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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.
مؤشر Pine Script®
من ‎BOSWaves‎
1
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.
مؤشر Pine Script®
من ‎DCAUT‎
Proxit Gold Strike V.1.2Proxit Gold Strike v.1.2 is a scalping-focused indicator designed to pinpoint fast in–out entries on lower timeframes (1–5m). It blends momentum, short-term trend bias, and reversal/pricing zones to surface high-probability setups while filtering out low-volatility chop. Core Logic: Detect micro-trend bias to stay aligned with short-term direction Trigger Momentum Pulse when buy/sell pressure expands Highlight Pullback/Exhaustion zones where quick bounces often occur Apply a Volatility Filter to reduce noise in dead markets On-chart Elements: Buy / Sell arrows when conditions align Soft background Trend Bias shading Signal Baseline for directional reference Scalp Zones for pragmatic entry/exit placement No-Trade Zone warning during ultra-low volatility Signals & Trade Ideas: Scalp Buy: Positive momentum crossover + price above Baseline + not in No-Trade Zone Scalp Sell: Negative momentum crossover + price below Baseline + not in No-Trade Zone Exit: Quick targets (e.g., R:1–1.5) or upon opposite momentum/weakening signal Recommended Inputs: Sensitivity (1–5): Higher = faster/more signals (default: 3) Baseline Length: 50–100 for volatile instruments Momentum Window: 8–14 tuned for scalps Volatility Filter: On for chop reduction Show Labels/Alerts: Toggle visual/alert elements Best Timeframes & Markets: 1m / 3m / 5m on Forex, Gold, Crypto, Index Futures For Gold, start with TF 3–5m during active sessions/liquidity peaks. Alerts: “Proxit Buy” and “Proxit Sell” on signal confirmation “Exit/Flip” when momentum flips Use Once per bar close for more reliable alerts. Best Practices: Favor trades with the current Trend Bias; avoid strong counter-trend attempts Keep tight stops nearby and size positions responsibly Be cautious around major news releases unless your playbook accounts for them Combine with market structure/S&R for added confluence Disclaimer: This tool is for educational and decision-support purposes only and is not financial advice. Results depend on your risk management and discipline. Always forward-test on demo before going live. Suggested TradingView Tags: scalping, momentum, trend, gold, crypto, forex, volatility, pullback, intraday, alerts
مؤشر Pine Script®
من ‎proxitclub‎
UOT Gold Pressure IndexGold Pressure Index combines the momentum of the US Dollar Index (DXY) and US 10-Year Treasury Yields into a single, easy-to-read oscillator that helps traders identify high-probability setups in gold markets. What Does This Indicator Do? This indicator measures the combined directional pressure from the two primary fundamental drivers of gold prices: DXY (US Dollar Index) - Gold's primary inverse correlation US 10-Year Treasury Yields - Alternative to gold for safe-haven flows When both are rising together, gold typically faces strong selling pressure. When both are falling together, gold typically finds support. The GPI simplifies this analysis into one visual metric.
مؤشر Pine Script®
من ‎decentAuthor8156‎
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.
مؤشر Pine Script®
من ‎BackQuant‎
Scalp Recent High/Low (Stable v5 r4)UMA Scalp Levels（ウマ・スキャル・レベルズ） UMA Scalp Levels Automatically detects recent swing highs and lows — the “psychological levels” most watched by traders — and alerts you when a valid breakout occurs. 🔹 Detects swing highs/lows automatically (non-repainting) 🔹 Confirm breakouts by close or wick (configurable) 🔹 Filters small fakeouts using ATR / % thresholds 🔹 Supports breakout alerts (up / down / retest) 🔹 MTF compatible — e.g., show 15m levels on 5m chart Ideal for scalpers and day traders who want to catch momentum immediately after a breakout of key levels. 直近で“市場が意識している高値・安値ライン”を自動で検出し、 ブレイク時にサインとアラートを出す、順張り型のスキャルピング指標。 🔹 スイング高値・安値を自動抽出（リペイント耐性あり） 🔹 終値 or ヒゲ抜けでブレイク判定（選択可能） 🔹 ATRや％幅でノイズを除外（小さな抜けをフィルタリング） 🔹 アラート対応（上抜け／下抜け／リテスト検知） 🔹 MTF対応（例：15分足ラインを5分足チャートに表示） 短期トレードで最も意識される「節目の抜け」を視覚化し、 勢いに乗る順張りトレードの精度を高めます。
مؤشر Pine Script®
من ‎fxdeuma‎
Options Position Size CalculatorOptions Position Size Calculator Automate your options position sizing directly on the chart. This indicator calculates the optimal number of options contracts to buy based on your risk management parameters, entry price, stop loss, and expected options decay. 📋 What It Does Eliminates the need for external calculators by computing your position size directly on TradingView. Simply set your entry and stop loss prices, configure your risk parameters, and the indicator instantly shows you how many contracts to buy. ✨ Key Features Visual Price Lines: Set entry and stop loss prices with draggable horizontal lines Custom Loss Table: Input your own options loss percentages for distances from 0.1% to 1.5% (with interpolation between values) Automatic Calculations: Calculates distance to stop loss, expected options loss, dollar risk, and final contract quantity Live Display: All calculations shown in a clean info box on your chart Accounts for Contract Multiplier: Correctly factors in the standard 100x options multiplier 🎯 How to Use 1. Configure Settings First Add the indicator to your chart (set any initial prices when prompted) Open indicator Settings (gear icon) Enter your Portfolio Size (e.g., $10,000) Set Risk Percentage (e.g., 2%) Enter the Contract Price (the premium per contract, e.g., $1.50) 2. Fill Your Options Loss Table This is crucial - you must input your own data For each distance (0.1%, 0.2%, up to 1.5%), enter the expected % loss your options will suffer Base this on your strategy (calls/puts), strike selection, and expiration Use historical data from your trades or an options calculator Example: If underlying moves 0.5% to your stop, your option might lose 30% 3. Set Entry & Stop Loss on Chart Go back to indicator settings Adjust Entry Price and Stop Loss Price to match your trade setup The indicator calculates your position size instantly 4. Read Results The indicator displays: Distance to stop loss (%) Expected options loss (%) Dollar risk amount CONTRACTS TO BUY - your position size 📊 Example Portfolio: $10,000 | Risk: 2% | Entry: $150 | Stop: $149 (0.67% distance) Expected loss: 38% | Contract price: $2.00 → Buy 2 contracts ⚠️ Important Your loss table values depend on your specific options strategy, strike, DTE, and IV Different strategies require different loss tables This is for educational purposes - always verify calculations Never risk more than you can afford to lose Made by traders, for traders. Trade safe, size smart.
مؤشر Pine Script®
من ‎dragich‎
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.
مؤشر Pine Script®
من ‎CARLOSVIZCARRA17‎
Smart Risk DCA Meter — Adaptive Market Risk EngineThe **Smart Risk DCA Meter** is an adaptive market-risk indicator that helps you invest smarter by scaling your DCA buys based on actual market conditions instead of emotion. It combines momentum, distance from trend, and drawdown factors into a single 0–1 risk score that automatically adjusts to each asset’s volatility — from stable indices like SPX to high-beta assets like BTC. Low readings (green zones) signal opportunity to buy heavier, while high readings (red zones) warn to slow down and protect capital.
مؤشر Pine Script®
من ‎poseidonpips‎
Sri - Daily & Weekly Candle Strength Sri - Daily & Weekly Candle Strength Short Title: Sri-Candle Overlay: Yes Description: The Sri - Daily & Weekly Candle Strength indicator is designed to visually display recent daily and weekly candle activity directly on your chart, highlighting buyer and seller dominance for each candle. It helps traders quickly assess the strength of bullish vs bearish pressure over recent periods and can be used with both Normal and Heikin Ashi candles. This tool is particularly useful for swing traders, position traders, and technical analysts who want a clear view of candle momentum without switching timeframes. Features: Multi-Timeframe Candles: Displays the last several daily candles and weekly candles on your chart. Supports Normal or Heikin Ashi candles for both daily and weekly views. Candle Strength Analysis: Calculates buyer strength and seller strength as percentages based on candle body relative to the total candle range. Highlights the dominant strength (higher of buyer or seller) above each candle. Option to round dominant strength percentages to whole numbers. Customizable Colors: Set separate bullish and bearish colors for daily and weekly candles. Customize wick colors independently for daily and weekly candles. Positioning and Layout Options: Adjust horizontal offset, candle thickness, and gap between candles for both daily and weekly candles. Choose label positions for date labels (Top, Bottom, Absolute level). Flexible Text Display: Choose label text size (Tiny, Small, Normal, Large, Huge). Daily candles display the day of the month on the candle optionally. Dynamic Candle Rendering: Each candle is plotted as a box with wicks, accurately reflecting open, high, low, and close. Dominant strength percentage label is colored green for bullish dominance and red for bearish dominance. Inputs: Daily Settings: Show Daily Candles – Toggle daily candle visibility. Daily Candle Type – Choose between Normal or Heikin Ashi. Daily Timeframe – Select Daily (D), Weekly (W), or Monthly (M). Bull Candle Color (D) – Color for bullish daily candles. Bear Candle Color (D) – Color for bearish daily candles. Wick Color (D) – Color for candle wicks. Horizontal Offset (D) – Distance from current bar to start drawing. Candle Thickness (D) – Width of candle boxes. Gap Between Candles (D) – Space between consecutive candles. Daily Label Position – Position for the date label. Absolute Level – Y-axis level when using absolute label position. Strength Label Text Size – Size of the dominant strength label. Round Dominant % (No Decimals) – Round the displayed strength to whole numbers. Weekly Settings: Show Weekly Candles – Toggle weekly candle visibility. Weekly Candle Type – Choose Normal or Heikin Ashi. Weekly Timeframe – Select Daily (D), Weekly (W), or Monthly (M). Bull Candle Color (W) – Color for bullish weekly candles. Bear Candle Color (W) – Color for bearish weekly candles. Wick Color (W) – Wick color for weekly candles. Horizontal Offset (W) – Distance from current bar for weekly candles. Candle Thickness (W) – Width of weekly candle boxes. Gap Between Candles (W) – Space between consecutive weekly candles. How It Works: The script fetches candle data using the request.security() function for the selected timeframe and type (Normal or Heikin Ashi). Each candle’s buyer and seller strength is calculated as: Buyer Strength (%) = ((Close - Low) / (High - Low)) * 100 Seller Strength (%) = ((High - Close) / (High - Low)) * 100 Candles are drawn as boxes with wicks on the chart at the specified horizontal offset. The dominant strength is displayed above each candle, colored green for bullish dominance or red for bearish dominance. Daily candles can optionally show the day of the month as a label. Use Cases: Quickly identify recent bullish or bearish trends on daily and weekly timeframes. Compare strength of buyers vs sellers across multiple periods. Combine with other technical indicators for multi-timeframe analysis.
مؤشر Pine Script®
من ‎venkat_27‎
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"
مؤشر Pine Script®
من ‎el1live‎