repainting) version where the current bar participates in its own estimate — useful for visual exploration but not recommended for backtesting or alerts.
█ HOW TO USE
Core use case — mean reversion
This is a mean reversion tool. It works best when price is oscillating rather than trending directionally. The recommended workflow:
1 — Confirm a ranging regime with a separate regime classifier before acting on signals.
2 — Wait for price to reach or pierce the upper or lower band (bars turn bright red or green).
3 — Check the VW% in the signal label. Higher volume weight on the signal bar = higher confidence.
4 — Enter on the reversion signal (▲ or ▼ label). Stop beyond the wick of the signal bar.
5 — Target the regression midline as the primary exit. The % from mid dashboard row tracks progress in real time.
Timeframe guidance
The volume-weighting advantage increases with timeframe because higher timeframes produce more meaningful volume data per bar. H4 and Daily are the strongest timeframes for this tool. For intraday use, reduce the Volume Weight Power to 0.3–0.5 to soften the impact of individual volume spikes.
Quick-start settings by asset class
• Stocks daily: Window=100, Bandwidth=8, Vol Power=1.0, ATR×2.0
• Crypto daily: Window=80, Bandwidth=6, Vol Power=0.7, ATR×1.8
• Forex H4: Window=100, Bandwidth=10, Vol Power=1.0, ATR×1.5
• Indices H1: Window=120, Bandwidth=12, Vol Power=0.8, Stdev×2.0
█ SETTINGS REFERENCE
Kernel Settings
• Lookback Window — number of historical bars in the regression. Larger = smoother, more lag.
• Bandwidth (h) — controls how fast kernel weight decays with time. Higher = older bars still contribute.
• Kernel Type — Gaussian / Rational Quadratic / Epanechnikov. See kernel section above.
• RQ Alpha (α) — Rational Quadratic only. Lower = smoother mixture of length scales.
• Non-Repainting Mode — uses offset. Recommended ON for backtesting.
Volume Weighting
• Enable Volume Weighting — toggle the core innovation on or off. OFF = standard NW.
• Volume Normalization Window — peak volume reference window. Match or exceed the lookback window.
• Volume Weight Power — exponent on the volume weight. 1.0 = linear. 2.0 = quadratic. 0.5 = softer.
• Volume Weight Floor — minimum weight for any bar. Prevents zero-volume bars from being ignored entirely.
Envelope Bands
• Band Width Method — ATR (volatility-adaptive), Stdev (statistical), or Percent (fixed).
• ATR Length — period for ATR calculation.
• ATR / Stdev Mult — multiplier applied to ATR or standard deviation.
• Percent Offset % — used when Percent method is selected.
Signals
• Signal on band crossover — enable signals on band cross events.
• Signal on extension close — fire signal when price closes outside a band (early warning mode).
• Require slope change — only signal when regression slope direction agrees.
• Min bars between signals — gap guard to prevent repeat signals.
Visuals
• Dashboard — regression stats and live metrics table.
• Signal labels — ▲/▼ REVERT labels with volume weight percentage.
• Band fill — fill between upper and lower bands.
• Background flash — bright background color on signal bars.
• Vertical line on signal bar — thick line through full bar height at signal.
• Large dot marker — additional plotchar layer on signal bars.
• Dashboard position — Top Right / Top Left / Bottom Right / Bottom Left.
█ ALERTS
Seven alert conditions are available:
• Long signal — reversion through lower band
• Short signal — reversion through upper band
• Any signal — either direction
• Extended below lower band — early warning before reversion fires
• Extended above upper band — early warning before reversion fires
• Regression slope turned bullish
• Regression slope turned bearish
█ DISCLAIMER
This indicator is a decision-support tool. It does not constitute financial advice and does not guarantee future results. Past statistical patterns do not predict future price behavior. Always use proper risk management.
Method: Nadaraya-Watson Kernel Regression (Non-Parametric ML)
Innovation: Volume × Time Kernel Weighting
Kernels: Gaussian · Rational Quadratic · Epanechnikov
Signals: Mean Reversion (band crossover or extension)
Repainting: Configurable — non-repainting mode available Indicador
Indicador
Tectonic Regime Protocol [JOAT]Tectonic Regime Protocol
Introduction
Tectonic Regime Protocol is an open-source Pine Script v6 strategy that combines four analytical modules into a single rule-based trading system: a four-state regime classifier, a three-layer trend filter, a six-pillar confluence entry engine, and an adaptive exit module using ATR-based partial take-profit and a regime-adaptive trailing stop.
The strategy is designed for traders who want a fully automated systematic framework to study how regime-gating affects signal quality. Its primary hypothesis is that directional entries made when (1) the market is classified as a trending regime, (2) trend filters across multiple timeframes align, and (3) multiple structural, volume, and momentum inputs agree, produce statistically better outcomes than entries based on any single condition alone.
Strategy Default Properties
Initial capital: $100,000
Order size: 2% of equity per trade
Commission: 0.04% per side
Slippage: 2 ticks
Maximum open positions: 1
These settings represent realistic conditions for a funded discretionary trader using a liquid futures or equity instrument. The 2% equity sizing limits maximum theoretical drawdown from any single trade while providing meaningful position exposure. Commission and slippage values reflect typical institutional-grade execution costs for electronically traded instruments.
Core Concepts
1. Four-State Regime Classifier
The regime module classifies each bar into one of four states using ADX relative to a threshold and the ATR-to-SMA(ATR) ratio: Trend Bull, Trend Bear, Range High-Vol, Range Low-Vol. Only Trend states are eligible for entry. Range classifications suppress all entries regardless of how strong the confluence score is. This is the primary market context filter.
2. Three-Layer Trend Filter
Three independently computed trend conditions must all agree before a long or short entry is considered: close versus VWMA(200) determines whether price is above or below long-term value; the relationship between fast and slow HMA lines determines medium-term momentum direction; and the close versus a 50-period EMA on a higher timeframe provides multi-timeframe context.
3. Six-Pillar Confluence Score
The entry engine scores six market dimensions and requires the composite bull or bear score to exceed 50 of 100 (default, configurable) with a directional lead of at least 8 points above the opposing score. The six pillars are: market structure, OBV slope direction, KAMA position + RSI + WPR composite, swing-low liquidity sweep detection, ATR ratio in productive range, and Fractal Efficiency Ratio above 0.30.
bool longSetup = validRegime and regime == 1 and trendBull
and bull >= confThreshold and (bull - bear) >= confGap
and barstate.isconfirmed
4. Adaptive Exit Module
The exit logic uses partial exits at two take-profit levels. TP1 closes 50% of the position at 1.0× risk distance. TP2 closes the remaining position at 2.0× risk distance. After TP1 is reached, the stop is moved to the entry price (breakeven). The stop before TP1 uses a regime-adaptive ATR trail — the stop multiplier is lower in low-volatility regimes (tighter) and higher in high-volatility regimes (looser). A 30-bar time-based exit closes any remaining position if neither TP nor stop is reached.
5. Non-Repainting Architecture
All entry conditions are evaluated only when barstate.isconfirmed is true. The HTF EMA is requested with lookahead=barmerge.lookahead_off. Pivot-based conditions use confirmed pivot detection with symmetric lookback. No future bar references are used.
Default Settings and Performance Notes
The strategy is published with the default Properties values listed above. Results shown on the publication chart are generated using these exact settings. Commission of 0.04% per side is representative of typical electronic execution on liquid instruments.
Win rate alone does not characterize strategy performance. The strategy is designed around a two-tier partial exit structure targeting positive expectancy (wins × average win greater than losses × average loss) rather than high win rate. The profit factor and average R-multiple are the more relevant metrics for this type of system.
Input Parameters
Regime Module:
ADX Trend Threshold (default: 20)
ATR Ratio High-Vol Threshold (default: 1.2)
Trend Filter:
VWMA Length (default: 200)
Ribbon Fast HMA and Slow HMA lengths
HTF Timeframe for EMA(50) filter (default: 240)
Enable HTF Filter toggle
Confluence Engine:
Min Score (default: 50, range 50–95)
Min Direction Lead (default: 8)
Min FER (default: 0.30)
FER Lookback (default: 14)
Individual pillar weights (Structure, Volume, Momentum, Liquidity, Volatility, FER)
Exit Module:
TP1 RR Multiple (default: 1.0)
TP2 RR Multiple (default: 2.0)
Stop Multiplier for Low / Med / High Volatility Regimes
Max Bars Hold (default: 30)
How to Evaluate This Strategy
Apply it to a liquid instrument with sufficient historical data to generate more than 100 trades. Compare profit factor, Sharpe ratio, average R-multiple, and maximum drawdown — not win rate in isolation. Test it across at least two different instruments or timeframes to assess whether the results reflect genuine structural edge or data-fitting to one specific market.
The strategy is not optimized for any single market. Default parameters are deliberately conservative to avoid overfitting. Users who adjust parameters to improve backtested results should recognize that improvement on historical data does not guarantee improvement on future data.
Strategy Limitations
On lower-timeframe charts with short histories, fewer than 100 trades may result, reducing the statistical reliability of the backtest
The HTF filter uses request.security() with a higher timeframe EMA. In live trading, the HTF value updates when the higher timeframe bar closes, which may differ slightly from live server-side execution
ATR-based stops and targets mean position sizes and outcomes scale with volatility. In abnormally low-volatility environments, commission costs represent a larger proportion of expected gain
The time-based exit at 30 bars may close profitable positions before TP2 is reached in slow-moving markets
Backtested performance on any instrument does not predict future performance. Markets change, and parameters that produced edge historically may not do so in future regimes
Originality Statement
Combining a four-state regime classifier, a three-layer multi-timeframe trend filter, a six-pillar confluence score including Fractal Efficiency Ratio, and a partial-exit adaptive trailing stop system in a single non-repainting open-source strategy is an original integration of methods
The Fractal Efficiency Ratio as a pillar in a multi-factor entry score, and as a required gate condition for entry, is not present in existing open-source Pine Script v6 strategy publications as of this writing
The regime-adaptive stop multiplier — loosening in high-volatility regimes and tightening in low-volatility regimes — is an original stop calibration approach within this strategic framework
The dual entry mode (edge transition OR re-entry when flat with elevated score) increases signal frequency without compromising the fundamental regime and trend filter requirements
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Backtested results are simulated and do not represent real trading. Simulated results have inherent limitations and may not reflect actual trading outcomes due to market impact, execution differences, and changing market conditions. Past backtested performance does not guarantee future results. Trading involves substantial risk of loss. Always conduct independent due diligence and apply proper risk management before using any strategy with real capital. The author accepts no responsibility for trading losses resulting from use of this strategy.
Made with passion by jackofalltrades
Estratégia
Indicador
Indicador
No-Repaint Entry Score Multi-Factor Confluence [LunqFX]No-Repaint Entry Score — Multi-Factor Confluence
Most indicators tell you a signal exists. This one tells you how strong
it is, why it fired, and how long it has been holding — on every bar,
across every market.
One number: 0–100. Five factors. Zero repainting.
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█ HOW TO USE IT — 4 STEPS
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STEP 1 — CHECK HTF TREND
Look at the SIGNAL section of the panel.
HTF Trend shows ▲ BULL or ▼ BEAR based on a confirmed higher
timeframe EMA. Only take setups in this direction.
Counter-trend setups are automatically penalised by the score.
STEP 2 — WAIT FOR THE ENTRY WINDOW
When score reaches your Signal Threshold (default 75), the panel
shows "✓ ENTRY WINDOW" and a green Entry Zone box appears on the chart.
Do not enter below this threshold — conditions are not aligned.
STEP 3 — CHECK THE CAUTION ROW
The panel always shows your weakest component.
Caution: Momentum ↓ → wait for a strong candle close
Caution: Session ↓ → wait for market session to open
Caution: Structure ↓ → you may be entering against the trend
Fix the caution before entering.
STEP 4 — LOOK FOR PRIME AND PERSISTENCE
PRIME label (score ≥80) = all 5 factors aligned. Best entries.
◆ SUSTAINED (3+ bars) → candles turn cyan. High conviction.
◆◆ ELITE (6+ bars) → candles turn gold. Exceptional setup.
The longer the streak holds, the stronger the setup.
STOP LOSS — place below/above the Entry Zone outer band (±0.55 ATR).
TAKE PROFIT — next confirmed swing level or session high/low.
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█ SCORE TIERS
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◆◆ ELITE PRIME ≥80, held 6+ bars — exceptional, rare
◆ SUSTAINED ≥80, held 3+ bars — high conviction
PRIME ≥80, first bar — valid entry signal
GOOD 65–79 — quality setup, consider entry
MODERATE 40–64 — mixed signals, wait
WEAK <40 — avoid, confluence collapsed
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█ READING THE DASHBOARD PANEL
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ENTRY SCORE — composite score 0–100. Header color shifts with tier:
green (PRIME) → cyan (SUSTAINED) → gold (ELITE) → red (WEAK)
Progress bar — 8-block visual bar. Updates every tick.
Score ▲▼— — arrow shows if score is building (▲) or fading (▼).
Useful for timing: enter when score is rising, not when it peaks.
Tier row — current tier label. Upgrades automatically to
◆ SUSTAINED PRIME or ◆◆ ELITE PRIME when streak activates.
COMPONENTS — individual 0–100 scores:
Structure = HTF EMA alignment × candle direction
Proximity = distance from nearest swing pivot level
Session = trading session quality by hour
Momentum = candle body strength (body ÷ total range)
Volatility = ATR vs 50-bar average (filters dead and spiking markets)
HTF Trend — higher timeframe direction. Confirmed bar only, no drift.
Caution — your weakest component. One actionable reason to wait.
Entry — ENTRY WINDOW or WAIT based on your Signal Threshold setting.
Persistence — consecutive PRIME bar counter.
— = no active streak 3 bars = SUSTAINED 6 bars = ELITE
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█ RECOMMENDED TIMEFRAMES AND MARKETS
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Best timeframes: 1H · 4H · Daily
Works on: 5M · 15M · 30M (more signals, lower quality per signal)
Avoid: below 5M
Forex (EURUSD GBPUSD USDJPY) → NY or London session mode
Gold (XAUUSD) → NY session, 1H or 4H
Crypto (BTCUSD ETHUSD) → Crypto 24/7 mode
Indices (SPX NAS DAX) → NY session
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█ WEIGHT PRESETS FOR DIFFERENT TRADING STYLES
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Weights are fully adjustable. Presets to get you started:
Trend Following (default)
Structure 30 / Proximity 25 / Session 20 / Momentum 15 / Volatility 10
Scalping (5M–15M)
Structure 20 / Proximity 15 / Session 30 / Momentum 25 / Volatility 10
Swing Trading (Daily–Weekly)
Structure 35 / Proximity 30 / Session 5 / Momentum 20 / Volatility 10
Mean Reversion (range markets)
Structure 15 / Proximity 40 / Session 20 / Momentum 15 / Volatility 10
Crypto 24/7
Structure 30 / Proximity 30 / Session 5 / Momentum 20 / Volatility 15
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█ ALERTS — 6 CONDITIONS
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1. Prime Setup Detected — score enters ≥80
2. Good Setup Forming — score enters 65–79 from below
3. Setup Degraded — score drops from quality zone
4. Weak Setup Warning — score collapses below 40
5. Sustained PRIME (3 bars)— streak hits 3 consecutive PRIME bars
6. Elite PRIME (6 bars) — streak hits 6 consecutive PRIME bars
Set alerts to "Once per bar close" in TradingView settings.
All alerts fire on confirmed closed bars only — no false triggers.
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█ HOW THE SCORE IS CALCULATED
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Score = weighted average of 5 components, normalised to 100%.
Weights are user-configurable and auto-normalised — they do not
need to sum to exactly 100.
1. STRUCTURE (default 30%)
Compares candle direction to HTF EMA(20) direction.
Fully bi-directional: bearish candle in bearish HTF = same score
as bullish candle in bullish HTF.
Aligned: score = 65 + (body ratio × 35), max 100
Misaligned: score = 5 + (body ratio × 25), max 30
2. PROXIMITY (default 25%)
Measures distance from the nearest confirmed pivot high or low
using ta.pivothigh/pivotlow (5-bar lookback) in ATR units.
Score = 100 − (ATR distance × 18), clamped 0–100.
At the level = 97–100. Far from structure = 0–20.
3. SESSION (default 20%)
Hour-by-hour quality score based on New York time.
NY mode: 08:00–11:00 = 100 · 03:00–05:00 = 88 ·
11:00–13:00 = 72 · 13:00–16:00 = 60 ·
dead zones = 25
London and Tokyo modes follow their respective peak hours.
Crypto 24/7 = flat 75 (no session bias).
4. MOMENTUM (default 15%)
Candle body divided by total candle range.
Full-body candle = 100. Doji = 0.
Filters indecisive wick-heavy candles.
5. VOLATILITY (default 10%)
ATR(14) divided by its 50-bar SMA.
Sweet spot 0.7–1.6 = score 100.
Too quiet (< 0.7): score scales down.
Too explosive (> 1.6): score drops sharply.
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█ NO-REPAINT — HOW IT IS ACHIEVED
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Three sources of repaint addressed:
HTF EMA: request.security(..., ta.ema(close,20) , lookahead_on)
The reads the EMA of the PREVIOUS confirmed HTF bar.
Locked until the next HTF candle closes. No live-bar drift.
Labels: all signals fire only on barstate.isconfirmed.
Never drawn on an open bar.
Pivots: 5-bar right lookback on confirmed bars only.
Verify: TradingView Replay mode — bar-by-bar playback matches
published chart exactly on any historical period.
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█ SETTINGS REFERENCE
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Higher Timeframe — blank = auto.
Auto logic: 1–5M→30M · 6–15M→1H · 16–60M→4H ·
61–240M→Daily · Daily→Weekly · Weekly→Monthly
Signal Threshold — Entry Window fires above this score. Default 75.
PRIME tier is always fixed at ≥80 regardless of this setting.
Trading Session — NY · London · Tokyo · Crypto 24/7
Component Weights — all five individually adjustable.
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█ RISK DISCLAIMER
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This indicator is a decision-support tool, not a trading strategy.
No backtested win rate or profit factor is implied or claimed.
Past signals do not guarantee future performance.
Always use a defined stop loss and proper position sizing.
Trading involves risk of loss. Use at your own discretion. Indicador
MTF Volume Delta Bar Synchrony | Rainbow MatrixGENERAL OVERVIEW
MTF Volume Delta Bar Synchrony is a multi-timeframe volume percentile fusion oscillator that condenses five independent volume readings — one per Fibonacci-spaced timeframe — into a single weighted Master Line, surrounded by per-TF "ghost lines" that fade visually as they diverge from the consensus. When the five timeframes align, the rainbow becomes a solid band; when they spread apart, the disagreement becomes a visible density property of the indicator itself. A compact 7×9 MTF Legend Table surfaces every dimension simultaneously: per-TF volume percentile values, trend direction, divergence flags, Pulse magnitude ratio, and named State classification — with an antenna marker flagging the row whose timeframe matches your chart's native resolution.
Optional Delta Twin Bars project per-candle directional overlays directly onto the price chart via force_overlay=true, combining the oscillator pane and an order-flow approximation in a single indicator. A hybrid Black Swan zone detects volume climax (surge) and squeeze (drought) extremes — either as static 80/20 thresholds (classic) or as a dynamic Fibonacci-scaled channel that adapts to recent volatility. A classic price↔volume divergence engine detects Wyckoff-style "no demand" rallies and selling-climax bottoms on every timeframe and on the Master line.
Designed as a sibling to the MTF RSI Synchrony indicator. Apply both side-by-side for the complete momentum + volume picture: RSI shows where price sits in its momentum range; Volume Synchrony shows whether the move has institutional backing. Same visual signature, same canonical color zones, same Legend Table layout — instant cross-indicator readability.
WHAT IS THE THEORY BEHIND THIS INDICATOR
Most volume indicators on TradingView operate on a single timeframe — volume bars, OBV, CVD approximations — and report raw, unbounded volume values that vary wildly across timescales. A 5-minute volume bar of 50,000 contracts is meaningless without context: is that "high" for 5-minute bars on this asset, or "low"? Compared to what window? A trader watching a 5-minute chart cannot intuitively cross-reference whether that surge corresponds to anything notable on the 4-hour view.
This indicator solves the cross-timescale comparison problem by bounding every volume reading to a 0-100 percentile rank: the same scale, regardless of timeframe, regardless of asset. The percentile answers a single question: "where does this bar's volume sit in the distribution of recent volume on this timeframe?" — a number anyone can read at a glance.
Five percentile readings are then fused via canonical Fibonacci weights (0.15 / 0.20 / 0.25 / 0.25 / 0.15 — peak weight on the macro TF3/TF4 where institutional consolidation tends to occur) into a single weighted Master Line. The Master adapts to a self-calibrating Fibonacci channel built from its own highest/lowest values over a configurable lookback, smoothed by EMA. Channel boundaries use the brand's canonical ratios: Z-Breathing (1.50σ), Z-Alert (1.85σ anchor), Z-Exhaustion (2.75σ), Black Swan (3.85σ) — same proportions as the RSI sibling for cross-indicator consistency.
The result is a volume picture that updates in real time, accounts for five timescales simultaneously, encodes "synchrony" itself as a visible rainbow density property, and triggers as an alertable signal when extremes converge.
FEATURES
🔹 Multi-Timeframe Volume Percentile Fusion Engine
🔹 Adaptive Fibonacci Channel (Z-Breathing → Z-Alert → Z-Exhaustion → Black Swan)
🔹 Hybrid Black Swan Zones (static 80/20 or dynamic Fibonacci-scaled)
🔹 Classic Price↔Volume Divergence Detection (per-TF + Master)
🔹 MTF Legend Table (7 columns × 9 rows, multilingual)
🔹 Volume Profile Reading (Pulse magnitude + State classification — 7-tier vocabulary)
🔹 Delta Twin Bars (per-candle chart overlay with 4 display modes + live intra-bar updates)
🔹 Multilingual Interface (EN / PT / ES / RU / ZH)
🔹 Multi-Timeframe Volume Percentile Fusion Engine
What It Does
Aggregates five independent volume percentile readings — one per Fibonacci-spaced timeframe — into a single weighted Master Line. Each per-TF reading is plotted as a "ghost" line that fades by distance to the Master, so the rainbow becomes a visual representation of multi-timeframe consensus.
Method
Default timeframes are 5 / 15 / 60 / 240 / D (Trigger / Intraday / Macro 1 / Macro 2 / Base). On each timeframe, ta.percentrank(volume, length) produces a 0-100 percentile rank with lookahead=barmerge.lookahead_off for anti-repaint integrity. The five percentiles are fused via canonical Fibonacci weights (0.15 / 0.20 / 0.25 / 0.25 / 0.15 — peak weight on TF3 and TF4 where institutional volume tends to consolidate). The Master itself is then clamped to for pane containment.
Per-TF length defaults are tuned to each timeframe's natural look-back window:
◇ TF1 (5m): 30 bars = 2.5 hours
◇ TF2 (15m): 50 bars = 12.5 hours
◇ TF3 (60m): 80 bars = 3.3 days
◇ TF4 (240m): 100 bars = 16 days
◇ TF5 (D): 150 bars = ~5 months
Set any per-TF override to 0 to inherit the global default (50). One-size-fits-all 50 bars across timeframes either lags on TF1 (16 hours of stale 5-minute history) or feels too reactive on TF5; the per-TF defaults match each horizon's natural cadence.
Why It Matters
Volume distribution is regime-dependent and timeframe-dependent. A single timeframe view can miss whether a 5-minute volume surge is the leading edge of a broader institutional move (visible on TF3/TF4) or a one-off scalper spike. The fusion engine surfaces alignment and disagreement instantly.
🔹 Adaptive Fibonacci Channel
What It Does
Renders six color-coded bands around the Master Line that adapt to its own recent volatility, using the brand's canonical Fibonacci ratios.
Method
Highest/lowest of the Master over lookback_dyn bars (default 50) are smoothed by EMA (default 10) to form dyn_up and dyn_dn. Channel bands are placed at canonical Fibonacci proportions:
◇ Z-Breathing: 1.50/1.85 ≈ 0.811 of half-channel
◇ Z-Alert: anchor at 1.85σ (the channel boundary itself)
◇ Z-Exhaustion: 2.75/1.85 ≈ 1.486
◇ Black Swan: 3.85/1.85 ≈ 2.081
All six band values are mathematically clamped to before rendering, so the rainbow stays inside the visible pane in volatile regimes (no auto-scale stretching). The algorithm itself is preserved bit-exact; only the rendered values are bounded.
Why It Matters
Static thresholds (e.g., 80/20) cannot adapt to regime changes. During a low-volatility consolidation, "70" might be a meaningful surge; during a news-driven trend, "70" might be the new baseline. The Fibonacci channel calibrates the warning levels to the asset's current regime, so the alerts stay informative regardless of market state.
🔹 Hybrid Black Swan Zones
What It Does
Flags volume climax (surge) and squeeze (drought) extremes either at static 80/20 thresholds (top 20% / bottom 20% historically) or at the dynamic Fibonacci 3.85σ band, depending on the operator's preference. Each zone is rendered as a glow line that brightens proportionally as the Master approaches.
Method
By default, Dynamic Black Swan Mode is ON for this indicator (matching the volume distribution's wider range vs canonical RSI). The Black Swan high/low values become osc_up4 / osc_dn4 — the Fibonacci 3.85σ proportion of the Master's channel. Toggle the mode OFF to revert to static 80/20 (top/bottom 20% volume thresholds — classic).
The proximity glow uses the canonical f_calc_glow pattern: transparency = 95 - (1 - dist/range) × 75, where range is the half-channel width. At zero distance, transparency = 20 (solid); at full range distance, transparency = 95 (invisible).
Why It Matters
Black Swan events on volume mark institutional climax moments — news breakouts, capitulation, distribution. The dynamic mode lets the indicator self-calibrate per asset and per regime, so a "climax" on a calm Forex pair and a "climax" on a meme stock both trigger at the appropriate statistical extremes rather than at an arbitrary 80% line.
🔹 Classic Price↔Volume Divergence Detection
What It Does
Detects regular bear divergences (price makes higher high while volume percentile pivot makes lower high — Wyckoff "no demand" rally) and regular bull divergences (price makes lower low while volume percentile pivot makes higher low — selling climax / capitulation). Runs on every individual timeframe AND on the Master line directly.
Method
For each TF, f_classic_divergence_vol(length, lookback) runs inside request.security: it detects pivot highs/lows on the per-TF volume percentile via ta.pivothigh / ta.pivotlow, captures pivot values using ta.valuewhen, and compares the current pivot vs the previous pivot. Default pivot lookback is 5 bars (matches the community standard).
Master divergence runs on the chart-TF directly (no request.security), so it always reflects the current chart resolution's pivot structure. When detected, it renders a connecting line + label between the two pivots on the indicator pane (red for bear, green for bull) and triggers the alert_divergence_native alert if enabled.
Per-TF divergence surfaces in the Legend Table's "Div" column: 🔻 for bear, 🔺 for bull, — for none. Multiple timeframes showing the same divergence direction = stronger conviction signal.
Why It Matters
Divergences between price and volume have been a cornerstone of Wyckoff/Volume Spread Analysis for decades. Most TradingView divergence indicators run on a single timeframe — by detecting per-TF AND Master simultaneously, this indicator surfaces both fast warnings (TF1 divergence) and high-conviction confirmations (Master + multiple TFs aligning).
🔹 MTF Legend Table
What It Does
Compact 7×9 table positioned in a configurable chart corner. Surfaces every dimension of the analysis at a single glance: per-TF resolutions, volume percentile values, trend direction, divergence status, Pulse magnitude, named State classification, plus a Master row and a status row.
Method
The table is rendered via table.new(force_overlay=false) on the indicator pane (kept off the price chart for mobile readability). Per-TF cells use:
◇ Col 0: ● TF label (matches ghost line color) + 📡 antenna marker if this TF == chart's native resolution
◇ Col 1: TF resolution string ("5", "15", "60", "240", "D"...)
◇ Col 2: Volume percentile value (color-coded by zone via the thermal matrix)
◇ Col 3: Trend arrow ▲ rising / ▼ falling / ▬ flat (±0.5 percentile point deadzone to avoid flicker)
◇ Col 4: Div indicator 🔺 bull / 🔻 bear / — none
◇ Col 5: Pulse magnitude ratio (color-coded by intensity tier)
◇ Col 6: State name (multilingual EXTREME / HIGH / ELEVATED / NORMAL / LOW / COMPRESSED / SQUEEZE)
The Master row (row 7) merges cols 0-1 into "🌈 Master (~XhYm)" — the "~XhYm" suffix is the geometric weighted mean of the 5 TF resolutions (same weights as the Master volume fusion), giving you the "effective timeframe" the Master is reading. The status row (row 8) merges cols 0-6 and shows the MTF Divergence summary: Aligned / Strong Top / Strong Bottom / Moderate Top / Moderate Bottom — with background color matching the severity.
All header strings, status messages, and state names support 5 languages via the System Language input (English / Português / Español / Русский / 中文).
Why It Matters
The Legend Table compresses what would otherwise require 5 separate chart panels into a single ~150-pixel-wide compact widget. The antenna marker is especially useful on mobile: it tells you instantly which row is "your" timeframe, so you can scan up/down to see whether faster/slower TFs confirm or contradict.
🔹 Volume Profile Reading — Pulse Magnitude + State Classification
What It Does
Two complementary readings that answer different questions about volume — both surfaced as dedicated columns in the Legend Table.
Method — Pulse Column
Pulse is the ratio volume / SMA(volume, length) per TF. 1.0× = volume at the baseline; below = drought; above = elevated. Color-coded by intensity tier:
◇ < 0.5× → aqua (drought extreme)
◇ 0.5-0.8× → teal (below baseline)
◇ 0.8-1.3× → gray (typical)
◇ 1.3-2.0× → yellow (elevated)
◇ 2.0-3.5× → orange (high activity)
◇ 3.5-6.0× → red (surge)
◇ ≥ 6.0× → purple (climax extreme)
Pulse values cap display at "9.9x+" to avoid overflow in narrow cells.
Method — State Column
State classifies the percentile rank into 7 named tiers using a multilingual dictionary:
◇ ≥ 85 → EXTREME (purple zone — top 15% historically)
◇ 71-85 → HIGH (red — top 30%)
◇ 62-71 → ELEVATED (orange)
◇ 38-62 → NORMAL (yellow / green — middle 24%)
◇ 29-38 → LOW (teal)
◇ 15-29 → COMPRESSED (blue)
◇ ≤ 15 → SQUEEZE (aqua — bottom 15%)
Why It Matters
Pulse and State answer different questions about the same volume reading:
◇ Value (percentile column 2): "Where in the historical distribution?" — a ranking answer.
◇ Pulse (column 5): "How intense vs recent baseline?" — a magnitude answer.
◇ State (column 6): "What's the human-readable label?" — a vocabulary answer.
These three columns together tell a complete story. A bar can be at Percentile 60 (NORMAL state) with Pulse = 3.5x (red surge) — meaning: "this bar's volume isn't historically rare, but it's a massive jump versus what's been happening recently." That's a different signal than Percentile 95 / Pulse = 1.0x (EXTREME state but typical magnitude) — meaning: "this is a rare historical bar, but the magnitude is normal relative to recent activity." The columns disambiguate.
🔹 Delta Twin Bars (Chart Overlay)
What It Does
Renders per-candle directional bars on the price chart (via force_overlay=true) whose dimensions encode the selected volume score and whose color encodes buy/sell pressure approximation. Bridges the gap between this script's oscillator pane and the price action itself.
Method
For each candle, the bar size = candle_range × (score / 100) × user_multiplier. The score source is configurable (Master or any TF1-TF5; default TF1 Trigger for the most responsive read).
Four display modes:
◇ Fixed High: bar always projects above the candle high (regardless of direction)
◇ Fixed Low: bar always projects below the candle low
◇ Dynamic: buy candles get bar above high, sell candles get bar below low (intuitive directional reading)
◇ Dynamic Inverted (default): buy candles get bar BELOW low, sell candles get bar ABOVE high — an order book metaphor where buy pressure builds support and sell pressure presses resistance
Bar color follows the user-configured buy/sell colors (green / red by default — matching the OHLC tick rule: close > open = buy bias, close < open = sell bias). An optional toggle ("Use Master Line Color") overrides this with the Master zone color via the thermal matrix — giving rainbow-colored bars that match the pane oscillator.
Bar width is pixel-controlled (1-8, default 8) via line.new with the user-selected linewidth — visually independent of chart zoom, distinguishable from candle wicks at any chart density.
Two update modes:
◇ Live (default): the current bar's twin bar updates on every tick — score, direction, and color reflect real-time data. When the bar closes, the live line is "frozen" into the confirmed pool. One additional persistent line is used (zero pool overhead).
◇ Confirmed-only: twin bar appears only when the candle closes (useful for backtesting comparisons where intra-bar flicker is unwanted).
The last 500 bars are rendered (Pine v6 line pool limit) with rolling FIFO management — older candles fall out of the pool and lose their twin bar, but the most recent 500 stay live.
🚨 Honest tick-rule disclosure
The buy/sell direction encoding uses the OHLC tick rule — close > open = buy bias, close < open = sell bias. This is NOT order-flow tick-data delta. Pine Script v6 has no tick-by-tick data access in indicator scripts on the free tier. The OHLC approximation is what virtually every "delta" indicator on TradingView free uses; this script discloses it transparently rather than claiming real order flow.
For most use cases (visual confirmation, trend bias, magnitude readings) the OHLC approximation captures the essential information. Traders who need true bid/ask delta should look at paid Order Flow tools or Sierra Chart / Bookmap.
Why It Matters
The Delta Twin Bars combine two analytical layers in a single indicator: the oscillator pane (Master fusion + ghost lines + Legend Table) and the chart overlay (per-candle directional reference). Most TradingView indicators force users to choose between oscillator-only or overlay-only paradigms; this script delivers both via force_overlay=true on selectively-rendered lines, preserving full pane functionality while adding a quick visual reference directly on the price candles.
🔹 Multilingual Interface
What It Does
Translates all HUD labels, status messages, alert text, state classifications, and Legend Table headers to 5 languages: English (default), Português, Español, Русский, 中文 (Chinese). 33 multilingual keys are maintained across all 5 languages.
Method
A single language dropdown input (in the GLOBAL SETTINGS group) selects the active language. The script uses Pine v6's _l == "PT" ? ... : _l == "ES" ? ... ternary chain pattern for each translated string, evaluated once at startup. Configuration tooltips, variable names, and code comments remain in English by convention — this script is designed to be readable to developers globally.
Why It Matters
Trading is a global activity. The Rainbow Matrix product family is designed for traders worldwide; multilingual UI removes a friction point for non-English-native users without adding development overhead.
HOW TO USE
Reading the Rainbow (Pane Oscillator)
◇ Master between 30 and 70 with all 5 ghost lines solid: typical volume profile, no anomaly to flag.
◇ Master entering Z-Alert (orange / teal bands): notable volume deviation — watch for follow-through confirmation across timeframes.
◇ Master in Z-Exhaustion (red high / blue low): elevated probability of climax or drought completing.
◇ Master touches Black Swan High (purple glow): volume climax event — statistically rare top-of-distribution moment, often coincides with news catalysts, breakouts, or capitulation.
◇ Master touches Black Swan Low (aqua glow): volume drought / squeeze — extreme compression, often precedes breakouts when paired with price consolidation.
Reading the Legend Table
The antenna marker (📡) flags your chart's native timeframe. Start your read there, then scan up/down the table to see whether faster/slower TFs confirm or contradict the current volume bias. Look at the relationship between Value (where in distribution), Pulse (how intense vs baseline), and State (named tier) for each row — divergences between these three readings within a single TF are early warnings.
The status row at the bottom summarizes MTF divergence: Aligned (TFs in agreement, default), Strong Top (TF1 ≥ 70 vs TF5 ≤ 30 — fast surge with slow drought), Strong Bottom (TF1 ≤ 30 vs TF5 ≥ 70 — fast quiet with slow surge), or Moderate variants of either.
Reading the Delta Twin Bars (Chart Overlay)
Tall bars = high volume score for that candle's TF source. With Dynamic Inverted mode (default), bars projecting BELOW buy candles signal "support building"; bars projecting ABOVE sell candles signal "resistance pressing" — an order book metaphor. Switch to Dynamic mode for a more intuitive directional read (buy bars project up, sell bars hang down). Use Fixed High/Low for cleaner price action when delta-only context is needed.
Reading Divergences
Master divergence (red line + 🔻 label on the pane) = price made a higher high while Master volume percentile made a lower high — Wyckoff "no demand" rally, often precedes reversal. Master bull divergence (green + 🔺) = price made a lower low while Master volume made a higher low — selling climax, often precedes bottom.
Per-TF divergences in the Legend Table's Div column give early granular warning: a TF1 divergence might fire 5-10 candles before the Master confirms. Multiple TFs aligning on the same divergence direction = high-conviction signal.
Tactical Combinations
◇ Master Black Swan High + Strong Top divergence + Bear Master divergence simultaneously = strongest reversal signal from highs.
◇ Master Black Swan Low + Strong Bottom divergence + Bull Master divergence = strongest reversal signal from lows.
◇ Master SQUEEZE state + multiple TFs SQUEEZE state + Pulse < 0.5x = pre-breakout compression — often precedes expansion events.
◇ Pulse spikes (red / purple tier) preceding percentile shifts = often mark turning points before the percentile catches up.
◇ Pair with MTF RSI Synchrony: Aligned RSI + Aligned Volume = high-conviction setup. Bear RSI div + Bear Volume div on Master simultaneously = strongest reversal signal.
INPUTS EXPLAINED
GLOBAL SETTINGS
◇ System Language (EN / PT / ES / RU / ZH) — affects HUD and alerts only; code stays in English.
◇ Table / Labels Font Size — Tiny / Small (default) / Normal / Large.
MULTI-TIMEFRAME
◇ AI Auto-Sync TFs — when ON, auto-adjusts the 5 TFs based on chart resolution.
◇ TF1-TF5 — manual TF override (defaults: 5/15/60/240/D).
◇ Default Volume Percentile Length — global default (default 50).
◇ TF1-TF5 Length Overrides — per-TF overrides; defaults 30/50/80/100/150; set to 0 to inherit global.
ENGINE
◇ Dynamic Black Swan Mode — ON by default (Fibonacci 3.85σ adaptive). OFF = static 80/20.
◇ Dynamic Channel Lookback (default 50) and Smoothing (default 10).
◇ Divergence Pivot Lookback — default 5 (community standard).
VISUALIZATION
◇ TF1-TF5 Color + Show toggles — TF1 and TF5 visible by default; TF2/3/4 hidden (opt-in).
◇ Ghost Fade Sensitivity — default 3.5 (lines invisible at ~20 percentile points from Master).
◇ Show Master Line / Show Rainbow Fills / Show Black Swan / Show Dynamic Channel — all default ON.
◇ Show MTF Legend Table — default ON.
◇ Show Divergence Column / Pulse Column — both default ON.
◇ Show Master Divergence Chart Line — default ON.
◇ Legend Table Position — Top/Bottom × Left/Right (default Bottom Right).
◇ Show Divergence Event Markers — default OFF (reduces clutter; toggle ON to display triangles).
◇ Show Static Reference Lines — default OFF (cleaner pane on install; toggle ON for 20 / 50 / 80 guides).
ALERTS
◇ Alert on Black Swan crossings (high / low) — default ON.
◇ Alert on Strong MTF Divergence — default ON.
◇ Alert on Z-Exhaustion zone entries — default OFF (opt-in).
◇ Alert on Master Classic Divergence — default ON.
DELTA TWIN BARS
◇ Show Delta Twin Bars — default ON.
◇ Score Source — Master / TF1 (default) / TF2 / TF3 / TF4 / TF5.
◇ Display Mode — Fixed High / Fixed Low / Dynamic / Dynamic Inverted (default).
◇ Buy / Sell Colors + Transparency + Size Multiplier — fully customizable.
◇ Use Master Line Color (override) — default OFF; toggle ON for rainbow-colored bars.
◇ Bar Width (pixels) — 1-8, default 8 (bold, high-visibility).
◇ Lookback (bars) — default 500 (Pine v6 pool maximum).
◇ Live Bar (intra-bar update) — default ON; toggle OFF for confirmed-only rendering.
IMPORTANT NOTES
🔸 Pine Script v6 — uses request.security with lookahead=barmerge.lookahead_off for anti-repaint integrity. The 5 per-TF volume fetches + 5 per-TF Pulse fetches + 5 per-TF divergence fetches + 6 other security calls = 21 total request.security calls; within TradingView's free-tier limits but noteworthy if combining with other heavy multi-TF indicators on the same chart.
🔸 Repaint behavior — historical bars use confirmed close data; the current real-time bar updates as ticks arrive (especially with Live Delta Bars enabled). The pivot-based divergence detection requires div_lookback confirmed bars before triggering — so divergence labels appear on the pivot bar in retrospect, not as live signals. This is standard pivot divergence behavior across all TradingView divergence indicators.
🔸 Tick rule approximation — Delta Twin Bars use the OHLC tick rule (close > open = buy bias) as a direction encoder. This is NOT real order-flow tick data. Pine Script v6 has no tick data access in indicator scripts. Same approximation is used by virtually every "delta" indicator on the TradingView free tier; this script discloses it transparently. For real bid/ask delta, use paid order flow tools.
🔸 Pine v6 line pool limit — Delta Twin Bars are bounded to 500 lines (Pine v6 hard limit). Older candles fall out of the rolling FIFO and lose their twin bar — this is a Pine engine constraint, not a bug. The current bar's live line uses ONE persistent slot reused across bars (no additional pool consumption).
🔸 Fibonacci ratios are canonical — the channel proportions (1.50 / 1.85 / 2.75 / 3.85) match the Rainbow Matrix brand standard across all sibling indicators. They are derived from the brand's design system and are not user-configurable — preserving cross-indicator visual consistency.
🔸 Master effective TF — the "~XhYm" label in the Master row is the geometric weighted mean of the 5 TF resolutions (same weights as the Master fusion: 0.15/0.20/0.25/0.25/0.15). With defaults 5/15/60/240/D, the effective TF is approximately 71 minutes (~1h11m). This tells you the "average horizon" the Master is reading.
🔸 License: MPL 2.0 (Mozilla Public License 2.0) — open source. Free to fork, modify, and republish under the same license terms.
UNIQUENESS
Three pillars differentiate this from the dozens of volume indicators already on TradingView:
1. Multi-timeframe percentile fusion with synchrony as a visual property. Most volume tools operate on a single timeframe with raw unbounded readings. This indicator bounds every reading to a 0-100 percentile scale, fuses five timeframes via Fibonacci-proportioned weights, and expresses synchrony itself as a "rainbow density" — solid when aligned, spread-out when diverging. The disagreement between fast and slow timeframes becomes immediately readable.
2. Three complementary volume readings in one Legend Table. Value (percentile rank), Pulse (magnitude ratio), and State (named tier) answer three different questions about the same volume reading. Most indicators give you one number; this one disambiguates "rare historical event" from "extreme recent magnitude" from "elevated relative position." The combination catches signals that single-metric views miss.
3. Combined oscillator + chart overlay in a single script. Delta Twin Bars project the per-candle volume score and tick-rule direction directly onto the price chart via force_overlay=true, while the full pane oscillator (Master fusion, ghost lines, Legend Table, divergence engine, dynamic channel) continues to operate independently. Most TradingView indicators force you to choose between oscillator-only or overlay-only paradigms; this script gives you both, with honest disclosure about the OHLC tick rule approximation.
Rainbow Matrix AI | Multi-timeframe institutional analysis tools for traders.
🌐 rainbowmatrix.ai
✉️ Contact: contact@rainbowmatrix.ai Indicador
Smart Trend Flow Pro [MarkitTick]💡 Navigating modern market structures requires a robust mechanism capable of filtering out transient noise while capturing the dominant directional vectors. The Smart Trend Flow pro is an advanced analytical framework designed to dynamically track market momentum and volatility, transforming complex price action into a highly readable, visual heatmap. By synthesizing trend identification with continuous volatility scaling, this tool aims to provide clarity in both ranging environments and high-expansion phases, allowing for more structured and disciplined market analysis.
✨ Originality and Utility
● A Paradigm Shift in Trend Visualization
Traditional channel-based indicators often suffer from severe lag or become entirely unreadable during periods of intense market contraction. The utility of this script lies in its adaptive ability to map structural boundaries and instantly correlate them with localized market energy. By discarding static thresholds in favor of a dynamic, self-adjusting baseline, the tool presents a unified view of both direction and conviction.
● Beyond Binary Signals
Standard indicators frequently rely on binary conditions—such as a simple moving average crossover—which ignore the underlying volatility context. This script pioneers a synthesized approach where the strength of a trend is continuously evaluated against its own historical variance. This allows users to visually differentiate between a low-conviction drift and a highly energized breakout, providing a much richer context for potential trade management and risk assessment.
🔬 Methodology and Concepts
● Dynamic Boundary Engine
At the core of the script is a reactive boundary detection mechanism. Rather than projecting fixed bands, the engine establishes fluid upper and lower parameters based on recent localized extremes. These boundaries can be structurally smoothed using various adaptive algorithms, effectively tuning the sensitivity of the channel to match the specific rhythm of the asset being analyzed.
● Volatility Normalization Process
To accurately gauge market energy, the framework continuously measures the distance between the established boundaries. This raw measurement is then subjected to a rigorous statistical normalization process. By evaluating current fluctuations against a rolling historical baseline, the engine maps the resulting variance onto a bounded curvilinear scale. This abstract transformation isolates the pure kinetic energy of the market, stripping away absolute price dependencies to provide a standardized metric of volatility expansion and contraction.
● Integrated State Tracking
The logical engine monitors the interaction between the closing prices and the smoothed boundary parameters. A structural shift is recognized only when price definitively breaches and sustains its position relative to these dynamic thresholds. This state-tracking ensures that the primary directional bias is maintained until a statistically significant reversal occurs, minimizing false positives during minor retracements.
🎨 Visual Guide
● Color-Coded Heatmap Candles
The primary visual feature is the complete transformation of the standard candlestick chart into a continuous heatmap. The colors directly correspond to the synchronized output of the trend direction and the normalized volatility metric.
Bullish Gradients: When the market establishes an upward bias, the candles transition through a cool-to-hot spectrum. Deep, cold colors represent low-volatility accumulation phases, while bright, hot neon colors signify intense, high-volatility bullish expansion.
Bearish Gradients: Conversely, downward structural shifts are mapped using a separate color spectrum. Dark, muted tones indicate slow, grinding bearish action, whereas vivid, hot colors highlight rapid, high-volatility sell-offs.
Neutral States: When the price resides within the core boundary parameters, demonstrating no clear directional dominance, the candles default to a flat, neutral gray to reduce visual noise.
● Signal Markers
Buy Labels: Distinct markers appear precisely below the price action when the engine confirms a definitive upward structural breach.
Sell Labels: Clear markers are printed above the price action upon the confirmation of a downward structural breach.
📖 How to Use
● Interpreting the Heatmap
The most effective way to utilize this tool is to read the candle colors as a topographical map of market energy. A transition from a neutral state into a cold bullish or bearish color suggests the early formation of a trend. As the colors heat up and transition toward their neon extremes, it confirms that the directional move is being supported by expanding volatility, which often characterizes the most robust phase of a trend.
● Managing Trend Exhaustion
Traders can monitor the intensity of the heatmap to gauge potential momentum decay. If a strong trend has been characterized by hot, neon colors, a gradual cooling off—where the colors revert to darker, colder shades—may indicate that the localized volatility is subsiding, suggesting potential consolidation or a pending structural shift.
● Confirming Breakouts
The printed Buy and Sell labels serve as structural confirmation points. These markers are best utilized not in isolation, but in confluence with the heatmap. A signal label accompanied by an immediate transition into a high-volatility color spectrum carries significantly more analytical weight than a signal that remains mired in a cold or neutral visual state.
⚙️ Inputs and Settings
● Channel Settings
Channel Length: Determines the primary lookback window for establishing the core upper and lower boundaries. Increasing this value creates a wider, slower-moving channel, while decreasing it makes the system highly sensitive to recent price action.
Channel MA Type: Allows the user to apply different smoothing algorithms to the boundaries. Options range from the standard baseline to advanced weighting methods, providing precise control over signal reactivity.
● Analytics Settings
Squeeze/Z-Score Length: Defines the historical window used to evaluate the relative volatility. A longer length provides a smoother, more macro-level volatility assessment, while a shorter length makes the heatmap highly reactive to sudden micro-expansions.
● Candle Heatmap Settings
Bullish/Bearish Color Controls: Fully customizable inputs allowing the user to define the exact hex values for the cold and hot extremes of both the bullish and bearish spectrums.
Neutral Market Base: The default color applied when the market is bound within the channel without a confirmed directional state.
● Signal Settings
Label Colors: Configurable color selections for the printed Buy and Sell confirmation markers.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
● Topological Price Mapping
At a fundamental level, the script treats financial time-series data not as discrete data points, but as a continuous topological surface. By evaluating the highest and lowest ranges over a specified temporal window, it effectively creates a rolling bounding box that encapsulates the probable distribution of future price vectors. The application of sophisticated moving average algorithms to these boundaries acts as a low-pass filter, mathematically attenuating high-frequency noise and exposing the true underlying macroeconomic drift.
● Non-Linear Variance Scaling
The most complex aspect of the engine is its approach to variance. Standard deviation on its own is an unbounded metric, making it difficult to utilize in a standardized visual format. The script solves this by isolating the width of the bounding box and comparing it against its own moving average and standard deviation. This transforms the raw width into a standardized probabilistic metric.
● The Sigmoidal Activation Function
To achieve the seamless visual gradient, this standardized variance must be mapped onto a finite plane. The engine employs a logistic function—specifically, a sigmoidal activation curve—to compress the unbounded variance data strictly between a 0 and 100 scale. This non-linear mapping ensures that the visual heatmap remains highly sensitive to subtle shifts around the mean, while gracefully asymptotically compressing extreme, outlier volatility spikes, thereby maintaining absolute visual coherence regardless of the asset's inherent behavior.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicador
Probabilistic Regime Tensor [JOAT]Probabilistic Regime Tensor
Introduction
Probabilistic Regime Tensor classifies market state into Trend, Mean Reversion, or Shock using logistic transforms of statistical inputs.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Trend Probability
Regression slope, variance ratio, and normalized return behavior feed the trend model.
2. Mean-Reversion Probability
Contracting variance ratio, weak slope, and autocorrelation behavior feed the reversion model.
3. Shock Probability
Volatility rank and fast/slow return divergence feed the shock model.
4. Probability Entropy
The three probabilities are normalized and entropy shows whether the classifier is decisive or uncertain.
pTrend = logistic(trendInput) / probabilitySum
Features
Three-state probability model
Trend, mean, and shock probabilities
Dominant confidence and entropy
Sparse regime labels
Movable quant HUD
Input Parameters
Statistical and fast windows
Dominant probability gate
Cooldown
Candle and HUD toggles
HUD position selector
How to Use This Script
Use PRT to decide which style of analysis is more appropriate: continuation, mean reversion, or volatility caution.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
PRT is original in using normalized logistic probabilities and entropy to classify market regime.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Indicador
Automatic Support & Resistance1. Overview
This is an automatic Support and Resistance (S/R) level detector for TradingView. It identifies significant price pivots (peaks and troughs) based on user-defined settings and plots up to 8 dynamic levels on your chart.
The script is intended for educational and informational purposes to demonstrate automatic S/R detection using pivot points and to help traders identify potential areas of interest.
2. Key Logic & Features
A. Pivot Detection
The script detects price pivots (local highs and lows) using ta.pivothigh() and ta.pivotlow().
Two detection speeds:
Regular Pivots: Use the Right Bars setting to define the confirmation period.
Quick Pivots: Use the Quick Right setting for more sensitive, faster-moving levels.
Source Selection: Choose between using Close price or High/Low values for detection.
B. Level Hierarchy
The script plots eight levels, organized as:
Resistance Levels (Red/Green): Levels 1, 3, 5, 7 (top 4 lines).
Support Levels (Red/Green): Levels 2, 4, 6, 8 (bottom 4 lines).
C. Visual Customization (NEW)
Line Styles: Independently set the style for Resistance and Support lines:
Solid (default for both)
Dotted (uses plot.style_circles)
Dashed (uses plot.style_stepline)
Color Logic: Each level dynamically changes color:
Green: Current close price is above the level (bullish context).
Red: Current close price is below the level (bearish context).
D. Additional Features
show_last=1: Only the most recent segment of each level is shown, keeping the chart clean.
trackprice=true: Extends the line horizontally to the right edge of the chart for easy reference.
3. User Inputs (Customization)
Input Description Default
Left Bars Number of bars to the left of a pivot. 50
Right Bars Number of bars to the right of a pivot (confirmation). 25
Quick Right Faster confirmation period for quick pivots. 5
Source Use Close or High/Low for pivot detection. Close
Resistance Line Style Style for top (resistance) levels. Solid
Support Line Style Style for bottom (support) levels. Solid
4. How to Use
Add the script to any chart.
Adjust Pivot Sensitivity:
Increase Left Bars and Right Bars for longer-term, stronger S/R levels.
Decrease them for more, shorter-term levels.
Use Quick Right to add a more sensitive, faster-responding layer.
Interpret the Levels:
Resistance (top lines): Price may face selling pressure when approaching these levels from below.
Support (bottom lines): Price may find buying pressure when approaching these levels from above.
Green level: Price is currently trading above that level (potentially acting as support).
Red level: Price is currently trading below that level (potentially acting as resistance).
Combine with other tools: Use this as one component of a complete trading strategy, alongside trend indicators, candlestick patterns, or volume analysis.
5. Compliance & Transparency
No Financial Advice: This script is strictly for educational and informational purposes. It does not provide financial advice, trading recommendations, or guaranteed results. All trading decisions are your own responsibility.
Original Work: The code is the original work of the author, based on standard Pine Script pivot functions (ta.pivothigh, ta.pivotlow). It is published under the Mozilla Public License 2.0.
No Guarantee: The accuracy, reliability, or profitability of the detected S/R levels is not guaranteed. Different market conditions may require different parameter adjustments.
6. Technical Notes & Limitations
Version: Converted to Pine Script v6 for optimal performance and future compatibility.
Repainting: Pivot-based levels are non-repainting by nature (ta.pivothigh/low only confirms after the right bars have passed). However, the dynamic coloring reacts to each new bar's close.
Performance: The script is lightweight and runs efficiently on most charts.
7. Credits & Open Source
This script is published under the Mozilla Public License 2.0. You are free to use, modify, and share this code for non-commercial purposes, provided you retain the original license and attribution. No private keys, external dependencies, or hidden functions are included. Indicador
Synapse Trail Pro [WillyAlgoTrader]◆ SYNAPSE TRAIL PRO — FREE & OPEN-SOURCE
Synapse Trail Pro is an overlay indicator that fuses a ratcheted ATR trail, a 3-factor market regime engine, a 5-factor signal quality score, and a complete risk-management layer (SL + TP1/TP2/TP3 + automatic break-even) into one decision-support system. Every signal arrives pre-graded (A / B / C), pre-leveled (SL and three targets drawn on the chart), and pre-contextualized (regime, HTF bias, volume, RSI, ATR percentile — all in one dashboard).
The core problem it solves: classic SuperTrend-style trails fire too many signals in choppy markets, and the trader is left guessing which ones to trust. Synapse Trail Pro keeps the clean visual of an ATR trail but scores each signal 0–100 using multi-factor confluence and tells you the market regime in plain language — so you know at a glance whether the chart wants a trend signal taken or skipped.
This is fully free, open-source Pine v6 — no paywall, no invite, no DM required. Use it, study it, adapt it.
🧩 WHY THESE COMPONENTS WORK TOGETHER
A trail line alone tells you direction. A quality score alone tells you confidence. A regime filter alone tells you environment. None of these are useful in isolation — a high-confidence signal in a choppy regime is still a coin flip, and a clean trail flip in a strong trend with no volume confirmation can still fail.
Synapse Trail Pro fuses them into a single pipeline:
ATR Trail (with optional ratchet) → Direction Flip Detection → Regime Score (ADX + Choppiness + R²) → Quality Score (HTF + Volume + RSI + Regime + Break Strength) → Grade A/B/C → Risk Levels (preset SL + TP1/TP2/TP3) → Break-Even after TP1 → Lifecycle Stats
The trail produces the raw signal. The regime engine tells you whether the market is even capable of trending right now. The quality score weighs five independent confluence factors against that regime. The grade compresses the score into a single letter you can act on. The risk layer then drops your SL, three TPs, and break-even logic onto the chart automatically — so the moment the signal fires, you already see the trade plan.
Without the regime engine, you'd take signals in chop. Without the quality score, you'd treat every flip equally. Without the risk levels, you'd still be calculating SL and TPs manually after the signal. Each component covers a blind spot of the others.
🔍 WHAT MAKES IT ORIGINAL
1️⃣ Ratcheted ATR Trail with Adaptive Volatility Multiplier.
The trail center is an EMA (default 21) of close, with bands at ±ATR × multiplier (default base 1.618 — the golden ratio). When the Ratchet option is on (recommended), the lower band only moves up in a long position and the upper band only moves down in a short — never loosens, only tightens. On a direction flip, the band resets to its raw value.
When the Adaptive Volatility Multiplier is on, the base multiplier auto-scales based on the 100-bar ATR percentile rank:
— Low vol (rank < 30) → multiplier × 0.8 (narrower band, catch the move earlier)
— Mid vol (30–70) → multiplier × 1.0 (default)
— High vol (rank > 70) → multiplier × 1.25 (wider band, avoid noise wicks)
Why this matters: a fixed multiplier overreacts in calm markets and gets whipsawed in volatile ones. Percentile-rank scaling keeps the trail behavior consistent across market conditions.
2️⃣ Composite Market Regime Score (0–100) — three-factor blend.
Each bar, three independent measurements vote on whether the market is trending or choppy:
— ADX (weight 40%) : standard Directional Movement ADX, length 14. Score = min(ADX / 50 × 100, 100). High ADX = strong directional pressure.
— Choppiness Index (weight 35%) : ChopIdx = 100 × log10(sum(TR, N) / (highest(high, N) − lowest(low, N))) / log10(N), then inverted to a trend score: chopScore = 100 − ChopIdx. Length 14. Low choppiness = clean directional movement.
— R² Linearity (weight 25%) : R² = correlation(close, bar_index, 50)². Measures how linearly price is moving. R² near 1 = clean trend, R² near 0 = pure noise.
Final regime score = ADX × 0.40 + chopScore × 0.35 + R² × 100 × 0.25.
Thresholds:
— Score ≥ 60 → Trending (green)
— Score < 35 → Choppy (red) — signals flagged with ⚠ or hard-skipped
— Between → Mixed (yellow)
Why three indicators instead of one: ADX measures strength but lags. Choppiness measures range expansion but can spike on news. R² measures linearity but is noisy on short windows. Combined and weighted, they cover each other's failure modes.
3️⃣ 5-Factor Quality Score (0–100) with letter grading.
When a trail-flip signal fires, it's scored on five confluence factors:
— HTF Bias (max 30 points) : higher-timeframe (4× current TF by default) EMA-50 bias. Match = 30, against = 0, HTF data missing or filter off = 15 (neutral credit).
— Volume Confirmation (max 20 points) : volume > 20-bar SMA × 1.3 (configurable). Auto-bypassed and given full credit on volume-less instruments (FX).
— RSI Momentum (max 20 points) : bullish signal needs RSI > 50, bearish needs RSI < 50.
— Regime Score (max 20 points) : regimeScore × 0.20.
— Break Strength (max 10 points) : how far past the band close pierced, capped at 3 × ATR. breakStrength = min(|breakDist| / ATR, 3) / 3 × 100, then × 0.10.
Grades:
— Score ≥ 75 → A (high-quality, all factors aligned)
— Score ≥ 55 → B (acceptable, most factors aligned)
— Score < 55 → C (weak — most factors against, consider skipping)
A "Min Quality Score" input lets you hide everything below a threshold (e.g., set to 55 to show only A and B grades).
4️⃣ Risk Presets with Per-Trade Snapshot Locking.
Four risk presets (plus Custom) auto-set SL × ATR and TP1/TP2/TP3 as R-multiples:
— Conservative : SL 2.5 × ATR, TP 1R / 2R / 4R
— Balanced (default): SL 1.5 × ATR, TP 1R / 2R / 3R
— Aggressive : SL 1.0 × ATR, TP 1.5R / 2.5R / 4R
— Scalping : SL 0.8 × ATR, TP 0.8R / 1.5R / 2R
— Custom : full manual control
Critical detail: SL and TP multipliers are snapshotted at entry . If you change the preset mid-trade, the open position keeps its original levels — and the Avg R statistic stays accurate (each closed trade contributes its own-time R values).
5️⃣ Break-Even Logic with Diagnostic BE-Save Counter.
When Break-Even After TP1 is on (recommended), reaching TP1 automatically moves the stop-loss to entry price. From the next bar onward, any wick at entry stops out at break-even instead of original SL — letting winners run risk-free to TP2/TP3.
A dedicated BE Saves counter on the dashboard tracks wins that closed because BE-stop fired (TP1 reached but TP3 didn't). A high BE-save ratio is a diagnostic signal that your TP3 may be too far — consider tightening.
6️⃣ Same-Bar Hit Guard + Realistic Closure Logic.
Two guards prevent unrealistic results:
— Entry-bar hold : SL/TP hits are ignored on the entry bar itself. A hairpin wick can't instantly stop out a fresh position.
— Same-bar SL+TP1 : if both SL and TP1 are hit on the same bar, the trade closes as a LOSS (conservative — mirrors realistic broker behavior on a single wick).
Closures are routed through a single classifier function so flip-closures, SL-closures, and TP3-closures are all tallied identically.
7️⃣ Flip Detection + Dedicated Flip Alert.
A "flip" is when an opposite signal fires while a position is still active. The old trade is classified and counted (its TP-reached state determines W/L and R-multiple), THEN the new position opens. A dedicated POSITION FLIP alert fires in addition to the new buy/sell alert, with from-direction, to-direction, prior entry, and new entry — useful for closing managed positions externally.
8️⃣ Unified Dashboard with Three Toggleable Sections.
One positioned table with three sections you can switch on/off individually:
— Trade section : Direction (with grade), SL (with BE marker), TP1/TP2/TP3 (with ✓ on hit), Risk % / R:R with unicode gauge, Bars in Trade.
— Market section : Regime (with 0–100 gauge), HTF bias, Volume status, RSI, ATR | Volatility-rank with adaptive multiplier.
— Statistics section : Total signals + grade breakdown (A:N B:N C:N), Buy/Sell split, Closed trades, W/L, Win rate, Avg R-multiple, BE Saves, Flips.
Dynamic section headers carry live context (e.g., "─── Trade · LONG · 23 bars ───") so the divider itself summarizes state.
9️⃣ Three Trail Visual Schemes for Different Aesthetics.
— Adaptive (Bull/Bear) : classic bright green/red — high visibility.
— Premium Indigo (recommended): muted indigo (long) and earth-brown (short) — financial-terminal aesthetic, never competes with green TP lines.
— Monochrome : neutral grey for ultra-minimal charts.
Optional Double Trail Line adds a dashed secondary line offset by a fraction of ATR (configurable 0.05–1.0 × ATR), creating a "channel" visual. The dashed segments are drawn via a ring-buffer of line.new(... line.style_dashed) instead of plot() — this produces TradingView's native dashed look that plot() can't render natively.
🔟 Theme Auto-Detection + Premium Color Palette.
The indicator detects whether your chart background is dark or light (using color.r(chart.bg_color) < 128) and adapts every palette element accordingly. Theme can also be force-set to Dark or Light. Light-theme variants use deeper, more saturated colors to maintain contrast (e.g., deep crimson SL on white, dark amber for BE).
All label text colors are calibrated for ≥4.5:1 contrast against their background (e.g., dark green text on bright green long labels = 7.8:1 ratio).
1️⃣1️⃣ Webhook-Ready JSON Alerts with Full Payload.
Every buy/sell/flip/SL-hit/TP-hit/BE-activation event can fire as plain text OR structured JSON. The JSON payload includes action, ticker, timeframe, price, SL, TP1/TP2/TP3, R:R, grade, quality score, regime, choppy flag, and flip flag — ready for any webhook automation.
🧠 HOW IT WORKS — STEP BY STEP
Step 1 — ATR + Trail Center: ATR(13) and EMA(21) of close are computed. Raw bands = EMA ± ATR × multiplier (base 1.618).
Step 2 — Adaptive Multiplier (optional): If on, the multiplier scales by 100-bar ATR percentile (×0.8 / ×1.0 / ×1.25).
Step 3 — Ratchet Logic (optional): In a long, the lower band can only move up. In a short, the upper band can only move down. On a direction flip, the band resets to raw.
Step 4 — Direction Flip Detection: Close > prev upper band → direction = 1 (long). Close < prev lower band → direction = −1 (short). A change in direction is the raw signal.
Step 5 — Regime Score: ADX × 0.40 + ChopScore × 0.35 + R² × 100 × 0.25. Trending ≥ 60, Choppy < 35.
Step 6 — Quality Score: HTF (0/15/30) + Volume (0 or 20) + RSI (0 or 20) + Regime × 0.20 + BreakStrength × 0.10. Grade A ≥ 75, B ≥ 55, C < 55.
Step 7 — Filtering: Min Quality threshold, choppy-skip toggle, barstate.isconfirmed gating.
Step 8 — Risk Levels: SL = entry ± ATR × slMult. TP1/TP2/TP3 = entry ± slDistance × tpMult. All snapshotted to the trade.
Step 9 — Lifecycle: On TP1 first-touch → BE activates (SL → entry). On SL or TP3 → trade closes, classified by tp1Reached (WIN if true, LOSS if false), R-multiple credited (1/3 per TP partition), state reset.
Step 10 — Visuals + Alerts: SL/TP lines drawn forward, labels updated on hit (✓ + cyan), alerts fired with full payload, dashboard updated.
📖 HOW TO USE — BEGINNER GUIDE
🎯 Quick start (5 steps):
1. Add Synapse Trail Pro to your chart on any timeframe.
2. Open Settings. Leave defaults for the first session — they are tuned for general use (Balanced preset, Premium Indigo trail, HTF filter on, BE on).
3. Wait for the first signal to fire (▲ Long or ▼ Short marker). The marker shows the grade (A/B/C) and a ⚠ flag if in choppy regime.
4. Read the dashboard (top-right by default). Note the Direction , Grade , Regime , and the SL/TP1/TP2/TP3 levels — these are your full trade plan.
5. Execute the trade in your broker using the SL and TPs from the dashboard. Optionally partition position 1/3 at each TP.
👁️ Reading the chart:
— 🟢 ▲ Long Grade-letter below a bar = Buy signal. Color matches grade quality.
— 🔴 ▼ Short Grade-letter above a bar = Sell signal.
— ⚠ next to the grade = signal fired in choppy regime (be cautious or skip).
— Trail line = current direction context. Indigo = long bias, terracotta = short bias (in Premium scheme).
— Dashed secondary line = soft/hard limit zone, offset by a fraction of ATR.
— ENTRY line (dotted blue) = your entry reference price.
— SL line (solid red) = your stop-loss.
— TP1 / TP2 / TP3 lines (dashed green) = your take-profit targets. Turn solid teal with ✓ on hit.
— Entry → SL (BE) label in amber = break-even is active (TP1 was reached, SL is now at entry).
📊 Dashboard fields (Trade section):
— Direction : LONG / SHORT / FLAT + Grade letter.
— SL : stop-loss price. Shows "BE @" prefix when break-even is active.
— TP1 / TP2 / TP3 : target prices. ✓ prefix once reached.
— Risk / R:R : distance % from entry to SL + current R:R + visual gauge.
— Bars in Trade : how many bars since entry.
📊 Dashboard fields (Market section):
— Regime : Trending / Mixed / Choppy + 0–100 gauge.
— HTF : higher-timeframe bias (Bullish / Bearish / Flat / off).
— Volume : Confirmed / Weak / no data / off.
— RSI : current 14-period RSI value, color-coded.
— ATR | Vol : ATR value, 100-bar volatility percentile, and current adaptive multiplier.
📊 Dashboard fields (Statistics section):
— Signals : total fired + breakdown (A:N B:N C:N).
— Buy / Sell : directional split.
— Closed : total wins + losses (flip, SL, and TP3 closures all counted).
— W / L : wins / losses.
— Win Rate : TP1-reached = WIN. Color-coded ≥ 55% green, ≥ 45% yellow, else red.
— Avg R : average realized R-multiple per closed trade.
— BE Saves : wins that closed because BE-stop fired (diagnostic).
— Flips : trades closed by opposite signal mid-position.
💡 Beginner trading workflow:
1. Start with the Balanced preset and HTF Bias Filter ON .
2. Only take A-grade or B-grade signals — set Min Quality Score to 55.
3. Skip every signal flagged with ⚠ (choppy regime) until you understand the regime engine — or enable Hard-skip Choppy .
4. Use the Premium Indigo trail scheme — the muted colors keep your focus on the SL/TP levels, not the trail itself.
5. Always partition position 1/3 at each TP — that's what the R-multiple math assumes.
6. After 30–50 trades, review the Statistics section: if Avg R is positive, the setup works. If BE Saves > 30% of wins, consider tightening TP3.
🔧 Tuning guide:
— Too many signals: increase Min Quality Score to 75 (A-grade only), enable Hard-skip Choppy.
— Too few signals: lower Min Quality to 0, turn off HTF filter, switch from Balanced to Aggressive preset.
— Stops too tight: switch to Conservative preset (SL 2.5 × ATR).
— Stops too wide: switch to Scalping preset (SL 0.8 × ATR).
— BE stopping you out too often: disable Break-Even After TP1.
— Trail too jumpy: increase Trail EMA Length from 21 to 34, enable Ratchet.
— Trail too sluggish: decrease Trail EMA Length to 13, decrease ATR Length to 8.
— Chart too busy: turn off Double Trail Line and Regime Background, set Trail History Bars to 50.
⚙️ KEY SETTINGS REFERENCE
⚙️ Main Settings:
— ATR Length (default 13): ATR period for volatility band.
— Base ATR Multiplier (default 1.618 — golden ratio): base band width.
— Trail EMA Length (default 21): EMA period for trail center.
— Adaptive Volatility Multiplier (default off): auto-scale multiplier by 100-bar ATR percentile.
— Ratchet Trail (default on): trail only tightens in position direction.
🔍 Signal Filters:
— Min Quality Score (default 0): hide signals below threshold (0 = all, 55 = B+, 75 = A only).
— Hard-skip Choppy Signals (default off): fully suppress signals in choppy regime.
— Use HTF Bias Filter (default on): Quality Score bonus for HTF-aligned signals.
— HTF for Bias (default empty = auto 4×): higher timeframe for bias check.
— Use Volume Confirmation (default off): bonus when volume > 20-SMA × threshold.
— Volume Threshold (default 1.3): volume × SMA20 to count as confirmation.
🌊 Market Regime:
— ADX Length (default 14)
— Choppiness Length (default 14)
— R² Regression Length (default 50)
🛡️ Risk Management:
— Risk Preset (default Balanced): Conservative / Balanced / Aggressive / Scalping / Custom.
— Custom SL × ATR (default 1.5)
— Custom TP1/TP2/TP3 × Risk (default 1.0 / 2.0 / 3.0)
— Break-Even After TP1 (default on): move SL to entry on TP1.
— Show SL/TP Lines / Labels / % Distance : all on by default.
— Entry / SL / TP Line Styles : Dotted / Solid / Dashed defaults.
🎨 Visual:
— Theme (default Auto)
— Trail Color Scheme (default Adaptive Bull/Bear) — try Premium Indigo for a financial-terminal look.
— Trail Line Width (default 2)
— Trail History Bars (default 0 = all)
— Double Trail Line (default on)
— Double Trail Offset × ATR (default 0.25)
— Show Buy/Sell Labels / Grade / Regime Background / Watermark
📊 Dashboard:
— Show Dashboard (default on) — master toggle
— Position (default Top Right) — 6 positions available
— Trade / Market / Statistics Section toggles
🔔 Alerts:
— Webhook JSON Format (default off): plain text or structured JSON.
— Alert on TP Hits (default off)
— Alert on SL Hit (default on)
— Alert on Position Flip (default on)
🔔 ALERTS
— 🟢 BUY — ticker, TF, price, SL, TP1/TP2/TP3, R:R, grade, quality score, regime, choppy flag, flip flag
— 🔴 SELL — same payload
— 🔄 POSITION FLIP — from-direction, to-direction, prior entry, new entry
— 🛑 SL HIT — entry, SL price, time
— 🛡️ BE STOP-OUT — fires instead of regular SL when break-even was active
— 🎯 TP1 / TP2 / TP3 HIT — first-touch only, no duplicate fires
— 🛡️ BREAK-EVEN — fires the bar TP1 is reached and SL moves to entry
All alerts support plain text and JSON webhook format. All fire bar-close confirmed (alert.freq_once_per_bar_close).
⚠️ IMPORTANT NOTES
— 🚫 No repainting. All signals require barstate.isconfirmed. Alerts fire once per bar close. The HTF security() call uses the canonical non-repaint pattern (close + ema with lookahead_on), reading the closed HTF bar without future leakage.
— 📐 The trail flip is the raw signal source; quality score and filters only suppress, never invent signals. Same-bar SL+TP1 always resolves as a LOSS (conservative bias toward stop).
— 📐 Statistics counters are session-scoped — they reset on script reload, input change, or by incrementing the "Reset Stats Counter" input. The Stats section is descriptive, not predictive: past behavior on a chart does not guarantee future behavior on the same chart.
— ⚖️ Win = TP1 reached (regardless of how the trade ultimately closed). Avg R assumes 1/3 position partitioned at each TP. These are conventions; your live execution may differ.
— 🛠️ This is an analysis tool, not an automated trading bot. It detects trail flips, scores quality, projects SL/TP zones, and tracks outcomes — trade decisions and execution remain yours.
— 🌐 Works on all markets and timeframes. Volume-based filters auto-bypass on instruments without volume data (FX). Adaptive multiplier and regime engine scale naturally across symbols.
— 📜 Fully open-source Pine v6. Read the code, fork it, adapt it. Feedback and forks welcome. Indicador
Artemis Wave Oscillator🟦 Artemis Wave Oscillator is a Pine v6 reimagination of the classical WaveTrend family, built on a Welford running-stdev channel and EMA-smoothed normalization. Unlike fixed-band WaveTrend variants that ship with hard-coded levels, the engine continuously rescales itself against its own dispersion — producing a momentum curve that stays perfectly bounded between visually consistent reversion bands on every asset and every timeframe, with no manual recalibration.
The indicator integrates six analytical layers — WaveTrend core, dynamic reversion bands, histogram momentum gauge, extremity reversion dots, regular + hidden divergence detection with a Smart AI Filter, and a theme-adaptive PRO dashboard — each operating independently and rendered on a single, clean oscillator panel.
🟦 HOW THE CORE ENGINE WORKS
**WaveTrend Channel**
Each bar, the engine builds an EMA-smoothed midline from the selected price aggregate over the Channel Length window. In parallel, a Welford single-pass running standard deviation measures the channel width — a numerically stable O(N) algorithm that updates the running mean and squared deviation simultaneously, preserving precision on long histories where naive sum-of-squares accumulators drift.
The raw wave is then computed as:
wave_raw = (src − chanMid) / chanDev × 100
This produces a z-score-like signal scaled to the ±100 range. Dividing by the running standard deviation normalizes the output regardless of asset volatility — BTC, EURUSD, SPY, and a small-cap stock all swing through the same band structure without parameter changes.
**EMA Smoothing**
The raw wave is then passed through an EMA of length Average Length to produce the visible `wave` line. This is the dominant responsiveness control — larger values produce a calmer curve with fewer reversion-zone touches.
**Signal Line**
An SMA of the wave (Signal Length) builds the trigger line. Crossovers between the wave and signal line mark momentum regime changes — the same convention used by classical MACD and Stochastic.
**Histogram**
The wave − signal delta is rendered as a filled area. Two opacity tiers distinguish rising momentum (brighter) from fading momentum (dimmer), so the eye picks up acceleration vs. deceleration at a glance.
**Source Selector**
Nine price aggregates are available:
| Source | Formula | Use case |
|---|---|---|
| Open | open | Open-of-bar bias |
| High | high | Top-of-range tracking |
| Low | low | Bottom-of-range tracking |
| Close | close | Standard, fastest reaction |
| OC2 | (open + close) / 2 | Body midpoint |
| HL2 | (high + low) / 2 | Body-independent midpoint |
| HLC3 | (high + low + close) / 3 | Typical mean — default |
| OHLC4 | (open + high + low + close) / 4 | Smoothest |
| HLCC4 | (high + low + 2×close) / 4 | Close-weighted |
🟦 REVERSION BANDS
The user picks a single Reversion Threshold (T) — the distance from zero (in normalized wave units) beyond which the wave is considered overbought (positive side) or oversold (negative side). Three proportional tiers render automatically:
| Tier | Level | Visual |
|---|---|---|
| Inner | ±T | Outer ring of the gradient fill |
| Middle | ±T × 1.25 | Boundary between outer ring and inner extreme |
| Outer | ±T × 1.5 | Hard outer boundary of the gradient fill |
Because the bands are derived from T, they always wrap the threshold no matter how the user tunes it. A trader scaling T from 80 (volatile assets) to 150 (trending assets) keeps the visual context intact without retuning the band levels.
The Reversion Threshold itself drives three downstream features:
- Extremity Dot triggers
- The "Extremities" bar-coloring mode
- The Dashboard Zone tag (OB / MID / OS)
🟦 EXTREMITY DOTS
OB / OS reversion markers — small dual-layer dots that fire when the wave crosses the signal line beyond the Reversion Threshold:
- **OS dot** (bull theme color) → wave crossed UP past −T
- **OB dot** (bear theme color) → wave crossed DOWN past +T
These are the highest-conviction mean-reversion triggers in the script. The dots use a two-track rendering — a pixel-perfect glow + core visual via `plot.style_circles`, paired with an invisible `label.style_circle` carrying a rich tooltip. Hovering on a dot surfaces:
- Direction (Crossed UP / DOWN through Signal)
- Active zone (Below −T / Above +T)
- Current wave value
- Current signal value
- Trading interpretation (mean-reversion long / short opportunity)
🟦 DIVERGENCE DETECTION
Pivots are calculated using `ta.pivothigh` and `ta.pivotlow` with an arm of `Channel Length / 2`. All divergence results appear `Channel Length / 2` bars late — this is standard Pine Script pivot behavior, not a bug.
**Four divergence types:**
| Type | Price | Wave | Signal |
|---|---|---|---|
| Regular Bull (D▲) | Lower Low | Higher Low | Potential reversal up |
| Regular Bear (D▼) | Higher High | Lower High | Potential reversal down |
| Hidden Bull (H▲) | Higher Low | Lower Low | Uptrend continuation |
| Hidden Bear (H▼) | Lower High | Higher High | Downtrend continuation |
Regular divergence uses solid lines (width 2). Hidden divergence uses dashed lines (width 1) — the thinner, dashed style makes the continuation signal visually quieter than the reversal signal, matching their respective conviction tiers. Labels use bracketed symbols (D▲ / D▼ / H▲ / H▼) and each carries a tooltip-rich hover with price + wave context.
**Smart Divergence Filter (AI)**
An optional pre-filter that rejects low-quality divergences before they render. Three independent gates:
1. **Min Wave Swing** — minimum oscillator swing between the two pivots (default: 5 units). Drops noise-level differences where the wave barely moved between pivots.
2. **Min Price Swing (%)** — minimum price swing between pivots as a percentage of the recent `Channel Length × 4` high-low range (default: 0.3%). Drops divergences where price barely moved relative to recent volatility.
3. **Zone Confirmation** — the wave at the current pivot must sit in the matching reversion half:
- Bullish divergence → wave at LL pivot ≤ −T × 0.5 (oversold half)
- Bearish divergence → wave at HH pivot ≥ +T × 0.5 (overbought half)
This encodes the classical "best divergences form at extremes" rule using the wave value itself as the gate — no MFI or volume input required.
When the master toggle is OFF (default), all detected divergences render. When ON, only divergences that clear all three gates survive. The filter applies identically to both chart rendering and alert conditions — no mismatch between visual and alert signals.
🟦 HISTOGRAM
The wave − signal histogram is rendered as a filled area between the histogram value and the zero line. Two opacity tiers per side:
| State | Color | Opacity |
|---|---|---|
| Bull, rising | thBull | Rising Opacity (default 60) |
| Bull, fading | thBull | Fading Opacity (default 40) |
| Bear, rising | thBear | Rising Opacity (default 60) |
| Bear, fading | thBear | Fading Opacity (default 40) |
Rising bars are the most actionable visual cue — they mark momentum that is accelerating in the active direction. Fading bars indicate momentum stalling.
🟦 BAR COLORING
Five mutually exclusive modes apply a wave-driven color to every price bar on the chart:
| Mode | Behavior |
|---|---|
| None | Leave bars untouched (default) |
| Midline Cross | Bull above zero, bear below zero |
| Extremities | Bull beyond +T, bear beyond −T, neutral elsewhere |
| Reversions | Bull on OS dot trigger, bear on OB dot trigger |
| Slope | Bull when wave > signal, bear when wave < signal |
Colors are pulled from the active theme — no per-mode color picker needed.
🟦 DASHBOARD
A compact 2-column, 7-row data panel renders on the last bar when enabled. Every value derives from variables already computed upstream, so the dashboard adds zero overhead until the final bar.
| Row | Left | Right |
|---|---|---|
| Header | Artemis Wave | ▲ BULL / ▼ BEAR / ■ NEUTRAL |
| Wave | Wave | Current value + trend arrow (▲ ▼ ■) |
| Signal | Signal | Current SMA trigger value |
| Strength | Strength | 10-block monospace bar gauge |
| Zone | Zone | OB / MID / OS tag |
| Div | Div | Most recent divergence within last 50 bars (▲ REG / ▼ REG / ▲ HID / ▼ HID / —) |
| Slope | Slope | ▲ UP / ▼ DOWN / ■ FLAT |
The strength gauge normalizes `|wave − signal|` against 50 (typical mid-amplitude swing) and buckets the result into 10 monospace blocks (`█` filled, `░` empty), giving an at-a-glance read of crossover conviction.
**Theme-Adaptive Chrome**
The dashboard auto-inverts its layout based on the active theme:
- **Dark themes** (Tropic, Amber, Pastel, Cyber, Helios, Electric, Candy, Bloomberg, Solar, Royal): header and footer use a faint `thBull` tint, middle rows stay solid dark, text uses full-saturation `thBull`. Border uses `thBull` at 20% transparency for strong theme presence.
- **Light themes** (Midnight, Graphite): backgrounds flip to white, text stays `thBull` (which is itself dark on these themes), border uses `thBull` at 40% transparency.
This guarantees text legibility against every palette without per-theme manual tuning.
**Position & Size**
Six anchor slots (Top/Middle/Bottom × Left/Right) and four text sizes (Tiny / Small / Normal / Large).
🟦 COLOR THEMES
Twelve cohesive palettes, each resolving to four axis colors:
| Theme | Character | Bull | Bear |
|---|---|---|---|
| Tropic | Cyan steel + deep orange | #00bcd4 | #ff6d00 |
| Amber | Warm amber + indigo blue | #ff9800 | #e53935 |
| Pastel | Sky blue + soft lavender | #4fc3f7 | #9575cd |
| Cyber | Neon lime + hot crimson | #00e676 | #ff1744 |
| Helios | Bright gold + scarlet | #ffd600 | #ef5350 |
| Electric | Electric aqua + magenta | #00e5ff | #e040fb |
| Candy | Neon green + hot pink | #69F0AE | #FF4081 |
| Bloomberg | Terminal orange + cyan | #ff8c00 | #00b0ff |
| Solar | Solarized olive + crimson | #859900 | #dc322f |
| Royal | Imperial gold + deep purple | #ffd700 | #6a0dad |
| Midnight | Deep navy + dark crimson | #0d47a1 | #b71c1c |
| Graphite | Near-black + silver grey | #1a1a1a | #757575 |
All four color roles (bull / bear / neutral / signal) change simultaneously when the theme changes. The whole script reads through these four variables — nothing below the resolver references a raw hex literal, so a single dropdown selection drives every plot, fill, dot, divergence line, dashboard cell and border.
🟦 ALERT SYSTEM
Ten alert conditions, all using `alert.freq_once_per_bar_close`:
| Alert | Condition |
|---|---|
| OS Reversion | Wave crossed UP through signal while wave < −T |
| OB Reversion | Wave crossed DOWN through signal while wave > +T |
| Regular Divergence | D▲ or D▼ detected (respects Smart Filter) |
| Hidden Divergence | H▲ or H▼ detected (respects Smart Filter) |
| Bullish Trend | Wave crossed above the midline (zero) |
| Bearish Trend | Wave crossed below the midline (zero) |
| Bullish Swing | Wave × signal upward cross, regardless of zone |
| Bearish Swing | Wave × signal downward cross, regardless of zone |
Each alert fires through `alert()` so the message body carries live context — direction, current wave value, and the threshold that triggered. Divergence alerts respect the Smart Divergence Filter — if the filter is ON and a divergence is rejected visually, the alert will also not fire.
🟦 SETTINGS REFERENCE
**WaveTrend Core**
- Source — 9 price aggregates. Default: HLC3
- Channel Length — EMA midline + Welford stdev lookback. Default: 10
- Average Length — EMA smoothing of the normalized wave. Default: 21
- Signal Length — SMA smoothing of the wave to build the trigger. Default: 4
**Reversion Bands**
- Reversion Threshold — 50–200, step 5. Default: 100
- Show Band Fills — Toggle. Default: ON
- Band Opacity — 0–100. Default: 30
**Histogram**
- Show Histogram — Toggle. Default: ON
- Rising Opacity — Default: 60
- Fading Opacity — Default: 40
**Extremity Dots**
- Show Extremity Dots — Toggle. Default: ON
**Divergence**
- Regular Divergence — Toggle. Default: ON
- Regular Opacity — Default: 80
- Hidden Divergence — Toggle. Default: ON
- Hidden Opacity — Default: 80
- Label Size — Tiny / Small / Normal / Large. Default: Tiny
- Smart Divergence Filter (AI) — Master toggle. Default: OFF
- Min Wave Swing — Default: 5.0
- Min Price Swing (%) — Default: 0.3%
- Require Zone Confirmation — Default: ON
**Bar Coloring**
- Bar Color Mode — None / Midline Cross / Extremities / Reversions / Slope. Default: None
**Dashboard**
- Show Dashboard — Toggle. Default: ON
- Panel Position — 6 anchor slots. Default: Middle Right
- Panel Text Size — Tiny / Small / Normal / Large. Default: Small
**Alerts**
- OS Reversion — Default: ON
- OB Reversion — Default: ON
- Regular Divergence — Default: ON
- Hidden Divergence — Default: OFF
- Bullish Trend — Default: ON
- Bearish Trend — Default: ON
- Bullish Swing — Default: OFF
- Bearish Swing — Default: OFF
🟦 COMPATIBILITY
Works on all asset classes and all timeframes in TradingView Pine Script v6.
- Crypto: Spot, futures, perpetual contracts
- Forex: All pairs
- Equities: Stocks, ETFs, indices
- Commodities: Metals, energy, agriculture
- Timeframes: 1m through Monthly
The Welford running standard deviation normalizes the wave against its own dispersion, making the engine fully volatility-agnostic. The same default settings work on a 5-second BTC chart and a weekly index chart without retuning.
🟦 TECHNICAL NOTES
- Pine Script v6
- `max_lines_count = 500`, `max_labels_count = 500` (divergence drawings + extremity dot hover labels)
- No repainting — all values calculated on bar close. Pivot-based divergence results appear `Channel Length / 2` bars late by design
- WaveTrend engine intentionally mirrors EliCobra's original Enhanced WaveTrend formulation — the value added by Artemis Wave is in the Pine v6 idioms, the dynamic band scaling, the divergence engine, the Smart Filter, the theme system, and the dashboard, not in altering the well-tested core curve
- UDT fields declared without defaults to comply with Pine v6's compile-time-literal requirement; objects constructed via `Bar.new(...)` and `WaveReading.new(...)`
- `var int x = int(na)` pattern used for safe persistent integer state (pivot bar indices)
- Reversion-band anchors rendered as hidden `plot()`s rather than `hline()`s — `hline()` only accepts compile-time constants, but the band levels are series values driven by the user-tunable Reversion Threshold
- Extremity Dots use a dual-track rendering: `plot.style_circles` for the pixel-perfect visual, plus a parallel invisible `label.style_circle` carrying the hover tooltip (since `plot()` does not support the `tooltip` argument)
🟦 DISCLAIMER
This indicator is provided for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and apply proper risk management. Indicador
Veyra Shift Ledger [JOAT]Veyra Shift Ledger
Introduction
Veyra Shift Ledger is an open-source execution-context ledger that combines trend, pressure, structure, auction location, displacement, and volatility state. It also draws qualified supply and demand zones anchored to confirmed swing memory.
The indicator is designed to show when several independent context layers align, while keeping signals confirmed and visually organized.
Core Concepts
1. Trend and Regime
Fast, mid, and slow EMAs define trend alignment. ADX, RSI, MACD, and VWAP context contribute to directional quality.
2. Pressure Engine
Signed candle body, range location, and volume are used to estimate bid or ask pressure.
3. Auction Location
Weighted price and deviation bands identify premium, discount, and value conditions.
4. Structure and Displacement
Confirmed pivots define swing memory. BOS, sweeps, and FVG-style gaps contribute to the structure side of the ledger.
5. Supply and Demand Zones
Zones are created only when quality gates pass. Demand zones anchor around confirmed pivot lows and supply zones anchor around confirmed pivot highs, with ATR-scaled height.
Features
Long and short ledger scores: Combines trend, momentum, pressure, structure, auction, and HTF context
Confirmed HTF filter: Optional higher-timeframe EMA uses confirmed previous HTF data
Supply/demand zones: Anchored to confirmed swing memory and ATR-scaled
Zone lifecycle: Zones change appearance when mitigated or invalidated
Execution rails: Optional educational entry, stop, and target projections
Dashboard: Shows scores, pressure, auction, structure, volatility, HTF, and trigger state
Input Parameters
EMA lengths control trend memory
Pressure and auction inputs control volume/weighted-price calculations
Pivot confirmation controls structure sensitivity
Score thresholds control signal selectivity
Risk inputs control optional rail projection
How to Use This Indicator
Step 1: Compare ledger scores
The dashboard shows whether long or short context has stronger evidence.
Step 2: Inspect zones
Supply and demand zones are contextual areas, not certain turning points.
Step 3: Watch mitigation state
Zone color changes help distinguish active, mitigated, and invalidated areas.
Indicator Limitations
Supply and demand zones are approximations from chart data
Pivot confirmation creates natural delay
Pressure is candle-derived and not true order book data
Execution rails are educational projections only
Originality Statement
Veyra Shift Ledger combines a multi-factor score ledger with swing-anchored supply/demand zones, auction context, pressure state, displacement logic, and zone lifecycle visualization.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Zones and scores can fail in live markets.
-Made with passion by jackofalltrades
Indicador
Multi-Factor Regime Engine Pro [MarkitTick]💡 This indicator represents a robust framework designed to quantify market regimes by analyzing an array of price action, volatility, and momentum metrics. By synthesizing ten distinct market features into a unified confidence score, it dynamically adjusts its threshold bands, providing a highly adaptive approach to trend identification on any standard chart.
✨ Originality and Utility
Standard trend-following tools often rely on static lookback periods and fixed multipliers, which can lead to delayed signals during sudden market shifts or excessive false signals during consolidation. This indicator diverges from traditional methods by introducing a dynamic, feature-engineered confidence score. Instead of relying on a single data point like closing price or standard volatility, it aggregates inputs from momentum oscillators, directional movement indices, volume profiles, and standard deviation bands. This multi-dimensional analysis allows the indicator's bands to compress during high-confidence trends and expand during uncertain, low-confidence environments, offering a highly responsive and adaptive utility for modern chart analysis. Furthermore, it incorporates strict internal safeguards to prohibit execution on non-standard charts, ensuring the integrity of the data and preventing repainting vulnerabilities.
🔬 Methodology and Concepts
● The Feature Engineering Engine
The core of this indicator is built upon extracting ten distinct normalized features from the market data, evaluating multiple dimensions of price action simultaneously:
Momentum Normalization: Utilizes relative strength metrics, centered and scaled, to gauge underlying momentum bias without relying on absolute thresholds.
Directional Strength: Analyzes directional movement indices to quantify the strength of the current trajectory, applying directional penalties when negative movement overpowers positive movement.
Moving Average Distances: Measures the current price relative to fast and slow moving averages, standardizing the distance using the Average True Range to identify structural overextension.
Rate of Change Standardization: Normalizes the rate of change against its own rolling standard deviation to detect statistical anomalies in speed and acceleration.
Standard Deviation Extremes: Evaluates the position of the price relative to upper and lower Bollinger Bands, calculating the precise percentile of the close within the volatility envelope.
Volatility Stability: Compares short-term volatility against long-term volatility baselines to measure market stress and detect rapid expansions.
Volume Anomalies: Assesses current volume against its simple moving average, clamping the result to identify participation spikes that validate price movement.
Price Action Consistency: Calculates the ratio of bullish to bearish closes within the defined lookback period, serving as a raw footprint of buyer versus seller control.
● The Confidence Score Assembly
These standardized features are separated into distinct sub-components. A Directional Score identifies the probable path of the trend by weighting momentum and moving average slopes. A Quality Score measures the structural integrity of that trend by analyzing volume participation and volatility stability. These are mathematically combined to produce a Raw Confidence value. This raw output undergoes an adaptive smoothing process using a dynamic moving average, resulting in a highly stable, final Confidence Score bounded precisely between 0% and 100%.
● Adaptive Ratcheting Bands
The calculated Confidence Score directly influences the width of the trend bands. When the confidence is high, the internal multiplier decreases, tightening the bands closer to the price action to capture shifts quickly and protect accumulated distance. Conversely, when confidence is low, the bands expand to avoid noise and erratic whipsaws. The bands utilize a state-machine logic that only ratchets in the direction of the trend, acting as a trailing threshold that reacts to both price crosses and sudden regime shifts identified by extreme volatility spikes.
🎨 Visual Guide
● Heatmap Candles
The indicator actively repaints the chart candles based on a calculated mathematical "stress" metric.
Colors transition dynamically from a baseline trend color (Deep Sky Blue for bullish conditions, Radical Red for bearish conditions) to a bright orange "Regime Alert" color when underlying volatility spikes significantly.
Candle body opacity is heavily controlled by the alignment of the price action with the overall trend direction, fading to a darker tone during contrary movements or low-confidence pullbacks.
● ML Supertrend Band
Displayed as a prominent, solid line representing the adaptive trailing threshold on the chart.
This band is colored Deep Sky Blue during bullish market phases and Radical Red during bearish phases, updating in real-time as the state machine ratchets.
● Confidence Gradient Cloud
This visual element fills the spatial gap between the median price baseline and the trailing Supertrend band.
The exact opacity and gradient of this cloud are mapped directly to the Confidence Score. A highly opaque, solid cloud represents high confidence, while a highly transparent, fading cloud visually indicates low confidence and potential market transition.
● Visual Labels
Small directional visual markers appear directly above or below the price action when a trend flip occurs.
These labels display an arrow alongside a precise percentage value, representing the exact calculated Confidence Score at the moment the signal was generated.
● Info Table
Located statically in the top right corner, this dashboard displays crucial real-time internal metrics.
It includes the current trend direction, a visual text-based progress bar for the Confidence Score, the live Adaptive Multiplier value adjusting in real-time, the selected Model configuration, and a dynamic text alert that triggers during active Regime Shifts.
📖 How to Use
● Trend Identification
Observe the dominant color of the ML Supertrend Band and the Confidence Gradient Cloud. Deep Sky Blue strongly indicates a bullish environment, while Radical Red suggests a bearish environment. The visibility and thickness of the cloud serve as your primary visual gauge of the trend's structural health.
● Interpreting the Confidence Metric
Monitor the Confidence Score inside the Info Table or at signal generation. A high percentage (e.g., above 70%) suggests that multiple underlying market factors (volume, momentum, standard deviation) are in full agreement with the current directional bias. A rapidly dropping confidence score often precedes a period of choppy consolidation or warns of a potential reversal, allowing for tighter risk parameters.
● Reading Heatmap Candles for Shifts
When the standard colored candles begin transitioning toward the bright orange Regime Alert color, it indicates an abnormal spike in volatility combined with a directional momentum shift. This visually warns the user of a potential "Regime Shift" where the market is undergoing severe internal stress. These specific visual cues often signal an impending breakout from a range or a violent capitulation event.
⚙️ Inputs and Settings
● Model Configuration
Strategic Cycle Mode: Allows the choice between an "Auto" mode and a "Custom" mode. Auto mode dynamically selects the most mathematically optimal lookback lengths, thresholds, and weighting coefficients based purely on the current timeframe in seconds.
Strategic Cycle: When in custom mode, this determines the core lookback period for all volatility and momentum calculations. Smaller values drastically increase reactivity, while larger values provide smoother, long-term macroeconomic analysis.
Macro Trend Threshold: Sets the baseline mathematical width of the threshold bands. Higher values require significantly larger price movements to trigger a trend flip, reducing noise.
Prediction Weight: Controls the internal sensitivity of the bands to rapid changes in the Confidence Score, determining how aggressively the bands compress.
● Visual Settings & Colors
Dedicated toggles are provided to enable or disable the Confidence Labels, the Info Table, and the Heatmap Candles to keep the chart interface as clean as desired.
All core graphical colors, including the specific bands, gradient clouds, table text, and alert highlights, are fully customizable by the user via hex selection.
● Webhook Settings
The indicator is pre-configured to output detailed, formatted JSON payloads designed for external execution automation.
Users can securely define specific action strings for entering and closing both long and short positions directly within the settings menu, mapping exactly to their webhook parser logic.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
● Multi-Variate Feature Standardization
The mathematical foundation of this tool relies heavily on statistical normalization techniques designed to process heterogeneous data. Financial time series data is notoriously non-stationary and spans vastly different numerical scales. To effectively combine disparate metrics like Volume (often measured in millions) and relative strength oscillators (strictly bounded between 0 and 100), the indicator employs rigorous Min-Max scaling and localized Z-score approximations. For instance, the rate of change is evaluated against its own rolling standard deviation over a defined period, successfully standardizing the momentum readout into a continuous, comparable spectrum bounded cleanly between -1.0 and 1.0.
● Linear Weighted Ensembles
The internal architecture utilizes a deterministic linear weighted model to synthesize the final output. By assigning highly specific fractional coefficients to directional features (like the exponential moving average slope and relative strength) and structural features (like Bollinger Band width extremes and volatility stability), the script constructs a singular composite index. This mirrors standard ensemble methodologies found in data science, where the consensus of multiple independent weak learners generates a stronger, more reliable predictive metric than any single indicator could achieve in isolation.
● Volatility-Adjusted State Machines
The adaptive threshold logic operates as a strict finite-state machine incorporating the Average True Range metric. The specific mathematical innovation lies in rendering the ATR multiplier as an inverse linear function of the composite confidence index. In quantitative terms, this produces a dynamically dampened volatility envelope. When the composite index approaches a maximum value indicating high convergence, the dampening factor aggressively compresses the envelope, mathematically acknowledging that high-conviction trends exhibit less erratic mean-reversion behavior and therefore require drastically tighter invalidation levels to preserve structural alpha.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicador
Easy Trend DirectionEasy Trend Direction (ETD) – Smart UI Arrow
Keep your charts completely clean! Easy Trend Direction (ETD) places a dynamic trend arrow directly in the top right corner of your chart , giving you instant, distraction-free visual feedback on the current market structure and momentum.
Instead of cluttering your workspace with multiple moving averages and oscillators, ETD combines the logic of structural EMAs and RSI momentum into one single, elegant UI element.
How it Works
The indicator analyzes two key technical factors to dynamically update the symbol, angle, and color of the arrow in real-time:
Trend Structure (Direction): The script calculates the relationship between a Fast EMA (default 50) and a Slow EMA (default 200).
Fast EMA > Slow EMA = Bullish (Green)
Fast EMA < Slow EMA = Bearish (Red)
If both EMAs are extremely close to each other (defined by the customizable "Neutral Zone"), the market is consolidating, resulting in a Neutral state (Gray, horizontal arrow) .
Momentum (Strength): Once a trend direction is established, the script uses the RSI (default 14) to determine the angle of the arrow.
High momentum (RSI hitting extreme thresholds like 70 or 30) points the arrow straight up or down.
Normal momentum results in a diagonal arrow, indicating a steady, healthy trend.
Key Features
Zero Chart Clutter: Designed for minimalists. The UI table sits quietly in the top right corner, leaving your candles and price action fully visible.
Customizable Arrow Styles: Use the dropdown menu in the settings to choose between three clean, built-in design sets: "Classic Line", "Heavy Blocks", or "Simple Triangles".
Fully Adjustable Logic: Tweak the EMA lengths, RSI momentum thresholds, and the percentage-based "Neutral Zone" to perfectly fit your preferred asset and timeframe.
Theme Integration: Personalize the Bullish, Bearish, and Neutral colors to match your specific chart setup.
ETD is the perfect confluence filter for daytraders and swing traders who want to stay aligned with the trend at a single glance. Add it to your favorites and never lose sight of the market direction again! Indicador
AlphaTrend Momentum Matrix [MarkitTick]💡 The AlphaTrend Momentum Matrix is an advanced, comprehensive trend-following architecture designed to dynamically track market momentum, manage dynamic trade states, and seamlessly bridge the gap between technical charting and automated execution. Far from a simple overlay, this script acts as a multi-layered analytical suite. It evaluates primary trend direction using volatility and volume-weighted money flow, filters out market noise with a custom state-matrix, and projects actionable higher-timeframe data onto the active chart. Furthermore, it incorporates an internal mathematical framework capable of dynamically calculating strict risk-to-reward targets and dispatching meticulously formatted JSON payloads for external webhook execution.
✨ Originality and Utility
● The Momentum Matrix Advantage
While traditional trend indicators rigidly lock onto moving averages or standard price bands, the AlphaTrend Momentum Matrix thrives on market dynamism. Its true utility lies in its multifaceted approach to trend validation. It introduces an exclusive "ATR Breakout Override" system—a custom logic module that forces a trend recalibration if an explosive price movement severely disrupts the standard deviation envelope, regardless of standard trailing conditions. This ensures the indicator remains highly responsive to sudden, high-impact market events without waiting for lagging conditions to catch up.
● Automated Payload and State Management
A standout feature of this tool is its embedded Trade State system. It does not merely paint a signal on the chart; it internalizes the exact entry price, computes a precise stop-loss based on the active AlphaTrend baseline, and mathematically projects a 1:2 risk-to-reward Take Profit target. This localized tracking seamlessly interfaces with the built-in Alert Engine, dynamically injecting these critical metrics into formatted JSON templates ready for third-party automated execution systems.
🔬 Methodology and Concepts
● AlphaTrend Core Engine
The primary directional engine relies on the interplay between the Average True Range (ATR) and the Money Flow Index (MFI). A trailing upper band (Support) and lower band (Resistance) are calculated using a user-defined ATR coefficient. The script interrogates the 14-period MFI; if the MFI reads above 50, indicating positive money flow momentum, the algorithm biases toward the Support band, updating it only when the price makes higher lows. Conversely, an MFI below 50 shifts the bias to the Resistance band.
● Breakout Override Protocol
To counteract the inherent lag of volume-weighted smoothing, the indicator employs a momentum breakout scanner. By measuring the absolute distance between the previous two closing prices and comparing it against the prior ATR multiplied by a sensitivity factor, the script can definitively detect volatility shocks. If a shock occurs concurrently with a directional price cross over the active AlphaTrend line, the system immediately forces a directional shift, bypassing the standard MFI requirements.
● Signal Filtering and Matrix Constraints
Raw signal crossovers are notoriously noisy during consolidation. To mitigate whipsaw trades, this script implements a continuous loop counter (the K and O matrices). It tracks the consecutive bars since the last primary buy or sell condition. A signal is only declared "valid" if it successfully breaks the historical sequence of the opposing trend counter, ensuring that localized micro-fluctuations do not trigger premature trade entries.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
● Volatility and the Average True Range
Developed by J. Welles Wilder Jr. in 1978, the Average True Range is a foundational pillar of this indicator. The ATR scientifically quantifies absolute market volatility by decomposing the entire range of an asset's periodic price action, factoring in gaps and limit moves. By applying a multiplier to the ATR, this script establishes a statistically significant standard deviation envelope, distinguishing between normal market "breathing" and definitive structural shifts.
● Volume-Weighted Momentum via Money Flow Index
The MFI, created by Gene Quigley and Colin Dysart, represents an evolution of the Relative Strength Index (RSI). From an academic standpoint, the MFI incorporates volume into its momentum calculation, producing a more robust metric of buying and selling pressure. It uses the Typical Price (High + Low + Close / 3) multiplied by volume to calculate raw money flow. The 50-level threshold serves as the equilibrium point; sustaining above this level empirically signifies net accumulation, providing the mathematical justification for the indicator's bullish bias.
● Algorithmic State Machines
The signal filtering mechanism and the internal Trade State tracker are practical applications of Finite State Machines (FSM) commonly used in quantitative algorithmic design. The script holds memory of its current operational state (Long, Short, Neutral) and refuses state transitions unless specifically validated mathematical conditions (boolean logic gates) are met, significantly reducing error rates inherent in purely reactive, memory-less indicators.
● Repainting and Lookahead Warning
This script utilizes the request component to pull Higher Timeframe (HTF) context into the primary chart. Crucially, it employs the barmerge.lookahead_on parameter. While this creates a visually perfect, non-lagging representation of higher timeframe trends when analyzing historical data, it introduces lookahead bias. Traders must understand that historical HTF visuals and signals may appear with perfect precision on past bars, but real-time execution will lack this future data context, potentially resulting in different localized behavior in live markets.
🎨 Visual Guide
● The AlphaTrend Trailing Line
Up Trend (Bullish): A bold, solid step-line tracking below the price, rendered in a distinctive golden-yellow (#F0D080).
Down Trend (Bearish): A bold, solid step-line tracking above the price, colored in a deep crimson (#7A2010).
● The Cloud Fill
Dynamic Channel: A semi-transparent shaded area connecting the active AlphaTrend line to a central Cloud Reference Line (a smoothing of the typical price). This cloud visually represents the buffer zone of the current trend.
Color Coding: The cloud dynamically changes color to match the dominant trend (Gold for bullish, Crimson for bearish), allowing for rapid peripheral analysis of market conditions.
● Price Action Overrides
Colored Candles: The bodies and wicks of the actual price candles are uniformly colored to reflect the AlphaTrend matrix state, instantly identifying periods of alignment or divergence.
● Execution Elements
Signal Labels: Distinct "BUY" and "SELL" textual shapes appear precisely on the chart at the moment the state matrix validates a trend shift.
HTF Stepline: When enabled, a secondary, smoothed step-line appears to show the overarching macro trend, colored accordingly to dictate the broader market regime.
📖 How to Use
● Trend Riding and Context
The most effective way to utilize this tool is to align the primary chart timeframe with the HTF AlphaTrend line. If the HTF line is Gold, you should strictly look for "BUY" signals generated by the primary indicator to trade in the direction of the macro trend, ignoring temporary bearish signals as minor pullbacks.
● Momentum Breakout Confirmation
When you observe a sudden color change accompanied by an unusually large price bar, this is often the Breakout Override triggering. These scenarios represent high-momentum events. Instead of waiting for a retest, aggressive traders may use these specific signals to capture immediate volatility expansions, placing their stop-loss strictly on the opposite side of the newly formed AlphaTrend line.
● Automating Your Strategy
For quantitative traders, the indicator handles the heavy lifting of trade logic. Ensure you configure the exact JSON payload strings required by your third-party execution platform (like 3Commas, PineConnector, etc.) in the settings. The indicator will autonomously calculate your risk/reward parameters upon every valid signal and fire a perfectly formatted JSON alert.
⚙️ Inputs and Settings
• ⚙️ Core Calculations
ATR Multiplier: Defines the sensitivity of the trailing line. Lower values (e.g., 0.5) track price closely for scalping; higher values (e.g., 2.0) provide wide breathing room for swing trades.
ATR & MFI Lookback Period: The standard window (default 14) for calculating both volatility and volume momentum.
Display Signals: Toggles the visibility of the "BUY" and "SELL" chart labels.
• 🛡️ Breakout Override
Enable ATR Breakout Override: Turns the momentum-shock detection system on or off.
Breakout Sensitivity: Determines how large a price jump must be (relative to the ATR) to force a trend change. Lower values trigger more aggressively.
• 🕐 Higher Timeframe
Show HTF AlphaTrend: Projects the higher timeframe data onto the current chart.
HTF Timeframe: The specific macro timeframe to monitor (e.g., Daily "D" when trading on the 1-Hour chart).
• ☁️ Cloud Fill
Show Cloud Fill: Toggles the visual buffer zone on the chart.
Cloud Reference Length: Adjusts the smoothing period of the central reference line.
Color Candles: Enables or disables the overriding of standard chart candle colors based on trend direction.
• 🔌 Webhook Execution Config
Payload Actions: Four distinct text fields where you can define the exact syntax your external bot requires for entering longs, entering shorts, closing longs, and closing shorts. These values are automatically injected into the dynamic JSON alert string.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicador
Adaptive Trend Intelligence + SMC + RVOL + ML - FloAlgoThis indicator combines an Adaptive SuperTrend with Smart Money Concepts (SMC) market structure, Relative Volume (RVOL) filtering, and an online Machine Learning model to produce high-confidence trend-following signals.
How It Works
Adaptive SuperTrend — A SuperTrend band whose ATR multiplier scales automatically based on the short/long volatility ratio. In quiet markets the band tightens; in expansions it widens. An optional noise filter requires price to hold on the new side for N bars before a flip is accepted, eliminating whipsaws.
SMC Market Structure Engine — Uses a Stochastic Momentum Oscillator to detect overbought/oversold pivots and build an alternating High/Low swing chain. From those swings it tracks Dow-Theory labels (HH, HL, LH, LL), draws a zigzag, plots S/R zones, and detects BOS (Break of Structure) when price closes beyond the previous major swing confirming trend continuation, and CHoCH (Change of Character) when price closes beyond the prior opposing major swing signaling a trend flip. Both events require an established trend direction and fire only against the correct structural level, preventing false signals on internal corrections.
RVOL Filter — Computes directional buy/sell volume from candle structure and ranks it against a rolling percentile. Signals are suppressed unless the directional volume percentile clears a configurable threshold, keeping entries to high-participation moves only.
Online ML Model — A logistic regression model with L2 regularisation trained incrementally on every confirmed SuperTrend flip. It learns 17 features per signal including candle shape, volume, momentum, ATR slope, RSI, Bollinger position, RVOL, and SMC bias, then resolves each trade when the next flip occurs. Probability is displayed in the info table and can gate signals via a minimum confidence threshold.
Visual Elements
SuperTrend line with bull/bear fill
▲ / ▼ signal arrows and labels
BOS / CHoCH labels at structure breaks
HH / HL / LH / LL Dow labels at each pivot
Zigzag lines connecting momentum pivots
S/R zone boxes, colour-coded and fading on break
Info table showing Signal, Trend, ML Confidence, RVOL, Momentum, Volatility, Quality, MS Bias, and last Structure event
Key Settings
ATR Length — lookback for ATR calculation
ATR Multiplier — base band width
Adaptive Multiplier — auto-scales multiplier with volatility ratio
Noise Filter (bars) — bars price must hold before flip is confirmed
RVOL Lookback — rolling window for volume percentile ranking
RVOL Min Percentile % — minimum directional volume percentile to allow a signal
Min ML Probability % — minimum ML model confidence to allow a signal
Stochastic Length — sensitivity of the momentum pivot oscillator
Overbought / Oversold — stochastic zone thresholds for pivot detection
Filter Signals by MS — gate signals to align with SMC trend direction
Max S/R Zones per Side — maximum supply/demand boxes kept on chart
Indicador
Sentinel Trailing Bench [JOAT]Sentinel Trailing Bench
Introduction
Sentinel Trailing Bench is an open-source contextual trailing-stop overlay designed to behave differently from a standard ATR stop. It blends a sorted price-distribution engine, ATR protection, adaptive recovery behavior, and a benchmark rail so the trailing structure can react to both volatility and local value geometry.
The problem Sentinel solves is stop quality. Simple trailing stops either hug price too tightly in noisy conditions or drift too far away to be useful. Sentinel uses neighborhood structure from a sorted close buffer to estimate contextual bands, then mixes that with ATR logic and recovery tightening when the active side is under pressure.
Core Concepts
1. Sorted distribution engine
The script maintains a rolling close buffer and a sorted mirror of that buffer. This allows it to derive contextual neighborhood slices around the current price instead of relying on ATR alone.
2. Percentile-derived context bands
Supportive and defensive reference levels are estimated from the nearby distribution rather than only from recent swing points.
3. ATR-backed resilience
An ATR anchor remains part of the design so the stop still respects current volatility when distribution structure becomes thin or unstable.
4. Recovery tightening
If price moves materially against the active side relative to the last switch price, the adaptive rail is pulled closer to price to avoid stale trailing behavior.
5. Institutional bench display
The overlay shows the active stop, a benchmark line, the adaptive rail, directional clouding, candle tinting, and a compact dashboard that summarizes trend state, value state, stop gap, and recovery status.
Features
Distribution-aware trailing stop: Uses a sorted close engine and local neighborhood structure
ATR defensive anchor: Keeps the stop grounded in current volatility
Adaptive recovery pull: Tightens the guidance rail when the active side is stressed
Benchmark line and adaptive rail: Adds visual context beyond the raw stop itself
Directional cloud and candle tint: Clean visual bias cues without retail-style arrows
Top-right dashboard: Reports trend state, regime context, value position, stop gap, and recovery status
Confirmed-bar flips: Regime flips are confirmed on closed bars only
Input Parameters
Core:
Distribution Buffer
Neighborhood Radius
ATR Length
ATR Anchor
Benchmark Length
Context:
Distribution Blend
Recovery Threshold xATR
Recovery Pull
Anchor Smoothing
Visuals:
Show Benchmark
Show Adaptive Rail
Show Band Clouds
Color Candles
Show Dashboard
How to Use This Indicator
Step 1: Read the active side
The dashboard and cloud color show whether the stop is currently managing an ascent or descent state.
Step 2: Watch stop gap and rail gap
The dashboard shows how far price sits from the active stop and adaptive rail in ATR terms. This helps frame whether the trailing structure is loose or tight.
Step 3: Monitor recovery
If recovery becomes active, the stop structure is signaling that the current side is under stress and the rail is tightening.
Step 4: Use it as trade management context
Sentinel is most effective as a management tool layered onto entries generated elsewhere.
Indicator Limitations
Distribution-derived bands depend on the sample window and will evolve as new closes enter the buffer
In extremely fast conditions, any trailing stop can still gap beyond the intended exit area
Recovery tightening improves responsiveness but can also accelerate exits in choppy reversals
Originality Statement
Sentinel Trailing Bench is original in how it fuses sorted-distribution neighborhood structure, ATR resilience, and adaptive recovery behavior into one trailing-stop overlay. It is published because:
The stop uses local price distribution context instead of ATR alone
The recovery module changes behavior when the active side is materially under pressure
The benchmark, rail, cloud, and dashboard turn trailing logic into a full management framework rather than a single line
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice and does not guarantee future market behavior. Trailing stops can still be affected by volatility shocks, gaps, and structural changes in the market. Always use independent judgment and proper risk management.
Indicador
RSI Optimized with Smoothings & Divergence (RSI Optimized)This indicator enhances the classic RSI by adding multiple smoothing layers, a dynamic background based on the average of six smoothings, an info table, and regular divergence detection.
🔹 **Core RSI**
Standard RSI calculation (Wilder) with fully adjustable length and source. Overbought/oversold levels (70/30) are highlighted with a gradient fill.
🔹 **Smoothing MA**
Optionally apply a moving average to the RSI line (SMA, EMA, SMMA, WMA, VWMA). The "SMA + Bollinger Bands" mode adds Bollinger Bands around the smoothed RSI.
🔹 **Six Smoothings (instead of a ribbon)**
Six independent moving averages of the RSI (customizable type and lengths) are plotted. Useful to visualise multiple timeframes or sensitivities at once.
🔹 **Background color (RSI vs Avg of 6 Smoothings)**
Compares the RSI value to the simple average of the six smoothings. Green background when RSI > average (bullish bias), red when RSI < average (bearish bias).
🔹 **Info Table**
Displays in real time:
- Current RSI value (color‑coded by overbought/oversold)
- Average of the six smoothings
- Ratio = (RSI + Avg)/2
- Trend direction (based on RSI vs average)
- Zone (Oversold / Overbought / Bull / Bear / Neutral)
- Smooth trend (fast smoothing 1 vs upper smoothing 6)
🔹 **Regular Divergences**
Detects regular bullish and bearish divergences between price and RSI. Pivot lookback is fixed to 5 bars left/right. An alert is available for each divergence type.
🔹 **All options are configurable via the Settings tab** – from lengths, colors, smoothing types to enabling/disabling the table or divergences.
📌 **How to use**
- Use the six smoothings to identify trend alignment (e.g., all above 50 = strong uptrend).
- The background turns green when RSI stays above the average of all smoothings.
- Watch for divergence signals (labelled "Bull" / "Bear") for potential reversals.
- The info table gives a quick snapshot of momentum and trend state.
This tool is ideal for traders who want a richer RSI experience without cluttering the chart.
NOTE PERSO :THANK TRADING VIEW FOR YOU WORKS , YOU ARE BEST !!! & ENJOY TEAM TRADING VIEW MAKE PEACE NOT WARS !!! STAY TUNED !! Indicador
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