Começar

Indicadores e estratégias

Illuminati Zone🟣 Illuminati Zone — Hidden Power of the 11 PM NZ Candle The Illuminati Zone reveals the hidden footprints of liquidity and market imbalance formed by the 11 PM New Zealand 15-minute candle — a time when global liquidity transitions between major sessions. This candle often defines key intraday supply and demand boundaries, serving as a magnet for price and a pivot point for high-probability reversals or breakouts. 🧠 How it works Automatically detects and marks the 11 PM NZ 15-minute candle each day. Draws a translucent zone box between its high and low. Extends two reference lines at +1 × range and –1 × range above and below the zone — ideal for spotting overextensions or liquidity sweeps. Supports custom lookback, colors, and visual options. 💡 How to use it Watch how price interacts with the zone — rejection often signals smart-money activity. Use +1 and –1 levels as overextended zones for potential reversals or breakout retests. Combine with your own confluence tools or volume analysis for precision entries. ⚙️ Customization Options Target hour (NZ time) Days back to display Zone and line colors Transparency and visual preferences 🔮 Pro Tip: Pair it with a volume or imbalance indicator for surgical-level precision in identifying where smart money positions are built or released.
Indicador Pine Script®
por SimkeBoi
2
Volume Delta [BigBeluga]🔵 OVERVIEW The Volume Delta indicator visualizes the dominance between buying and selling volume within a given period. It calculates the percentage of bullish (buy) versus bearish (sell) volume, then color-codes the candles and provides a real-time dashboard comparing delta values across multiple currency pairs. This makes it a powerful tool for monitoring order-flow strength and intermarket relationships in real time. 🔵 CONCEPTS Each bar’s buy volume is counted when the close is higher than the open. Each bar’s sell volume is counted when the close is lower than the open. volumeBuy = 0. volumeSell = 0. for i = 0 to period if close > open volumeBuy += volume else volumeSell += volume The indicator sums both over a chosen period to calculate the ratio of buy-to-sell pressure. Delta (%) = (Buy Volume ÷ (Buy Volume + Sell Volume)) × 100. Gradient colors highlight whether buying or selling pressure dominates. 🔵 FEATURES Calculates real-time Volume Delta for the selected chart or for multiple assets. Colors candles dynamically based on the delta intensity (green = buy pressure, red = sell pressure). Displays a dashboard table showing volume delta % for up to five instruments. The dashboard features visual progress bars for quick intermarket comparison. An optional Delta Bar Panel shows the ratio of Buy/Sell volumes near the latest bar. A floating label shows the exact Buy/Sell percentages. Works across all symbols and timeframes for multi-asset delta tracking. 🔵 HOW TO USE When Buy % > Sell % , it often signals bullish momentum or strong accumulation—but can also indicate over-excitement and a possible market top. Market Tops When Sell % > Buy % , it typically reflects bearish pressure or distribution—but may also occur near a market bottom where selling exhaustion forms. Market Bottom Use the Dashboard to compare volume flow across correlated assets (e.g., major Forex pairs or sector groups). Combine readings with trend or volatility filters to confirm whether the imbalance aligns with broader directional conviction. Treat the Delta Bar visualization as a real-time sentiment gauge—showing which side (buyers or sellers) dominates the current session. 🔵 CONCLUSION Volume Delta transforms volume analysis into an intuitive directional signal. By quantifying buy/sell pressure and displaying it as a percentage or color gradient, it provides traders with a clearer picture of real-time volume imbalance — whether within one market or across multiple correlated instruments.
Indicador Pine Script®
por BigBeluga
5
Enhanced Holt-Winters RSI [BOSWaves]Enhanced Holt-Winters RSI – Next-Level Momentum Smoothing & Signal Precision Overview The Enhanced Holt-Winters RSI transforms the classic Relative Strength Index into a robust, lag-minimized momentum oscillator through Holt-Winters triple exponential smoothing. By modeling the level, trend, and cyclical behavior of the RSI series, this indicator delivers smoother, more responsive signals that highlight overbought/oversold conditions, momentum shifts, and high-conviction trading setups without cluttering the chart with noise. Unlike traditional RSI, which reacts to historical data and produces frequent whipsaws, the Enhanced Holt-Winters RSI filters transient price fluctuations, enabling traders to detect emerging momentum and potential reversal zones earlier. Theoretical Foundation The traditional RSI measures relative strength by comparing average gains and losses, but suffers from: Lag in trend recognition : Signals often arrive after momentum has shifted. Noise sensitivity : High-frequency price movements generate unreliable crossovers. Limited insight into structural market shifts : Standard RSI cannot contextualize cyclical or momentum patterns. The Enhanced Holt-Winters RSI addresses these limitations by applying triple exponential smoothing directly to the RSI series. This decomposes the series into: Level (Lₜ) : Represents the smoothed central tendency of RSI. Trend (Tₜ) : Captures rate-of-change in smoothed momentum. Seasonal Component (Sₜ) : Models short-term cyclical deviations in momentum. By incorporating these elements, the oscillator produces smoothed RSI values that react faster to emerging trends while suppressing erratic noise. Its internal forecast is mathematical, influencing the smoothed RSI output and signals, rather than being directly plotted. How It Works The Enhanced Holt-Winters RSI builds its signal framework through several layers: 1. Base RSI Calculation Computes standard RSI over the selected period as the primary momentum input. 2. Triple Exponential Smoothing (Holt-Winters) The RSI is smoothed recursively to extract underlying momentum structure: Level, trend, and seasonal components are combined to produce a smoothed RSI. This internal smoothing reduces lag and enhances signal reliability. 3. Momentum Analysis Short-term momentum shifts are tracked via a moving average of the smoothed RSI, highlighting acceleration or deceleration in directional strength. 4. Volume Confirmation (Optional) Buy/sell signals can be filtered through a configurable volume threshold, ensuring only high-conviction moves trigger alerts. 5. Visual Output Colored Candles : Represent overbought (red), oversold (green), or neutral (yellow) conditions. Oscillator Panel : Plots the smoothed RSI with dynamic color coding for immediate trend context. Signals : Triangular markers indicate bullish or bearish setups, with stronger signals flagged in extreme zones. Interpretation The Enhanced Holt-Winters RSI provides a multi-dimensional perspective on price action: Trend Strength : Smoothed RSI slope and color coding reflect the direction and momentum intensity. Momentum Shifts : Rapid changes in the smoothed RSI indicate emerging strength or weakness. Overbought/Oversold Zones : Highlight areas where price is stretched relative to recent momentum. High-Conviction Signals : Combined with volume filtering, markers indicate optimal entries/exits. Cycle Awareness : Smoothing reveals structural patterns, helping traders avoid reacting to noise. By combining these elements, traders gain early insight into market structure and momentum without relying on raw, lag-prone RSI data. Strategy Integration The Enhanced Holt-Winters RSI can be applied across trading styles: Trend Following Enter when RSI is aligned with price momentum and color-coded signals confirm trend direction. Strong slope in the smoothed RSI signals trend continuation. Reversal Trading Look for RSI extremes with momentum shifts and strong signal markers. Compression in oscillator values often precedes reversal setups. Breakout Detection Oscillator flattening in neutral zones followed by directional expansion indicates potential breakout conditions. Multi-Timeframe Confluence Higher timeframes provide directional bias; lower timeframes refine entry timing using smoothed RSI dynamics. Technical Implementation Details Input Source : Close, open, high, low, or price. Smoothing : Holt-Winters triple exponential smoothing applied to RSI. Parameters : Level (α) : Controls smoothing of RSI. Trend (β) : Adjusts responsiveness to momentum changes. Seasonal Length : Defines cycles for short-term adjustments. Delta Smoothing : Reduces choppiness in smoothed RSI difference. Outputs : Smoothed RSI Colored candles and oscillator panel Buy/Sell signal markers (with optional strength filtering) Volume Filtering : Optional threshold to confirm signals. Optimal Application Parameters Asset-Specific Guidance: Forex : Use moderate smoothing (α, β) to capture medium-term momentum swings while filtering minor price noise. Works best when combined with volume or volatility filters. Equities : Balance responsiveness and smoothness to identify sustained sector momentum or rotational shifts; ideal for capturing clean directional transitions. Cryptocurrency : Increase smoothing parameters slightly to stabilize RSI during extreme volatility; optional volume confirmation can help filter false signals. Futures/Indices : Lower smoothing sensitivity emphasizes macro momentum and structural trend durability over short-term fluctuations. Timeframe Optimization: Scalping (1-5m) : Use higher sensitivity (lower smoothing factors) to react quickly to micro-momentum reversals. Intraday (15m-1h) : Balance smoothing and responsiveness for detecting short-term acceleration and exhaustion zones. Swing (4h-Daily) : Apply moderate smoothing to reveal underlying directional persistence and cyclical reversals. Position (Daily-Weekly) : Use stronger smoothing to isolate dominant momentum trends and filter temporary pullbacks. Integration Guidelines Combine with trend filters (EMAs, SuperSmoother MA, ATR-based tools) for confirmation. Use volume and signal strength markers to filter low-conviction trades. Slope, color, and signal alignment can guide entry, stop placement, and scaling. Disclaimer The Enhanced Holt-Winters RSI is a technical analysis tool, not a guaranteed profit system. Effectiveness depends on proper settings, market structure, and disciplined risk management. Always backtest before live trading.
Indicador Pine Script®
por BOSWaves
T3 ATR [DCAUT]█ T3 ATR 📊 ORIGINALITY & INNOVATION The T3 ATR indicator represents an important enhancement to the traditional Average True Range (ATR) indicator by incorporating the T3 (Tilson Triple Exponential Moving Average) smoothing algorithm. While standard ATR uses fixed RMA (Running Moving Average) smoothing, T3 ATR introduces a configurable volume factor parameter that allows traders to adjust the smoothing characteristics from highly responsive to heavily smoothed output. This innovation addresses a fundamental limitation of traditional ATR: the inability to adapt smoothing behavior without changing the calculation period. With T3 ATR, traders can maintain a consistent ATR period while adjusting the responsiveness through the volume factor, making the indicator adaptable to different trading styles, market conditions, and timeframes through a single unified implementation. The T3 algorithm's triple exponential smoothing with volume factor control provides improved signal quality by reducing noise while maintaining better responsiveness compared to traditional smoothing methods. This makes T3 ATR particularly valuable for traders who need to adapt their volatility measurement approach to varying market conditions without switching between multiple indicator configurations. 📐 MATHEMATICAL FOUNDATION The T3 ATR calculation process involves two distinct stages: Stage 1: True Range Calculation The True Range (TR) is calculated using the standard formula: TR = max(high - low, |high - close |, |low - close |) This captures the greatest of the current bar's range, the gap from the previous close to the current high, or the gap from the previous close to the current low, providing a comprehensive measure of price movement that accounts for gaps and limit moves. Stage 2: T3 Smoothing Application The True Range values are then smoothed using the T3 algorithm, which applies six exponential moving averages in succession: First Layer: e1 = EMA(TR, period), e2 = EMA(e1, period) Second Layer: e3 = EMA(e2, period), e4 = EMA(e3, period) Third Layer: e5 = EMA(e4, period), e6 = EMA(e5, period) Final Calculation: T3 = c1×e6 + c2×e5 + c3×e4 + c4×e3 The coefficients (c1, c2, c3, c4) are derived from the volume factor (VF) parameter: a = VF / 2 c1 = -a³ c2 = 3a² + 3a³ c3 = -6a² - 3a - 3a³ c4 = 1 + 3a + a³ + 3a² The volume factor parameter (0.0 to 1.0) controls the weighting of these coefficients, directly affecting the balance between responsiveness and smoothness: Lower VF values (approaching 0.0): Coefficients favor recent data, resulting in faster response to volatility changes with minimal lag but potentially more noise Higher VF values (approaching 1.0): Coefficients distribute weight more evenly across the smoothing layers, producing smoother output with reduced noise but slightly increased lag 📊 COMPREHENSIVE SIGNAL ANALYSIS Volatility Level Interpretation: High Absolute Values: Indicate strong price movements and elevated market activity, suggesting larger position risks and wider stop-loss requirements, often associated with trending markets or significant news events Low Absolute Values: Indicate subdued price movements and quiet market conditions, suggesting smaller position risks and tighter stop-loss opportunities, often associated with consolidation phases or low-volume periods Rapid Increases: Sharp spikes in T3 ATR often signal the beginning of significant price moves or market regime changes, providing early warning of increased trading risk Sustained High Levels: Extended periods of elevated T3 ATR indicate sustained trending conditions with persistent volatility, suitable for trend-following strategies Sustained Low Levels: Extended periods of low T3 ATR indicate range-bound conditions with suppressed volatility, suitable for mean-reversion strategies Volume Factor Impact on Signals: Low VF Settings (0.0-0.3): Produce responsive signals that quickly capture volatility changes, suitable for short-term trading but may generate more frequent color changes during minor fluctuations Medium VF Settings (0.4-0.7): Provide balanced signal quality with moderate responsiveness, filtering out minor noise while capturing significant volatility changes, suitable for swing trading High VF Settings (0.8-1.0): Generate smooth, stable signals that filter out most noise and focus on major volatility trends, suitable for position trading and long-term analysis 🎯 STRATEGIC APPLICATIONS Position Sizing Strategy: Determine your risk per trade (e.g., 1% of account capital - adjust based on your risk tolerance and experience) Decide your stop-loss distance multiplier (e.g., 2.0x T3 ATR - this varies by market and strategy, test different values) Calculate stop-loss distance: Stop Distance = Multiplier × Current T3 ATR Calculate position size: Position Size = (Account × Risk %) / Stop Distance Example: $10,000 account, 1% risk, T3 ATR = 50 points, 2x multiplier → Position Size = ($10,000 × 0.01) / (2 × 50) = $100 / 100 points = 1 unit per point Important: The ATR multiplier (1.5x - 3.0x) should be determined through backtesting for your specific instrument and strategy - using inappropriate multipliers may result in stops that are too tight (frequent stop-outs) or too wide (excessive losses) Adjust the volume factor to match your trading style: lower VF for responsive stop distances in short-term trading, higher VF for stable stop distances in position trading Dynamic Stop-Loss Placement: Determine your risk tolerance multiplier (typically 1.5x to 3.0x T3 ATR) For long positions: Set stop-loss at entry price minus (multiplier × current T3 ATR value) For short positions: Set stop-loss at entry price plus (multiplier × current T3 ATR value) Trail stop-losses by recalculating based on current T3 ATR as the trade progresses Adjust the volume factor based on desired stop-loss stability: higher VF for less frequent adjustments, lower VF for more adaptive stops Market Regime Identification: Calculate a reference volatility level using a longer-period moving average of T3 ATR (e.g., 50-period SMA) High Volatility Regime: Current T3 ATR significantly above reference (e.g., 120%+) - favor trend-following strategies, breakout trades, and wider targets Normal Volatility Regime: Current T3 ATR near reference (e.g., 80-120%) - employ standard trading strategies appropriate for prevailing market structure Low Volatility Regime: Current T3 ATR significantly below reference (e.g., <80%) - favor mean-reversion strategies, range trading, and prepare for potential volatility expansion Monitor T3 ATR trend direction and compare current values to recent history to identify regime transitions early Risk Management Implementation: Establish your maximum portfolio heat (total risk across all positions, typically 2-6% of capital) For each position: Calculate position size using the formula Position Size = (Account × Individual Risk %) / (ATR Multiplier × Current T3 ATR) When T3 ATR increases: Position sizes automatically decrease (same risk %, larger stop distance = smaller position) When T3 ATR decreases: Position sizes automatically increase (same risk %, smaller stop distance = larger position) This approach maintains constant dollar risk per trade regardless of market volatility changes Use consistent volume factor settings across all positions to ensure uniform risk measurement 📋 DETAILED PARAMETER CONFIGURATION ATR Length Parameter: Default Setting: 14 periods This is the standard ATR calculation period established by Welles Wilder, providing balanced volatility measurement that captures both short-term fluctuations and medium-term trends across most markets and timeframes Selection Principles: Shorter periods increase sensitivity to recent volatility changes and respond faster to market shifts, but may produce less stable readings Longer periods emphasize sustained volatility trends and filter out short-term noise, but respond more slowly to genuine regime changes The optimal period depends on your holding time, trading frequency, and the typical volatility cycle of your instrument Consider the timeframe you trade: Intraday traders typically use shorter periods, swing traders use intermediate periods, position traders use longer periods Practical Approach: Start with the default 14 periods and observe how well it captures volatility patterns relevant to your trading decisions If ATR seems too reactive to minor price movements: Increase the period until volatility readings better reflect meaningful market changes If ATR lags behind obvious volatility shifts that affect your trades: Decrease the period for faster response Match the period roughly to your typical holding time - if you hold positions for N bars, consider ATR periods in a similar range Test different periods using historical data for your specific instrument and strategy before committing to live trading T3 Volume Factor Parameter: Default Setting: 0.7 This setting provides a reasonable balance between responsiveness and smoothness for most market conditions and trading styles Understanding the Volume Factor: Lower values (closer to 0.0) reduce smoothing, allowing T3 ATR to respond more quickly to volatility changes but with less noise filtering Higher values (closer to 1.0) increase smoothing, producing more stable readings that focus on sustained volatility trends but respond more slowly The trade-off is between immediacy and stability - there is no universally optimal setting Selection Principles: Match to your decision speed: If you need to react quickly to volatility changes for entries/exits, use lower VF; if you're making longer-term risk assessments, use higher VF Match to market character: Noisier, choppier markets may benefit from higher VF for clearer signals; cleaner trending markets may work well with lower VF for faster response Match to your preference: Some traders prefer responsive indicators even with occasional false signals, others prefer stable indicators even with some delay Practical Adjustment Guidelines: Start with default 0.7 and observe how T3 ATR behavior aligns with your trading needs over multiple sessions If readings seem too unstable or noisy for your decisions: Try increasing VF toward 0.9-1.0 for heavier smoothing If the indicator lags too much behind volatility changes you care about: Try decreasing VF toward 0.3-0.5 for faster response Make meaningful adjustments (0.2-0.3 changes) rather than small increments - subtle differences are often imperceptible in practice Test adjustments in simulation or paper trading before applying to live positions 📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES Responsiveness Characteristics: The T3 smoothing algorithm provides improved responsiveness compared to traditional RMA smoothing used in standard ATR. The triple exponential design with volume factor control allows the indicator to respond more quickly to genuine volatility changes while maintaining the ability to filter noise through appropriate VF settings. This results in earlier detection of volatility regime changes compared to standard ATR, particularly valuable for risk management and position sizing adjustments. Signal Stability: Unlike simple smoothing methods that may produce erratic signals during transitional periods, T3 ATR's multi-layer exponential smoothing provides more stable signal progression. The volume factor parameter allows traders to tune signal stability to their preference, with higher VF settings producing remarkably smooth volatility profiles that help avoid overreaction to temporary market fluctuations. Comparison with Standard ATR: Adaptability: T3 ATR allows adjustment of smoothing characteristics through the volume factor without changing the ATR period, whereas standard ATR requires changing the period length to alter responsiveness, potentially affecting the fundamental volatility measurement Lag Reduction: At lower volume factor settings, T3 ATR responds more quickly to volatility changes than standard ATR with equivalent periods, providing earlier signals for risk management adjustments Noise Filtering: At higher volume factor settings, T3 ATR provides superior noise filtering compared to standard ATR, producing cleaner signals for long-term analysis without sacrificing volatility measurement accuracy Flexibility: A single T3 ATR configuration can serve multiple trading styles by adjusting only the volume factor, while standard ATR typically requires multiple instances with different periods for different trading applications Suitable Use Cases: T3 ATR is well-suited for the following scenarios: Dynamic Risk Management: When position sizing and stop-loss placement need to adapt quickly to changing volatility conditions Multi-Style Trading: When a single volatility indicator must serve different trading approaches (day trading, swing trading, position trading) Volatile Markets: When standard ATR produces too many false volatility signals during choppy conditions Systematic Trading: When algorithmic systems require a single, configurable volatility input that can be optimized for different instruments Market Regime Analysis: When clear identification of volatility expansion and contraction phases is critical for strategy selection Known Limitations: Like all technical indicators, T3 ATR has limitations that users should understand: Historical Nature: T3 ATR is calculated from historical price data and cannot predict future volatility with certainty Smoothing Trade-offs: The volume factor setting involves a trade-off between responsiveness and smoothness - no single setting is optimal for all market conditions Extreme Events: During unprecedented market events or gaps, T3 ATR may not immediately reflect the full scope of volatility until sufficient data is processed Relative Measurement: T3 ATR values are most meaningful in relative context (compared to recent history) rather than as absolute thresholds Market Context Required: T3 ATR measures volatility magnitude but does not indicate price direction or trend quality - it should be used in conjunction with directional analysis Performance Expectations: T3 ATR is designed to help traders measure and adapt to changing market volatility conditions. When properly configured and applied: It can help reduce position risk during volatile periods through appropriate position sizing It can help identify optimal times for more aggressive position sizing during stable periods It can improve stop-loss placement by adapting to current market conditions It can assist in strategy selection by identifying volatility regimes However, volatility measurement alone does not guarantee profitable trading. T3 ATR should be integrated into a comprehensive trading approach that includes directional analysis, proper risk management, and sound trading psychology. USAGE NOTES This indicator is designed for technical analysis and educational purposes. T3 ATR provides adaptive volatility measurement but has limitations and should not be used as the sole basis for trading decisions. The indicator measures historical volatility patterns, and past volatility characteristics do not guarantee future volatility behavior. Market conditions can change rapidly, and extreme events may produce volatility readings that fall outside historical norms. Traders should combine T3 ATR with directional analysis tools, support/resistance analysis, and other technical indicators to form a complete trading strategy. Proper backtesting and forward testing with appropriate risk management is essential before applying T3 ATR-based strategies to live trading. The volume factor parameter should be optimized for specific instruments and trading styles through careful testing rather than assuming default settings are optimal for all applications.
Indicador Pine Script®
por DCAUT
Volume Sampled Supertrend [BackQuant]Volume Sampled Supertrend A Supertrend that runs on a volume sampled price series instead of fixed time. New synthetic bars are only created after sufficient traded activity, which filters out low participation noise and makes the trend much easier to read and model. Original Script Link This indicator is built on top of my volume sampling engine. See the base implementation here: Why Volume Sampling Traditional charts print a bar every N minutes regardless of how active the tape is. During quiet periods you accumulate many small, low information bars that add noise and whipsaws to downstream signals. Volume sampling replaces the clock with participation. A new synthetic bar is created only when a pre-set amount of volume accumulates (or, in Dollar Bars mode, when pricevolume reaches a dollar threshold). The result is a non-uniform time series that stretches in busy regimes and compresses in quiet regimes. This naturally: filters dead time by skipping low volume chop; standardizes the information content per bar, improving comparability across regimes; stabilizes volatility estimates used inside banded indicators; gives trend and breakout logic cleaner state transitions with fewer micro flips. What this tool does It builds a synthetic OHLCV stream from volume based buckets and then applies a Supertrend to that synthetic price. You are effectively running Supertrend on a participation clock rather than a wall clock. Core Features Sampling Engine - Choose Volume buckets or Dollar Bars . Thresholds can be dynamic from a rolling mean or median, or fixed by the user. Synthetic Candles - Plots the volume sampled OHLC candles so you can visually compare against regular time candles. Supertrend on Synthetic Price - ATR bands and direction are computed on the sampled series, not on time bars. Adaptive Coloring - Candle colors can reflect side, intensity by volume, or a neutral scheme. Research Panels - Table shows total samples, current bucket fill, threshold, bars-per-sample, and synthetic return stats. Alerts - Long and Short triggers on Supertrend direction flips for the synthetic series. How it works Sampling Pick Sampling Method = Volume or Dollar Bars. Set the dynamic threshold via Rolling Lookback and Filter (Mean or Median), or enable Use Fixed and type a constant. The script accumulates volume (or pricevolume) each time bar. When the bucket reaches the threshold, it finalizes one or more synthetic candles and resets accumulation. Each synthetic candle stores its own OHLCV and is appended to the synthetic series used for all downstream logic. Supertrend on the sampled stream Choose Supertrend Source (Open, High, Low, Close, HLC3, HL2, OHLC4, HLCC4) derived from the synthetic candle. Compute ATR over the synthetic series with ATR Period , then form upperBand = src + factorATR and lowerBand = src - factorATR . Apply classic trailing band and direction rules to produce Supertrend and trend state. Because bars only come when there is sufficient participation, band touches and flips tend to align with meaningful pushes, not idle prints. Reading the display Synthetic Volume Bars - The non-uniform candles that represent equal information buckets. Expect more candles during active sessions and fewer during lulls. Volume Sampled Supertrend - The main line. Green when Trend is 1, red when Trend is -1. Markers - Small dots appear when a new synthetic sample is created, useful for aligning activity cycles. Time Bars Overlay (optional) - Plot regular time candles to compare how the synthetic stream compresses quiet chop. Settings you will use most Data Settings Sampling Method - Volume or Dollar Bars. Rolling Lookback and Filter - Controls the dynamic threshold. Median is robust to outliers, Mean is smoother. Use Fixed and Fixed Threshold - Force a constant bucket size for consistent sampling across regimes. Max Stored Samples - Ring buffer limit for performance. Indicator Settings SMA over last N samples - A moving average computed on the synthetic close series. Can be hidden for a cleaner layout. Supertrend Source - Price field from the synthetic candle. ATR Period and Factor - Standard Supertrend controls applied on the synthetic series. Visuals and UI Show Synthetic Bars - Turn synthetic candles on or off. Candle Color Mode - Green/Red, Volume Intensity, Neutral, or Adaptive. Mark new samples - Puts a dot when a bucket closes. Show Time Bars - Overlay regular candles for comparison. Paint candles according to Trend - Colors chart candles using current synthetic Supertrend direction. Line Width , Colors , and Stats Table toggles. Some workflow notes: Trend Following Set Sampling Method = Volume, Filter = Median, and a reasonable Rolling Lookback so busy regimes produce more samples. Trade in the direction of the Volume Sampled Supertrend. Because flips require real participation, you tend to avoid micro whipsaws seen on time bars. Use the synthetic SMA as a bias rail and trailing reference for partials or re-entries. Breakout and Continuation Watch for rapid clustering of new sample markers and a clean flip of the synthetic Supertrend. The compression of quiet time and expansion in busy bursts often makes breakouts more legible than on uniform time charts. Mean Reversion In instruments that oscillate, faded moves against the synthetic Supertrend are easier to time when the bucket cadence slows and Supertrend flattens. Combine with the synthetic SMA and return statistics in the table for sizing and expectation setting. Stats table (top right) Method and Total Samples - Sampling regime and current synthetic history length. Current Vol or Dollar and Threshold - Live bucket fill versus the trigger. Bars in Bucket and Avg Bars per Sample - How much time data each synthetic bar tends to compress. Avg Return and Return StdDev - Simple research metrics over synthetic close-to-close changes. Why this reduces noise Time based bars treat a 5 minute print with 1 percent of average participation the same as one with 300 percent. Volume sampling equalizes bar information content. By advancing the bar only when sufficient activity occurs, you skip low quality intervals that add variance but little signal. For banded systems like Supertrend, this often means fewer false flips and cleaner runs. Notes and tips Use Dollar Bars on assets where nominal price varies widely over time or across symbols. Median filter can resist single burst outliers when setting dynamic thresholds. If you need a stable research baseline, set Use Fixed and keep the threshold constant across tests. Enable Show Time Bars occasionally to sanity check what the synthetic stream is compressing or stretching. Link again for reference Original Volume Based Sampling engine: Bottom line When you let participation set the clock, your Supertrend reacts to meaningful flow instead of idle prints. The result is a cleaner state machine, fewer micro whipsaws, and a trend read that respects when the market is actually trading.
Indicador Pine Script®
por BackQuant
SPY200SMA (+4%/-3%) TQQQ/QQQ STRATEGYSummary of the Improved Strategy: When the price of AMEX:SPY is +4% above the 200SMA BUY NASDAQ:TQQQ and when the price of SPY drops to -3% under the SPY 200SMA SELL everything and slowly DCA into NASDAQ:QQQ over the next 6-12 months or until price returns to +4% above the SPY 200SMA at which point you will go back into 100% TQQQ. Note: (if the price of QQQ goes 30% above the 200SMA of QQQ deleverage to QQQ or Sell to protect yourself from dot com level event) More info and stats -https://www.reddit.com/r/LETFs/comments/1nhye66/spy_200sma_43_tqqqqqq_long_term_investment/
Estratégia Pine Script®
por freefighter07
1
AO Divergence RCT PRO//@description=This indicator, AO Divergence Pro, is a powerful tool designed to automatically identify and plot both classic and hidden divergences on the Awesome Oscillator (AO). Divergences occur when the price action and the oscillator move in opposite directions, often signaling a potential shift in market momentum. // // --- Key Features --- // 1. Regular (Classic) Divergence Detection: This feature identifies potential trend reversals. // - A **Bullish Regular Divergence** (labeled 'R') is found when the price makes a lower low, but the AO makes a higher low. This suggests that downward momentum is weakening and a reversal to the upside may be imminent. // - A **Bearish Regular Divergence** (labeled 'R') is found when the price makes a higher high, but the AO makes a lower high. This suggests that upward momentum is fading and a reversal to the downside may be coming. // // 2. Hidden Divergence Detection: This feature identifies potential trend continuations. // - A **Bullish Hidden Divergence** (labeled 'H') is found when the price makes a higher low, but the AO makes a lower low. This often occurs during a pullback in an uptrend, suggesting the trend is likely to resume. // - A **Bearish Hidden Divergence** (labeled 'H') is found when the price makes a lower high, but the AO makes a higher high. This often occurs during a rally in a downtrend, suggesting the downtrend is likely to continue. // // 3. Full Customization: The indicator allows you to toggle the display of each type of divergence (Bullish/Bearish, Regular/Hidden) independently. You can also adjust the pivot detection sensitivity and the time range between divergences to filter signals according to your trading style. // // --- How to Use --- // 1. **Identify Reversals:** Look for the 'R' labels on the chart. A bullish 'R' in a downtrend is a strong signal to consider a long position. A bearish 'R' in an uptrend is a signal to consider a short position. // 2. **Confirm Continuations:** Look for the 'H' labels. A bullish 'H' during an uptrend pullback can be a good opportunity to add to your position. A bearish 'H' during a downtrend rally can be a signal to enter a short trade. // 3. **Filter Signals:** Use the settings panel to control the number of signals. For example, increasing the "Min Bars Between" will show fewer, but potentially more reliable, divergences. // // --- Attribution --- // Created by Carlos Mauricio Vizcarra. // // --- Disclaimer --- // This script is for informational and educational purposes only. It is not financial advice. Past performance is not indicative of future results.
Indicador Pine Script®
por CARLOSVIZCARRA17
DARVAS BOX V5 Darvas Box indicator from Pine Script v3 to v5 with these improvements: Triangle breakout signals (green up, red down) Toggle option to show/hide signals Breakout detection logic that tracks when price exits the box Alert conditions for both upside and downside breakouts Color Options: Customize all visual elements to match your preferences: Adjustable colors for top and bottom box lines Custom colors for bullish and bearish breakout triangles Flexible styling to fit any chart theme"
Indicador Pine Script®
por el1live
RSI Bollinger Bands [DCAUT]█ RSI Bollinger Bands 📊 ORIGINALITY & INNOVATION The RSI Bollinger Bands indicator represents a meaningful advancement in momentum analysis by combining two proven technical tools: the Relative Strength Index (RSI) and Bollinger Bands. This combination addresses a significant limitation in traditional RSI analysis - the use of fixed overbought/oversold thresholds (typically 70/30) that fail to adapt to changing market volatility conditions. Core Innovation: Rather than relying on static threshold levels, this indicator applies Bollinger Bands statistical analysis directly to RSI values, creating dynamic zones that automatically adjust based on recent momentum volatility. This approach helps reduce false signals during low volatility periods while remaining sensitive to genuine extremes during high volatility conditions. Key Enhancements Over Traditional RSI: Dynamic Thresholds: Overbought/oversold zones adapt to market conditions automatically, eliminating the need for manual threshold adjustments across different instruments and timeframes Volatility Context: Band width provides immediate visual feedback about momentum volatility, helping traders distinguish between stable trends and erratic movements Reduced False Signals: During ranging markets, narrower bands filter out minor RSI fluctuations that would trigger traditional fixed-threshold signals Breakout Preparation: Band squeeze patterns (similar to price-based BB) signal potential momentum regime changes before they occur Self-Referencing Analysis: By measuring RSI against its own statistical behavior rather than arbitrary levels, the indicator provides more relevant context 📐 MATHEMATICAL FOUNDATION Two-Stage Calculation Process: Stage 1: RSI Calculation RSI = 100 - (100 / (1 + RS)) where RS = Average Gain / Average Loss over specified period The RSI normalizes price momentum into a bounded 0-100 scale, making it ideal for statistical band analysis. Stage 2: Bollinger Bands on RSI Basis = MA(RSI, BB Length) Upper Band = Basis + (StdDev(RSI, BB Length) × Multiplier) Lower Band = Basis - (StdDev(RSI, BB Length) × Multiplier) Band Width = Upper Band - Lower Band The Bollinger Bands measure RSI's standard deviation from its own moving average, creating statistically-derived dynamic zones. Statistical Interpretation: Under normal distribution assumptions with default 2.0 multiplier, approximately 95% of RSI values should fall within the bands Band touches represent statistically significant momentum extremes relative to recent behavior Band width expansion indicates increasing momentum volatility (strengthening trend or increasing uncertainty) Band width contraction signals momentum consolidation and potential regime change preparation 📊 COMPREHENSIVE SIGNAL ANALYSIS Visual Color Signals: This indicator features dynamic color fills that highlight extreme momentum conditions: Green Fill (Above Upper Band): Appears when RSI breaks above the upper band, indicating exceptionally strong bullish momentum Represents dynamic overbought zone - not necessarily a reversal signal but a warning of extreme conditions In strong uptrends, green fills can persist as RSI "rides the band" - this indicates sustained momentum strength Exit of green zone (RSI falling back below upper band) often signals initial momentum weakening Red Fill (Below Lower Band): Appears when RSI breaks below the lower band, indicating exceptionally weak bearish momentum Represents dynamic oversold zone - potential reversal or continuation signal depending on trend context In strong downtrends, red fills can persist as RSI "rides the band" - this indicates sustained selling pressure Exit of red zone (RSI rising back above lower band) often signals initial momentum recovery Position-Based Signals: Upper Band Interactions: RSI Touching Upper Band: Dynamic overbought condition - momentum is extremely strong relative to recent volatility, potential exhaustion or continuation depending on trend context RSI Riding Upper Band: Sustained strong momentum, often seen in powerful trends, not necessarily an immediate reversal signal but warrants monitoring for exhaustion RSI Crossing Below Upper Band: Initial momentum weakening signal, particularly significant if accompanied by price divergence Lower Band Interactions: RSI Touching Lower Band: Dynamic oversold condition - momentum is extremely weak relative to recent volatility, potential reversal or continuation of downtrend RSI Riding Lower Band: Sustained weak momentum, common in strong downtrends, monitor for potential exhaustion RSI Crossing Above Lower Band: Initial momentum strengthening signal, early indication of potential reversal or consolidation Basis Line Signals: RSI Above Basis: Bullish momentum regime - upward pressure dominant RSI Below Basis: Bearish momentum regime - downward pressure dominant Basis Crossovers: Momentum regime shifts, more significant when accompanied by band width changes RSI Oscillating Around Basis: Balanced momentum, often indicates ranging market conditions Volatility-Based Signals: Band Width Patterns: Narrow Bands (Squeeze): Momentum volatility compression, often precedes significant directional moves, similar to price coiling patterns Expanding Bands: Increasing momentum volatility, indicates trend acceleration or growing uncertainty Narrowest Band in 100 Bars: Extreme compression alert, high probability of upcoming volatility expansion Advanced Pattern Recognition: Divergence Analysis: Bullish Divergence: Price makes lower lows while RSI touches or stays above previous lower band touch, suggests downward momentum weakening Bearish Divergence: Price makes higher highs while RSI touches or stays below previous upper band touch, suggests upward momentum weakening Hidden Bullish: Price makes higher lows while RSI makes lower lows at the lower band, indicates strong underlying bullish momentum Hidden Bearish: Price makes lower highs while RSI makes higher highs at the upper band, indicates strong underlying bearish momentum Band Walk Patterns: Upper Band Walk: RSI consistently touching or staying near upper band indicates exceptionally strong trend, wait for clear break below basis before considering reversal Lower Band Walk: RSI consistently at lower band signals very weak momentum, requires break above basis for reversal confirmation 🎯 STRATEGIC APPLICATIONS Strategy 1: Mean Reversion Trading Setup Conditions: Market Type: Ranging or choppy markets with no clear directional trend Timeframe: Works best on lower timeframes (5m-1H) or during consolidation phases Band Characteristic: Normal to narrow band width Entry Rules: Long Entry: RSI touches or crosses below lower band, wait for RSI to start rising back toward basis before entry Short Entry: RSI touches or crosses above upper band, wait for RSI to start falling back toward basis before entry Confirmation: Use price action confirmation (candlestick reversal patterns) at band touches Exit Rules: Target: RSI returns to basis line or opposite band Stop Loss: Fixed percentage or below recent swing low/high Time Stop: Exit if position not profitable within expected timeframe Strategy 2: Trend Continuation Trading Setup Conditions: Market Type: Clear trending market with higher highs/lower lows Timeframe: Medium to higher timeframes (1H-Daily) Band Characteristic: Expanding or wide bands indicating strong momentum Entry Rules: Long Entry in Uptrend: Wait for RSI to pull back to basis line or slightly below, enter when RSI starts rising again Short Entry in Downtrend: Wait for RSI to rally to basis line or slightly above, enter when RSI starts falling again Avoid Counter-Trend: Do not fade RSI at bands during strong trends (band walk patterns) Exit Rules: Trailing Stop: Move stop to break-even when RSI reaches opposite band Trend Break: Exit when RSI crosses basis against trend direction with conviction Band Squeeze: Reduce position size when bands start narrowing significantly Strategy 3: Breakout Preparation Setup Conditions: Market Type: Consolidating market after significant move or at key technical levels Timeframe: Any timeframe, but longer timeframes provide more reliable breakouts Band Characteristic: Narrowest band width in recent 100 bars (squeeze alert) Preparation Phase: Identify band squeeze condition (bands at multi-period narrowest point) Monitor price action for consolidation patterns (triangles, rectangles, flags) Prepare bracket orders for both directions Wait for band expansion to begin Entry Execution: Breakout Confirmation: Enter in direction of RSI band breakout (RSI breaks above upper band or below lower band) Price Confirmation: Ensure price also breaks corresponding technical level Volume Confirmation: Look for volume expansion supporting the breakout Risk Management: Stop Loss: Place beyond consolidation pattern opposite extreme Position Sizing: Use smaller size due to false breakout risk Quick Exit: Exit immediately if RSI returns inside bands within 1-3 bars Strategy 4: Multi-Timeframe Analysis Timeframe Selection: Higher Timeframe: Daily or 4H for trend context Trading Timeframe: 1H or 15m for entry signals Confirmation Timeframe: 5m or 1m for precise entry timing Analysis Process: Trend Identification: Check higher timeframe RSI position relative to bands, trade only in direction of higher timeframe momentum Setup Formation: Wait for trading timeframe RSI to show pullback to basis in trending direction Entry Timing: Use confirmation timeframe RSI band touch or crossover for precise entry Alignment Confirmation: All timeframes should show RSI moving in same direction for highest probability setups 📋 DETAILED PARAMETER CONFIGURATION RSI Source: Close (Default): Standard price point, balances responsiveness and reliability HL2: Reduces noise from intrabar volatility, provides smoother RSI values HLC3 or OHLC4: Further smoothing for very choppy markets, slower to respond but more stable Volume-Weighted: Consider using VWAP or volume-weighted prices for additional liquidity context RSI Length Parameter: Shorter Periods (5-10): More responsive but generates more signals, suitable for scalping or very active trading, higher noise level Standard (14): Default and most widely used setting, proven balance between responsiveness and reliability, recommended starting point Longer Periods (21-30): Smoother momentum measurement, fewer but potentially more reliable signals, better for swing trading or position trading Optimization Note: Test across different market regimes, optimal length often varies by instrument volatility characteristics RSI MA Type Parameter: RMA (Default): Wilder's original smoothing method, provides traditional RSI behavior with balanced lag, most widely recognized and tested, recommended for standard technical analysis EMA: Exponential smoothing gives more weight to recent values, faster response to momentum changes, suitable for active trading and trending markets, reduces lag compared to RMA SMA: Simple average treats all periods equally, smoothest output with highest lag, best for filtering noise in choppy markets, useful for long-term position analysis WMA: Weighted average emphasizes recent data less aggressively than EMA, middle ground between SMA and EMA characteristics, balanced responsiveness for swing trading Advanced Options: Full access to 25+ moving average types including HMA (reduced lag), DEMA/TEMA (enhanced responsiveness), KAMA/FRAMA (adaptive behavior), T3 (smoothness), Kalman Filter (optimal estimation) Selection Guide: RMA for traditional analysis and backtesting consistency, EMA for faster signals in trending markets, SMA for stability in ranging markets, adaptive types (KAMA/FRAMA) for varying volatility regimes BB Length Parameter: Short Length (10-15): Tighter bands that react quickly to RSI changes, more frequent band touches, suitable for active trading styles Standard (20): Balanced approach providing meaningful statistical context without excessive lag Long Length (30-50): Smoother bands that filter minor RSI fluctuations, captures only significant momentum extremes, fewer but higher quality signals Relationship to RSI Length: Consider BB Length greater than RSI Length for cleaner signals BB MA Type Parameter: SMA (Default): Standard Bollinger Bands calculation using simple moving average for basis line, treats all periods equally, widely recognized and tested approach EMA: Exponential smoothing for basis line gives more weight to recent RSI values, creates more responsive bands that adapt faster to momentum changes, suitable for trending markets RMA: Wilder's smoothing provides consistent behavior aligned with traditional RSI when using RMA for both RSI and BB calculations WMA: Weighted average for basis line balances recent emphasis with historical context, middle ground between SMA and EMA responsiveness Advanced Options: Full access to 25+ moving average types for basis calculation, including HMA (reduced lag), DEMA/TEMA (enhanced responsiveness), KAMA/FRAMA (adaptive to volatility changes) Selection Guide: SMA for standard Bollinger Bands behavior and backtesting consistency, EMA for faster band adaptation in dynamic markets, matching RSI MA type creates unified smoothing behavior BB Multiplier Parameter: Conservative (1.5-1.8): Tighter bands resulting in more frequent touches, useful in low volatility environments, higher signal frequency but potentially more false signals Standard (2.0): Default setting representing approximately 95% confidence interval under normal distribution, widely accepted statistical threshold Aggressive (2.5-3.0): Wider bands capturing only extreme momentum conditions, fewer but potentially more significant signals, reduces false signals in high volatility Adaptive Approach: Consider adjusting multiplier based on instrument characteristics, lower multiplier for stable instruments, higher for volatile instruments Parameter Optimization Workflow: Start with default parameters (RSI:14, BB:20, Mult:2.0) Test across representative sample period including different market regimes Adjust RSI length based on desired responsiveness vs stability tradeoff Tune BB length to match your typical holding period Modify multiplier to achieve desired signal frequency Validate on out-of-sample data to avoid overfitting Document optimal parameters for different instruments and timeframes Reference Levels Display: Enabled (Default): Shows traditional 30/50/70 levels for comparison with dynamic bands, helps visualize the adaptive advantage Disabled: Cleaner chart focusing purely on dynamic zones, reduces visual clutter for experienced users Educational Value: Keeping reference levels visible helps understand how dynamic bands differ from fixed thresholds across varying market conditions 📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES Comparison with Traditional RSI: Fixed Threshold RSI Limitations: In ranging low-volatility markets: RSI rarely reaches 70/30, missing tradable extremes In trending high-volatility markets: RSI frequently breaks through 70/30, generating excessive false reversal signals Across different instruments: Same thresholds applied to volatile crypto and stable forex pairs produce inconsistent results Threshold Adjustment Problem: Manually changing thresholds for different conditions is subjective and lagging RSI Bollinger Bands Advantages: Automatic Adaptation: Bands adjust to current volatility regime without manual intervention Consistent Logic: Same statistical approach works across different instruments and timeframes Reduced False Signals: Band width filtering helps distinguish meaningful extremes from noise Additional Information: Band width provides volatility context missing in standard RSI Objective Extremes: Statistical basis (standard deviations) provides objective extreme definition Comparison with Price-Based Bollinger Bands: Price BB Characteristics: Measures absolute price volatility Affected by large price gaps and outliers Band position relative to price not normalized Difficult to compare across different price scales RSI BB Advantages: Normalized Scale: RSI's 0-100 bounds make band interpretation consistent across all instruments Momentum Focus: Directly measures momentum extremes rather than price extremes Reduced Gap Impact: RSI calculation smooths price gaps impact on band calculations Comparable Analysis: Same RSI BB appearance across stocks, forex, crypto enables consistent strategy application Performance Characteristics: Signal Quality: Higher Signal-to-Noise Ratio: Dynamic bands help filter RSI oscillations that don't represent meaningful extremes Context-Aware Alerts: Band width provides volatility context helping traders adjust position sizing and stop placement Reduced Whipsaws: During consolidations, narrower bands prevent premature signals from minor RSI movements Responsiveness: Adaptive Lag: Band calculation introduces some lag, but this lag is adaptive to current conditions rather than fixed Faster Than Manual Adjustment: Automatic band adjustment is faster than trader's ability to manually modify thresholds Balanced Approach: Combines RSI's inherent momentum lag with BB's statistical smoothing for stable yet responsive signals Versatility: Multi-Strategy Application: Supports both mean reversion (ranging markets) and trend continuation (trending markets) approaches Universal Instrument Coverage: Works effectively across equities, forex, commodities, cryptocurrencies without parameter changes Timeframe Agnostic: Same interpretation applies from 1-minute charts to monthly charts Limitations and Considerations: Known Limitations: Dual Lag Effect: Combines RSI's momentum lag with BB's statistical lag, making it less suitable for very short-term scalping Requires Volatility History: Needs sufficient bars for BB calculation, less effective immediately after major regime changes Statistical Assumptions: Assumes RSI values are somewhat normally distributed, extreme trending conditions may violate this Not a Standalone System: Like all indicators, should be combined with price action analysis and risk management Optimal Use Cases: Best for swing trading and position trading timeframes Most effective in markets with alternating volatility regimes Ideal for traders who use multiple instruments and timeframes Suitable for systematic trading approaches requiring consistent logic Suboptimal Conditions: Very low timeframes (< 5 minutes) where lag becomes problematic Instruments with extreme volatility spikes (gap-prone markets) Markets in strong persistent trends where mean reversion rarely occurs Periods immediately following major structural changes (new trading regime) USAGE NOTES This indicator is designed for technical analysis and educational purposes to help traders understand the interaction between momentum measurement and statistical volatility bands. The RSI Bollinger Bands has limitations and should not be used as the sole basis for trading decisions. Important Considerations: No Predictive Guarantee: Past band touches and patterns do not guarantee future price behavior Market Regime Dependency: Indicator performance varies significantly between trending and ranging market conditions Complementary Analysis Required: Should be used alongside price action, support/resistance levels, and fundamental analysis Risk Management Essential: Always use proper position sizing, stop losses, and risk controls regardless of signal quality Parameter Sensitivity: Different instruments and timeframes may require parameter optimization for optimal results Continuous Monitoring: Band characteristics change with market conditions, requiring ongoing assessment Recommended Supporting Analysis: Price structure analysis (support/resistance, trend lines) Volume confirmation for breakout signals Multiple timeframe alignment Market context awareness (news events, session times) Correlation analysis with related instruments The indicator aims to provide adaptive momentum analysis that adjusts to changing market volatility, but traders must apply sound judgment, proper risk management, and comprehensive market analysis in their decision-making process.
Indicador Pine Script®
por DCAUT
Premarket Power Bar StrategyStep 1: Mark Your Levels Before the Open When: Between 9:00–9:25 AM ET Premarket High – the highest price before 9:30 AM Premarket Low – the lowest price before 9:30 AM
Use extended hours view on your chart platform. These levels act as magnets and turning points once the market opens. They form the foundation for your first trade of the day. Step 2: Let Price Come to the Level Do not chase early price action.
Wait for price to approach either the premarket high or low during regular market hours.
Look for a pause, hesitation, or test near the level. This keeps you from overtrading and forces you to wait for structure to form. Step 3: Watch for the Power Bar A power bar is a large-bodied candle with strong momentum and little to no wick on the opposite side.
It should form directly at the premarket level—not near it, not after a breakout. At the premarket low, a bullish power bar is your buy trigger. At the premarket high, a bearish power bar signals a short opportunity. No power bar? No trade. The level and the candle must come together to create the edge. (BONUS: As you identify specific patterns, eg, double bottoms, double tops, etc. look for those patterns near the premarket high or low) Step 4: Entry, Stop, and Target Entry: For longs: place your order just above the high of the bullish power bar For shorts: enter just below the low of the bearish power bar Stop: Long trade: just under the low of the power bar Short trade: just above the high of the power bar Profit Target Options: VWAP Prior day’s close Key support/resistance levels Keep your trade logic mechanical and consistent. Execution Guidelines Only trade when price reacts at your marked level Wait for the power bar to fully form before entering Do not jump in early or chase candles that form away from your levels
Indicador Pine Script®
por elivgorelick
Extreme Candle Pattern Visualizer🟠 OVERVIEW This indicator compares the current candle's percentage change against historical data, then highlights past candles with equal or bigger magnitude of movement. Also, for all the highlighted past candles, it tracks how far price extends before recovering to its starting point. It also provides statistical context through percentile rankings. IN SHORT: Quickly spot similar price movements in the past and understand how unusual the current candle is using percentile rankings. 🟠 CORE CONCEPT The indicator operates on two fundamental principles: 1. Statistical Rarity Detection The script calculates the percentage change (open to close) of every candle within a user-defined lookback period and determines where the current candle ranks in this distribution. A candle closing at -9% might fall in the bottom 5th percentile, indicating it's more extreme than 95% of recent candles. This percentile ranking helps traders identify statistically unusual moves that often precede reversals or extended trends. 2. Recovery Path Mapping Once extreme candles are identified (those matching or exceeding the current candle's magnitude), the indicator tracks their subsequent price action. For bearish candles, it measures how far price dropped before recovering back to the candle's opening price. For bullish candles, it tracks how high price climbed before returning to the open. This reveals whether extreme moves typically extend further or reverse quickly. 🟠 PRACTICAL APPLICATIONS Mean Reversion Trading: Candles in extreme percentiles (below 10% or above 90%) often signal oversold/overbought conditions. The recovery lines show typical extension distances, helping traders set profit targets for counter-trend entries. Momentum Continuation: When extreme candles show small recovery percentages before price reverses back, it suggests strong directional momentum that may continue. Stop Loss Placement: Historical recovery data reveals typical extension ranges after extreme moves, informing more precise stop loss positioning beyond noise but before major reversals. Pattern Recognition: By visualizing how similar historical extremes resolved, traders gain context for current price action rather than trading in isolation. 🟠 VISUAL ELEMENTS Orange Circles: Mark historical candles with similar or greater magnitude to current candle Red Lines: Track downward extensions after bearish extreme candles Green Lines: Track upward extensions after bullish extreme candles Percentage Labels: Show exact extension distance from candle close to extreme point Percentile Label: Color-coded box displaying current candle's statistical ranking Hollow Candles: Background rendering for clean chart presentation 🟠 ORIGINALITY This indicator uniquely combines statistical percentile analysis with forward-looking recovery tracking. While many indicators identify extreme moves, few show what happened next across multiple historical instances simultaneously. The dual approach provides both the "how rare is this?" question (percentile) and "what typically happens after?" answer (recovery paths) in a single visual framework.
Indicador Pine Script®
por osprey0
3