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MSFusion- MultiScoreFusionThis Pine Script strategy, MSFusion - MultiScoreFusion, combines Ichimoku components and Hull Moving Average (HMA) signals to generate a composite score for each bar. It evaluates several conditions—such as price crossing above HMA55, Tenkan and Kijun lines, and price position relative to the Ichimoku cloud—and assigns scores to each. The script displays a label with the total score and a tooltip listing the contributing conditions when a strong bullish signal is detected. This approach helps traders quickly assess market momentum and trend strength using multiple technical criteria.
Pine Script®指标
由anesboz3提供
Trend Compass (Manual)## Trend Compass (Manual) - A Discretionary Trader's Dashboard ### Summary Trend Compass is a simple yet powerful dashboard designed for discretionary traders who want a constant, visual reminder of their market analysis directly on their chart. Instead of relying on automated indicators, this tool gives you **full manual control** to define the market state across different timeframes or conditions. It helps you stay aligned with your higher-level analysis (e.g., HTF bias, current market structure) and avoid making impulsive decisions that go against your plan. ### Key Features - **Fully Manual Control:** You decide the trend. No lagging indicators, no confusing signals. Just your own analysis, displayed clearly. - **Multiple Market States:** Define each row as an `Uptrend`, `Downtrend`, `Pullback`, or `Neutral` market. - **Customizable Rows:** Display up to 8 rows. You can label each one however you like (e.g., "D1", "H4", "Market Structure", "Liquidity Bias"). - **Flexible Panel:** Change all colors, text sizes, and place the panel in any of the 9 positions on your chart. - **Clean & Minimalist:** Designed to provide essential information at a glance without cluttering your chart. ### How to Use 1. **Add to Chart:** Add the indicator to your chart. 2. **Open Settings:** Go into the indicator settings. 3. **Configure Rows:** - In the "Rows (Manual Control)" section, set the "Number of rows" you want to display. - For each row, give it a custom **Label** (e.g., "m15"). - Select its current state from the dropdown menu (`Uptrend`, `Downtrend`, etc.). - To remove a row, simply set its state to `Hidden`. 4. **Customize Style:** - In the "Panel & Visual Style" section, adjust colors, text sizes, and the panel's position to match your chart's theme. This tool is perfect for price action traders, ICT/SMC traders, or anyone who values a clean chart and a disciplined approach to their analysis.
Pine Script®指标
由GCGFx_SMC提供
1
Bollinger Adaptive Trend Navigator [QuantAlgo]🟢 Overview The Bollinger Adaptive Trend Navigator synthesizes volatility channel analysis with variable smoothing mechanics to generate trend identification signals. It uses price positioning within Bollinger Band structures to modify moving average responsiveness, while incorporating ATR calculations to establish trend line boundaries that constrain movement during volatile periods. The adaptive nature makes this indicator particularly valuable for traders and investors working across various asset classes including stocks, forex, commodities, and cryptocurrencies, with effectiveness spanning multiple timeframes from intraday scalping to longer-term position analysis. 🟢 How It Works The core mechanism calculates price position within Bollinger Bands and uses this positioning to create an adaptive smoothing factor: bbPosition = bbUpper != bbLower ? (source - bbLower) / (bbUpper - bbLower) : 0.5 adaptiveFactor = (bbPosition - 0.5) * 2 * adaptiveMultiplier * bandWidthRatio alpha = math.max(0.01, math.min(0.5, 2.0 / (bbPeriod + 1) * (1 + math.abs(adaptiveFactor)))) This adaptive coefficient drives an exponential moving average that responds more aggressively when price approaches Bollinger Band extremes: var float adaptiveTrend = source adaptiveTrend := alpha * source + (1 - alpha) * nz(adaptiveTrend , source) finalTrend = 0.7 * adaptiveTrend + 0.3 * smoothedCenter ATR-based volatility boundaries constrain the final trend line to prevent excessive movement during volatile periods: volatility = ta.atr(volatilityPeriod) upperBound = bollingerTrendValue + (volatility * volatilityMultiplier) lowerBound = bollingerTrendValue - (volatility * volatilityMultiplier) The trend line direction determines bullish or bearish states through simple slope comparison, with the final output displaying color-coded signals based on the synthesis of Bollinger positioning, adaptive smoothing, and volatility constraints (green = long/buy, red = short/sell). 🟢 Signal Interpretation Rising Trend Line (Green): Indicates upward direction based on Bollinger positioning and adaptive smoothing = Potential long/buy opportunity Falling Trend Line (Red): Indicates downward direction based on Bollinger positioning and adaptive smoothing = Potential short/sell opportunity Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant development without constantly monitoring the charts Candle Coloring: Optional feature applies trend colors to price bars for visual consistency Configuration Presets: Three parameter sets available - Default (standard settings), Scalping (faster response), and Swing Trading (slower response)
Pine Script®指标
由QuantAlgo提供
4
FSVZO [Alpha Extract]A sophisticated volume-weighted momentum oscillator that combines Fourier smoothing with Volume Zone Oscillator methodology to deliver institutional-grade flow analysis and divergence detection. Utilizing advanced statistical filtering including ADF trend analysis and multi-dimensional volume dynamics, this indicator provides comprehensive market sentiment assessment through volume-price relationships with extreme zone detection and intelligent divergence recognition for high-probability reversal and continuation signals. 🔶 Advanced VZO Calculation Engine Implements enhanced Volume Zone Oscillator methodology using relative volume analysis combined with smoothed price changes to create momentum-weighted oscillator values. The system applies exponential smoothing to both volume and price components before calculating positive and negative momentum ratios with trend factor integration for market regime awareness. 🔶 Fourier-Based Smoothing Architecture Features advanced Fourier approximation smoothing using cosine-weighted calculations to reduce noise while preserving signal integrity. The system applies configurable Fourier length parameters with weighted sum normalization for optimal signal clarity across varying market conditions with enhanced responsiveness to genuine trend changes. // Fourier Smoothing Algorithm fourier_smooth(src, length) => sum = 0 weightSum = 0 for i = 0 to length - 1 weight = cos(2 * π * i / length) sum += src * weight weightSum += weight sum / weightSum 🔶 Intelligent Divergence Detection System Implements comprehensive divergence analysis using pivot point methodology with configurable lookback periods for both standard and hidden divergence patterns. The system validates divergence conditions through range analysis and provides visual confirmation through plot lines, labels, and color-coded identification for precise timing analysis. 15MIN 4H 12H 🔶 Flow Momentum Analysis Framework Calculates flow momentum by measuring oscillator deviation from its exponential moving average, providing secondary confirmation of volume flow dynamics. The system creates momentum-based fills and visual indicators that complement the primary oscillator analysis for comprehensive market flow assessment. 🔶 Extreme Zone Detection Engine Features sophisticated extreme zone identification at ±98 levels with specialized marker system including white X markers for signals occurring in extreme territory and directional triangles for potential reversal points. The system provides clear visual feedback for overbought/oversold conditions with institutional-level threshold accuracy. 🔶 Dynamic Visual Architecture Provides advanced visualization engine with bullish/bearish color transitions, dynamic fill regions between oscillator and signal lines, and flow momentum overlay with configurable transparency levels. The system includes flip markers aligned to color junction points for precise signal timing with optional bar close confirmation to prevent repainting. 🔶 ADF Trend Filtering Integration Incorporates Augmented Dickey-Fuller inspired trend filtering using normalized price statistics to enhance signal quality during trending versus ranging market conditions. The system calculates trend factors based on mean deviation and standard deviation analysis for improved oscillator accuracy across market regimes. 🔶 Comprehensive Alert System Features intelligent multi-tier alert framework covering bullish/bearish flow detection, extreme zone reversals, and divergence confirmations with customizable message templates. The system provides real-time notifications for critical volume flow changes and structural market shifts with exchange and ticker integration. 🔶 Performance Optimization Framework Utilizes efficient calculation methods with optimized variable management and configurable smoothing parameters to balance signal quality with computational efficiency. The system includes automatic pivot validation and range checking for consistent performance across extended analysis periods with minimal resource usage. This indicator delivers sophisticated volume-weighted momentum analysis through advanced Fourier smoothing and comprehensive divergence detection capabilities. Unlike traditional volume oscillators that focus solely on volume patterns, the FSVZO integrates volume dynamics with price momentum and statistical trend filtering to provide institutional-grade flow analysis. The system's combination of extreme zone detection, intelligent divergence recognition, and multi-dimensional visual feedback makes it essential for traders seeking systematic approaches to volume-based market analysis across cryptocurrency, forex, and equity markets with clearly defined reversal and continuation signals.
Pine Script®指标
由AlphaExtract提供
12
Anrazzi - EMAs/ATR - 1.0.2The Anrazzi – EMAs/ATR indicator is a multi-purpose overlay designed to help traders track trend direction and market volatility in a single clean tool. It plots up to six customizable moving averages (MAs) and an Average True Range (ATR) value directly on your chart, allowing you to quickly identify market bias, dynamic support/resistance, and volatility levels without switching indicators. This script is ideal for traders who want a simple, configurable, and efficient way to combine trend-following signals with volatility-based position sizing. 📌 Key Features Six Moving Averages (MA1 → MA6) Toggle each MA on/off individually Choose between EMA or SMA for each Customize length and color Perfect for spotting trend direction and pullback zones ATR Display Uses Wilder’s ATR formula (ta.rma(ta.tr(true), 14)) Can be calculated on current or higher timeframe Adjustable multiplier for position sizing (e.g., 1.5× ATR stops) Displays cleanly in the bottom-right corner Custom Watermark Displays symbol + timeframe in top-right Adjustable color and size for streamers, screenshots, or clear charting Compact UI Organized with group and inline inputs for quick configuration Lightweight and optimized for real-time performance ⚙️ How It Works MAs: The script uses either ta.ema() or ta.sma() to compute each moving average based on the user-selected type and length. ATR: The ATR is calculated using ta.rma(ta.tr(true), 14) (Wilder’s smoothing), and optionally scaled by a multiplier for easier use in risk management. Tables: ATR value and watermark are displayed using table.new() so they stay anchored to the screen regardless of zoom level. 📈 How to Use Enable the MAs you want to track and adjust their lengths, type, and colors. Enable ATR if you want to see volatility — optionally select a higher timeframe for broader context. Use MAs to: Identify overall trend direction (e.g. price above MA20 = bullish) Spot pullback zones for entries See when multiple MAs cluster together as support/resistance zones Use ATR value to: Size your stop-loss dynamically (e.g. stop = entry − 1.5×ATR) Detect volatility breakouts (ATR spikes = market expansion) 🎯 Recommended For Day traders & swing traders Trend-following & momentum strategies Volatility-based risk management Traders who want a clean, all-in-one dashboard
Pine Script®指标
由Anrazzi提供
CHiLo — Custom HiLo (SMA/EMA, Activator, Shading, Auto-Decimals)CHiLo is a clean Hi/Lo trend read with SMA/EMA options, a HiLo vs. HiLo Activator mode, optional band shading , and a right-side HiLo marker with automatic decimals based on the symbol. Optional Buy/Sell labels mark state flips. Inspired by the broader trend-following literature and practitioners; in Brazil, educator Hulisses “Tio Huli” Dias is a notable voice popularizing trend following. What it does CHiLo plots a Hi/Lo state with two modes: HiLo (classic high/low bands) HiLo Activator (activator-style behavior) It includes: SMA/EMA selection Optional shading between Hi/Lo bands Optional Buy/Sell labels on state flips HiLo marker (auto-decimals from the symbol’s tick size) Goal: deliver a fast, visual trend context that you can pair with your own risk rules and confirmations. How to use Add the indicator and choose Mode (HiLo / Activator) and MA type (SMA/EMA). Tune Period (and Offset if needed). Higher = smoother (fewer flips); lower = more responsive. Toggle Shading to emphasize the envelope. Toggle Buy/Sell labels if you want flip markers. Use the HiLo marker on the right to read the current level (auto-formatted). Inputs (quick reference) Period / Offset — sensitivity vs. delay. Type — HiLo or HiLo Activator. MA Type — SMA (steadier) or EMA (snappier). HiLo Style — Points or Line. Shading & Transparency — highlight the band area. Buy/Sell Labels — on/off. HiLo Marker — size and horizontal offset (decimals automatic). Notes & credits Educational use only; not financial advice. For best results, combine with position sizing, stops, and regime filters.
Pine Script®指标
由Parize提供
1
cd_indiCATor_CxGeneral: This indicator is the redesigned, simplified, and feature-enhanced version of the previously shared indicators: cd_cisd_market_Cx, cd_HTF_Bias_Cx, cd_sweep&cisd_Cx, cd_SMT_Sweep_CISD_Cx, and cd_RSI_divergence_Cx. Within the holistic setup, the indicator tracks: • HTF bias • Market structure (trend) in the current timeframe • Divergence between selected pairs (SMT) • Divergence between price and RSI values • Whether the price is in an important area (FVG, iFVG, and Volume Imbalance) • Whether the price is at a key level • Whether the price is within a user-defined special timeframe The main condition and trigger of the setup is an HTF sweep with CISD confirmation on the aligned timeframe. When the main condition occurs, the indicator provides the user with a real-time market status summary, enriched with other data. ________________________________________ What’s new? -In the SMT module: • Triad SMT analysis (e.g.: NQ1!, ES1!, and YM1!) • Dyad SMT analysis (e.g.: EURUSD, GBPUSD) • Alternative pair definition and divergence analysis for non-correlated assets o For crypto assets (xxxUSDT <--> xxxUSDT.P) (e.g.: SOLUSDT.P, SOLUSDT) o For stocks, divergence analysis by comparing the asset with its value in another currency (BIST:xxx <--> BIST:xxx / EURTRY), (BAT:xxx <--> BAT:xxx / EURUSD) -Special timeframe definition -Configurable multi-option alarm center -Alternative summary presentation (check list / status table / stickers) ________________________________________ Details and usage: The user needs to configure four main sections: • Pair and correlated pairs • Timeframes (Auto / Manual) • Alarm center • Visual arrangement and selections Pair Selections: The user should adjust trading pairs according to their trade preferences. Examples: • Triad: NQ1!-ES1!-YM1!, BTC-ETH-Total3 • Dyad: NAS100-US500, XAUUSD-XAGUSD, XRPUSDT-XLMUSDT Single pairs: -Crypto Assets: If crypto assets are not in the triad or dyad list, they are automatically matched as: Perpetual <--> Spot (e.g.: DOGEUSDT.P <--> DOGEUSDT) If the asset is already defined in a dyad list (e.g., DOGE – SHIB), the dyad definition takes priority. ________________________________________ -Stocks: If stocks are defined in the dyad list (e.g.: BIST:THYAO <--> BIST:PGSUS), the dyad definition takes priority. If not defined, the stock is compared with its value in the selected currency. For example, in the Turkish Stock Exchange: BIST:FENER stock, if EUR is chosen from the menu, is compared as BIST:FENER / OANDA:EURTRY. Here, “OANDA” and the stock market currency (TRY) are automatically applied for the exchange rate. For NYSE:XOM, its pair will be NYSE:XOM / EURUSD. ________________________________________ Timeframes: By default, the menu is set to “Auto.” In this mode, aligned timeframes are automatically selected. Aligned timeframes (LTF-HTF): 1m-15m, 3m-30m, 5m-1h, 15m-4h, 1h-D, 4h-W, D-M Example: if monitoring the chart on 5m: • 1h sweep + 5m CISD confirmation • D sweep + 1h CISD confirmation (bias) • 5m market structure • 1h SMT and 1h RSI divergence analysis For manual selections, the user must define the timeframes for Sweep and HTF bias. FVG, iFVG, and Volume Imbalance timeframes must be manually set in both modes. ________________________________________ Alarm Center: The user can choose according to preferred criteria. Each row has options. “Yes” → included in alarm condition. “No” → not included in alarm condition. If special timeframe criteria are added to the alarm, the hour range must also be entered in the same row, and the “Special Zone” tab (default: -4) should be checked. Key level timeframes and plot options must be set manually. Example alarm setup: Alongside the main Sweep + CISD condition, if we also want HTF bias + Trend alignment + key level (W, D) and special timeframe (09:00–11:00), we should set up the menu as follows: ________________________________________ Visual Arrangement and Selections: Users can control visibility with checkboxes according to their preferences. In the Table & Sticker tab, table options and labels can be controlled. • Summary Table has two options: Check list and Status Table • From the HTF bias section, real-time bias and HTF sweep zone (optional) are displayed • The RSI divergence section only shows divergence analysis results • The SMT 2 sub-section only functions when triad is selected Labels are shown on the bar where the sweep + CISD condition occurs, displaying the current situation. With the Check box option, all criteria’s real-time status is shown (True/False). Status Table provides a real-time summary table. Although the menu may look crowded, most settings only need to be adjusted once during initial use. ________________________________________ What’s next? • Suggestions from users • Standard deviation projection • Mitigation/order blocks (cd special mtg) • PSP /TPD ________________________________________ Final note: Every additional criterion in the alarm settings will affect alarm frequency. Multiple conditions occurring at the same time is not, by itself, sufficient to enter a trade—you should always apply your own judgment. Looking forward to your feedback and suggestions. Happy trading! 🎉
Pine Script®指标
由cdikici71提供
111
Anrazzi - EMAs/ATR - 1.0.2Description: The Anrazzi - EMAs/ATR indicator is a versatile tool for technical traders looking to monitor multiple moving averages alongside the Average True Range (ATR) on any chart. Designed for simplicity and customization, it allows traders to visualize up to six moving averages with configurable type, color, and length, while keeping real-time volatility information via ATR directly on the chart. This indicator is perfect for spotting trends, identifying support/resistance zones, and gauging market volatility for intraday or swing trading strategies. Key Features: Supports up to six independent moving averages (MA1 → MA6) Each MA is fully customizable: Enable/disable individually Type: EMA or SMA Length Color ATR Display: Custom timeframe Color and position configurable Adjustable multiplier Compact and organized settings for easy configuration Lightweight and efficient code for smooth chart performance Watermark Inputs / Settings: MA Options: MA1 → MA6 (Enable/Disable, Type, Length, Color) Additional Settings: ATR (Enable, Timeframe, Color, Multiplier) How to Use: Enable the moving averages you want to track Configure type, length, and color for each MA Enable ATR if needed and adjust settings Watch MAs plotted dynamically and ATR in bottom-right corner Recommended For: Day traders and swing traders Trend-following strategies Volatility analysis and breakout detection Traders needing a compact multi-MA dashboard
Pine Script®指标
由Anrazzi提供
Liquidity Pro Map [ChartPrime]⯁ OVERVIEW Liquidity Pro Map is a market-structure tool that simulates liquidity distribution by splitting price history into buy-side and sell-side profiles. Using candle volume and the standard deviation of close, the indicator builds two mirrored volume maps on the right-hand side of the chart. It also extends liquidity levels backwards in time until they are crossed by price, allowing you to see which zones remain untouched and where liquidity is most likely resting. Cumulative skew lines and highlighted POC levels give additional clarity on imbalance between buyers and sellers. ⯁ KEY FEATURES Dual Liquidity Profiles: The chart is divided into buy-side (green) and sell-side (red) liquidity profiles, letting you instantly compare both sides of order flow. Level Extension Logic: Each liquidity level is extended back in time until price crosses it. If not crossed, it persists all the way to the indicator’s lookback period, marking zones that remain “untapped.” Dynamic Binning with Standard Deviation: The indicator distributes candle volumes into bins using close-price deviation, creating a more realistic liquidity map than static price levels. priceDeviation = ta.stdev(close, 25) * 2 priceReference = close > open ? low - priceDeviation : high + priceDeviation Cumulative Volume Skew Lines: Polylines on the right-hand side show the aggregated buy and sell volume profiles, making it easy to spot imbalance. POC Identification: Highest-volume levels on both sides are marked as POC (Point of Control) , providing key zones of interest. Clear Color Coding: Gradient shading intensifies with volume concentration—dark teal/green for buy zones, dark pink/red for sell zones. ⯁ HOW IT WORKS (UNDER THE HOOD) Volume Distribution: Each bar’s volume is assigned to a price bin based on its reference price (close ± standard deviation offset). Buy vs. Sell Splitting: If bins above last close price, volume is allocated to sell-side liquidity; otherwise, it’s allocated to buy-side liquidity. Level Extension: Boxes marking liquidity bins extend back until crossed by price. If uncrossed, they anchor all the way to the start of the lookback window. Cumulative Polylines: As bins are stacked, cumulative buy and sell values form skew polylines plotted at the right edge. POC Levels: The highest-volume bin on each side is highlighted with labels and arrows, marking where the heaviest liquidity is concentrated. ⯁ USAGE Use buy/sell profiles to see where liquidity is likely resting. Green shelves suggest potential support zones; red shelves suggest resistance or sell liquidity pools. Watch untouched extended levels —these often become magnets for price as liquidity is swept. Track POC levels as primary liquidity targets, where reactions or fakeouts are most common. Compare cumulative skew lines to judge which side dominates in volume. Heavy buy skew may indicate absorption of sell pressure, and vice versa. Adjust lookback period to switch between intraday liquidity maps and larger swing-based profiles. Use separator feature to hide bins borders for better visual clarity. Use as a confluence tool with OBs, support/resistance, and liquidity sweep setups. ⯁ CONCLUSION Liquidity Pro Map transforms candle volume into a structured simulation of where liquidity may rest across the chart. By dividing buy vs. sell profiles, extending untouched levels, and marking cumulative skew and POC, it equips traders with a clear visual map of potential liquidity pools. This allows for better anticipation of sweeps, reversals, and areas of high market activity.
Pine Script®指标
由ChartPrime提供
24
PolyFilter [BackQuant]PolyFilter A flexible, low-lag trend filter with three smoothing engines—optimized for clean bias, fewer whipsaws, and clear alerting. What it does PolyFilter draws a single “intelligent” baseline that adapts to price while suppressing noise. You choose the engine— Fractional MA , Ehlers 2-Pole Super Smoother , or a Multi-Kernel blend . The line can color itself by slope (trend) or by position vs price (above/below), and you get four ready-made alerts for flips and crosses. What it plots PolyFilter line — your smoothed trend baseline (width set by “Line Width”). Optional candle & background coloring — choose: color by trend slope or by whether price is above/below the filter. Signal markers — Arrows with L/S when the slope flips or when price crosses the line (if you enable shapes/alerts). How the three engines differ Fractional MA (experimental) — A power-law weighting of past bars (heavier focus on the most recent samples without throwing away history). The Adaptation Speed acts like the “fraction” exponent (default 0.618). Lower values lean more on recent bars; higher values spread weight further back. Ehlers 2-Pole Super Smoother — Classic low-lag IIR smoother that aggressively reduces high-frequency noise while preserving turns. Great default when you want a steady, responsive baseline with minimal parameter fuss. Multi-Kernel — A 70/30 blend of a Gaussian window and an exponential kernel. The Gaussian contributes smooth structure; the exponential adds a hint of responsiveness. Useful for assets that oscillate but still trend. Reading the colors Trend mode (default) — Line & candles turn green while the filter is rising (signal > signal ) and red while it’s falling. Above/Below mode — Line & candles reflect price’s position relative to the filter: green when price > filter, red when price < filter. This is handy if you treat the filter like a dynamic “fair value” or bias line. Inputs you’ll actually use Calculation Settings Price Source — Default HLC/3. Switch to Close for stricter trend, or HLC3/HL2 to soften single-print spikes. Filter Length — Window/period for all engines. Shorter = snappier turns; longer = smoother line. Adaptation Speed — Only affects Fractional MA . Lower it for faster, more local weighting; raise it for smoother, more global weighting. Filter Type — Pick one of: Fractional MA, Ehlers 2-Pole, Multi-Kernel. UI & Plotting Color based off… — Choose Trend (slope) or > or < Close (position vs price). Long/Short Colors — Customize bull/bear hues to your theme. Show Filter Line / Paint candles / Color background — Visual toggles for the line, bars, and backdrop. Line Width — Make the filter stand out (2–3 works well on most charts). Signals & Alerts PolyFilter Trend Up — Slope flips upward (the filter crosses above its prior value). Good for early continuation entries or stop-tightening on shorts. PolyFilter Trend Down — Slope flips downward. Often used to scale out longs or rotate bias. PolyFilter Above Price — The filter line crosses up through price (filter > price). This can confirm that mean has “caught up” after a pullback. PolyFilter Below Price — The filter line crosses down through price (filter < price). Useful to confirm momentum loss on bounces. Quick starts (suggested presets) Intraday (5–15m, crypto or indices) — Ehlers 2-Pole, Length 55–80. Trend coloring ON, candle paint ON. Look for pullbacks to a rising filter; avoid fading a falling one. Swing (1H–4H) — Multi-Kernel, Length 80–120. Background color OFF (cleaner), candle paint ON. Add a higher-TF confirmation (e.g., 4H filter rising when you trade 1H). Range-prone FX — Fractional MA, Length 70–100, Adaptation ~0.55–0.70. Consider Above/Below mode to trade mean reversion to the line with a strict risk cap. How to use it in practice Bias line — Trade in the direction of the filter slope; stand aside when it flattens and color chops back and forth. Dynamic support/resistance — Treat the line as a moving value area. In trends, entries often appear on shallow tags of the line with structure confluence. Regime switch — When the filter flips and holds color for several bars, tighten stops on the opposing side and look for first pullback in the new color. Stacking filters — Many users run PolyFilter on the active chart and a slower instance (longer length) on a higher timeframe as a “macro bias” guardrail. Tuning tips If you see too many flips, lengthen the filter or switch to Multi-Kernel. If turns feel late, shorten the filter or try Ehlers 2-Pole for lower lag. On thin or very noisy symbols, prefer HLC3 as the source and longer lengths. Performance note: very large lengths increase computation time for the Multi-Kernel and Fractional engines. Start moderate and scale up only if needed. Summary PolyFilter gives you a single, trustworthy baseline that you can read at a glance—either as a pure trend line (slope coloring) or as a dynamic “above/below fair value” reference. Pick the engine that matches your market’s personality, set a sensible length, and let the color and alerts guide bias, entries on pullbacks, and risk on reversals.
Pine Script®指标
由BackQuant提供
2
Harmonic Super GuppyHarmonic Super Guppy – Harmonic & Golden Ratio Trend Analysis Framework Overview Harmonic Super Guppy is a comprehensive trend analysis and visualization tool that evolves the classic Guppy Multiple Moving Average (GMMA) methodology, pioneered by Daryl Guppy to visualize the interaction between short-term trader behavior and long-term investor trends. into a harmonic and phase-based market framework. By combining harmonic weighting, golden ratio phasing, and multiple moving averages, it provides traders with a deep understanding of market structure, momentum, and trend alignment. Fast and slow line groups visually differentiate short-term trader activity from longer-term investor positioning, while adaptive fills and dynamic coloring clearly illustrate trend coherence, expansion, and contraction in real time. Traditional GMMA focuses primarily on moving average convergence and divergence. Harmonic Super Guppy extends this concept, integrating frequency-aware harmonic analysis and golden ratio modulation, allowing traders to detect subtle cyclical forces and early trend shifts before conventional moving averages would react. This is particularly valuable for traders seeking to identify early trend continuation setups, preemptive breakout entries, and potential trend exhaustion zones. The indicator provides a multi-dimensional view, making it suitable for scalping, intraday trading, swing setups, and even longer-term position strategies. The visual structure of Harmonic Super Guppy is intentionally designed to convey trend clarity without oversimplification. Fast lines reflect short-term trader sentiment, slow lines capture longer-term investor alignment, and fills highlight compression or expansion. The adaptive color coding emphasizes trend alignment: strong green for bullish alignment, strong red for bearish, and subtle gray tones for indecision. This allows traders to quickly gauge market conditions while preserving the granularity necessary for sophisticated analysis. How It Works Harmonic Super Guppy uses a combination of harmonic averaging, golden ratio phasing, and adaptive weighting to generate its signals. Harmonic Weighting : Each moving average integrates three layers of harmonics: Primary harmonic captures the dominant cyclical structure of the market. Secondary harmonic introduces a complementary frequency for oscillatory nuance. Tertiary harmonic smooths higher-frequency noise while retaining meaningful trend signals. Golden Ratio Phase : Phases of each harmonic contribution are adjusted using the golden ratio (default φ = 1.618), ensuring alignment with natural market rhythms. This reduces lag and allows traders to detect trend shifts earlier than conventional moving averages. Adaptive Trend Detection : Fast SMAs are compared against slow SMAs to identify structural trends: UpTrend : Fast SMA exceeds slow SMA. DownTrend : Fast SMA falls below slow SMA. Frequency Scaling : The wave frequency setting allows traders to modulate responsiveness versus smoothing. Higher frequency emphasizes short-term moves, while lower frequency highlights structural trends. This enables adaptation across asset classes with different volatility characteristics. Through this combination, Harmonic Super Guppy captures micro and macro market cycles, helping traders distinguish between transient noise and genuine trend development. The multi-harmonic approach amplifies meaningful price action while reducing false signals inherent in standard moving averages. Interpretation Harmonic Super Guppy provides a multi-dimensional perspective on market dynamics: Trend Analysis : Alignment of fast and slow lines reveals trend direction and strength. Expanding harmonics indicate momentum building, while contraction signals weakening conditions or potential reversals. Momentum & Volatility : Rapid expansion of fast lines versus slow lines reflects short-term bullish or bearish pressure. Compression often precedes breakout scenarios or volatility expansion. Traders can quickly gauge trend vigor and potential turning points. Market Context : The indicator overlays harmonic and structural insights without dictating entry or exit points. It complements order blocks, liquidity zones, oscillators, and other technical frameworks, providing context for informed decision-making. Phase Divergence Detection : Subtle divergence between harmonic layers (primary, secondary, tertiary) often signals early exhaustion in trends or hidden strength, offering preemptive insight into potential reversals or sustained continuation. By observing both structural alignment and harmonic expansion/contraction, traders gain a clear sense of when markets are trending with conviction versus when conditions are consolidating or becoming unpredictable. This allows for proactive trade management, rather than reactive responses to lagging indicators. Strategy Integration Harmonic Super Guppy adapts to various trading methodologies with clear, actionable guidance. Trend Following : Enter positions when fast and slow lines are aligned and harmonics are expanding. The broader the alignment, the stronger the confirmation of trend persistence. For example: A fast line crossover above slow lines with expanding fills confirms momentum-driven continuation. Traders can use harmonic amplitude as a filter to reduce entries against prevailing trends. Breakout Trading : Periods of line compression indicate potential volatility expansion. When fast lines diverge from slow lines after compression, this often precedes breakouts. Traders can combine this visual cue with structural supports/resistances or order flow analysis to improve timing and precision. Exhaustion and Reversals : Divergences between harmonic components, or contraction of fast lines relative to slow lines, highlight weakening trends. This can indicate liquidity exhaustion, trend fatigue, or corrective phases. For example: A flattening fast line group above a rising slow line can hint at short-term overextension. Traders may use these signals to tighten stops, take partial profits, or prepare for contrarian setups. Multi-Timeframe Analysis : Overlay slow lines from higher timeframes on lower timeframe charts to filter noise and trade in alignment with larger market structures. For example: A daily bullish alignment combined with a 15-minute breakout pattern increases probability of a successful intraday trade. Conversely, a higher timeframe divergence can warn against taking counter-trend trades in lower timeframes. Adaptive Trade Management : Harmonic expansion/contraction can guide dynamic risk management: Stops may be adjusted according to slow line support/resistance or harmonic contraction zones. Position sizing can be modulated based on harmonic amplitude and compression levels, optimizing risk-reward without rigid rules. Technical Implementation Details Harmonic Super Guppy is powered by a multi-layered harmonic and phase calculation engine: Harmonic Processing : Primary, secondary, and tertiary harmonics are calculated per period to capture multiple market cycles simultaneously. This reduces noise and amplifies meaningful signals. Golden Ratio Modulation : Phase adjustments based on φ = 1.618 align harmonic contributions with natural market rhythms, smoothing lag and improving predictive value. Adaptive Trend Scaling : Fast line expansion reflects short-term momentum; slow lines provide structural trend context. Fills adapt dynamically based on alignment intensity and harmonic amplitude. Multi-Factor Trend Analysis : Trend strength is determined by alignment of fast and slow lines over multiple bars, expansion/contraction of harmonic amplitudes, divergences between primary, secondary, and tertiary harmonics and phase synchronization with golden ratio cycles. These computations allow the indicator to be highly responsive yet smooth, providing traders with actionable insights in real time without overloading visual complexity. Optimal Application Parameters Asset-Specific Guidance: Forex Majors : Wave frequency 1.0–2.0, φ = 1.618–1.8 Large-Cap Equities : Wave frequency 0.8–1.5, φ = 1.5–1.618 Cryptocurrency : Wave frequency 1.2–3.0, φ = 1.618–2.0 Index Futures : Wave frequency 0.5–1.5, φ = 1.618 Timeframe Optimization: Scalping (1–5min) : Emphasize fast lines, higher frequency for micro-move capture. Day Trading (15min–1hr) : Balance fast/slow interactions for trend confirmation. Swing Trading (4hr–Daily) : Focus on slow lines for structural guidance, fast lines for entry timing. Position Trading (Daily–Weekly) : Slow lines dominate; harmonics highlight long-term cycles. Performance Characteristics High Effectiveness Conditions: Clear separation between short-term and long-term trends. Moderate-to-high volatility environments. Assets with consistent volume and price rhythm. Reduced Effectiveness: Flat or extremely low volatility markets. Erratic assets with frequent gaps or algorithmic dominance. Ultra-short timeframes (<1min), where noise dominates. Integration Guidelines Signal Confirmation : Confirm alignment of fast and slow lines over multiple bars. Expansion of harmonic amplitude signals trend persistence. Risk Management : Place stops beyond slow line support/resistance. Adjust sizing based on compression/expansion zones. Advanced Feature Settings : Frequency tuning for different volatility environments. Phase analysis to track divergences across harmonics. Use fills and amplitude patterns as a guide for dynamic trade management. Multi-timeframe confirmation to filter noise and align with structural trends. Disclaimer Harmonic Super Guppy is a trend analysis and visualization tool, not a guaranteed profit system. Optimal performance requires proper wave frequency, golden ratio phase, and line visibility settings per asset and timeframe. Traders should combine the indicator with other technical frameworks and maintain disciplined risk management practices.
Pine Script®指标
由BOSWaves提供
Kalman Adjusted Average True Range [BackQuant]Kalman Adjusted Average True Range A volatility-aware trend baseline that fuses a Kalman price estimate with ATR “rails” to create a smooth, adaptive guide for entries, exits, and trailing risk. Built on my original Kalman This indicator is based on my original Kalman Price Filter: That core smoother is used here to estimate the “true” price path, then blended with ATR to control step size and react proportionally to market noise. What it plots Kalman ATR Line the main baseline that turns up/down with the filtered trend. Optional Moving Average of the Kalman ATR a secondary line for confluence (SMA/Hull/EMA/WMA/DEMA/RMA/LINREG/ALMA). Candle Coloring (optional) paint bars by the baseline’s current direction. Why combine Kalman + ATR? Kalman reduces measurement noise and produces a stable path without the lag of heavy MAs. ATR rails scale the baseline’s step to current volatility, so it’s calm in chop and more responsive in expansion. The result is a single, intelligible line you can trade around: slope-up = constructive; slope-down = caution. How it works (plain English) Each bar, the Kalman filter updates an internal state (tunable via Process Noise , Measurement Noise , and Filter Order ) to estimate the underlying price. An ATR band (Period × Factor) defines the allowed per-bar adjustment. The baseline cannot “jump” beyond those rails in one step. A direction flip is detected when the baseline’s slope changes sign (upturn/downturn), and alerts are provided for both. Typical uses Trend confirmation Trade in the baseline’s direction; avoid fading a firmly rising/falling line. Pullback timing Look for entries when price mean-reverts toward a rising baseline (or exits on tags of a falling one). Trailing risk Use the baseline as a dynamic guide; many traders set stops a small buffer beyond it (e.g., a fraction of ATR). Confluence Enable the MA overlay of the Kalman ATR; alignment (baseline above its MA and rising) supports continuation. Inputs & what they do Calculation Kalman Price Source which price the filter tracks (Close by default). Process Noise how quickly the filter can adapt. Higher = more responsive (but choppier). Measurement Noise how much you distrust raw price. Higher = smoother (but slower to turn). Filter Order (N) depth of the internal state array. Higher = slightly steadier behavior. Kalman ATR Period ATR lookback. Shorter = snappier; longer = steadier. Factor scales the allowed step per bar. Larger factors permit faster drift; smaller factors clamp movement. Confluence (optional) MA Type & Period compute an MA on the Kalman ATR line , not on price. Sigma (ALMA) if ALMA is selected, this input controls the curve’s shape. (Ignored for other MA types.) Visuals Plot Kalman ATR toggle the main line. Paint Candles color bars by up/down slope. Colors choose long/short hues. Signals & alerts Trend Up baseline turns upward (slope crosses above 0). Alert: “Kalman ATR Trend Up” Trend Down baseline turns downward (slope crosses below 0). Alert: “Kalman ATR Trend Down” These are state flips , not “price crossovers,” so you avoid many one-bar head-fakes. How to start (fast presets) Swing (daily/4H) ATR Period 7–14, Factor 0.5–0.8, Process Noise 0.02–0.05, Measurement Noise 2–4, N = 3–5. Intraday (5–15m) ATR Period 5–7, Factor 0.6–1.0, Process Noise 0.05–0.10, Measurement Noise 2–3, N = 3–5. Slow assets / FX raise Measurement Noise or ATR Period for calmer lines; drop Factor if the baseline feels too jumpy. Reading the line Rising & curving upward momentum building; consider long bias until a clear downturn. Flat & choppy regime uncertainty; many traders stand aside or tighten risk. Falling & accelerating distribution lower; short bias until a clean upturn. Practical playbook Continuation entries After a Trend Up alert, wait for a minor pullback toward the baseline; enter on evidence the line keeps rising. Exit/reduce If long and the baseline flattens then turns down, trim or exit; reverse logic for shorts. Filters Add a higher-timeframe check (e.g., only take longs when the daily Kalman ATR is rising). Stops Place stops just beyond the baseline (e.g., baseline − x% ATR for longs) to avoid “tag & reverse” noise. Notes This is a guide to state and momentum, not a guarantee. Combine with your process (structure, volume, time-of-day) for decisions. Settings are asset/timeframe dependent; start with the presets and nudge Process/Measurement Noise until the baseline “feels right” for your market. Summary Kalman ATR takes the noise-reduction of a Kalman price estimate and couples it with volatility-scaled movement to produce a clean, adaptive baseline. If you liked the original Kalman Price Filter (), this is its trend-trading cousin purpose-built for cleaner state flips, intuitive trailing, and confluence with your existing
Pine Script®指标
由BackQuant提供
16
RSI Trend Navigator [QuantAlgo]🟢 Overview The RSI Trend Navigator integrates RSI momentum calculations with adaptive exponential moving averages and ATR-based volatility bands to generate trend-following signals. The indicator applies variable smoothing coefficients based on RSI readings and incorporates normalized momentum adjustments to position a trend line that responds to both price action and underlying momentum conditions. 🟢 How It Works The indicator begins by calculating and smoothing the RSI to reduce short-term fluctuations while preserving momentum information: rsiValue = ta.rsi(source, rsiPeriod) smoothedRSI = ta.ema(rsiValue, rsiSmoothing) normalizedRSI = (smoothedRSI - 50) / 50 It then creates an adaptive smoothing coefficient that varies based on RSI positioning relative to the midpoint: adaptiveAlpha = smoothedRSI > 50 ? 2.0 / (trendPeriod * 0.5 + 1) : 2.0 / (trendPeriod * 1.5 + 1) This coefficient drives an adaptive trend calculation that responds more quickly when RSI indicates bullish momentum and more slowly during bearish conditions: var float adaptiveTrend = source adaptiveTrend := adaptiveAlpha * source + (1 - adaptiveAlpha) * nz(adaptiveTrend , source) The normalized RSI values are converted into price-based adjustments using ATR for volatility scaling: rsiAdjustment = normalizedRSI * ta.atr(14) * sensitivity rsiTrendValue = adaptiveTrend + rsiAdjustment ATR-based bands are constructed around this RSI-adjusted trend value to create dynamic boundaries that constrain trend line positioning: atr = ta.atr(atrPeriod) deviation = atr * atrMultiplier upperBound = rsiTrendValue + deviation lowerBound = rsiTrendValue - deviation The trend line positioning uses these band constraints to determine its final value: if upperBound < trendLine trendLine := upperBound if lowerBound > trendLine trendLine := lowerBound Signal generation occurs through directional comparison of the trend line against its previous value to establish bullish and bearish states: trendUp = trendLine > trendLine trendDown = trendLine < trendLine if trendUp isBullish := true isBearish := false else if trendDown isBullish := false isBearish := true The final output colors the trend line green during bullish states and red during bearish states, creating visual buy/long and sell/short opportunity signals based on the combined RSI momentum and volatility-adjusted trend positioning. 🟢 Signal Interpretation Rising Trend Line (Green): Indicates upward momentum where RSI influence and adaptive smoothing favor continued price advancement = Potential buy/long positions Declining Trend Line (Red): Indicates downward momentum where RSI influence and adaptive smoothing favor continued price decline = Potential sell/short positions Flattening Trend Lines: Occur when momentum weakens and the trend line slope approaches neutral, suggesting potential consolidation before the next move Built-in Alert System: Automated notifications trigger when bullish or bearish states change, sending "RSI Trend Bullish Signal" or "RSI Trend Bearish Signal" messages for timely entry/exit Color Bar Candles Option: Optional candle coloring feature that applies the same green/red trend colors to price bars, providing additional visual confirmation of the current trend direction
Pine Script®指标
由QuantAlgo提供
10
Guppy MMA [Alpha Extract]A sophisticated trend-following and momentum assessment system that constructs dynamic trader and investor sentiment channels using multiple moving average groups with advanced scoring mechanisms and smoothed CCI-style visualizations for optimal market trend analysis. Utilizing enhanced dual-group methodology with threshold-based trend detection, this indicator delivers institutional-grade GMMA analysis that adapts to varying market conditions while providing high-probability entry and exit signals through crossover and extreme value detection with comprehensive visual mapping and alert integration. 🔶 Advanced Channel Construction Implements dual-group architecture using short-term and long-term moving averages as foundation points, applying customizable MA types to reduce noise and score-based averaging for sentiment-responsive trend channels. The system creates trader channels from shorter periods and investor channels from longer periods with configurable periods for optimal market reaction zones. // Core Channel Calculation Framework maType = input.string("EMA", title="Moving Average Type", options= ) // Short-Term Group Construction stMA1 = ma(close, st1, maType) stMA2 = ma(close, st2, maType) // Long-Term Group Construction ltMA1 = ma(close, lt1, maType) ltMA2 = ma(close, lt2, maType) // Smoothing Application smoothedavg = ma(overallAvg, 10, maType) 🔶 Volatility-Adaptive Zone Framework Features dynamic score-based averaging that expands sentiment signals during strong trend periods and contracts during consolidation phases, preventing false signals while maintaining sensitivity to genuine momentum shifts. The dual-group averaging system optimizes zone boundaries for realistic market behavior patterns. // Dynamic Sentiment Adjustment shortTermAvg = (stScore1 + stScore2 + ... + stScore11) / 11 longTermAvg = (ltScore1 + ltScore2 + ... + ltScore11) / 11 // Dual-Group Zone Optimization overallAvg = (shortTermAvg + longTermAvg) / 2 allMAAvg = (shortTermAvg * 11 + longTermAvg * 11) / 22 🔶 Step-Like Boundary Evolution Creates threshold-based trend boundaries that update on smoothed average changes, providing visual history of evolving bullish and bearish levels with performance-optimized threshold management limited to key zones for clean chart presentation and efficient processing. 🔶 Comprehensive Signal Detection Generates buy and sell signals through sophisticated crossover analysis, monitoring smoothed average interaction with zero-line and thresholds for high-probability entry and exit identification. The system distinguishes between trend continuation and reversal patterns with precision timing. 🔶 Enhanced Visual Architecture Provides translucent zone fills with gradient intensity scaling, threshold-based historical boundaries, and dynamic background highlighting that activates upon trend changes. The visual system uses institutional color coding with green bullish zones and red bearish zones for intuitive market structure interpretation. 🔶 Intelligent Zone Management Implements automatic trend relevance filtering, displaying signals only when smoothed average proximity warrants analysis attention. The system maintains optimal performance through smart averaging management and historical level tracking with configurable MA periods for various market conditions. 🔶 Multi-Dimensional Analysis Framework Combines trend continuation analysis through threshold crossovers with momentum detection via extreme markers, providing comprehensive market structure assessment suitable for both trending and ranging market conditions with score-normalized accuracy. 🔶 Advanced Alert Integration Features comprehensive notification system covering buy signals, sell signals, strong bull conditions, and strong bear conditions with customizable alert conditions. The system enables precise position management through real-time notifications of critical sentiment interaction events and zone boundary violations. 🔶 Performance Optimization Utilizes efficient MA smoothing algorithms with configurable types for noise reduction while maintaining responsiveness to genuine market structure changes. The system includes automatic visual level cleanup and performance-optimized visual rendering for smooth operation across all timeframes. This indicator delivers sophisticated GMMA-based market analysis through score-adaptive averaging calculations and intelligent group construction methodology. By combining dynamic trader and investor sentiment detection with advanced signal generation and comprehensive visual mapping, it provides institutional-grade trend analysis suitable for cryptocurrency, forex, and equity markets. The system's ability to adapt to varying market conditions while maintaining signal accuracy makes it essential for traders seeking systematic approaches to trend trading, momentum reversals, and sentiment continuation analysis with clearly defined risk parameters and comprehensive alert integration.
Pine Script®指标
由AlphaExtract提供
2
Deadband Hysteresis Supertrend [BackQuant]Deadband Hysteresis Supertrend A two-stage trend tool that first filters price with a deadband baseline, then runs a Supertrend around that baseline with optional flip hysteresis and ATR-based adverse exits. What this is A hybrid of two ideas: Deadband Hysteresis Baseline that only advances when price pulls far enough from the baseline to matter. This suppresses micro noise and gives you a stable centerline. Supertrend bands wrapped around that baseline instead of raw price. Flips are further gated by an extra margin so side changes are more deliberate. The goal is fewer whipsaws in chop and clearer regime identification during trends. How it works (high level) Deadband step — compute a per-bar “deadband” size from one of four modes: ATR, Percent of price, Ticks, or Points. If price deviates from the baseline by more than this amount, move the baseline forward by a fraction of the excess. If not, hold the line. Centered Supertrend — build upper and lower bands around the baseline using ATR and a user factor. Track the usual trailing logic that tightens a band while price moves in its favor. Flip hysteresis — require price to exceed the active band by an extra flip offset × ATR before switching sides. This adds stickiness at the boundary. Adverse exit — once a side is taken, trigger an exit if price moves against the entry by K × ATR . If you would like to check out the filter by itself: What it plots DBHF baseline (optional) as a smooth centerline. DBHF Supertrend as the active trailing band. Candle coloring by trend side for quick read. Signal markers 𝕃 and 𝕊 at flips plus ✖ on adverse exits. Inputs that matter Price Source — series being filtered. Close is typical. HL2 or HLC3 can be steadier. Deadband mode — ATR, Percent, Ticks, or Points. This defines the “it’s big enough to matter” zone. ATR Length / Mult (DBHF) — only used when mode = ATR. Larger values widen the do-nothing zone. Percent / Ticks / Points — alternatives to ATR; pick what fits your market’s convention. Enter Mult — scales the deadband you must clear before the baseline moves. Increase to filter more noise. Response — fraction of the excess applied to baseline movement. Higher responds faster; lower is smoother. Supertrend ATR Period & Factor — traditional band size controls; higher factor widens and flips less often. Flip Offset ATR — extra ATR buffer required to flip. Useful in choppy regimes. Adverse Stop K·ATR — per-trade danger brake that forces an exit if price moves K×ATR against entry. UI — toggle baseline, supertrend, signals, and bar painting; choose long and short colors. How to read it Green regime — candles painted long and the Supertrend running below price. Pullbacks toward the baseline that fail to breach the opposite band often resume higher. Red regime — candles painted short and the Supertrend running above price. Rallies that cannot reclaim the band may roll over. Frequent side swaps — reduce sensitivity by increasing Enter Mult, using ATR mode, raising the Supertrend factor, or adding Flip Offset ATR. Use cases Bias filter — allow entries only in the direction of the current side. Use your preferred triggers inside that bias. Trailing logic — treat the active band as a dynamic stop. If the side flips or an adverse K·ATR exit prints, reduce or close exposure. Regime map — on higher timeframes, the combination baseline + band produces a clean up vs down template for allocation decisions. Tuning guidance Fast markets — ATR deadband, modest Enter Mult (0.8–1.2), response 0.2–0.35, Supertrend factor 1.7–2.2, small Flip Offset (0.2–0.5 ATR). Choppy ranges — widen deadband or raise Enter Mult, lower response, and add more Flip Offset so flips require stronger evidence. Slow trends — longer ATR periods and higher Supertrend factor to keep you on side longer; use a conservative adverse K. Included alerts DBHF ST Long — side flips to long. DBHF ST Short — side flips to short. Adverse Exit Long / Short — K·ATR stop triggers against the current side. Strengths Deadbanded baseline reduces micro whipsaws before Supertrend logic even begins. Flip hysteresis adds a second layer of confirmation at the boundary. Optional adverse ATR stop provides a uniform risk cut across assets and regimes. Clear visuals and minimal parameters to adjust for symbol behavior. Putting it together Think of this tool as two decisions layered into one view. The deadband baseline answers “does this move even count,” then the Supertrend wrapped around that baseline answers “if it counts, which side should I be on and where do I flip.” When both parts agree you tend to stay on the correct side of a trend for longer, and when they disagree you get an early warning that conditions are changing. When the baseline bends and price cannot reclaim the opposite band , momentum is usually continuing. Pullbacks into the baseline that stall before the far band often resolve in trend. When the baseline flattens and the bands compress , expect indecision. Use the Flip Offset ATR to avoid reacting to the first feint. Wait for a clean band breach with follow through. When an adverse K·ATR exit prints while the side has not flipped , treat it as a risk event rather than a full regime change. Many users cut size, re-enter only if the side reasserts, and let the next flip confirm a new trend. Final thoughts Deadband Hysteresis Supertrend is best read as a regime lens. The baseline defines your tolerance for noise, the bands define your trailing structure, and the flip offset plus adverse ATR stop define how forgiving or strict you want to be at the boundary. On strong trends it helps you hold through shallow shakeouts. In choppy conditions it encourages patience until price does something meaningful. Start with settings that reflect the cadence of your market, observe how often flips occur, then nudge the deadband and flip offset until the tool spends most of its time describing the move you care about rather than the noise in between.
Pine Script®指标
由BackQuant提供
8
Theil-Sen Line Filter [BackQuant]Theil-Sen Line Filter A robust, median-slope baseline that tracks price while resisting outliers. Designed for the chart pane as a clean, adaptive reference line with optional candle coloring and slope-flip alerts. What this is A trend filter that estimates the underlying slope of price using a Theil-Sen style median of past slopes, then advances a baseline by a controlled fraction of that slope each bar. The result is a smooth line that reacts to real directional change while staying calm through noise, gaps, and single-bar shocks. Why Theil-Sen Classical moving averages are sensitive to outliers and shape changes. Ordinary least squares is sensitive to large residuals. The Theil-Sen idea replaces a single fragile estimate with the median of many simple slopes, which is statistically robust and less influenced by a few extreme bars. That makes the baseline steadier in choppy conditions and cleaner around regime turns. What it plots Filtered baseline that advances by a fraction of the robust slope each bar. Optional candle coloring by baseline slope sign for quick trend read. Alerts when the baseline slope turns up or down. How it behaves (high level) Looks back over a fixed window and forms many “current vs past” bar-to-bar slopes. Takes the median of those slopes to get a robust estimate for the bar. Optionally caps the magnitude of that per-bar slope so a single volatile bar cannot yank the line. Moves the baseline forward by a user-controlled fraction of the estimated slope. Lower fractions are smoother. Higher fractions are more responsive. Inputs and what they do Price Source — the series the filter tracks. Typical is close; HL2 or HLC3 can be smoother. Window Length — how many bars to consider for slopes. Larger windows are steadier and slower. Smaller windows are quicker and noisier. Response — fraction of the estimated slope applied each bar. 1.00 follows the robust slope closely; values below 1.00 dampen moves. Slope Cap Mode — optional guardrail on each bar’s slope: None — no cap. ATR — cap scales with recent true range. Percent — cap scales with price level. Points — fixed absolute cap in price points. ATR Length / Mult, Cap Percent, Cap Points — tune the chosen cap mode’s size. UI Settings — show or hide the line, paint candles by slope, choose long and short colors. How to read it Up-slope baseline and green candles indicate a rising robust trend. Pullbacks that do not flip the slope often resolve in trend direction. Down-slope baseline and red candles indicate a falling robust trend. Bounces against the slope are lower-probability until proven otherwise. Flat or frequent flips suggest a range. Increase window length or decrease response if you want fewer whipsaws in sideways markets. Use cases Bias filter — only take longs when slope is up, shorts when slope is down. It is a simple way to gate faster setups. Stop or trail reference — use the line as a trailing guide. If price closes beyond the line and the slope flips, consider reducing exposure. Regime detector — widen the window on higher timeframes to define major up vs down regimes for asset rotation or risk toggles. Noise control — enable a cap mode in very volatile symbols to retain the line’s continuity through event bars. Tuning guidance Quick swing trading — shorter window, higher response, optionally add a percent cap to keep it stable on large moves. Position trading — longer window, moderate response. ATR cap tends to scale well across cycles. Low-liquidity or gappy charts — prefer longer window and a points or ATR cap. That reduces jumpiness around discontinuities. Alerts included Theil-Sen Up Slope — baseline’s one-bar change crosses above zero. Theil-Sen Down Slope — baseline’s one-bar change crosses below zero. Strengths Robust to outliers through median-based slope estimation. Continuously advances with price rather than re-anchoring, which reduces lag at turns. User-selectable slope caps to tame shock bars without over-smoothing everything. Minimal visuals with optional candle painting for fast regime recognition. Notes This is a filter, not a trading system. It does not account for execution, spreads, or gaps. Pair it with entry logic, risk management, and higher-timeframe context if you plan to use it for decisions.
Pine Script®指标
由BackQuant提供
Adaptive Trend Following Suite [Alpha Extract]A sophisticated multi-filter trend analysis system that combines advanced noise reduction, adaptive moving averages, and intelligent market structure detection to deliver institutional-grade trend following signals. Utilizing cutting-edge mathematical algorithms and dynamic channel adaptation, this indicator provides crystal-clear directional guidance with real-time confidence scoring and market mode classification for professional trading execution. 🔶 Advanced Noise Reduction Filter Eliminates market noise using sophisticated Gaussian filtering with configurable sigma values and period optimization. The system applies mathematical weight distribution across price data to ensure clean signal generation while preserving critical trend information, automatically adjusting filter strength based on volatility conditions. advancedNoiseFilter(sourceData, filterLength, sigmaParam) => weightSum = 0.0 valueSum = 0.0 centerPoint = (filterLength - 1) / 2 for index = 0 to filterLength - 1 gaussianWeight = math.exp(-0.5 * math.pow((index - centerPoint) / sigmaParam, 2)) weightSum += gaussianWeight valueSum += sourceData * gaussianWeight valueSum / weightSum 🔶 Adaptive Moving Average Core Engine Features revolutionary volatility-responsive averaging that automatically adjusts smoothing parameters based on real-time market conditions. The engine calculates adaptive power factors using logarithmic scaling and bandwidth optimization, ensuring optimal responsiveness during trending markets while maintaining stability during consolidation phases. // Calculate adaptive parameters adaptiveLength = (periodLength - 1) / 2 logFactor = math.max(math.log(math.sqrt(adaptiveLength)) / math.log(2) + 2, 0) powerFactor = math.max(logFactor - 2, 0.5) relativeVol = avgVolatility != 0 ? volatilityMeasure / avgVolatility : 0 adaptivePower = math.pow(relativeVol, powerFactor) bandwidthFactor = math.sqrt(adaptiveLength) * logFactor 🔶 Intelligent Market Structure Analysis Employs fractal dimension calculations to classify market conditions as trending or ranging with mathematical precision. The system analyzes price path complexity using normalized data arrays and geometric path length calculations, providing quantitative market mode identification with configurable threshold sensitivity. 🔶 Multi-Component Momentum Analysis Integrates RSI and CCI oscillators with advanced Z-score normalization for statistical significance testing. Each momentum component receives independent analysis with customizable periods and significance levels, creating a robust consensus system that filters false signals while maintaining sensitivity to genuine momentum shifts. // Z-score momentum analysis rsiAverage = ta.sma(rsiComponent, zAnalysisPeriod) rsiDeviation = ta.stdev(rsiComponent, zAnalysisPeriod) rsiZScore = (rsiComponent - rsiAverage) / rsiDeviation if math.abs(rsiZScore) > zSignificanceLevel rsiMomentumSignal := rsiComponent > 50 ? 1 : rsiComponent < 50 ? -1 : rsiMomentumSignal ❓How It Works 🔶 Dynamic Channel Configuration Calculates adaptive channel boundaries using three distinct methodologies: ATR-based volatility, Standard Deviation, and advanced Gaussian Deviation analysis. The system automatically adjusts channel multipliers based on market structure classification, applying tighter channels during trending conditions and wider boundaries during ranging markets for optimal signal accuracy. dynamicChannelEngine(baselineData, channelLength, methodType) => switch methodType "ATR" => ta.atr(channelLength) "Standard Deviation" => ta.stdev(baselineData, channelLength) "Gaussian Deviation" => weightArray = array.new_float() totalWeight = 0.0 for i = 0 to channelLength - 1 gaussWeight = math.exp(-math.pow((i / channelLength) / 2, 2)) weightedVariance += math.pow(deviation, 2) * array.get(weightArray, i) math.sqrt(weightedVariance / totalWeight) 🔶 Signal Processing Pipeline Executes a sophisticated 10-step signal generation process including noise filtering, trend reference calculation, structure analysis, momentum component processing, channel boundary determination, trend direction assessment, consensus calculation, confidence scoring, and final signal generation with quality control validation. 🔶 Confidence Transformation System Applies sigmoid transformation functions to raw confidence scores, providing 0-1 normalized confidence ratings with configurable threshold controls. The system uses steepness parameters and center point adjustments to fine-tune signal sensitivity while maintaining statistical robustness across different market conditions. 🔶 Enhanced Visual Presentation Features dynamic color-coded trend lines with adaptive channel fills, enhanced candlestick visualization, and intelligent price-trend relationship mapping. The system provides real-time visual feedback through gradient fills and transparency adjustments that immediately communicate trend strength and direction changes. 🔶 Real-Time Information Dashboard Displays critical trading metrics including market mode classification (Trending/Ranging), structure complexity values, confidence scores, and current signal status. The dashboard updates in real-time with color-coded indicators and numerical precision for instant market condition assessment. 🔶 Intelligent Alert System Generates three distinct alert types: Bullish Signal alerts for uptrend confirmations, Bearish Signal alerts for downtrend confirmations, and Mode Change alerts for market structure transitions. Each alert includes detailed messaging and timestamp information for comprehensive trade management integration. 🔶 Performance Optimization Utilizes efficient array management and conditional processing to maintain smooth operation across all timeframes. The system employs strategic variable caching, optimized loop structures, and intelligent update mechanisms to ensure consistent performance even during high-volatility market conditions. This indicator delivers institutional-grade trend analysis through sophisticated mathematical modelling and multi-stage signal processing. By combining advanced noise reduction, adaptive averaging, intelligent structure analysis, and robust momentum confirmation with dynamic channel adaptation, it provides traders with unparalleled trend following precision. The comprehensive confidence scoring system and real-time market mode classification make it an essential tool for professional traders seeking consistent, high-probability trend following opportunities with mathematical certainty and visual clarity.
Pine Script®指标
由AlphaExtract提供
4
RB — Rejection Blocks (Price Structure)This indicator detects and visualizes Rejection Blocks (RBs) using pure price action logic. A bullish RB occurs when a down candle forms a lower low than both its neighbors. A bearish RB occurs when an up candle forms a higher high than both its neighbors. Validated RBs are displayed as boxes, optional lines, or labels. Blocks are automatically removed when invalidated (price closes through them), keeping the chart uncluttered and focused. How to use • Apply on any timeframe, from intraday to higher timeframes. • Watch how price reacts when revisiting RB zones. • Treat these zones as contextual areas, not entry signals. • Combine with your own trading methods for confirmation. Originality Unlike generic support/resistance tools, this indicator isolates a specific structural pattern (rejection blocks) and renders it visually on the chart. This selective focus allows traders to study structural reactions with more clarity and precision. ⚠️ Disclaimer: This is not a trading system or a signal provider. It is a visual analysis tool designed for structural and educational purposes.
Pine Script®指标
由theunlockedtrading提供
3
Smart Structure Breaks & Order BlocksOverview (What it does) The indicator “Smart Structure Breaks & Order Blocks” detects market structure using swing highs and lows, identifies Break of Structure (BOS) events, and automatically draws order blocks (OBs) from the origin candle. These zones extend to the right and change color/outline when mitigated or invalidated. By formalizing and automating part of discretionary analysis, it provides consistent zone recognition. Main Components Swing Detection: ta.pivothigh/ta.pivotlow identify confirmed swing points. BOS Detection: Determines if the recent swing high/low is broken by close (strict mode) or crossover. OB Creation: After a BOS, the opposite candle (bearish for bullish BOS, bullish for bearish BOS) is used to generate an order block zone. Zone Management: Limits the number of zones, extends them to the right, and tracks tagged (mitigated) or invalidated states. Input Parameters Left/Right Pivot (default 6/6): Number of bars required on each side to confirm a swing. Higher values = smoother swings. Max Zones (default 4): Maximum zones stored per direction (bull/bear). Oldest zones are overwritten. Zone Confirmation Lookback (default 3): Ensures OB origin candle validity by checking recent highs/lows. Show Swing Points (default ON): Displays triangles on swing highs/lows. Require close for BOS? (default ON): Strict BOS (close required) vs loose BOS (line crossover). Use candle body for zones (default OFF): Zones drawn from candle body (ON) or wick (OFF). Signal Definition & Logic Swing Updates: Latest confirmed pivots update lastHighLevel / lastLowLevel. BOS (Break of Structure): 　Bullish – close breaks last swing high. 　Bearish – close breaks last swing low. 　Only one valid BOS per swing (avoids duplicates). OB Detection: 　Bullish BOS → previous bearish candle with lowest low forms the OB. 　Bearish BOS → previous bullish candle with highest high forms the OB. 　Zones: Bull = green, Bear = red, semi-transparent, extended to the right. Zone States: 　Mitigated: Price touches the zone → border highlighted. 　Invalidated: 　　Bull zone → close below → turns red. 　　Bear zone → close above → turns green. Chart Appearance Swing High: red triangle above bar Swing Low: green triangle below bar Bull OB: green zone (border highlighted on touch) Bear OB: red zone (border highlighted on touch) Invalid Zones: Bull zones turn reddish, Bear zones turn greenish Practical Use (Trading Assistance) Trend Following Entries: Buy pullbacks into green OBs in uptrends, sell rallies into red OBs in downtrends. Focus on First Touch: First mitigation after BOS often has higher reaction probability. Confluence: Combine with higher timeframe trend, volume, session levels, key price levels (previous highs/lows, VWAP, etc.). Stops/Targets: 　Bull – stop below zone, partial take profit at swing high or resistance. 　Bear – stop above zone, partial take profit at swing low or support. Parameter Tuning (per market/timeframe) Pivot (6/6 → 4/4/8/8): Lower for scalping (3–5), medium for day trading (5–8), higher for swing trading (8–14). Increase to reduce noise. Strict Break: ON to reduce false breaks in ranging markets; OFF for earlier signals. Body Zones: ON for assets with long wicks, OFF for cleaner OBs in liquid instruments. Zone Confirmation (default 3): Increase for stricter OB origin, fewer zones. Max Zones (default 4 → 6–10): Increase for higher volatility, decrease to avoid clutter. Strengths Standardizes BOS and OB detection that is usually subjective. Tracks mitigation and invalidation automatically. Adaptable: allows body/wick zone switching for different instruments. Limitations Pivot-based: Signals appear only after pivots confirm (slight lag). Zones reflect past balance: Can fail after new events (news, earnings, macro data). Range-heavy markets: More false BOS; consider stricter settings. Backtesting: This script is for drawing/visual aid; trading rules must be defined separately. Workflow Example Identify higher timeframe trend (4H/Daily). On lower TF (15–60m), wait for BOS and new OB. Enter on first mitigation with confirmation candle. Stop beyond zone; targets based on R multiples and swing points. FAQ Q: Why are zones invalidated quickly? A: Flow reversal after BOS. Adjust pivots higher, enable Strict mode, or switch to Body zones to reduce noise. Q: What does “tagged” mean? A: Price touched the zone once = mitigated. Implies some orders in that zone may have been filled. Q: Body or Wick zones? A: Wick zones are fine in clean markets. For volatile pairs with long wicks, body zones provide more realistic areas. Customization Tips (Code perspective) Zone storage: Currently ring buffer ((idx+1) % zoneLimit). Could prioritize keeping unmitigated zones. Automated testing: Add strategy.entry/exit for rule-based backtests. Multi-timeframe: Use request.security() for higher timeframe swings/BOS. Visualization: Add labels for BOS bars, tag zones with IDs, count touches. Summary This indicator formalizes the cycle Swing → BOS → OB creation → Mitigation/Invalidation, providing consistent structure analysis and zone tracking. By tuning sensitivity and strictness, and combining with higher timeframe context, it enhances pullback/continuation trading setups. Always combine with proper risk management.
Pine Script®指标
由PakunFX提供
Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator Purpose This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns. What a martingale is A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged: Lose one leg → increase next position size Lose again → increase again Win → reset to the base size The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops. What it plots Equity – simulated portfolio equity including compounding Buy & Hold – equity from holding the chart symbol for context Optional helpers – last trade outcome, current streak length, current allocation fraction Optional diagnostics – daily portfolio return, rolling drawdown, metrics table Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands Model assumptions Bar-close execution with no slippage or commissions Shorting allowed and frictionless No margin interest, borrow fees, or position limits No intrabar moves or gaps within a bar (returns are close-to-close) Sizing applies to equity fraction only and is capped by your setting All results are hypothetical and for education only. How the simulator applies it 1) Directional signal You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts. 2) Sizing after losses and wins Position size is a fraction of equity: Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double Reset after win – return to the initial allocation Max allocation cap – hard ceiling to prevent runaway growth At a high level the size after k consecutive losses is alloc(k) = min( cap , base × factor^k ) . In practice the simulator changes size only when a leg ends and its PnL is known. 3) Equity update Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds: eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) . This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled. Why traders experiment with martingale sizing Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live Why martingale is dangerous Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic: Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N. Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible. No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels. Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest. Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs. Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected. The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty. Interpreting losing streaks with numbers A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check: If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare. If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap. This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests.. Using the simulator productively Parameter studies Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond. Initial allocation – lower base reduces volatility and drawdowns across the board Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive Max cap – the most important brake; many users keep it between 20 and 50 percent Signal selection Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each. Diagnostics to watch Use the built-in metrics to quantify risk: Max Drawdown – worst peak-to-trough equity loss Sharpe and Sortino – volatility and downside-adjusted return VaR 95 percent and CVaR – tail risk measures from the realized distribution Alpha and Beta – relationship to your chosen benchmark If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see Monte Carlo exploration When enabled, the forecast draws many synthetic paths from your realized daily returns: Choose a horizon and a number of runs Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path Use the table to read the expected return over the horizon and the tail outcomes Remember it is a sketch based on your recent distribution, not a predictor Concrete examples Example A: Modest martingale Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing. Example B: Aggressive martingale Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk. Strengths Bar-by-bar, transparent computation of equity from stance and size Explicit handling of wins, losses, streaks, and caps Portable signal inputs so you can A–B test ideas quickly Risk diagnostics and forward uncertainty visualization in one place Example, Rolling Max Drawdown Limitations and important notes Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs. No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled. Signals are evaluated on closes. Real execution and fills will differ. Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes. All results are hypothetical. Use this as an educational tool, not a production risk engine. Practical tips Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples. Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg. Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear. Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off. If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop. Settings recap Backtest start date and initial capital Initial allocation, increase-after-loss factor, max allocation cap Signal source selector Trading days per year and risk-free rate Benchmark symbol for Alpha and Beta UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown Monte Carlo controls for enable, runs, horizon, and result table Final thoughts A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.
Pine Script®指标
由BackQuant提供
ADX Tide ZonesADX Tide Zones – Adaptive Momentum & Trend Strength Framework Overview ADX Tide Zones – Professional is a dynamic trend-strength visualizer designed for traders who want to interpret momentum with precision and context. By combining the Average Directional Index (ADX) with adaptive threshold logic, the indicator segments price action into distinct “tide zones” that reflect varying levels of market strength: Calm, Rising, Strong, and Falling Tides. These zones transform raw ADX readings into an interpretable framework that highlights when markets are consolidating, building momentum, trending strongly, or losing strength. Unlike standard ADX readings, which can be difficult to interpret in real time, ADX Tide Zones translate momentum shifts into a continuous, color-coded system that traders can instantly read. Whether applied to scalping, intraday, or swing trading, the indicator offers a consistent methodology for identifying actionable opportunities across assets and timeframes. How It Works The foundation of ADX Tide Zones lies in momentum analysis via the ADX. By measuring the strength (not direction) of a trend, ADX provides an objective read on when markets are gaining or losing energy. ADX Tide Zones enhances this by applying threshold logic to classify ADX values into four distinct states: Calm Tide : Low ADX values indicate sideways or consolidating conditions. Rising Tide : ADX increases past a threshold, signaling momentum building. Strong Tide : ADX remains elevated, confirming robust and sustained trend strength. Falling Tide : ADX declines after strength, hinting at exhaustion or early reversal setups. These states are displayed on the chart through adaptive visualizations (zones, bar colors, or overlays), offering real-time clarity on when to expect expansion, continuation, or contraction in price action. Interpretation Trend Analysis : By mapping transitions between tides, traders can instantly gauge whether markets are in accumulation, expansion, or exhaustion phases. Rising/Strong Tides reinforce trend continuation, while Falling Tides highlight weakening conditions. Volatility & Risk Assessment : Shifts between Calm → Rising Tide often precede volatility expansions. Falling Tides can signal a period of compression or corrective moves, warning traders to manage risk proactively. Market Context : The indicator does not dictate direction; instead, it overlays strength on top of price action, allowing traders to combine it with directional tools such as moving averages, order blocks, or liquidity zones for confirmation. Strategy Integration ADX Tide Zones adapts seamlessly to a wide range of trading strategies by translating momentum dynamics into actionable frameworks: Trend Following : Traders can align with dominant flows by entering positions when the indicator confirms a Rising Tide or Strong Tide. These conditions signal persistent directional strength, making them ideal for continuation setups. Combining directional bias with ADX confirmation reduces the risk of trading against prevailing momentum. Breakout Trading : When the market transitions from Calm Tide into a Rising Tide, it often precedes a volatility expansion. This shift highlights breakout conditions where accumulation gives way to impulsive price movement. Traders can use this transition as a timing tool to catch early entries into new momentum phases. Exhaustion Reversals : Strong Tide phases don’t last forever—when they begin to fade into Falling Tide, it can mark trend fatigue or liquidity exhaustion. This offers contrarian traders an early edge in spotting overextended moves and positioning for corrective pullbacks or full reversals. Multi-Timeframe Analysis : By overlaying higher timeframe tide zones on intraday or scalping charts, traders can filter noise and trade in alignment with larger flows. For example, combining a daily Rising Tide bias with a 15-minute breakout confirmation can significantly improve entry precision while reducing exposure to false signals. Advanced Techniques For traders seeking an extra edge, ADX Tide Zones can be pushed further with advanced methods: Volume & Liquidity Confirmation : Pair the tide transitions with volume spikes, order flow, or liquidity sweep tools. When directional strength confirmed by the ADX coincides with institutional activity, it validates setups and increases probability of follow-through. Cross-Asset Synchronization : Momentum rarely exists in isolation. Monitoring tide shifts across correlated instruments (e.g., majors vs. USD, or indices vs. risk assets) can uncover synchronized volatility events. These correlations help traders identify whether a move is isolated noise or part of a broader systemic trend. Threshold Optimization : The sensitivity of ADX Tide Zones can be fine-tuned for different trading objectives. Lower thresholds heighten responsiveness, capturing micro-moves suitable for scalpers. Higher thresholds filter minor fluctuations, isolating major structural swings that align with swing or position trading. Contextual Trade Management : Instead of using static stops or targets, traders can adapt risk management dynamically by tracking tide progression. For example, a trade initiated during Rising Tide may remain valid as long as conditions sustain, but partial profits or tighter stops can be applied once the zone shifts to Calm Tide. Inputs & Customization ADX Length : Define the lookback period for ADX calculation. Threshold Levels : Adjust sensitivity for Calm, Rising, Strong, and Falling Tides. Zone Visualization : Choose between bar coloring, background shading, or overlays. Color Customization : Configure bullish, bearish, neutral, and tide-specific colors. Multi-Timeframe Options : Enable tide readings from higher timeframes for confirmation. Why Use ADX Tide Zones ADX Tide Zones turns the complexity of momentum analysis into a visual system that highlights when markets are gearing up for moves, trending with conviction, or running out of steam. By combining adaptive ADX interpretation with customizable thresholds, traders can: Anticipate breakouts before volatility expands. Confirm the strength behind price trends. Spot exhaustion phases early to secure profits or prepare for reversals. Adapt strategies seamlessly between scalping, intraday, and swing trading. With its balance of simplicity and depth, ADX Tide Zones provides a structured lens for reading market momentum, equipping traders with the clarity needed to execute with discipline and confidence.
Pine Script®指标
由BOSWaves提供
4
POC Migration Velocity (POC-MV) [PhenLabs]📊POC Migration Velocity (POC-MV) Version: PineScript™v6 📌Description The POC Migration Velocity indicator revolutionizes market structure analysis by tracking the movement, speed, and acceleration of Point of Control (POC) levels in real-time. This tool combines sophisticated volume distribution estimation with velocity calculations to reveal hidden market dynamics that conventional indicators miss. POC-MV provides traders with unprecedented insight into volume-based price movement patterns, enabling the early identification of continuation and exhaustion signals before they become apparent to the broader market. By measuring how quickly and consistently the POC migrates across price levels, traders gain early warning signals for significant market shifts and can position themselves advantageously. The indicator employs advanced algorithms to estimate intra-bar volume distribution without requiring lower timeframe data, making it accessible across all chart timeframes while maintaining sophisticated analytical capabilities. 🚀Points of Innovation Micro-POC calculation using advanced OHLC-based volume distribution estimation Real-time velocity and acceleration tracking normalized by ATR for cross-market consistency Persistence scoring system that quantifies directional consistency over multiple periods Multi-signal detection combining continuation patterns, exhaustion signals, and gap alerts Dynamic color-coded visualization system with intensity-based feedback Comprehensive customization options for resolution, periods, and thresholds 🔧Core Components POC Calculation Engine: Estimates volume distribution within each bar using configurable price bands and sophisticated weighting algorithms Velocity Measurement System: Tracks the rate of POC movement over customizable lookback periods with ATR normalization Acceleration Calculator: Measures the rate of change of velocity to identify momentum shifts in POC migration Persistence Analyzer: Quantifies how consistently POC moves in the same direction using exponential weighting Signal Detection Framework: Combines trend analysis, velocity thresholds, and persistence requirements for signal generation Visual Rendering System: Provides dynamic color-coded lines and heat ribbons based on velocity and price-POC relationships 🔥Key Features Real-time POC calculation with 10-100 configurable price bands for optimal precision Velocity tracking with customizable lookback periods from 5 to 50 bars Acceleration measurement for detecting momentum changes in POC movement Persistence scoring to validate signal strength and filter false signals Dynamic visual feedback with blue/orange color scheme indicating bullish/bearish conditions Comprehensive alert system for continuation patterns, exhaustion signals, and POC gaps Adjustable information table displaying real-time metrics and current signals Heat ribbon visualization showing price-POC relationship intensity Multiple threshold settings for customizing signal sensitivity Export capability for use with separate panel indicators 🎨Visualization POC Connecting Lines: Color-coded lines showing POC levels with intensity based on velocity magnitude Heat Ribbon: Dynamic colored ribbon around price showing POC-price basis intensity Signal Markers: Clear exhaustion top/bottom signals with labeled shapes Information Table: Real-time display of POC value, velocity, acceleration, basis, persistence, and current signal status Color Gradients: Blue gradients for bullish conditions, orange gradients for bearish conditions 📖Usage Guidelines POC Calculation Settings POC Resolution (Price Bands): Default 20, Range 10-100. Controls the number of price bands used to estimate volume distribution within each bar Volume Weight Factor: Default 0.7, Range 0.1-1.0. Adjusts the influence of volume in POC calculation POC Smoothing: Default 3, Range 1-10. EMA smoothing period applied to the calculated POC to reduce noise Velocity Settings Velocity Lookback Period: Default 14, Range 5-50. Number of bars used to calculate POC velocity Acceleration Period: Default 7, Range 3-20. Period for calculating POC acceleration Velocity Significance Threshold: Default 0.5, Range 0.1-2.0. Minimum normalized velocity for continuation signals Persistence Settings Persistence Lookback: Default 5, Range 3-20. Number of bars examined for persistence score calculation Persistence Threshold: Default 0.7, Range 0.5-1.0. Minimum persistence score required for continuation signals Visual Settings Show POC Connecting Lines: Toggle display of colored lines connecting POC levels Show Heat Ribbon: Toggle display of colored ribbon showing POC-price relationship Ribbon Transparency: Default 70, Range 0-100. Controls transparency level of heat ribbon Alert Settings Enable Continuation Alerts: Toggle alerts for continuation pattern detection Enable Exhaustion Alerts: Toggle alerts for exhaustion pattern detection Enable POC Gap Alerts: Toggle alerts for significant POC gaps Gap Threshold: Default 2.0 ATR, Range 0.5-5.0. Minimum gap size to trigger alerts ✅Best Use Cases Identifying trend continuation opportunities when POC velocity aligns with price direction Spotting potential reversal points through exhaustion pattern detection Confirming breakout validity by monitoring POC gap behavior Adding volume-based context to traditional technical analysis Managing position sizing based on POC-price basis strength ⚠️Limitations POC calculations are estimations based on OHLC data, not true tick-by-tick volume distribution Effectiveness may vary in low-volume or highly volatile market conditions Requires complementary analysis tools for complete trading decisions Signal frequency may be lower in ranging markets compared to trending conditions Performance optimization needed for very short timeframes below 1-minute 💡What Makes This Unique Advanced Estimation Algorithm: Sophisticated method for calculating POC without requiring lower timeframe data Velocity-Based Analysis: Focus on POC movement dynamics rather than static levels Comprehensive Signal Framework: Integration of continuation, exhaustion, and gap detection in one indicator Dynamic Visual Feedback: Intensity-based color coding that adapts to market conditions Persistence Validation: Unique scoring system to filter signals based on directional consistency 🔬How It Works Volume Distribution Estimation: Divides each bar into configurable price bands for volume analysis Applies sophisticated weighting based on OHLC relationships and proximity to close Identifies the price level with maximum estimated volume as the POC Velocity and Acceleration Calculation: Measures POC rate of change over specified lookback periods Normalizes values using ATR for consistent cross-market performance Calculates acceleration as the rate of change of velocity Signal Generation Process: Combines trend direction analysis using EMA crossovers Applies velocity and persistence thresholds to filter signals Generates continuation, exhaustion, and gap alerts based on specific criteria 💡Note: This indicator provides estimated POC calculations based on available OHLC data and should be used in conjunction with other analysis methods. The velocity-based approach offers unique insights into market structure dynamics but requires proper risk management and complementary analysis for optimal trading decisions.
Pine Script®指标
由PhenLabs提供
ZLEMA Trend Index 2.0ZTI — ZLEMA Trend Index 2.0 (0–1000) Overview Price Mapped ZTI v2.0 - Enhanced Zero-Lag Trend Index. This indicator is a significant upgrade to the original ZTI v1.0, featuring enhanced resolution from 0-100 to 0-1000 levels for dramatically improved price action accuracy. The Price Mapped ZTI uses direct price-to-level mapping to eliminate statistical noise and provide true proportional representation of market movements. Key Innovation: Instead of statistical normalization, this version maps current price position within a user-defined lookback period directly to the ZTI scale, ensuring perfect correlation with actual price movements. I believe this is the best way to capture trends instead of directly on the charts using a plethora of indicators which introduces bad signals resulting in drawdowns. The RSI-like ZTI overbought and oversold lines filter valid trends by slicing through the current trading zone. Unlike RSI that can introduce false signals, the ZTI levels 1 to 1000 is faithfully mapped to the lowest to highest price in the current trading zone (lookback period in days) which can be changed in the settings. The ZTI line will never go off the beyond the ZTI levels in case of extreme trend continuation as the trading zone is constantly updated to reflect only the most recent bars based on lookback days. Core Features ✅ 10x Higher Resolution - 0-1000 scale provides granular movement detection ✅ Adjustable Trading Zone - Customizable lookback period from 1-50 days ✅ Price-Proportional Mapping - Direct correlation between price position and ZTI level ✅ Zero Statistical Lag - No rolling averages or standard deviation calculations ✅ Multi-Strategy Adaptability - Single parameter adjustment for different trading styles Trading Zone Optimization 📊 Lookback Period Strategies Short-term (1-3 days): Ultra-responsive to recent price action Perfect for scalping and day trading Tight range produces more sensitive signals Medium-term (7-14 days): Balanced view of recent trading range Ideal for swing trading Captures meaningful support/resistance levels Long-term (21-30 days): Broader market context Excellent for position trading Smooths out short-term market noise ⚡ Market Condition Adaptation Volatile Markets: Use shorter lookback (3-5 days) for tighter ranges Trending Markets: Use longer lookback (14-21 days) for broader context Ranging Markets: Use medium lookback (7-10 days) for clear boundaries 🎯 Timeframe Optimization 1-minute charts: 1-2 day lookback 5-minute charts: 2-5 day lookback Hourly charts: 7-14 day lookback Daily charts: 21-50 day lookback Trading Applications Scalping Setup (2-day lookback): Super tight range for quick reversals ZTI 800+ = immediate short opportunity ZTI 200- = immediate long opportunity Swing Trading Setup (10-day lookback): Meaningful swing levels captured ZTI extremes = high-probability reversal zones More stable signals, reduced whipsaws Advanced Usage 🔧 Real-Time Adaptability Trending days: Increase to 14+ days for broader perspective Range-bound days: Decrease to 3 days for tighter signals High volatility: Shorter lookback for responsiveness Low volatility: Longer lookback to avoid false signals 💡 Multi-Timeframe Approach Entry signals: Use 7-day ZTI on main timeframe Trend confirmation: Use 21-day ZTI on higher timeframe Exit timing: Use 3-day ZTI for precise exits 🌐 Session Optimization Asian session: Shorter lookback (3-5 days) for range-bound conditions London/NY session: Longer lookback (7-14 days) for trending conditions How It Works The indicator maps the current price position within the specified lookback period directly to a 0-1000 scale and plots it using ZLEMA (Zero Lag Exponential Moving Average) which has the least lag of the available popular moving averages: Price at recent high = ZTI at 1000 Price at recent low = ZTI at 1 Price at mid-range = ZTI at 500 This creates perfect proportional representation where every price movement translates directly to corresponding ZTI movement, eliminating the false signals common in traditional oscillators. This single, versatile indicator adapts to any market condition, timeframe, or trading style through one simple parameter adjustment, making it an essential tool for traders at every level. Credits ZLEMA techniques widely attributed to John Ehlers. Disclaimer This tool is for educational purposes only and is not financial advice. Backtest and forward‑test before live use, and always manage risk. Please note that I set this as closed source to prevent source code cloning by others, repackaging and republishing which results in multiple confusing choices of the same indicator.
Pine Script®指标
由Coinbank-MMXXV提供
1