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MVRV Z-Score (DEMA Smoothed) | CipherDecodedMVRV Z-Score (DEMA Smoothed) | CipherDecoded Overview The MVRV Z-Score (DEMA Smoothed) is a structural trend-following oscillator derived from Bitcoin’s on-chain capital positioning. Rather than interpreting MVRV purely as a valuation metric, this implementation treats the relationship between market value and realized value as a proxy for capital regime expansion and contraction. By statistically normalizing MVRV and applying Double Exponential Moving Average (DEMA) smoothing, the indicator converts on-chain profitability dynamics into a tradable trend signal. The result is a regime-sensitive momentum framework anchored to underlying cost basis structure. Structural Rationale Market cycles are driven by shifts in aggregate positioning: When market value persistently exceeds realized value, capital is in profit and reflexive expansion tends to dominate. When market value compresses toward or below realized value, distribution and contraction phases emerge. By standardizing MVRV into a rolling Z-score, the indicator measures the velocity and persistence of profitability expansion, not just its magnitude. The subsequent DEMA smoothing filters short-term volatility while preserving structural inflection points, making the signal more suitable for systematic trend models. Inputs BTC Market Capitalization BTC Realized Market Capitalization Daily confirmed data to prevent repainting ​ Z-Score Normalization Rolling lookback mean and standard deviation Converts raw ratio into standardized regime measure DEMA Smoothing Applied to the Z-score output Reduces noise while maintaining responsiveness to regime shifts Trend Threshold User-defined bias level (default: 0.0) Above threshold = expansion regime Below threshold = contraction regime Interpretation This indicator is designed to identify structural trend bias, not overbought/oversold extremes. Sustained positive readings indicate persistent capital expansion. Sustained negative readings indicate structural compression. Threshold crossovers signal potential regime transitions. Slope and persistence are often more informative than absolute level. Design Principles Statistical normalization separates signal from secular growth effects. Smoothing is applied post-normalization to preserve structural information. Inputs are modular, allowing independent control of regime sensitivity and signal responsiveness. Data is requested on confirmed daily closes to ensure signal stability. Strategic Context Unlike traditional price-only oscillators, this framework derives trend information from underlying capital positioning. It therefore reacts to structural shifts in profitability rather than short-term price volatility. This makes it particularly suited for: Medium- to long-horizon trend strategies Macro regime allocation models Risk scaling frameworks Summary The MVRV Z-Score (DEMA Smoothed) reframes on-chain valuation data into a structural trend engine. By combining statistical normalization with adaptive smoothing, it provides a capital-anchored momentum signal designed for regime-based trading and systematic bias control.
Indicador Pine Script®
por CipherDecoded
Ehlers Super Smoother Trend Score [BackQuant]Ehlers Super Smoother Trend Score Overview Ehlers Super Smoother Trend Score is a regime and trend-strength indicator built on a signal-processing filter created by John F. Ehlers. Instead of smoothing price with a standard moving average (which is mathematically crude and prone to noise and aliasing), this indicator applies the Ehlers Super Smoother, a Butterworth-style low-pass filter designed specifically for market data. The filtered series is then scored for directional persistence across a configurable lookback window, producing an oscillator-like trend score that measures how consistently the smoothed trend is advancing or deteriorating. This is not a simple “MA slope” tool. It is: A proper low-pass filter (Super Smoother) to reduce noise while preserving structure. A persistence score that converts the filtered trend into a quantitative regime signal. A threshold framework that turns the score into long/short regime transitions with clean state logic. Where the filter comes from (and why it matters) John F. Ehlers is known for applying digital signal processing (DSP) techniques to technical analysis. Traditional moving averages are not designed as proper frequency-selective filters. They blur price, lag heavily, and can introduce distortions, especially when the market contains high-frequency components (noise) near the Nyquist limit (the maximum representable frequency in sampled data). The Super Smoother is derived from a Butterworth low-pass filter design. Butterworth filters are engineered to have a maximally flat passband, meaning they smooth without introducing ripples in the filtered output. In trading terms: Less “wavy” smoothing artifacts than many MA variants. Better suppression of high-frequency noise. Cleaner trend structure for downstream logic. This script implements Ehlers’ recursive coefficient form, giving you a 2-pole (classic) or 3-pole (heavier) filter. What “Super Smoother” actually is The Super Smoother is a recursive IIR filter (Infinite Impulse Response). Unlike an SMA which averages a fixed window of past values, an IIR filter uses feedback from its own prior output values. That matters because it can achieve strong smoothing with less lag for a given “smoothness target.” Conceptually: Input: price series. Output: filtered estimate of the “low-frequency” component (trend structure). Mechanism: combine current input (or pre-filtered input) with previous filter outputs using coefficients derived from a chosen cutoff period. The coefficients (c1–c4) are not arbitrary, they are computed from exponential decay and cosine terms based on the cutoff period. This is what makes it a real DSP filter rather than “just another MA.” 2-pole vs 3-pole behavior 2-pole (classic) A standard Ehlers Super Smoother configuration. It offers a strong improvement over typical MAs in smoothness vs lag balance. 3-pole Adds an additional feedback term (one more prior filtered state). This increases smoothing and noise rejection, but introduces slightly more lag. The advantage is a cleaner structural line, which often improves regime stability when the market is noisy or mean-reverting. Anti-aliasing pre-filter step Before applying the recursive formula, the script averages the current and previous price: avg = (src + src ) / 2 This is a simple but important pre-filter that reduces high-frequency components that can alias into lower frequencies in sampled data. In practice, it helps stop “one-bar spikes” from contaminating the filter output as much. Inputs and what they really control Super Smoother Period (ssPeriod) This is the cutoff period used in the coefficient derivation. It is not the same as “MA length,” but it behaves similarly in that: Lower period = faster response, less smoothing, more sensitivity to noise. Higher period = smoother output, better noise rejection, more lag. Poles Selects filter order: 2 poles = balanced default. 3 poles = smoother, more conservative. Score Lookback Start/End Defines the persistence scoring window. The script compares the current filtered value to many prior filtered values across that range. A longer range makes the score more “confidence-based” and slower to change, while a shorter range makes it more reactive. Thresholds (Long/Short) Turns the score into a regime classification: Long threshold defines when bullish persistence is strong enough to be considered a trend regime. Short threshold defines when persistence has deteriorated enough to signal a bearish transition. How the trend score is computed After filtering, the indicator computes a directional persistence score on the filtered series (not raw price). That distinction matters because you are scoring structure, not noise. Mechanically: For each i in the scoring window: - If filt_now > filt , add +1 - Else add -1 Sum across the window to produce the score. Interpretation: High positive score means the filtered trend is consistently higher than many past points, persistent bullish structure. Low or negative score means the filtered trend is not advancing, or is consistently below prior points, bearish structure. Scores near the middle mean the filtered series is oscillating without clear persistence, chop or transition. This is a persistence metric, not a slope metric. It does not care about one-bar direction, it cares about consistency relative to history. Signal and state logic (why it stays clean) The indicator uses state logic to prevent constant flip-flopping: Long condition: score > long threshold. Short condition: score crosses below short threshold (uses prevScore and current score). That short logic is event-based, it triggers only on the breakdown transition, not on every bar below the threshold. Once a regime is set, it remains until a real threshold event forces change. Signals are plotted only on regime flips: Long marker when signal becomes +1 and prior was -1. Short marker when signal becomes -1 and prior was +1. This is designed for alerts and for clean backtesting interpretation. Visual layers The indicator can be used purely as a panel oscillator or as a structure overlay. Pane Trend Score line, colored by active regime. Optional reference lines at long/short thresholds for fast regime reading. On-chart (optional) Super Smoother line plotted over price, colored by regime. Optional candle painting and background shading to reflect active regime. This lets you treat the filter as a dynamic trend structure line while using the score as the regime classifier. How to interpret it properly 1) The Super Smoother line This is the cleaned trend structure estimate: When price respects the smoother line, trend structure is intact. When price repeatedly chops through it, structure is weak or range-bound. 2) The score This is the quantified persistence of that structure: Rising score implies strengthening trend persistence. Falling score implies deterioration, transition risk, or mean reversion. Score compression often shows consolidation before a regime shift. 3) Threshold regimes Above long threshold: bullish persistence regime, trend-following conditions. Below short threshold: bearish regime transition, defensive or short-biased conditions. Between thresholds: neutral/transition zone, where chop and fakeouts are common. Practical use cases Trend filter Only take long setups when score is above the long threshold. Reduce exposure or avoid trend trades in the neutral band. Treat a breakdown through the short threshold as regime invalidation. Trend quality assessment High score = continuation environment. Moderate score = trend exists but is fragile. Low/negative score = distribution, downtrend, or unstable structure. Trade management Use the Super Smoother line as a structure reference for trailing risk. Use score deterioration as an early warning before full regime flips. Use regime flips as hard exits or bias changes. Tuning guidelines If you want fewer signals and cleaner regimes Increase ssPeriod. Use 3 poles. Increase scoreEnd (longer scoring window). If you want faster reaction Decrease ssPeriod. Use 2 poles. Reduce the scoring window length. Keep in mind: faster settings increase sensitivity to chop. The filter is good, but no filter removes the reality of mean reversion. What makes this different from “just a smoothed MA score” The difference is the filter quality. The Super Smoother is a proper low-pass filter with coefficients derived from DSP principles, designed to suppress high-frequency noise and avoid common smoothing artifacts. Scoring that filtered structure gives you a regime metric that is more stable and more meaningful than scoring raw price or scoring a basic MA that still carries a lot of aliasing and distortion. Summary Ehlers Super Smoother Trend Score combines a DSP-derived Butterworth-style Super Smoother filter with a directional persistence scoring model. The filter provides a clean, low-noise trend structure series, and the score quantifies how consistently that structure is advancing or deteriorating across a defined window. Threshold-based regime logic converts the score into clean trend states and alerts, making it a practical tool for trend filtering, regime detection, and structure-aware trade management.
Indicador Pine Script®
por BackQuant
4
Relative Valuation Oscillator [QuantAlgo]🟢 Overview The Relative Valuation Oscillator identifies statistical price deviations from fair value using logarithmic price analysis and standard deviation bands. It calculates how far current price has deviated from its mean on a logarithmic scale, normalized by volatility, to generate a centered oscillator that highlights periods when price is statistically stretched above or below its historical average, helping traders identify potential mean reversion opportunities and extreme valuation conditions across different timeframes and markets. 🟢 How It Works The indicator's core methodology lies in its statistical approach to price valuation, where deviations are measured using logarithmic returns and normalized by standard deviation: log_price = math.log(close) mean_log_price = ta.sma(log_price, lookback_period) standard_deviation = ta.stdev(log_price, lookback_period) valuation_score = (log_price - mean_log_price) / standard_deviation First, the script converts price to logarithmic form to account for percentage-based price movements rather than absolute dollar changes, ensuring the indicator works consistently across different price levels and asset classes. Then, it calculates the mean log price over the specified lookback period to establish a baseline fair value reference: mean_log_price = ta.sma(log_price, lookback_period) Next, standard deviation measurement quantifies the typical volatility of log price around this mean, providing a statistical framework for defining normal versus extreme price behavior: standard_deviation = ta.stdev(log_price, lookback_period) The valuation score is then derived by measuring how many standard deviations the current log price sits from its mean, creating a normalized oscillator that fluctuates around zero: valuation_score = (log_price - mean_log_price) / standard_deviation Finally, threshold-based signal detection identifies extreme conditions when the valuation score exceeds user-defined standard deviation multiples: is_overvalued = valuation_score > threshold_mult is_undervalued = valuation_score < -threshold_mult This creates a statistical mean reversion system that identifies when price has deviated significantly from its historical average on a volatility-adjusted basis, providing traders with objective measurements of relative over or undervaluation. 🟢 Signal Interpretation ▶ Undervalued Zone (Below Negative Threshold): Oscillator falling below the negative threshold line indicates price has deviated significantly below its statistical mean = Potential long/buy opportunities for mean reversion strategies ▶ Overvalued Zone (Above Positive Threshold): Oscillator rising above the positive threshold line indicates price has deviated significantly above its statistical mean = Potential short/sell or profit-taking opportunities ▶ Fair Value Range (Between Thresholds): Oscillator remaining between positive and negative threshold lines indicates price is trading within normal statistical bounds. Within this range, the zero line acts as a directional filter: oscillator above zero but below the upper threshold suggests bullish trend/momentum with price trading above its statistical mean = Trend-following long positions can be maintained; oscillator below zero but above the lower threshold suggests bearish trend/momentum with price trading below its statistical mean = Trend-following short positions can be maintained. The oscillator can remain in these directional zones during sustained trends until mean reversion occurs, signaled by crosses back toward zero or transitions to the opposite extreme threshold. ▶ Zero Line Crosses: Oscillator crossing above zero indicates transition from below-average to above-average valuation, confirming shift to bullish momentum = Potential trend-following long entry; crossing below zero indicates transition from above-average to below-average valuation, confirming shift to bearish momentum = Potential trend-following short entry or long exit. These crosses can signal both the start of directional trends and early mean reversion from extreme conditions. 🟢 Features ▶ Preconfigured Presets: Three optimized parameter sets for different trading approaches and timeframes. "Default" provides balanced sensitivity for swing trading on 4-hour and daily charts, generating signals at statistically significant deviations. "Fast Response" delivers more frequent signals for intraday trading on 5-minute to 1-hour charts, reacting quickly to short-term deviations with increased signal frequency. "Smooth Trend" focuses on major extremes for position trading on daily to weekly timeframes, filtering noise to identify only the most significant statistical outliers. ▶ Built-in Alerts: Five alert conditions enable automated monitoring of valuation extremes and transitions. "Overvalued Threshold Crossed" triggers when the oscillator crosses above the positive threshold, signaling potential overvaluation. "Undervalued Threshold Crossed" activates when the oscillator crosses below the negative threshold, signaling potential undervaluation. "Crossed Above Fair Value (0)" and "Crossed Below Fair Value (0)" provide alerts for zero line transitions, indicating shifts between above-average and below-average valuation. "Any Extreme Valuation" offers a combined alert for any threshold breach regardless of direction, allowing traders to monitor both extremes with a single alert setup. ▶ Color Customization: Six visual themes (Classic, Aqua, Cosmic, Cyber, Neon, plus Custom) accommodate different chart backgrounds and visual preferences, with distinct colors for overvalued, undervalued, and fair value conditions. Optional background highlighting with adjustable transparency (0-100%) tints the main chart background during extreme valuation periods, providing immediate visual context without requiring continuous oscillator monitoring. Optional overlay signals display small circle markers directly on the price chart above bars during overvaluation and below bars during undervaluation, allowing correlation of statistical extremes with specific price levels and candlestick patterns.
Indicador Pine Script®
por QuantAlgo
SPY Quant ML + Session Filter Strategy [CocoChoco]S&P 500 Quant: Machine Learning & Mean Reversion (Session-Filtered) Overview This is a professional-grade quantitative strategy designed specifically for the S&P 500. It combines classical statistical mean reversion (Z-Score) with a modern Machine Learning filter and rigorous institutional-grade risk management. The strategy is optimized for traders who prioritize high win rates and capital preservation, specifically avoiding the "gap risk" associated with holding positions overnight. Core Methodology 1. Statistical Entry (The Z-Score Engine) The strategy identifies "oversold" conditions in a bullish context. It calculates the Z-Score of the price relative to its 20-period Mean (SMA). By default, it looks for a -1.2 Standard Deviation extension, signaling a high-probability "dip" ripe for a snap-back to the mean. 2. Trend & ML Filters To avoid "catching a falling knife," the strategy uses two layers of confirmation: Trend Filter: Only takes Long positions when the price is above the 200-period SMA, ensuring we only buy dips in a confirmed uptrend. ML Correlation Filter: A Machine Learning-inspired module that analyzes the correlation between RSI and Volatility (ATR). It only permits entries when market internal dynamics suggest a reversal is technically "healthy." 3. Institutional Risk Management This script is built for "safety-first" automation: Hard Stop Loss: Fixed at 1.5% to protect against sudden market shocks. Active Trailing: A dual-trigger trailing stop. It activates once the price touches the 20 SMA (The Mean) OR once a trade reaches a 0.50% profit threshold. This ensures near-winners are protected and large runners are captured. Intraday Circuit Breaker: Includes a Max Daily Drawdown (2%) limit. If hit, the script automatically closes losing positions and halts trading for the day, while allowing winning positions to continue. Key Features Session-Specific: Tailored for the US Trading Session (UTC/NY times). Zero Overnight Risk: Automatically flattens all positions before the market close (16:00 NY Time). Holiday Intelligence: Hard-coded logic for US Market Holidays and Early Closes (2026–2028), ensuring the bot doesn't get stuck in illiquid holiday markets. Hourly Entry Cap: Limits entries to one per hour to prevent over-concentration during a single price leg. How to Use Timeframe: I suggest you use it on the 5-minute or 1-hour timeframe for optimal results. Instrument: Designed for the S&P 500, but highly effective on SPY, IVV, and ES (Futures). Pyramiding: Designed to handle up to 3 concurrent positions, allowing the strategy to scale into a move as the Z-Score deepens. Automation Ready This script is fully compatible with webhook-based automation tools. All signals (Entry, SL, Trail, Market Close, and Daily Limit) are clearly labeled in the Alert comments for seamless execution. I haven't tasted it though. This is not financial advice. Please perform your own tests and manage your risk. Disclaimer Past performance does not guarantee future results. This script is a tool for quantitative analysis and should be used as part of a broader diversified trading plan.
Estratégia Pine Script®
por CocoChoco1
Chaikin Oscillator Z-Score With Divergences [MAXmks]Hello Traders, This is my take on the Chaikin Oscillator — statistically normalized into a Z-Score with built-in divergence detection. The problem with raw Chaikin The standard ChO is unbounded and extremely sensitive to volume spikes. A single anomalous bar can flatten the entire oscillator, making it hard to compare signals across time or between instruments. The fix Z-Score normalization with asinh (inverse hyperbolic sine) transformation. While standard Z-Scores assume a normal distribution, market data often features "fat tails" (extreme outliers). This transformation compresses those spikes effectively, ensuring the indicator remains responsive without getting stuck during high-volatility events. The result: a more comparable scale across instruments. What's inside: Adaptive normalization + EMA-based variance for smooth Z calculation Regular and hidden divergence detection with segment validation (fewer false signals) Gradient coloring that intensifies toward extremes Dashboard with current Z value Pre-built alerts for OB/OS entries/exits and all divergence types Note: This is a volume-based indicator. No volume = no signal. If you see "No Volume Data" in the dashboard, switch to a data source that provides volume. Works on any timeframe. Feedback welcome. For analysis purposes, not financial advice.
Indicador Pine Script®
por MAXmks
Volume-Weighted Price Z-Score [QuantAlgo]🟢 Overview The Volume-Weighted Price Z-Score indicator quantifies price deviations from volume-weighted equilibrium using statistical standardization. It combines volume-weighted moving average analysis with logarithmic deviation measurement and volatility normalization to identify when prices have moved to statistically extreme levels relative to their volume-weighted baseline, helping traders and investors spot potential mean reversion opportunities across multiple timeframes and asset classes. 🟢 How It Works The indicator's core methodology lies in its volume-weighted statistical approach, where price displacement is measured through normalized deviations from volume-weighted price levels: volumeWeightedAverage = ta.vwma(priceSource, lookbackPeriod) logDeviation = math.log(priceSource / volumeWeightedAverage) volatilityMeasure = ta.stdev(logDeviation, lookbackPeriod) The script uses logarithmic transformation to capture proportional price changes rather than absolute differences, ensuring equal treatment of percentage moves regardless of price level: rawZScore = logDeviation / volatilityMeasure zScore = ta.ema(rawZScore, smoothingPeriod) First, it establishes the volume-weighted baseline which gives greater weight to price levels where significant trading occurred, creating a more representative equilibrium point than simple moving averages. Then, the logarithmic deviation measurement converts the price-to-average ratio into a normalized scale: logDeviation = math.log(priceSource / volumeWeightedAverage) Next, statistical normalization is achieved by dividing the deviation by its own historical volatility, creating a standardized z-score that measures how many standard deviations the current price sits from the volume-weighted mean. Finally, EMA smoothing filters noise while preserving the signal's responsiveness to genuine market extremes: rawZScore = logDeviation / volatilityMeasure zScore = ta.ema(rawZScore, smoothingPeriod) This creates a volume-anchored statistical oscillator that combines price-volume relationship analysis with volatility-adjusted normalization, providing traders with probabilistic insights into market extremes and mean reversion potential based on standard deviation thresholds. 🟢 Signal Interpretation ▶ Positive Values (Above Zero): Price trading above volume-weighted average indicating potential overvaluation relative to volume-weighted equilibrium = Caution on longs, potential mean reversion downward = Short/sell opportunities ▶ Negative Values (Below Zero): Price trading below volume-weighted average indicating potential undervaluation relative to volume-weighted equilibrium = Caution on shorts, potential mean reversion upward = Long/buy opportunities ▶ Zero Line Crosses: Mean reversion transitions where price crosses back through volume-weighted equilibrium, indicating shift from overvalued to undervalued (or vice versa) territory ▶ Extreme Positive Zone (Above +2.5σ default): Statistically rare overvaluation representing 98.8%+ confidence level deviation, indicating extremely stretched bullish conditions with high mean reversion probability = Strong correction warning/short signal ▶ Extreme Negative Zone (Below -2.5σ default): Statistically rare undervaluation representing 98.8%+ confidence level deviation, indicating extremely stretched bearish conditions with high mean reversion probability = Strong buying opportunity signal ▶ ±1σ Reference Levels: Moderate deviation zones (±1 standard deviation) marking common price fluctuation boundaries where approximately 68% of price action occurs under normal distribution ▶ ±2σ Reference Levels: Significant deviation zones (±2 standard deviations) marking unusual price extremes where approximately 95% of price action should be contained under normal conditions 🟢 Features ▶ Preconfigured Presets: Three optimized parameter sets accommodate different analytical approaches, instruments and timeframes. "Default" provides balanced statistical measurement suitable for swing trading and daily/4-hour analysis, offering deviation detection with moderate responsiveness to price dislocations. "Fast Response" delivers heightened sensitivity optimized for intraday trading and scalping on 15-minute to 1-hour charts, using shorter statistical windows and minimal smoothing to capture rapid mean reversion opportunities as they develop. "Smooth Trend" offers conservative extreme identification ideal for position trading on daily to weekly charts, employing extended statistical periods and heavy noise filtering to isolate only the most significant market extremes. ▶ Built-in Alerts: Seven alert conditions enable comprehensive automated monitoring of statistical extremes and mean reversion events. Extreme Overbought triggers when z-score crosses above the extreme threshold (default +2.5σ) signaling rare overvaluation, Extreme Oversold activates when z-score crosses below the negative extreme threshold (default -2.5σ) signaling rare undervaluation. Exit Extreme Overbought and Exit Extreme Oversold alert when prices begin reverting from these statistical extremes back toward the mean. Bullish Mean Reversion notifies when z-score crosses above zero indicating shift to overvalued territory, while Bearish Mean Reversion triggers on crosses below zero indicating shift to undervalued territory. Any Extreme Level provides a combined alert for any extreme threshold breach regardless of direction. These notifications allow you to capitalize on statistically significant price dislocations without continuous chart monitoring. ▶ Color Customization: Six visual themes (Classic, Aqua, Cosmic, Ember, Neon, plus Custom) accommodate different chart backgrounds and visual preferences, ensuring optimal contrast for identifying positive versus negative deviations across trading environments. The adjustable fill transparency control (0-100%) allows fine-tuning of the gradient area prominence between the z-score line and zero baseline, with higher opacity values creating subtle background context while lower values produce bold deviation emphasis. Optional bar coloring extends the z-score gradient directly to the indicator pane bars, providing immediate visual reinforcement of current deviation magnitude and direction without requiring reference to the plotted line itself. *Note: This indicator requires volume data to function correctly, as it calculates deviations from a volume-weighted price average. Tickers with no volume data or extremely limited volume will not produce meaningful results, i.e., the indicator may display flat lines, erratic values, or fail to calculate properly. Using this indicator on assets without volume data (certain forex pairs, synthetic indices, or instruments with unreported/unavailable volume) will produce unreliable or no results at all. Additionally, ensure your chart has sufficient historical data to cover the selected lookback period, e.g., using a 100-bar lookback on a chart with only 50 bars of history will yield incomplete or inaccurate calculations. Always verify your chosen ticker has consistent, accurate volume information and adequate price history before applying this indicator.
Indicador Pine Script®
por QuantAlgo
13
Adaptive Z-Score Oscillator [QuantAlgo]🟢 Overview The Adaptive Z-Score Oscillator transforms price action into statistical significance measurements by calculating how many standard deviations the current price deviates from its moving average baseline, then dynamically adjusting threshold levels based on historical distribution patterns. Unlike traditional oscillators that rely on fixed overbought/oversold levels, this indicator employs percentile-based adaptive thresholds that automatically calibrate to changing market volatility regimes and statistical characteristics. By offering both adaptive and fixed threshold modes alongside multiple moving average types and customizable smoothing, the indicator provides traders and investors with a robust framework for identifying extreme price deviations, mean reversion opportunities, and underlying trend conditions through the visualization of price behavior within a statistical distribution context. 🟢 How It Works The indicator begins by establishing a dynamic baseline using a user-selected moving average type applied to closing prices over the specified length period, then calculates the standard deviation to measure price dispersion: basis = ma(close, length, maType) stdev = ta.stdev(close, length) The core Z-Score calculation quantifies how many standard deviations the current price sits above or below the moving average basis, creating a normalized oscillator that facilitates cross-asset and cross-timeframe comparisons: zScore = stdev != 0 ? (close - basis) / stdev : 0 smoothedZ = ma(zScore, smooth, maType) The adaptive threshold mechanism employs percentile calculations over a historical lookback period to determine statistically significant extreme zones. Rather than using fixed levels like ±2.0, the indicator identifies where a specified percentage of historical Z-Score readings have fallen, automatically adjusting to market regime changes: upperThreshold = adaptive ? ta.percentile_linear_interpolation(smoothedZ, percentilePeriod, upperPercentile) : fixedUpper lowerThreshold = adaptive ? ta.percentile_linear_interpolation(smoothedZ, percentilePeriod, lowerPercentile) : fixedLower The visualization architecture creates a four-tier coloring system that distinguishes between extreme conditions (beyond the adaptive thresholds) and moderate conditions (between the midpoint and threshold levels), providing visual gradation of statistical significance through opacity variations and immediate recognition of distribution extremes. 🟢 How to Use This Indicator ▶ Overbought and Oversold Identification: The indicator identifies potential overbought conditions when the smoothed Z-Score crosses above the upper threshold, indicating that price has deviated to a statistically extreme level above its mean. Conversely, oversold conditions emerge when the Z-Score crosses below the lower threshold, signaling statistically significant downward deviation. In adaptive mode (default), these thresholds automatically adjust to the asset's historical behavior, i.e., during high volatility periods, the thresholds expand to accommodate wider price swings, while during low volatility regimes, they contract to capture smaller deviations as significant. This dynamic calibration reduce false signals that plague fixed-level oscillators when market character shifts between volatile and ranging conditions. ▶ Mean Reversion Trading Applications: The Z-Score framework excels at identifying mean reversion opportunities by highlighting when price has stretched too far from its statistical equilibrium. When the oscillator reaches extreme bearish levels (below the lower threshold with deep red coloring), it suggests price has become statistically oversold and may snap back toward the mean, presenting potential long entry opportunities for mean reversion traders. Symmetrically, extreme bullish readings (above the upper threshold with bright green coloring) indicate potential short opportunities or long exit points as price becomes statistically overbought. The moderate zones (lighter colors between midpoint and threshold) serve as early warning areas where traders can prepare for potential reversals, while exits from extreme zones (crossing back inside the thresholds) often provide confirmation that mean reversion is underway. ▶ Trend and Distribution Analysis: Beyond discrete overbought/oversold signals, the histogram's color pattern and shape reveal the underlying trend structure and distribution characteristics. Sustained periods where the Z-Score oscillates primarily in positive territory (green bars) indicate a bullish trend where price consistently trades above its moving average baseline, even if not reaching extreme levels. Conversely, predominant negative readings (red bars) suggest bearish trend conditions. The distribution shape itself provides insight into market behavior, e.g., a narrow, centered distribution clustering near zero indicates tight ranging conditions with price respecting the mean, while a wide distribution with frequent extreme readings reveals volatile trending or choppy conditions. Asymmetric distributions skewed heavily toward one side demonstrate persistent directional bias, whereas balanced distributions suggest equilibrium between bulls and bears. ▶ Built-in Alerts: Seven alert conditions enable automated monitoring of statistical extremes and trend transitions. Enter Overbought and Enter Oversold alerts trigger when the Z-Score crosses into extreme zones, providing early warnings of potential reversal setups. Exit Overbought and Exit Oversold alerts signal when price begins reverting from extremes, offering confirmation that mean reversion has initiated. Zero Cross Up and Zero Cross Down alerts identify transitions through the neutral line, indicating shifts between above-mean and below-mean price action that can signal trend changes. The Extreme Zone Entry alert fires on any extreme threshold penetration regardless of direction, allowing unified monitoring of both overbought and oversold opportunities. ▶ Color Customization: Six visual themes (Classic, Aqua, Cosmic, Ember, Neon, plus Custom) accommodate different chart backgrounds and aesthetic preferences, ensuring optimal contrast and readability across trading platforms. The bar transparency control (0-90%) allows fine-tuning of visual prominence, with minimal transparency creating bold, attention-grabbing bars for primary analysis, while higher transparency values produce subtle background context when using the oscillator alongside other indicators. The extreme and moderate zone coloring system uses automatic opacity variation to create instant visual hierarchy, with darkest colors highlight the most statistically significant deviations demanding immediate attention, while lighter shades mark developing conditions that warrant monitoring but may not yet justify action. Optional candle coloring extends the Z-Score color scheme directly to the price candles on the main chart, enabling traders to instantly recognize statistical extremes and trend conditions without needing to reference the oscillator panel, creating a unified visual experience where both price action and statistical analysis share the same color language.
Indicador Pine Script®
por QuantAlgo
10
ZScore SemiConductoresZ-Score of Semiconductor Sector Volume This custom Pine Script indicator applies a Z-Score calculation to the aggregated trading volume of leading semiconductor companies. The goal is to highlight statistical extremes in sector activity that may signal unusual market behavior. 🔧 How it works - Fixed ticker list: NVDA, AVGO, TSM, AMD, ASML, MU, ARM, ON, TXN, QCOM, INTC. - Aggregate volume: The script sums the trading volume of all tickers in the list for the selected timeframe. - Z-Score calculation: - Moving average and standard deviation are computed over a configurable window (default = 50 bars). - Formula: Z= (Current Volume - Mean) / Standard Deviation Visualization: - Z-Score plotted in green. - Reference lines at 0, ±1σ, ±2σ. - Labels (triangles) mark critical signals when Z > +2 or Z < -2. 📈 Why it matters - Detects abnormal surges or drops in sector-wide volume. - Highlights potential euphoria (+2σ) or panic (-2σ) moments. - Useful as a filter for trading strategies or as a sector-level alert system. ⚠️ Disclaimer: This script is for educational purposes only and not financial advice
Indicador Pine Script®
por JuanDeNogoya
Z-EMA Fusion BandsDesigned with crypto markets in mind, particularly Bitcoin , it builds on the concept that the 1-Week 50 EMA often serves as a long-term bull/bear market threshold — an area where institutional bias, momentum shifts, and cyclical rotations tend to occur. 🔹 Core Components & Synergies: 1. 1W 50 EMA (Higher Timeframe) - This EMA is calculated on a weekly timeframe, regardless of your current chart. - In crypto, price above the 1W 50 EMA typically aligns with long-term bull market phases, while extended periods below can signify bearish macro structure. - The slope of the EMA is also analyzed to add directional confidence to trend strength. 2. ±1 Standard Deviation Bands - Surrounding the 50 EMA, these bands visualize normal price dispersion relative to trend. - When price consistently hugs or breaks outside these bands, it often reflects market expansion, volatility events, or mean-reversion opportunity. 3. Z-Score Gradient Fill - The area between the bands is filled using a Z-score-based gradient, which dynamically adjusts color based on how far price is from the EMA (in terms of standard deviations). - Color shifts from aqua (near EMA) to fuchsia (far from EMA) help you spot price compression, equilibrium, or overextension at a glance. - The fill also uses transparency scaling, making it fade as price stretches further, emphasizing the core structure. 4. Directional EMA Coloring - The EMA line itself is colored based on: - The slope of the EMA (rising/falling) - Whether the HTF candle is bullish or bearish - This provides intuitive color-coded confirmation of momentum alignment or potential exhaustion. 5. Price/EMA Divergence Detection - The script detects bullish and bearish divergence between price and the EMA (rather than using a traditional oscillator). - Bullish Divergence: Price makes a lower low, EMA makes a higher low. - Bearish Divergence: Price makes a higher high, EMA makes a lower high. - These signals often mark transitional zones where momentum fades before a trend reversal or correction. 📊 Suggested Uses: 🔸 Swing and Position Trading: - Use the 1W 50 EMA as a macro-trend anchor. - Stay long-biased when price is above with positive slope, and short-biased when below. - Consider entries near band edges for mean-reversion plays, especially if confluence forms with divergence signals. 🔸 Volatility-Based Filtering: - Use the Z-score fill to identify volatility compression (near EMA) or expansion (edge of bands). - Combine this with breakout strategies or dynamic position sizing. 🔸 Divergence Confirmation: - Combine divergence markers with HTF EMA slope for high-probability setups. - Bullish div + EMA flattening/rising can signal the start of accumulation after a macro dip. 🔸 Multi-Timeframe Analysis: - Works well as a structural overlay on intraday charts (1H, 4H, 1D). - Use this indicator to track long-term bias while executing lower timeframe trades. ⚠️ Disclaimer: This indicator is designed for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any asset. Always use proper risk management, and combine with your own analysis, tools, and strategy. Performance in past market conditions does not guarantee future results.
Indicador Pine Script®
por RWCS_LTD
Z-Score Regime DetectorThe Z-Score Regime Detector is a statistical market regime indicator that helps identify bullish and bearish market conditions based on normalized momentum of three core metrics: - Price (Close) - Volume - Market Capitalization (via CRYPTOCAP:TOTAL) Each metric is standardized using the Z-score over a user-defined period, allowing comparison of relative extremes across time. This removes raw value biases and reveals underlying momentum structure. 📊 How it Works - Z-Score: Measures how far a current value deviates from its average in terms of standard deviations. - A Bullish Regime is identified when both price and market cap Z-scores are above the volume Z-score. - A Bearish Regime occurs when price and market cap Z-scores fall below volume Z-score. Bias Signal: - Bullish Bias = Price Z-score > Market Cap Z-score - Bearish Bias = Market Cap Z-score > Price Z-score This provides a statistically consistent framework to assess whether the market is flowing with strength or stress. ✅ Why This Might Be Effective - Normalizing the data via Z-scores allows comparison of diverse metrics on a common scale. - Using market cap offers broader insight than price alone, especially for crypto. - Volume as a reference threshold helps identify accumulation/distribution regimes. - Simple regime logic makes it suitable for trend confirmation, filtering, or position biasing in systems. ⚠️ Disclaimer This script is for educational purposes only and should not be considered financial advice. Always perform your own research and risk management. Past performance is not indicative of future results. Use at your own discretion.
Indicador Pine Script®
por RWCS_LTD
Uptrick: Dynamic Z-Score DivergenceIntroduction Uptrick: Dynamic Z-Score Divergence is an oscillator that combines multiple momentum sources within a Z-Score framework, allowing for the detection of statistically significant mean-reversion setups, directional shifts, and divergence signals. It integrates a multi-source normalized oscillator, a slope-based signal engine, structured divergence logic, a slope-adaptive EMA with dynamic bands, and a modular bar coloring system. This script is designed to help traders identify statistically stretched conditions, evolving trend dynamics, and classical divergence behavior using a unified statistical approach. Overview At its core, this script calculates the Z-Score of three momentum sources—RSI, Stochastic RSI, and MACD—using a user-defined lookback period. These are averaged and smoothed to form the main oscillator line. This normalized oscillator reflects how far short-term momentum deviates from its mean, highlighting statistically extreme areas. Signals are triggered when the oscillator reverses slope within defined inner zones, indicating a shift in direction while the signal remains in a statistically stretched state. These mean-reversion flips (referred to as TP signals) help identify turning points when price momentum begins to revert from extended zones. In addition, the script includes a divergence detection engine that compares oscillator pivot points with price pivot points. It confirms regular bullish and bearish divergence by validating spacing between pivots and visualizes both the oscillator-side and chart-side divergences clearly. A dynamic trend overlay system is included using a Slope Adaptive EMA (SA-EMA). This trend line becomes more responsive when Z-Score deviation increases, allowing the trend line to adapt to market conditions. It is paired with ATR-based bands that are slope-sensitive and selectively visible—offering context for dynamic support and resistance. The script includes configurable bar coloring logic, allowing users to color candles based on oscillator slope, last confirmed divergence, or the most recent signal of any type. A full alert system is also built-in for key signals. Originality The script is based on the well-known concept of Z-Score valuation, which is a standard statistical method for identifying how far a signal deviates from its mean. This foundation—normalizing momentum values such as RSI or MACD to measure relative strength or weakness—is not unique to this script and is widely used in quantitative analysis. What makes this implementation original is how it expands the Z-Score foundation into a fully featured, signal-producing system. First, it introduces a multi-source composite oscillator by combining three momentum inputs—RSI, Stochastic RSI, and MACD—into a unified Z-Score stream. Second, it builds on that stream with a directional slope logic that identifies turning points inside statistical zones. The most distinctive additions are the layered features placed on top of this normalized oscillator: A structured divergence detection engine that compares oscillator pivots with price pivots to validate regular bullish and bearish divergence using precise spacing and timing filters. A fully integrated slope-adaptive EMA overlay, where the smoothing dynamically adjusts based on real-time Z-Score movement of RSI, allowing the trend line to become more reactive during high-momentum environments and slower during consolidation. ATR-based dynamic bands that adapt to slope direction and offer real-time visual zones for support and resistance within trend structures. These features are not typically found in standard Z-Score indicators and collectively provide a unique approach that bridges statistical normalization, structure detection, and adaptive trend modeling within one script. Features Z-Score-based oscillator combining RSI, StochRSI, and MACD Configurable smoothing for stable composite signal output Buy/Sell TP signals based on slope flips in defined zones Background highlighting for extreme outer bands Inner and outer zones with fill logic for statistical context Pivot-based divergence detection (regular bullish/bearish) Divergence markers on oscillator and price chart Slope-Adaptive EMA (SA-EMA) with real-time adaptivity based on RSI Z-Score ATR-based upper and lower bands around the SA-EMA, visibility tied to slope direction Configurable bar coloring (oscillator slope, divergence, or most recent signal) Alerts for TP signals and confirmed divergences Optional fixed Y-axis scaling for consistent oscillator view The full setup mode can be seen below: Input Parameters General Settings Full Setup: Enables rendering of the full visual system (lines, bands, signals) Z-Score Lookback: Lookback period for normalization (mean and standard deviation) Main Line Smoothing: EMA length applied to the averaged Z-Score Slope Detection Index: Used to calculate directional flips for signal logic Enable Background Highlighting: Enables visual region coloring in overbought/oversold areas Force Visible Y-Axis Scale: Forces max/min bounds for a consistent oscillator range Divergence Settings Enable Divergence Detection: Toggles divergence logic Pivot Lookback Left / Right: Defines the structure of oscillator pivot points Minimum / Maximum Bars Between Pivots: Controls the allowed spacing range for divergence validation Bar Coloring Settings Bar Coloring Mode: ➜ Line Color: Colors bars based on oscillator slope ➜ Latest Confirmed Signal: Colors bars based on the most recent confirmed divergence ➜ Any Latest Signal: Colors based on the most recent signal (TP or divergence) SA-EMA Settings RSI Length: RSI period used to determine adaptivity Z-Score Length: Lookback for normalizing RSI in adaptive logic Base EMA Length: Base length for smoothing before adaptivity Adaptivity Intensity: Scales the smoothing responsiveness based on RSI deviation Slope Index: Determines slope direction for coloring and band logic Band ATR Length / Band Multiplier: Controls the width and responsiveness of the trend-following bands Alerts The script includes the following alert conditions: Buy Signal (TP reversal detected in oversold zone) Sell Signal (TP reversal detected in overbought zone) Confirmed Bullish Divergence (oscillator HL, price LL) Confirmed Bearish Divergence (oscillator LH, price HH) These alerts allow integration into automation systems or signal monitoring setups. Summary Uptrick: Dynamic Z-Score Divergence is a statistically grounded trading indicator that merges normalized multi-momentum analysis with real-time slope logic, divergence detection, and adaptive trend overlays. It helps traders identify mean-reversion conditions, divergence structures, and evolving trend zones using a modular system of statistical and structural tools. Its alert system, layered visuals, and flexible input design make it suitable for discretionary traders seeking to combine quantitative momentum logic with structural pattern recognition. Disclaimer This script is for educational and informational purposes only. No indicator can guarantee future performance, and trading involves risk. Always use risk management and test strategies in a simulated environment before deploying with live capital.
Indicador Pine Script®
por Uptrick
14
Market Extreme Zones IndexThe Market Extreme Zones Index is a new mean reversion (valuation) tool focused on catching long term oversold/overbought zones. Combining an enhanced RSI with a smoothed Z-score this indicator allows traders to find oppurtunities during highly oversold/overbought zones. I will separate the explanation into the following parts: 1. How does it work? 2. Methodologies & Concepts 3. Use cases How does it work? The indicator attempts to catch highly unprobable events in either direction to capture reversal points over the long term. This is done by calculating the Z-Score of an enhanced RSI. First we need to calculate the Enhanced RSI: For this we need to calculate 2 additional lengths: Length1 = user defined length Length2 = Length1/2 Length3 = √Length Now we need to calculate 3 different RSIs: 1st RSI => uses classic user defined source and classic user defined length. 2nd RSI => uses classic user defined source and Length 2. 3rd RSI => uses RSI 2 as source and Length 2 Now calculate the divergence: RSI_base => 2nd RSI * 3 - 1st RSI - 3rd RSI After this we need to calculate the median of the RSI_base over √Length and make a divergence of these 2: RSI => RSI_base*2 - median All that remains now is the Z-score calculations: We need: Average RSI value Standard Deviation = a measure of how dispersed or spread out a set of data values are from their average Z-score = (Current Value - Average Value) / Standard Deviation After this we just smooth the Z-score with a Weighted Moving average with √Length Methodology & Concepts Mean Reversion Methodology: The methodology behind mean reversion is the theory that asset prices will eventually return to their long-term average after deviating significantly, driven by the belief that extreme moves are temporary. Z-Score Methodology: A Z-score, or standard score, is a statistical measure that indicates how many standard deviations a data point is from the mean of a dataset. A positive z-score means the value is above the mean, a negative score means it's below, and a score of zero means the value is equal to the mean. You might already be able to see where I am going with this: Z-Score could be used for the extreme moves to capture reversal points. By applying it to the RSI rather than the Price, we get a more accurate measurement that allow us to get a banger indicator. Use Cases Capturing reversal points Trend Direction - while the main use it for mean reversion, the values can indicate whether we are in an uptrend or a downtrend. Advantages: Visualization: The indicator has many plots to ensure users can easily see what the indicator signals, such as highlighting extreme conditions with background colors. Versatility: This indicator works across multiple assets, including the S&P500 and more, so it is not only for crypto. Final note: No indicator alone is perfect. Backtests are not indicative of future performance. Hope you enjoy Gs! Good luck!
Indicador Pine Script®
por MisinkoMaster
Uptrick: Volume Weighted BandsIntroduction This indicator, Uptrick: Volume Weighted Bands, overlays dynamic, volume-informed trend channels directly on the chart. By fusing price and volume data through volume-weighted and exponential moving averages, the script forms a core trend line with adaptive bandwidth controlled by volatility. It is designed to help traders identify trend direction, breakout entries, and extended conditions that may warrant take-profits or pullback re-entries. Overview The Volume Weighted Bands system is built around a trend line calculated by averaging a Volume Weighted Moving Average (VWMA) and an Exponential Moving Average (EMA), both over a configurable lookback period. This hybrid trend baseline is then smoothed further and expanded into dynamic upper and lower bands using an Average True Range (ATR) multiplier. These bands adapt with market volatility and shift color based on prevailing price action, helping traders quickly identify bullish, bearish, or neutral conditions. Originality and Unique Features This script introduces originality by blending both price and volume in the core trend calculation, a technique that is more responsive than traditional moving average bands. Its multi-mode visualization (cloud, single-band, or line-only), combined with selective buy/sell signals, makes it flexible for discretionary and algorithmic strategies alike. Optional modules for take-profit signals based on z-score deviation and RSI slope, as well as buy-back detection logic with cooldown filters, offer practical tools for managing trades beyond simple entries. Explanation of Inputs Every user input in this script is included to give the trader control over behavior and visual presentation: Trend Length (len): Defines the lookback window for both the VWMA and EMA, controlling the sensitivity of the core trend baseline. A lower value makes the bands more reactive, while a higher value smooths out short-term noise. Extra Smoothing (smoothLen): Applies an additional EMA to the blended VWMA/EMA average. This second-level smoothing ensures the central trend line reacts gradually to shifts in price. Band Width (ATR Multiplier) (bandMult): Multiplies the ATR to create the width of the upper and lower bands around the trend line. Larger values widen the bands, capturing more volatility, while smaller values narrow them. ATR Length (atrLen): Sets the length of the ATR used in calculating band width and signal offsets. Longer values produce smoother band boundaries. Show Buy/Sell Signals (showSignals): Toggles the primary crossover/crossunder entry signals, which are labeled when the close crosses the upper or lower band. Visual Mode (visualMode): Allows selection between three display modes: --> Cloud: Shows both bands and the central trend line with a shaded background. --> Single Band: Displays only the active (upper or lower) band depending on trend state, with gradient fill to price. --> Line Only: Shows only the trend line for a minimal visual profile. Take Profit Signals (enableTP): Enables a z-score-based profit-taking signal system. Signals occur when price deviates significantly from the trend line and RSI confirms exhaustion. TP Z-Score Threshold (tpThreshold): Sets the z-score deviation required to trigger a take-profit signal. Higher values reduce the frequency of signals, focusing on more extreme moves. Re-Entries (enableBuyBack): Enables logic to signal when price reverts into the band after an initial breakout, suggesting a possible re-entry or pullback setup. Buy Back Cooldown (bars) (buyBackCooldown): Defines a minimum bar count before a new buy-back signal is allowed, preventing rapid retriggering in choppy conditions. Buy Offset and Sell Offset: Hidden inputs used to vertically adjust the placement of the Buy ("𝓤𝓹") and Sell ("𝓓𝓸𝔀𝓷") labels relative to the bands. These use ATR units to maintain proportionality across different instruments and timeframes. Take-Profit Signal Module The take-profit module uses a z-score of the distance between price and the trend line to detect extended conditions. In bullish trends, a signal appears when price is well above the band and RSI indicates exhaustion; the opposite applies for bearish conditions. A boolean flag is used to prevent retriggering until RSI resets. These signals are plotted with minimalist “X” markers near recent highs or lows, based on whether the market is extended upward or downward. Re-Entry Logic The re-entry system identifies instances where price momentarily dips or spikes into the opposite band but closes back inside, implying a continuation of the prevailing trend. This module can be particularly useful for traders managing entries after brief pullbacks. A built-in cooldown period helps filter out noise and prevents signal overloading during fast markets. Visual markers are shown as upward or downward arrows near the relevant candle wicks. How to Use This Indicator The basic usage of this indicator follows a directional, signal-driven approach. When a buy signal appears, it suggests entering a long position. The recommended stop loss placement is below the lower band, allowing for some breathing space to accommodate natural volatility. As the position progresses, take partial profits—typically 10% to 15% of the position—each time a take-profit signal (marked with an "X") is shown on the chart. An optional feature is the buy-back signal, which can be used to re-enter after partial exits or missed entries. Utilizing this can help reduce losses during false breakouts or trend reversals by scaling in more gradually. However, it also means that in strong, clean trends, the full position may not be captured from the start, potentially reducing the total return. It is up to the trader to decide whether to enter fully on the initial signal or incrementally using buy-backs. When a sell signal appears, the strategy advises fully exiting any long positions and immediately switching to a short position. The short trade follows the same logic: place your stop loss above the upper band with some margin, and again, take partial profits at each take-profit signal. Visual Presentation and Signal Labels All signals are plotted with clean, minimal labels that avoid clutter, and are color-coded using a custom palette designed to remain clear across light and dark chart themes. Bullish trends are marked in teal and bearish trends in magenta. Candles and wicks are also colored accordingly to align price action with the detected trend state. Buy and sell entries are marked with "𝓤𝓹" and "𝓓𝓸𝔀𝓷" labels. Summary In summary, the Uptrick: Volume Weighted Bands indicator provides a versatile, visually adaptive trend and volatility tool that can serve multiple styles of trading. Through its integration of price, volume, and volatility, along with modular take-profit and buy-back signaling, it aims to provide actionable structure across a range of market conditions. Disclaimer This indicator is for educational purposes only. Trading involves risk, and past performance does not guarantee future results. Always test strategies before applying them in live markets.
Indicador Pine Script®
por Uptrick
23
Z-Score Regression Bands [BOSWaves]Z-Score Regression Bands – Adaptive Trend and Volatility Insight Overview The Z-Score Regression Bands is a trend and volatility analysis framework designed to give traders a clear, structured view of price behavior. It combines Least Squares Moving Average (LSMA) regression, a statistical method to detect underlying trends, with Z-Score standardization, which measures how far price deviates from its recent average. Traditional moving average bands, like Bollinger Bands, often lag behind trends or generate false signals in noisy markets. Z-Score Regression Bands addresses these limitations by: Tracking trends accurately using LSMA regression Normalizing deviations with Z-Scores to identify statistically significant price extremes Visualizing multiple bands for normal, strong, and extreme moves Highlighting trend shifts using diamond markers based on Z-Score crossings This multi-layered approach allows traders to understand trend strength, detect overextensions, and identify periods of low or high volatility — all from a single, clear chart overlay. It is designed for traders of all levels and can be applied across scalping, day trading, swing trading, and longer-term strategies. Theoretical Foundation The Z-Score Regression Bands are grounded in statistical and trend analysis principles. Here’s the idea in plain terms: Least Squares Moving Average (LSMA) – Unlike standard moving averages, LSMA fits a straight line to recent price data using regression. This “best-fit” line shows the underlying trend more precisely and reduces lag, helping traders see trend changes earlier. Z-Score Standardization – A Z-Score expresses how far the LSMA is from its recent mean in standard deviation units. This shows whether price is unusually high or low, which can indicate potential reversals, pullbacks, or acceleration of a trend. Multi-Band Structure – The three bands represent: Band #1: Normal range of price fluctuations; Band #2: Significant deviation from the trend; Band #3: Extreme price levels that are statistically rare. The distance between bands dynamically adapts to market volatility, allowing traders to visualize expansions (higher volatility) and contractions (lower volatility). Trend Signals – When Z-Score crosses zero, diamonds appear on the chart. These markers signal potential trend initiation, continuation, or reversal, offering a simple alert for shifts in market momentum. How It Works The indicator calculates and plots several layers of information: LSMA Regression (Trend Detection) Computes a line that best fits recent price points. The LSMA line smooths out minor fluctuations while reflecting the general direction of the market. Z-Score Calculation (Deviation Measurement) Standardizes the LSMA relative to its recent average. Positive Z-Score → LSMA above average, negative → LSMA below average. Helps identify overbought or oversold conditions relative to the trend. Multi-Band Construction (Volatility Envelope) Upper and lower bands are placed at configurable multiples of standard deviation. Band #1 captures typical price movement, Band #2 signals stronger deviation, Band #3 highlights extreme moves. Bands expand and contract with volatility, giving an intuitive visual guide to market conditions. Trend Signals (Diamonds) Appear when Z-Score crosses zero. Indicates moments when momentum may shift, helping traders time entries or exits. Visual Interpretation Band width = volatility: wide bands indicate strong movement; narrow bands indicate calm periods. LSMA shows underlying trend direction, while bands show how far price has strayed from that trend. Interpretation The Z-Score Regression Bands provide a multi-dimensional view of market behavior: Trend Analysis – LSMA line slope shows general market direction. Momentum & Volatility – Z-Score indicates whether the trend is accelerating or losing strength; band width indicates volatility levels. Price Extremes – Price touching Band #2 or #3 may suggest overextension and potential reversals. Trend Shifts – Diamonds signal statistically significant changes in momentum. Cycle Awareness – Standard deviation bands help distinguish normal market fluctuations from extreme events. By combining these insights, traders can avoid false signals and react to meaningful structural shifts in the market. Strategy Integration Trend Following Enter trades when diamonds indicate momentum aligns with LSMA direction. Use Band #1 and #2 for stop placement and partial exits. Breakout Trading Watch for narrow bands (low volatility) followed by price pushing outside Band #1 or #2. Confirm with Z-Score movement in the breakout direction. Mean Reversion/Pullback If price reaches Band #2 or #3 without continuation, expect a pullback toward LSMA. Exhaustion & Reversals Flattening Z-Score near zero while price remains at extreme bands signals trend weakening. Tighten stops or scale out before a potential reversal. Multi-Timeframe Confirmation High timeframe LSMA confirms the main trend. Lower timeframe bands provide refined entry and exit points. Technical Implementation LSMA Regression : Best-fit line minimizes lag and captures trend slope. Z-Score Standardization : Normalizes deviation to allow consistent interpretation across markets. Multi-Band Envelope : Three layers for normal, strong, and extreme deviations. Trend Signals : Automatic diamonds for Z-Score zero-crossings. Band Fill Options : Optional shading to visualize volatility expansions and contractions. Optimal Application Asset Classes: Forex : Capture breakouts, overextensions, and trend shifts. Crypto : High-volatility adaptation with adjustable band multipliers. Stocks/ETFs : Identify trending sectors, reversals, and pullbacks. Indices/Futures : Track cycles and structural trends. Timeframes: Scalping (1–5 min) : Focus on Band #1 and trend signals for fast entries. Intraday (15m–1h) : Use Bands #1–2 for continuation and breakout trades. Swing (4h–Daily) : Bands #2–3 capture trend momentum and exhaustion. Position (Daily–Weekly) : LSMA trend dominates; Bands #3 highlight regime extremes. Performance Characteristics Strong Performance: Trending markets with moderate-to-high volatility Assets with steady liquidity and identifiable cycles Weak Performance: Flat or highly choppy markets Very short timeframes (<1 min) dominated by noise Integration Tips Combine with support/resistance, volume, or order flow analysis for confirmation. Use bands for stops, targets, or scaling positions. Apply multi-timeframe analysis: higher timeframe LSMA confirms main trend, lower timeframe bands refine entries. Disclaimer The Z-Score Regression Bands is a trading analysis tool, not a guaranteed profit system. Its effectiveness depends on market conditions, parameter selection, and disciplined risk management. Use it as part of a broader trading strategy, not in isolation.
Indicador Pine Script®
por BOSWaves
2
Pairs Trading Scanner [BackQuant]Pairs Trading Scanner What it is This scanner analyzes the relationship between your chart symbol and a chosen pair symbol in real time. It builds a normalized “spread” between them, tracks how tightly they move together (correlation), converts the spread into a Z-Score (how far from typical it is), and then prints clear LONG / SHORT / EXIT prompts plus an at-a-glance dashboard with the numbers that matter. Why pairs at all? Markets co-move. When two assets are statistically related, their relationship (the spread) tends to oscillate around a mean. Pairs trading doesn’t require calling overall market direction you trade the relative mispricing between two instruments. This scanner gives you a robust, visual way to find those dislocations, size their significance, and structure the trade. How it works (plain English) Step 1 Pick a partner: Select the Pair Symbol to compare against your chart symbol. The tool fetches synchronized prices for both. Step 2 Build a spread: Choose a Spread Method that defines “relative value” (e.g., Log Spread, Price Ratio, Return Difference, Price Difference). Each lens highlights a different flavor of divergence. Step 3 Validate relationship: A rolling Correlation checks if the pair is moving together enough to be tradable. If correlation is weak, the scanner stands down. Step 4 Standardize & score: The spread is normalized (mean & variability over a lookback) to form a Z-Score . Large absolute Z means “stretched,” small means “near fair.” Step 5 Signals: When the Z-Score crosses user-defined thresholds with sufficient correlation , entries print: LONG = long chart symbol / short pair symbol, SHORT = short chart symbol / long pair symbol, EXIT = mean reversion into the exit zone or correlation failure. Core concepts (the three pillars) Spread Method Your definition of “distance” between the two series. Guidance: Log Spread: Focuses on proportional differences; robust when prices live on different scales. Price Ratio: Classic relative value; good when you care about “X per Y.” Return Difference: Emphasizes recent performance gaps; nimble for momentum-to-mean plays. Price Difference: Straight subtraction; intuitive for similar-scale assets (e.g., two ETFs). Correlation A rolling score of co-movement. The scanner requires it to be above your Min Correlation before acting, so you’re not trading random divergence. Z-Score “How abnormal is today’s spread?” Positive = chart richer than pair; negative = cheaper. Thresholds define entries/exits with transparent, statistical context. What you’ll see on the chart Correlation plot (blue line) with a dashed Min Correlation guide. Above the line = green zone for signals; below = hands off. Z-Score plot (white line) with colored, dashed Entry bands and dotted Exit bands. Zero line for mean. Normalized spread (yellow) for a quick “shape read” of recent divergence swings. Signal markers : LONG (green label) when Z < –Entry and corr OK, SHORT (red label) when Z > +Entry and corr OK, EXIT (gray label) when Z returns inside the Exit band or correlation drops below the floor. Background tint for active state (faint green for long-spread stance, faint red for short-spread stance). The two built-in dashboards Statistics Table (top-right) Pair Symbol Your chosen partner. Correlation Live value vs. your minimum. Z-Score How stretched the spread is now. Current / Pair Prices Real-time anchors. Signal State NEUTRAL / LONG / SHORT. Price Ratio Context for ratio-style setups. Analysis Table (bottom-right) Avg Correlation Typical co-movement level over your window. Max |Z| The recent extremes of dislocation. Spread Volatility How “lively” the spread has been. Trade Signal A human-readable prompt (e.g., “LONG A / SHORT B” or “NO TRADE” / “LOW CORRELATION”). Risk Level LOW / MEDIUM / HIGH based on current stretch (absolute Z). Signals logic (plain English) Entry (LONG): The spread is unusually negative (chart cheaper vs pair) and correlation is healthy. Expect mean reversion upward in the spread: long chart, short pair. Entry (SHORT): The spread is unusually positive (chart richer vs pair) and correlation is healthy. Expect mean reversion downward in the spread: short chart, long pair. Exit: The spread relaxes back toward normal (inside your exit band), or correlation deteriorates (relationship no longer trusted). A quick, repeatable workflow 1) Choose your pair in context (same sector/theme or known macro link). Think: “Do these two plausibly co-move?” 2) Pick a spread lens that matches your narrative (ratio for relative value, returns for short-term performance gaps, etc.). 3) Confirm correlation is above your floor no corr, no trade. 4) Wait for a stretch (Z beyond Entry band) and a printed LONG / SHORT . 5) Manage to the mean (EXIT band) or correlation failure; let the scanners’ state/labels keep you honest. Settings that matter (and why) Spread Method Defines the “mispricing” you care about. Correlation Period Longer = steadier regime read, shorter = snappier to regime change. Z-Score Period The window that defines “normal” for the spread; it sets the yardstick. Use Percentage Returns Normalizes series when using return-based logic; keep on for mixed-scale assets. Entry / Exit Thresholds Set your stretch and your target reversion zone. Wider entries = rarer but stronger signals. Minimum Correlation The gatekeeper. Raising it favors quality over quantity. Choosing pairs (practical cheat sheet) Same family: two index ETFs, two oil-linked names, two gold miners, two L1 tokens. Hedge & proxy: stock vs. sector ETF, BTC vs. BTC index, WTI vs. energy ETF. Cross-venue or cross-listing: instruments that are functionally the same exposure but price differently intraday. Reading the cues like a pro Divergence shape: The yellow normalized spread helps you see rhythm fast spike and snap-back versus slow grind. Corr-first discipline: Don’t fight the “Min Correlation” line. Good pairs trading starts with a relationship you can trust. Exit humility: When Z re-centers, let the EXIT do its job. The edge is the journey to the mean, not overstaying it. Frequently asked (quick answers) “Long/Short means what exactly?” LONG = long the chart symbol and short the pair symbol. SHORT = short the chart symbol and long the pair symbol. “Do I need same price scales?” No. The spread methods normalize in different ways; choose the one that fits your use case (log/ratio are great for mixed scales). “What if correlation falls mid-trade?” The scanner will neutralize the state and print EXIT . Relationship first; trade second. Field notes & patterns Snap-back days: After a one-sided session, return-difference spreads often flag cleaner intraday mean reversions. Macro rotations: Ratio spreads shine during sector re-weights (e.g., value vs. growth ETFs); look for steady corr + elevated |Z|. Event bleed-through: If one symbol reacts to news and its partner lags, Z often flags a high-quality, short-horizon re-centering. Display controls at a glance Show Statistics Table Live state & key numbers, top-right. Show Analysis Table Context/risk read, bottom-right. Show Correlation / Spread / Z-Score Toggle the sub-charts you want visible. Show Entry/Exit Signals Turn markers on/off as needed. Coloring Adjust Long/Short/Neutral and correlation line colors to match your theme. Alerts (ready to route to your workflow) Pairs Long Entry Z falls through the long threshold with correlation above minimum. Pairs Short Entry Z rises through the short threshold with correlation above minimum. Pairs Trade Exit Z returns to neutral or the relationship fails your correlation floor. Correlation Breakdown Rolling correlation crosses your minimum; relationship caution. Final notes The scanner is designed to keep you systematic: require relationship (correlation), quantify dislocation (Z-Score), act when stretched, stand down when it normalizes or the relationship degrades. It’s a full, visual loop for relative-value trading that stays out of your way when it should and gets loud only when the numbers line up.
Indicador Pine Script®
por BackQuant
1
z-score-calkusi-v1.143z-scores incorporate the moment of N look-back bars to allow future price projection. z-score = (X - mean)/std.deviation ; X = close z-scores update with each new close print and with each new bar. Each new bar augments the mean and std.deviation for the N bars considered. The old Nth bar falls away from consideration with each new historical bar. The indicator allows two other options for X: RSI or Moving Average. NOTE: While trading use the "price" option only. The other two options are provided for visualisation of RSI and Moving Average as z-score curves. Use z-scores to identify tops and bottoms in the future as well as intermediate intersections through which a z-score will pass through with each new close and each new bar. Draw lines from peaks and troughs in the past through intermediate peaks and troughs to identify projected intersections in the future. The most likely intersections are those that are formed from a line that comes from a peak in the past and another line that comes from a trough in the past. Try getting at least two lines from historical peaks and two lines from historical troughs to pass through a future intersection. Compute the target intersection price in the future by clicking on the z-score indicator header to see a drag-able horizontal line to drag over the intersection. The target price is the last value displayed in the indicator's status bar after the closing price. When the indicator header is clicked, a white horizontal drag-able line will appear to allow dragging the line over an intersection that has been drawn on the indicator for a future z-score projection and the associated future closing price. With each new bar that appears, it is necessary to repeat the procedure of clicking the z-score indicator header to be able to drag the drag-able horizontal line to see the new target price for the selected intersection. The projected price will be different from the current close price providing a price arbitrage in time. New intermediate peaks and troughs that appear require new lines be drawn from the past through the new intermediate peak to find a new intersection in the future and a new projected price. Since z-score curves are sort of cyclical in nature, it is possible to see where one has to locate a future intersection by drawing lines from past peaks and troughs. Do not get fixated on any one projected price as the market decides which projected price will be realised. All prospective targets should be manually updated with each new bar. When the z-score plot moves outside a channel comprised of lines that are drawn from the past, be ready to adjust to new market conditions. z-score plots that move above the zero line indicate price action that is either rising or ranging. Similarly, z-score plots that move below the zero line indicate price action that is either falling or ranging. Be ready to adjust to new market conditions when z-scores move back and forth across the zero line. A bar with highest absolute z-score for a cycle screams "reversal approaching" and is followed by a bar with a lower absolute z-score where close price tops and bottoms are realised. This can occur either on the next bar or a few bars later. The indicator also displays the required N for a Normal(0,1) distribution that can be set for finer granularity for the z-score curve.This works with the Confidence Interval (CI) z-score setting. The default z-score is 1.96 for 95% CI. Common Confidence Interval z-scores to find N for Normal(0,1) with a Margin of Error (MOE) of 1: 70% 1.036 75% 1.150 80% 1.282 85% 1.440 90% 1.645 95% 1.960 98% 2.326 99% 2.576 99.5% 2.807 99.9% 3.291 99.99% 3.891 99.999% 4.417 9-Jun-2025 Added a feature to display price projection labels at z-score levels 3, 2, 1, 0, -1, -2, 3. This provides a range for prices available at the current time to help decide whether it is worth entering a trade. If the range of prices from say z=|2| to z=|1| is too narrow, then a trade at the current time may not be worth the risk. Added plot for z-score moving average. 28-Jun-2025 Added Settings option for # of Std.Deviation level Price Labels to display. The default is 3. Min is 2. Max is 6. This feature allows likelihood assessment for Fibonacci price projections from higher time frames at lower time frames. A Fibonacci price projection that falls outside |3.x| Std.Deviations is not likely. Added Settings option for Chart Bar Count and Target Label Offset to allow placement of price labels for the standard z-score levels to the right of the window so that these are still visible in the window. Target Label Offset allows adjustment of placement of Target Price Label in cases when the Target Price Label is either obscured by the price labels for the standard z-score levels or is too far right to be visible in the window. 9-Jul-2025 z-score 1.142 updates: Displays in the status line before the close price the range for the selected Std. Deviation levels specified in Settings and |z-zMa|. When |z-zMa| > |avg(z-zMa)| and zMa rising, |z-zMa| and zMa displays in aqua. When |z-zMa| > |avg(z-zMa)| and zMa falling, |z-zMa| and zMa displays in red. When |z-zMa| <= |avg(z-zMa)|, z and zMa display in gray. z usually crosses over zMa when zMa is gray but not always. So if cross-over occurs when zMa is not gray, it implies a strong move in progress. Practice makes perfect. Use this indicator at your own risk
Indicador Pine Script®
por calkusi
Uptrick: Universal Z-Score ValuationOverview The Uptrick: Universal Z-Score Valuation is a tool designed to help traders spot when the market might be overreacting—whether that’s on the upside or the downside. It does this by combining the Z-scores of multiple key indicators into a single average, letting you see how far the current market conditions have stretched away from “normal.” This average is shown as a smooth line, supported by color-coded visuals, signal markers, optional background highlights, and a live breakdown table that shows the contribution of each indicator in real time. The focus here is on spotting potential reversals, not following trends. The indicator works well across all timeframes and asset classes, from fast intraday charts like the 1-minute and 5-minute, to higher timeframes such as the 4-hour, daily, or even weekly. Its universal design makes it suitable for any market — whether you're trading crypto, stocks, forex, or commodities. Introduction To understand what this indicator does, let’s start with the idea of a Z-score. In simple terms, a Z-score tells you how far a number is from the average of its recent history, measured in standard deviations. If the price of an asset is two standard deviations above its mean, that means it’s statistically “rare” or extended. That doesn’t guarantee a reversal—but it suggests the move is unusual enough to pay attention. This concept isn’t new, but what this indicator does differently is apply the Z-score to a wide set of market signals—not just price. It looks at momentum, volatility, volume, risk-adjusted performance, and even institutional price baselines. Each of those indicators is normalized using Z-scores, and then they’re combined into one average. This gives you a single, easy-to-read line that summarizes whether the entire market is behaving abnormally. Instead of reacting to one indicator, you’re reacting to a statistically balanced blend. Purpose The goal of this script is to catch turning points—places where the market may be topping out or bottoming after becoming overstretched. It’s built for traders who want to fade sharp moves rather than follow trends. Think of moments when price explodes upward and starts pulling away from every moving average, volume spikes, volatility rises, and RSI shoots up. This tool is meant to spot those situations—not just when price is stretched, but when multiple different indicators agree that something is overdone. Originality and Uniqueness Most indicators that use Z-scores only apply them to one thing—price, RSI, or maybe Bollinger Bands. This one is different because it treats each indicator as a contributor to the full picture. You decide which ones to include, and the script averages them out. This makes the tool flexible but also deeply informative. It doesn’t rely on complex or hidden math. It uses basic Z-score formulas, applies them to well-known indicators, and shows you the result. What makes it unique is the way it brings those signals together—statistically, visually, and interactively—so you can see what’s happening in the moment with full transparency. It’s not trying to be flashy or predictive. It’s just showing you when things have gone too far, too fast. Inputs and Parameters This indicator includes a wide range of configurable inputs, allowing users to customize which components are included in the Z-score average, how each indicator is calculated, and how results are displayed visually. Below is a detailed explanation of each input: General Settings Z-Score Lookback (default: 100): Number of bars used to calculate the mean and standard deviation for Z-score normalization. Larger values smooth the Z-scores; smaller values make them more reactive. Bar Color Mode (default: None): Determines how bars are visually colored. Options include: None: No candle coloring applied. - Heat: Smooth gradient based on the Z-score value. - Latest Signal: Applies a solid color based on the most recent buy or sell signal Boolean - General Plot Universal Valuation Line (default: true): If enabled, plots the average Z-score (zAvg) line in the separate pane. Show Signals (default: true): Displays labels ("𝓤𝓹" for buy, "𝓓𝓸𝔀𝓷" for sell) when zAvg crosses above or below user-defined thresholds. Show Z-Score Table (default: true): Displays a live table listing each enabled indicator's Z-score and the current average. Select Indicators These toggles enable or disable each indicator from contributing to the Z-score average: Use VWAP Z-Score (default: true) Use Sortino Z-Score (default: true) Use ROC Z-Score (default: true) Use Price Z-Score (default: true) Use MACD Histogram Z-Score (default: false) Use Bollinger %B Z-Score (default: false) Use Stochastic K Z-Score (default: false) Use Volume Z-Score (default: false) Use ATR Z-Score (default: false) Use RSI Z-Score (default: false) Use Omega Z-Score (default: true) Use Sharpe Z-Score (default: true) Only enabled indicators are included in the average. This modular design allows traders to tailor the signal mix to their preferences. Indicator Lengths These inputs control how each individual indicator is calculated: MACD Fast Length (default: 12) MACD Slow Length (default: 26) MACD Signal Length (default: 9) Bollinger Basis Length (default: 20): Used to compute the Bollinger %B. Bollinger Deviation Multiplier (default: 2.0): Standard deviation multiplier for the Bollinger Band calculation. Stochastic Length (default: 14) ATR Length (default: 14) RSI Length (default: 14) ROC Length (default: 10) Zones These thresholds define key signal levels for the Z-score average: Neutral Line Level (default: 0): Baseline for the average Z-score. Bullish Zone Level (default: -1): Optional intermediate zone suggesting early bullish conditions. Bearish Zone Level (default: 1): Optional intermediate zone suggesting early bearish conditions. Z = +2 Line Level (default: 2): Primary threshold for bearish signals. Z = +3 Line Level (default: 3): Extreme bearish warning level. Z = -2 Line Level (default: -2): Primary threshold for bullish signals. Z = -3 Line Level (default: -3): Extreme bullish warning level. These zone levels are used to generate signals, fill background shading, and draw horizontal lines for visual reference. Why These Indicators Were Merged Each indicator in this script was chosen for a specific reason. They all measure something different but complementary. The VWAP Z-score helps you see when price has moved far from the volume-weighted average, often used by institutions. Sortino Ratio Z-score focuses only on downside risk, which is often more relevant to traders than overall volatility. ROC Z-score shows how fast price is changing—strong momentum may burn out quickly. Price Z-score is the raw measure of how far current price has moved from its mean. RSI Z-score shows whether momentum itself is stretched. MACD Histogram Z-score captures shifts in trend strength and acceleration. %B (Bollinger) Z-score indicates how close price is to the upper or lower volatility envelope. Stochastic K Z-score gives a sense of how high or low price is relative to its recent range. Volume Z-score shows when trading activity is unusually high or low. ATR Z-score gives a read on volatility, showing if price movement is expanding or contracting. Sharpe Z-score measures reward-to-risk performance, useful for evaluating trend quality. Omega Z-score looks at the ratio of good returns to bad ones, offering a more nuanced view of efficiency. By normalizing each of these using Z-scores and averaging only the ones you turn on, the script creates a flexible, balanced view of the market’s statistical stretch. Calculations The core formula is the standard Z-score: Z = (current value - average) / standard deviation Every indicator uses this formula after it’s calculated using your chosen settings. For example, RSI is first calculated as usual, then its Z-score is calculated over your selected lookback period. The script does this for every indicator you enable. Then it averages those Z-scores together to create a single value: zAvg. That value is plotted and used to generate visual cues, signals, table values, background color changes, and candle coloring. Sequence Each selected indicator is calculated using your custom input lengths. The Z-score of each indicator is computed using the shared lookback period. All active Z-scores are added up and averaged. The resulting zAvg value is plotted as a line. Signal conditions check if zAvg crosses user-defined thresholds (default: ±2). If enabled, the script plots buy/sell signal labels at those crossover points. The candle color is updated using your selected mode (heatmap or signal-based). If extreme Z-scores are reached, background highlighting is applied. A live table updates with each individual Z-score so you know what’s driving the signal. Features This script isn’t just about stats—it’s about making them usable in real time. Every feature has a clear reason to exist, and they’re all there to give you a better read on market conditions. 1. Universal Z-Score Line This is your primary reference. It reflects the average Z-score across all selected indicators. The line updates live and is color-coded to show how far it is from neutral. The further it gets from 0, the brighter the color becomes—cyan for deeply oversold conditions, magenta for overbought. This gives you instant feedback on how statistically “hot” or “cold” the market is, without needing to read any numbers. 2. Signal Labels (“𝓤𝓹” and “𝓓𝓸𝔀𝓷”) When the average Z-score drops below your lower bound, you’ll see a "𝓤𝓹" label below the bar, suggesting potential bullish reversal conditions. When it rises above the upper bound, a "𝓓𝓸𝔀𝓷" label is shown above the bar—indicating possible bearish exhaustion. These labels are visually clear and minimal so they don’t clutter your chart. They're based on clear crossover logic and do not repaint. 3. Real-Time Z-Score Table The table shows each indicator's individual Z-score and the final average. It updates every bar, giving you a transparent breakdown of what’s happening under the hood. If the market is showing an extreme average score, this table helps you pinpoint which indicators are contributing the most—so you’re not just guessing where the pressure is coming from. 4. Bar Coloring Modes You can choose from three modes: None: Keeps your candles clean and untouched. Heat: Applies a smooth gradient color based on Z-score intensity. As conditions become more extreme, candle color transitions from neutral to either cyan (bullish pressure) or magenta (bearish pressure). Latest Signal: Applies hard coloring based on the most recent signal—greenish for a buy, purple for a sell. This mode is great for tracking market state at a glance without relying on a gradient. Every part of the candle is colored—body, wick, and border—for full visibility. 5. Background Highlighting When zAvg enters an extreme zone (typically above +2 or below -2), the background shifts color to reflect the market’s intensity. These changes aren’t overwhelming—they’re light fills that act as ambient warnings, helping you stay aware of when price might be reaching a tipping point. 6. Customizable Zone Lines and Fills You can define what counts as neutral, overbought, and oversold using manual inputs. Horizontal lines show your thresholds, and shaded regions highlight the most extreme zones (+2 to +3 and -2 to -3). These lines give you visual structure to understand where price currently stands in relation to your personal reversal model. 7. Modular Indicator Control You don’t have to use all the indicators. You can enable or disable any of the 12 with a simple checkbox. This means you can build your own “blend” of market context—maybe you only care about RSI, price, and volume. Or maybe you want everything on. The script adapts accordingly, only averaging what you select. 8. Fully Customizable Sensitivity and Lengths You can adjust the Z-score lookback length globally (default 100), and tweak individual indicator lengths separately. This lets you tune the indicator’s responsiveness to suit your trading style—slower for longer swings, faster for scalping. 9. Clean Integration with Any Chart Layout All visual elements are designed to be informative without taking over your chart. The coloring is soft but clear, the labels are readable without being huge, and you can turn off any feature you don’t need. The indicator can work as a full dashboard or as a simple line with a couple of alerts—it’s up to you. 10. Precise, Real-Time Signal Logic The crossover logic for signals is exact and only fires when the Z-score moves across your defined boundary. No estimation, no delay. Everything is calculated based on current and previous bar data, and nothing repaints or back-adjusts. Conclusion The Universal Z-Score Valuation indicator is a tool for traders who want a clear, unbiased way to detect overextension. Instead of relying on a single signal, you get a composite of several market perspectives—momentum, volatility, volume, and more—all standardized into a single view. The script gives you the freedom to control the logic, the visuals, and the components. Whether you use it as a confirmation tool or a primary signal source, it’s designed to give you clarity when markets become chaotic. Disclaimer This indicator is for research and educational use only. It does not constitute financial advice or guarantees of performance. All trading involves risk, and users should test any strategy thoroughly before applying it to live markets. Use this tool at your own discretion.
Indicador Pine Script®
por Uptrick
9
Volatility-Adjusted Momentum Score (VAMS) [QuantAlgo]🟢 Overview The Volatility-Adjusted Momentum Score (VAMS) measures price momentum relative to current volatility conditions, creating a normalized indicator that identifies significant directional moves while filtering out market noise. It divides annualized momentum by annualized volatility to produce scores that remain comparable across different market environments and asset classes. The indicator displays a smoothed VAMS Z-Score line with adaptive standard deviation bands and an information table showing real-time metrics. This dual-purpose design enables traders and investors to identify strong trend continuation signals when momentum persistently exceeds normal levels, while also spotting potential mean reversion opportunities when readings reach statistical extremes. 🟢 How It Works The indicator calculates annualized momentum using a simple moving average of logarithmic returns over a specified period, then measures annualized volatility through the standard deviation of those same returns over a longer timeframe. The raw VAMS score divides momentum by volatility, creating a risk-adjusted measure where high volatility reduces scores and low volatility amplifies them. This raw VAMS value undergoes Z-Score normalization using rolling statistical parameters, converting absolute readings into standardized deviations that show how current conditions compare to recent history. The normalized Z-Score receives exponential moving average smoothing to create the final VAMS line, reducing false signals while preserving sensitivity to meaningful momentum changes. The visualization includes dynamically calculated standard deviation bands that adjust to recent VAMS behavior, creating statistical reference zones. The information table provides real-time numerical values for VAMS Z-Score, underlying momentum percentages, and current volatility readings with trend indicators. 🟢 How to Use 1. VAMS Z-Score Bands and Signal Interpretation Above Mean Line: Momentum exceeds historical averages adjusted for volatility, indicating bullish conditions suitable for trend following Below Mean Line: Momentum falls below statistical norms, suggesting bearish conditions or downward pressure Mean Line Crossovers: Primary transition signals between bullish and bearish momentum regimes 1 Standard Deviation Breaks: Strong momentum conditions indicating statistically significant directional moves worth following 2 Standard Deviation Extremes: Rare momentum readings that often signal either powerful breakouts or exhaustion points 2. Information Table and Market Context Z-Score Values: Current VAMS reading displayed in standard deviations (σ), showing how far momentum deviates from its statistical norm Momentum Percentage: Underlying annualized momentum displayed as percentage return, quantifying the directional strength Volatility Context: Current annualized volatility levels help interpret whether VAMS readings occur in high or low volatility environments Trend Indicators: Directional arrows and change values provide immediate feedback on momentum shifts and market transitions 3. Strategy Applications and Alert System Trend Following: Use sustained readings beyond the mean line and 1σ band penetrations for directional trades, especially when VAMS maintains position in upper or lower statistical zones Mean Reversion: Focus on 2σ extreme readings for contrarian opportunities, particularly effective in sideways markets where momentum tends to revert to statistical norms Alert Notifications: Built-in alerts for mean crossovers (regime changes), 1σ breaks (strong signals), and 2σ touches (extreme conditions) help monitor multiple instruments for both continuation and reversal setups
Indicador Pine Script®
por QuantAlgo
10
Rolling Z-Score Trend [QuantAlgo]🟢 Overview The Rolling Z-Score Trend measures how far the current price deviates from its rolling mean in terms of standard deviations. It transforms price data into standardized scores to identify overbought and oversold conditions while tracking momentum shifts. The indicator displays a Z-Score line showing price deviation from statistical norms, with background momentum columns showing the rate of change in these deviations. This helps traders and investors identify mean reversion opportunities and momentum shifts across different asset classes and timeframes. 🟢 How It Works The indicator uses the Z-Score formula: Z = (X - μ) / σ, where X is the current closing price, μ is the rolling mean, and σ is the rolling standard deviation over a user-defined lookback period. This creates a dynamic baseline that adapts to changing market conditions and standardizes price movements for interpretation across different assets and volatility conditions. The raw Z-Score undergoes 3-period EMA smoothing to reduce noise while maintaining responsiveness to market signals. Beyond the basic Z-Score calculation, the indicator measures the rate of change in Z-Score values between successive bars, displayed as background momentum columns. This momentum component shows acceleration and deceleration of statistical deviations. All calculations are processed through confirmation filters, displaying signals only on confirmed bars to reduce premature signals based on incomplete price action. 🟢 How to Use 1. Z-Score Interpretation and Threshold Zones Positive Values (Above Zero) : Price trading above statistical mean, suggesting bullish momentum or potential overbought conditions Negative Values (Below Zero) : Price trading below statistical mean, suggesting bearish momentum or potential oversold conditions Zero Line Crosses : Signal transitions between statistical regimes and potential trend changes Upper Threshold Zone : Area above entry threshold (default 1.5) indicating potential overbought conditions Lower Threshold Zone : Area below negative entry threshold (default -1.5) indicating potential oversold conditions Extreme Values (±2.0 or higher) : Statistically significant deviations that may indicate reversal opportunities 2. Momentum Background Analysis and Info Table Green Columns : Accelerating positive momentum in Z-Score values Red Columns : Accelerating negative momentum in Z-Score values Column Height : Magnitude of momentum change between bars Momentum Divergence : When columns contradict primary Z-Score direction, often signals impending reversals Info Table : Displays real-time numerical values for both Z-Score and momentum, including trend direction indicators and bar-to-bar change calculations for position management 3. Preconfigured Settings Default : Balanced performance across multiple timeframes and asset classes for general trading and medium-term position management. Scalping : Responsive setup for ultra-short-term trading on 1-15 minute charts with frequent signals and increased sensitivity to quick price movements. Swing Trading : Optimized for multi-day positions with noise filtering, focusing on larger price swings. Most effective on 1-4 hour and daily timeframes. Trend Following : Maximum smoothing that prioritizes established trends over short-term volatility. Generates fewer signals for daily and weekly charts.
Indicador Pine Script®
por QuantAlgo
27
Uptrick: Z-Trend BandsOverview Uptrick: Z-Trend Bands is a Pine Script overlay crafted to capture high-probability mean-reversion opportunities. It dynamically plots upper and lower statistical bands around an EMA baseline by converting price deviations into z-scores. Once price moves outside these bands and then reenters, the indicator verifies that momentum is genuinely reversing via an EMA-smoothed RSI slope. Signal memory ensures only one entry per momentum swing, and traders receive clear, real-time feedback through customizable bar-coloring modes, a semi-transparent fill highlighting the statistical zone, concise “Up”/“Down” labels, and a live five-metric scoring table. Introduction Markets often oscillate between trending and reverting, and simple thresholds or static envelopes frequently misfire when volatility shifts. Standard deviation quantifies how “wide” recent price moves have been, and a z-score transforms each deviation into a measure of how rare it is relative to its own history. By anchoring these bands to an exponential moving average, the script maintains a fluid statistical envelope that adapts instantly to both calm and turbulent regimes. Meanwhile, the Relative Strength Index (RSI) tracks momentum; smoothing RSI with an EMA and observing its slope filters out erratic spikes, ensuring that only genuine momentum flips—upward for longs and downward for shorts—qualify. Purpose This indicator is purpose-built for short-term mean-reversion traders operating on lower–timeframe charts. It reveals when price has strayed into the outer 5 percent of its recent range, signaling an increased likelihood of a bounce back toward fair value. Rather than firing on price alone, it demands that momentum follow suit: the smoothed RSI slope must flip in the opposite direction before any trade marker appears. This dual-filter approach dramatically reduces noise-driven, false setups. Traders then see immediate visual confirmation—bar colors that reflect the latest signal and age over time, clear entry labels, and an always-visible table of metric scores—so they can gauge both the validity and freshness of each signal at a glance. Originality and Uniqueness Uptrick: Z-Trend Bands stands apart from typical envelope or oscillator tools in four key ways. First, it employs fully normalized z-score bands, meaning ±2 always captures roughly the top and bottom 5 percent of moves, regardless of volatility regime. Second, it insists on two simultaneous conditions—price reentry into the bands and a confirming RSI slope flip—dramatically reducing whipsaw signals. Third, it uses slope-phase memory to lock out duplicate signals until momentum truly reverses again, enforcing disciplined entries. Finally, it offers four distinct bar-coloring schemes (solid reversal, fading reversal, exceeding bands, and classic heatmap) plus a dynamic scoring table, rather than a single, opaque alert, giving traders deep insight into every layer of analysis. Why Each Component Was Picked The EMA baseline was chosen for its blend of responsiveness—weighting recent price heavily—and smoothness, which filters market noise. Z-score deviation bands standardize price extremes relative to their own history, adapting automatically to shifting volatility so that “extreme” always means statistically rare. The RSI, smoothed with an EMA before slope calculation, captures true momentum shifts without the false spikes that raw RSI often produces. Slope-phase memory flags prevent repeated alerts within a single swing, curbing over-trading in choppy conditions. Bar-coloring modes provide flexible visual contexts—whether you prefer to track the latest reversal, see signal age, highlight every breakout, or view a continuous gradient—and the scoring table breaks down all five core checks for complete transparency. Features This indicator offers a suite of configurable visual and logical tools designed to make reversal signals both robust and transparent: Dynamic z-score bands that expand or contract in real time to reflect current volatility regimes, ensuring the outer ±zThreshold levels always represent statistically rare extremes. A smooth EMA baseline that weights recent price more heavily, serving as a fair-value anchor around which deviations are measured. EMA-smoothed RSI slope confirmation, which filters out erratic momentum spikes by first smoothing raw RSI and then requiring its bar-to-bar slope to flip before any signal is allowed. Slope-phase memory logic that locks out duplicate buy or sell markers until the RSI slope crosses back through zero, preventing over-trading during choppy swings. Four distinct bar-coloring modes—Reversal Solid, Reversal Fade, Exceeding Bands, Classic Heat—plus a “None” option, so traders can choose whether to highlight the latest signal, show signal age, emphasize breakout bars, or view a continuous heat gradient within the bands. A semi-transparent fill between the EMA and the upper/lower bands that visually frames the statistical zone and makes extremes immediately obvious. Concise “Up” and “Down” labels that plot exactly when price re-enters a band with confirming momentum, keeping chart clutter to a minimum. A real-time, five-metric scoring table (z-score, RSI slope, price vs. EMA, trend state, re-entry) that updates every two bars, displaying individual +1/–1/0 scores and an averaged Buy/Sell/Neutral verdict for complete transparency. Calculations Compute the fair-value EMA over fairLen bars. Subtract that EMA from current price each bar to derive the raw deviation. Over zLen bars, calculate the rolling mean and standard deviation of those deviations. Convert each deviation into a z-score by subtracting the mean and dividing by the standard deviation. Plot the upper and lower bands at ±zThreshold × standard deviation around the EMA. Calculate raw RSI over rsiLen bars, then smooth it with an EMA of length rsiEmaLen. Derive the RSI slope by taking the difference between the current and previous smoothed RSI. Detect a potential reentry when price exits one of the bands on the prior bar and re-enters on the current bar. Require that reentry coincide with an RSI slope flip (positive for a lower-band reentry, negative for an upper-band reentry). On first valid reentry per momentum swing, fire a buy or sell signal and set a memory flag; reset that flag only when the RSI slope crosses back through zero. For each bar, assign scores of +1, –1, or 0 for the z-score direction, RSI slope, price vs. EMA, trend-state, and reentry status. Average those five scores; if the result exceeds +0.1, label “Buy,” if below –0.1, label “Sell,” otherwise “Neutral.” Update bar colors, the semi-transparent fill, reversal labels, and the scoring table every two bars to reflect the latest calculations. How It Actually Works On each new candle, the EMA baseline and band widths update to reflect current volatility. The RSI is smoothed and its slope recalculated. The script then looks back one bar to see if price exited either band and forward to see if it reentered. If that reentry coincides with an appropriate RSI slope flip—and no signal has yet been generated in that swing—a concise label appears. Bar colors refresh according to your selected mode, and the scoring table updates to show which of the five conditions passed or failed, along with the overall verdict. This process repeats seamlessly at each bar, giving traders a continuous feed of disciplined, statistically filtered reversal cues. Inputs All parameters are fully user-configurable, allowing you to tailor sensitivity, lookbacks, and visuals to your trading style: EMA length (fairLen): number of bars for the fair-value EMA; higher values smooth more but lag further behind price. Z-Score lookback (zLen): window for calculating the mean and standard deviation of price deviations; longer lookbacks reduce noise but respond more slowly to new volatility. Z-Score threshold (zThreshold): number of standard deviations defining the upper and lower bands; common default is 2.0 for roughly the outer 5 percent of moves. Source (src): choice of price series (close, hl2, etc.) used for EMA, deviation, and RSI calculations. RSI length (rsiLen): period for raw RSI calculation; shorter values react faster to momentum changes but can be choppier. RSI EMA length (rsiEmaLen): period for smoothing raw RSI before taking its slope; higher values filter more noise. Bar coloring mode (colorMode): select from None, Reversal Solid, Reversal Fade, Exceeding Bands, or Classic Heat to control how bars are shaded in relation to signals and band positions. Show signals (showSignals): toggle on-chart “Up” and “Down” labels for reversal entries. Show scoring table (enableTable): toggle the display of the five-metric breakdown table. Table position (tablePos): choose which corner (Top Left, Top Right, Bottom Left, Bottom Right) hosts the scoring table. Conclusion By merging a normalized z-score framework, momentum slope confirmation, disciplined signal memory, flexible visuals, and transparent scoring into one Pine Script overlay, Uptrick: Z-Trend Bands offers a powerful yet intuitive tool for intraday mean-reversion trading. Its adaptability to real-time volatility and multi-layered filter logic deliver clear, high-confidence reversal cues without the clutter or confusion of simpler indicators. Disclaimer This indicator is provided solely for educational and informational purposes. It does not constitute financial advice. Trading involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. Always conduct your own testing and apply careful risk management before trading live.
Indicador Pine Script®
por Uptrick
Neural Adaptive VWAPNeural Adaptive VWAP with ML Features is an advanced trading indicator that enhances traditional Volume Weighted Average Price (VWAP) calculations through machine learning-inspired adaptive algorithms and predictive volume modeling. 🌟 Key Features: 🧠 Machine Learning-Inspired Adaptation Dynamic weight adjustment system that learns from prediction errors Multi-feature volume prediction using time-of-day patterns, price momentum, and volatility Adaptive learning mechanism that improves accuracy over time 📊 Enhanced VWAP Calculation Combines actual and predicted volume for forward-looking VWAP computation Session-based reset with proper daily anchoring Confidence bands based on rolling standard deviation for dynamic support/resistance 🎯 Advanced Signal Generation Volume-confirmed crossover signals to reduce false entries Color-coded candle visualization based on VWAP position Multi-level strength indicators (strong/weak bullish/bearish zones) ⚙️ Intelligent Feature Engineering Normalized volume analysis with statistical z-score Time-series pattern recognition for intraday volume cycles Price momentum and volatility integration Sigmoid activation functions for realistic predictions 📈 How It Works: The indicator employs a sophisticated feature engineering approach that extracts meaningful patterns from: Volume Patterns: Normalized volume analysis and historical comparisons Temporal Features: Time-of-day and minute-based cyclical patterns Market Dynamics: Price momentum, volatility, and rate of change Adaptive Learning: Error-based weight adjustment similar to neural network training Unlike static VWAP indicators, this system continuously adapts its calculation methodology based on real-time market feedback, making it more responsive to changing market conditions while maintaining the reliability of traditional VWAP analysis. 🔧 Customizable Parameters: VWAP Length (1-200 bars) Volume Pattern Lookback (5-50 periods) Learning Rate (0.001-0.1) for adaptation speed Prediction Horizon (1-10 bars ahead) Adaptation Period for weight updates 📊 Visual Elements: Blue Line: Adaptive VWAP with predictive elements Red/Green Bands: Dynamic confidence zones Colored Candles: Position-based strength visualization Signal Arrows: Volume-confirmed entry points Info Table: Real-time performance metrics and weight distribution 🎯 Best Use Cases: Intraday Trading: Enhanced execution timing with volume prediction Institutional-Style Execution: Improved VWAP-based order placement Trend Following: Adaptive trend identification with confidence zones Support/Resistance Trading: Dynamic levels that adjust to market conditions
Indicador Pine Script®
por shui2967
1
Fibo Normalized RSI & RSI RibbonPlots both standard and Z-score normalized RSI ribbons using Fibonacci-based periods. Supports adjustable normalization, optional 0–100 scaling, and multi-line visualizations for momentum and deviation analysis. This tool is designed for traders who want to go beyond standard RSI by adding: Statistical normalization (Z-score) Multi-period analysis (Fibonacci structure) Advanced divergence and exhaustion detection It gives you both classical momentum context and mathematically rigorous deviation insight, making it ideal for: Swing traders Quant-inclined discretionary traders Multi-timeframe analysts Trend Confirmation When both RSI and normalized RSI across short and long periods are stacked in the same direction (e.g., above 50 or with high Z-scores), the trend is likely strong. Disagreement between the two ribbons (e.g., RSI high but normalized RSI flat) may indicate late-stage trend or false strength. Mean Reversion Trades Look for normalized RSI values > +2 or < -2 (i.e., ~2 standard deviations). Cross-check with standard RSI to see if the move aligns with a traditional overbought/oversold level. Great for fade/reversal setups when Z-score RSI is extreme but classic RSI is just beginning to turn. Divergence Detection Compare the slope of RSI vs. normalized RSI over same period: If RSI is rising but normalized RSI is falling → momentum is fading despite apparent strength. Excellent for early warnings before reversals. Multi-Timeframe Confluence Use short-period ribbons (e.g., 3–13) for tactical entries/exits. Use long-period ribbons (e.g., 55–233) for macro trend bias. Alignment across both = high-confidence zone.
Indicador Pine Script®
por SCJedi
Z-Score Trend Monitor [EdgeTerminal]The Z-Score Trend Monitor measures how far the short-term moving average deviates from the long-term moving average using the spread difference of the two — in standardized units. It’s designed to detect overextension, momentum exhaustion, and potential mean-reversion points by converting the spread between two moving averages into a normalized Z-score and tracking its change and direction over time. The idea behind this is to catch the changes in the direction of a trend earlier than the usual and lagging moving average lines, allowing you to react faster. The math behind the indicator itself is very simple. We take the simple moving average of the spread between a long term and short term moving average, and divide it by the difference between the spread and spread mean. This results in a relatively accurate and early acting trend detector that can easily identify overbought and oversold levels in any timeframe. From our own testing, we recommend using this indicator as a trend confirmation tool. How to Use It: Keep an eye on the Z-Score or the blue line. When it goes over 2, it indicates an overbought or near top level, and when it goes below -2, it indicates an oversold or near bottom. When Z-Score returns to zero or grey line, it suggests mean reversion is in progress. You can also change the Z-Score criteria from 2 and -2 in the settings to any number you’d like for tighter or wider levels. For scalping and fast trading setups, we recommend shorter SMAs, such as 5 and 20, and for longer trading setups such as swing trades, we recommend 20 and 100. Settings: Short SMA: Lookback period of short term simple moving average for the lower side of the SMA spread. Short Term Weight: Additional weight or multiplier to suppress the short term SMA calculation. This is used to refine the SMA calculation for more granular and edge cases when needed, usually left at 1, meaning it will take the entire given value in the short SMA field. Long SMA: Lookback period of long term simple moving average for the upper side of the SMA spread. Long Term Weight: Additional weight or multiplier to suppress the long term SMA calculation. This is used to refine the long SMA calculation for more granular and edge cases when needed, usually left at 1, meaning it will take the entire given value in the long SMA field. Z-Score Threshold: The threshold for upper (oversold) and lower (overbought) levels. This can also be set individually from the style page. Z-Score Lookback Window: The lookback period to calculate spread mean and spread standard deviation
Indicador Pine Script®
por EdgeTerminal