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Fanfans极简原版优化版### 中英文双语总结（300字内） 中文：该指标为Fanfans极简原版优化版，基于RSI和ATR构建核心交易信号，新增趋势（EMA）、成交量、时间、价格位置多维度过滤，及动态ATR倍数调整功能。含同方向订单间隔限制、多级止盈止损（支持阈值触发），内置信号质量评分、标签标注与警报推送，可自定义过滤规则和显示样式，通过多维度筛选降低无效信号，提升短周期交易信号准确性。 English: This is an optimized version of Fanfans' minimalist indicator, building core trading signals based on RSI and ATR. It adds multi-dimensional filters (trend/EMA, volume, time, price position) and dynamic ATR multiplier adjustment, includes same-direction order interval limits, multi-level SL/TP (supporting threshold triggers), built-in signal quality scoring, label annotation and alert push. Customizable filter rules and display styles reduce invalid signals via multi-dimensional screening, improving short-term trading signal accuracy.
Pine Script® göstergesi
ms023999 tarafından
Enhanced ONH / ONL Auto Levels (Fixed Alerts)This script automatically identifies and plots the Overnight High (ONH) and Overnight Low (ONL)—two of the most important liquidity levels for intraday futures and index traders. The indicator scans the entire overnight session (default: 18:00–09:30 EST for ES) and records the highest wick and lowest wick formed during Globex. These levels are then projected into the regular trading session, giving traders clear reference points for potential reversals, breakouts, liquidity grabs, and high-probability retest setups. ONH/ONL levels act as magnet zones, liquidity pockets, and institutional decision points—commonly targeted during the opening drive and London/New York overlap. Whether price sweeps, reclaims, or breaks these levels, the reaction often creates reliable trade opportunities for scalpers and day traders.
Pine Script® göstergesi
Queet tarafından
Cloud Matrix [CongTrader]🚀 Cloud Matrix — Advanced Multi-Layer Ichimoku System Cloud Matrix is an enhanced trend-analysis system built on the public-domain Ichimoku Kinko Hyo methodology. This indicator delivers a multi-dimensional view of trend, momentum, and market structure, allowing traders to evaluate market conditions at a glance. Cloud Matrix is not a simple Ichimoku clone. It introduces advanced confirmation logic, multi-timeframe trend filtering, and a modern visual framework designed for today’s dynamic markets. 🔥 Key Features & Highlights 1️⃣ Smart Preset Engine (4 Modes) Choose from optimized presets for different markets and volatility levels: Traditional 9/26/52 Crypto Fast 10/30/60 Crypto Medium 20/60/120 Custom Mode → Fast, adaptable, and beginner-friendly. 2️⃣ Advanced Trend Confirmation Engine Cloud Matrix uses a 5-factor scoring system to filter high-quality signals: Tenkan vs Kijun Price vs Cloud Cloud Twist Chikou Position Close vs Kijun A bullish/bearish signal only triggers when multiple Ichimoku conditions align, reducing noise dramatically. 3️⃣ Higher-Timeframe EMA200 Filter One of the signature strengths of Cloud Matrix: EMA200 from a higher timeframe Helps you follow the dominant macro trend Avoids counter-trend traps Ideal for swing and position traders 4️⃣ Intelligent Auto Signals The indicator includes refined and clean signals for: Bullish / Bearish TK Cross Bullish / Bearish Kumo Breakout All signals support: Labels Alerts “Alert on Close” mode to avoid repaint-related confusion 5️⃣ Enhanced Kumo Cloud Visualization Adjustable opacity (strong / soft) Clear bullish/bearish cloud shading Improved readability on fast markets 6️⃣ Real-Time Market State Dashboard A compact dashboard shows all key Ichimoku conditions: Price vs Cloud Cloud Twist (Bullish/Bearish) Tenkan–Kijun Relationship Chikou Status HTF EMA Trend Active Preset → Designed for instant market diagnostics. 🎯 How Traders Use Cloud Matrix Perfect for: Trend following Swing trading Crypto, Stocks, Forex Early breakout detection Filtering low-quality setups 📌 Suggested Usage Bullish Bias When: Price is above the Cloud Cloud Twist is bullish Tenkan crosses above Kijun Chikou is above price HTF EMA200 is bullish Bearish Bias When: Opposite conditions apply. ⚠️ Important Note This indicator is for analysis and educational purposes only. It does not provide financial advice or guaranteed trading results. Ichimoku concepts belong to the public domain; this is a modernized expansion built for study and research. ✍️ Author CongTrader – 2025 Designed to help traders see the market through a multi-layered, structured lens..
Pine Script® göstergesi
CongTrader_ tarafından
MACD Momentum Pro MACD Momentum Pro is an enhanced version of the classic MACD designed to help traders identify momentum strength with far greater clarity. In addition to the traditional MACD line, Signal line, and histogram, this tool introduces two new momentum-intensity alerts: • Strong Green – bullish momentum accelerating above the zero line • Strong Red – bearish momentum accelerating below the zero line These conditions allow traders to quickly spot when market pressure is truly strengthening, reducing noise and improving decision-making in trending environments. The indicator also includes real-time alerts for: • MACD/Signal crosses (bullish & bearish) • MACD zero-line crosses • Shifts between rising/falling histogram states All moving averages (EMA or SMA) are fully customizable, and the visual histogram automatically adapts color to reflect momentum transitions. Whether you are trading breakouts, trend reversals, or momentum continuation setups, this upgraded MACD version provides a clearer, more actionable view of market strength—while keeping the original MACD logic intact.
Pine Script® göstergesi
LionLabs tarafından
ATR Stop Loss Finder (Strict Breakout Mode)Title: ATR Stop Loss Finder (Strict Breakout Mode) Description: Volatility-Based Risk Management: Generates dynamic trailing stop-loss lines for both Long (Lower Line) and Short (Upper Line) positions based on ATR volatility. Strict Breakout Detection: Features a unique "Strict Breakout" logic that highlights trend acceleration. It visually marks whenever the Long SL breaks a historical high or the Short SL breaks a historical low over a user-defined lookback period (e.g., 50 bars). Visual Signals: Automatically plots Red Circles for bullish SL breakouts (New Highs) and Blue Circles for bearish SL breakdowns (New Lows), making strong momentum shifts easy to spot. Real-Time Dashboard: Includes an informative table displaying current ATR and SL price levels for quick reference.
Pine Script® göstergesi
jjf495932819 tarafından
EMA & SMA StackA clean, lightweight trend-structure tool that overlays six moving averages on price so you can instantly see direction, momentum, and trend health. Includes 3 Exponential Moving Averages with adjustable lengths 3 Simple Moving Averages with adjustable lengths Thin, color-coded lines for fast visual clarity Default layout: 8 EMA (red), 21 EMA (orange), 34 EMA (yellow), 50 SMA (green), 100 SMA (blue), 200 SMA (purple) How to use When faster EMAs are above slower EMAs and price is above all lines, trend strength is bullish. When faster EMAs fall below slower SMAs and price is under all lines, trend strength is bearish. Tight stacking = compression and potential breakout zones. Wide separation = strong trend or exhaustion risk. Why it helps This removes guesswork. You get immediate confirmation of trend direction, support and resistance, and momentum shift on any timeframe. Minimal clutter. Maximum signal.
Pine Script® göstergesi
ThetaDaddy tarafından
Daily Tracker Highs LowsSolid lines mark the most recent daily highs/lows that have not been crossed yet (you choose how many per side). Dashed lines mark daily highs/lows from the last N days that have been crossed since—use as secondary S/R or “magnet” levels. White lines show today’s high/low updating in real time. Tune settings to pick how many uncrossed levels per side (1–10), the lookback window for crossed levels, and an optional cap per side.
Pine Script® göstergesi
marcosmaps tarafından
Anand Bollinger Bands - Linear Regression SlopeSummary Bollinger Bands show price volatility using SMA ± standard deviation Linear Regression calculates the mathematical trend through the middle line Slope comparison (current vs. previous) determines if trend is rising or falling Color changes based on that trend: Green = up, Red = down Uses same period for both BB and slope = everything stays synchronized The result: A visual indicator that shows you not just where price is relative to volatility, but also which direction the trend is actually moving!
Pine Script® göstergesi
CA_Anand_kumar tarafından
Fanfans结构+极简合并增强版V2 中文：该指标整合Fanfans结构、高斯GWMA、动态摆动VWAP、MACD及极简交易信号，内置结构/GWMA/VWAP/EMA多维度过滤、成交量确认、动态ATR等优化功能。支持多空信号标注、止损止盈分层设置、信号质量评分，搭配图表信息面板与多级别警报共振机制，适用于1分钟等短周期交易，兼顾信号灵敏度与准确性。 English: This indicator integrates Fanfans structure, Gaussian GWMA, dynamic swing VWAP, MACD, and simple trading signals. It features multi-dimensional filters (structure/GWMA/VWAP/EMA), volume confirmation, dynamic ATR optimization. Supporting long/short signal labeling, layered SL/TP settings, signal quality scoring, it comes with a chart info panel and multi-level alert resonance. Suitable for short-term trading (e.g., 1-minute timeframe), balancing signal sensitivity and accuracy.
Pine Script® göstergesi
ms023999 tarafından
PEG RSI [Auto EPS Growth]The PEG RSI is a hybrid indicator that combines fundamental valuation with technical momentum. It applies the Relative Strength Index (RSI) directly to the Price/Earnings-to-Growth (PEG) Ratio. Unlike traditional PEG indicators that require manual input for growth rates, this script automatically calculates the Compound Annual Growth Rate (CAGR) of Earnings Per Share (EPS) based on historical data. Key Features - Auto-Calculated Growth: Uses historical TTM Earnings Per Share (EPS) to calculate the CAGR over a user-defined period (Default: 4 years). - Dynamic Valuation: Converts the static PEG ratio into an oscillator (RSI) to identify relative valuation extremes. - Trend & Momentum: Visualizes the momentum of the PEG ratio relative to its own history. Educational Case Study This indicator is designed for educational purposes and research. Instead of relying on fixed overbought or oversold levels, users are encouraged to study the correlation between the PEG RSI and price action independently. - Observe how the price reacts when the PEG RSI reaches upper or lower extremes. - Different stocks may respect different RSI zones based on their growth stability. - Use this tool to analyze how market valuation momentum shifts over time. Settings: - Years for CAGR Growth: Timeframe to calculate EPS growth (Default: 4 years). - RSI Length: Lookback period for the RSI calculation (Default: 14). Note: This indicator works best on stocks with a consistent history of earnings. It requires financial data to function (will not work on assets without EPS like Crypto or Forex).
Pine Script® göstergesi
waranyutrkm tarafından
Daily Buy Signal – RSI/EMA21 Daily Buy Signal – RSI/EMA21 A simple technical signal that identifies potential daily buy opportunities using RSI and EMA21 alignment. This script generates a daily buy signal when momentum and trend strength align. The signal triggers when the price closes above the 21-period EMA and the RSI(14) crosses above the 50 level, or when both the RSI stays above 50 and the price shifts from closing below the EMA21 to closing above it. A label is plotted below the candle, and the script includes an alert condition so users can receive real-time notifications.
Pine Script® göstergesi
Elias876 tarafından
Advanced Breakout System v2.0Advanced Breakout System v2.0 Developed by: Mohammed Bedaiwi This script hunts for high-probability breakouts by combining price consolidation zones, volume spikes vs. average volume, smart money flow (OBV), and a Momentum Override for explosive moves that skip consolidation. Additionally, it automatically identifies and plots Support and Resistance levels with price labels to help you visualize market structure. The system follows a "Watch & Confirm" logic: it first prints a WATCH setup, then a BUY only if price confirms strength. 💡 JUSTIFICATION OF CONCEPTS (MASHUP & ORIGINALITY) This script is an original mashup combining several analytical concepts to address common breakout failures: Volatility Compression Engine: Uses built-in functions like ta.highest() and ta.lowest() to mathematically define the setup phase where price volatility is compressed below a user-defined threshold. Volume Spike Confirmation: The breakout must be confirmed by a volume increase greater than a moving average of volume, signaling strong market interest. Smart Volume Filter (OBV): This is the key component. By checking if ta.obv is above its own Moving Average, we confirm that accumulation has been occurring during the consolidation period, suggesting institutional positioning before the price break. Multi-Exit Risk System: Employs dynamic exits (EMA cross, volume dump, bearish pattern) instead of static stop-losses to manage risk adaptively based on real-time market action. Market Structure Visualization: The script also includes a Support & Resistance engine to plot key swing pivots and price labels for visual context. ✅ STRATEGY RESULTS & POLICY COMPLIANCE To ensure non-misleading and transparent backtesting results, this strategy is published with the following fully compliant properties: Dataset Compliance: The backtest is performed on the CMTL Daily (1D) chart across a long history, generating 201 total trades. This significantly exceeds the minimum requirement of 100 trades, providing a robust test dataset. Risk Control: The strategy uses a conservative order size set to 2% of equity (default_qty_value=2), strictly adhering to the sustainable risk recommendation of 5-10% of equity per trade. Transaction Costs: Realistic trading conditions are modeled using 0.07% commission and 3 ticks slippage to prevent the overestimation of profitability. ⚙️ VISUAL GUIDE & SIGNAL LOGIC Key Color Legend (Visual Guide): WATCH – Setup (Yellow Arrow Down): Potential breakout setup detected. BUY – Confirmation (Green Arrow Up): Confirmed breakout, triggered when price trades above the high of the WATCH candle. SELL – Break (Orange Arrow): Short-term trend weakness, triggered when price closes below the Fast EMA (9). SELL – Dump (Dark Red Arrow): Distribution / volume dump, triggered by a bearish candle with abnormally high volume. SELL – Pattern (Purple Arrow): Bearish price-action pattern (such as a bearish engulfing). Support & Resistance Lines (Red/Green): Small horizontal lines plotted at key swing points with exact price labels. ⌨️ INPUTS (DEFAULT SETTINGS) Entry settings: Consolidation Lookback (default 20) = bars used to detect consolidation. Consolidation Range % (default 12%) = max allowed range size. Volume Spike Multiplier (default 1.2) = factor above average volume to count as a spike. Force Signal on Big Moves (default ON) = forces a WATCH signal on high-momentum moves. Exit settings: Enable Fast Exit (EMA 9) toggles the SELL – Break signal. Dump Volume Multiplier defines what counts as “dump” volume. Support & Resistance: Adjustable Pivot Left/Right bars control the sensitivity of the support and resistance lines. ⚠️ Disclaimer Trading involves significant risk of loss. This script is for educational and informational purposes only and is not financial advice or a recommendation to buy or sell any asset. BUY and SELL signals are rule-based and derived from historical behavior and do not guarantee future performance. Always use your own analysis and risk management. This is an open-source strategy; users are encouraged to test it across different symbols and timeframes.
Pine Script® stratejisi
mbedaiwi2 tarafından
Squeeze Momentum OmniViewSqueeze Momentum OmniView+ is an enhanced and modernized version of the classic Squeeze Momentum Indicator by LazyBear, rebuilt from the ground up in Pine Script v6. This upgraded edition introduces OmniView color-mapping, adaptive histogram scaling, extreme detection, heat-zone alerts, and dynamic fire/ice icons, all fully synchronized with your selected visualization mode. Key Features 1. OmniView Color Engine (Exact Price-State Matching) Reproduces the full OmniView color logic (aqua → yellow → red), tracking market compression, expansion, and directional strength using a seamless multi-gradient system. 2. Dual Histogram Modes Choose how the histogram is normalized: Price-State Mode: Colors reflect price position within its recent range. Self-Normalized Mode: Colors adapt to the histogram’s own momentum curve. Both modes automatically adjust alerts, extremes, and icons. 3. Enhanced Squeeze Logic The script includes the classic squeeze states (ON / OFF / Neutral) with clean visual dots and improved logic for precise state transitions. 4. Adaptive Extreme Detection (Upper & Lower Extremes) Detects when price or momentum sets new highs/lows according to the active mode. Automatically draws 🔥 fire labels near upper extremes and ❄️ ice labels near lower extremes, with: Adaptive or fixed offsets Customizable sizes Optional dimming on momentum fade Icon colors matching the histogram 5. Full Alert Suite Includes alerts for: New Upper / Lower Extremes Heat-Zone Crossings (25%, 50%, 75%) Momentum Turning Up / Down Zero-Line Crossovers Squeeze ON / OFF All alert conditions adapt dynamically to the mode selected. 6. Clean, modern, and fully customizable Every visual element—colors, transparency, icon sizing, offsets, squeeze dots, fades—can be adjusted from the settings panel. What This Indicator Helps You See Momentum acceleration and deceleration Market compression/expansion phases Heat levels in the current price context Momentum extremes that often signal turning points Trend continuation or exhaustion patterns High-precision squeeze entries with visual clarity Designed For Traders looking for a more intelligent version of Squeeze Momentum with: Better visual clarity Stronger adaptive behavior More actionable alerts More information per bar without clutter A special thanks to LazyBear, the original author of the Squeeze Momentum engine. This script is not affiliated with or endorsed by him, but it extends his outstanding contribution to the TradingView community.
Pine Script® göstergesi
LionLabs tarafından
ADR% / ATR / Dynamic LoD–HoD TableThis indicator displays a clean data table showing ADR%, ATR, and a dynamic LoD/HoD distance value based on daily trend conditions. When price is above the 21-day or 50-day moving average, the indicator shows the distance from the Low of Day. When price is below BOTH daily moving averages, it automatically switches to showing distance from the High of Day. The table updates in real-time and gives a fast, volatility-based view of where price sits inside the day’s range. Features • ADR% (Average Daily Range Percentage) • ATR (Average True Range) • Automatic LoD → HoD switching based on daily trend • Customizable colors and layout • Clean, space-efficient table format • Designed for intraday and volatility-focused traders
Pine Script® göstergesi
InsiderTradingCuh tarafından
KernelFunctionsLibrary "KernelFunctions" This library provides non-repainting kernel functions for Nadaraya-Watson estimator implementations. This allows for easy substition/comparison of different kernel functions for one another in indicators. Furthermore, kernels can easily be combined with other kernels to create newer, more customized kernels. rationalQuadratic(_src, _lookback, _relativeWeight, startAtBar)   Rational Quadratic Kernel - An infinite sum of Gaussian Kernels of different length scales.   Parameters:      _src (float) : The source series.      _lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.      _relativeWeight (simple float) : Relative weighting of time frames. Smaller values resut in a more stretched out curve and larger values will result in a more wiggly curve. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel.      startAtBar (simple int)   Returns: yhat The estimated values according to the Rational Quadratic Kernel. gaussian(_src, _lookback, startAtBar)   Gaussian Kernel - A weighted average of the source series. The weights are determined by the Radial Basis Function (RBF).   Parameters:      _src (float) : The source series.      _lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.      startAtBar (simple int)   Returns: yhat The estimated values according to the Gaussian Kernel. periodic(_src, _lookback, _period, startAtBar)   Periodic Kernel - The periodic kernel (derived by David Mackay) allows one to model functions which repeat themselves exactly.   Parameters:      _src (float) : The source series.      _lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.      _period (simple int) : The distance between repititions of the function.      startAtBar (simple int)   Returns: yhat The estimated values according to the Periodic Kernel. locallyPeriodic(_src, _lookback, _period, startAtBar)   Locally Periodic Kernel - The locally periodic kernel is a periodic function that slowly varies with time. It is the product of the Periodic Kernel and the Gaussian Kernel.   Parameters:      _src (float) : The source series.      _lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.      _period (simple int) : The distance between repititions of the function.      startAtBar (simple int)   Returns: yhat The estimated values according to the Locally Periodic Kernel.
Pine Script® kütüphanesi
TFU_Tradewise tarafından
MLExtensionsLibrary "MLExtensions" A set of extension methods for a novel implementation of a Approximate Nearest Neighbors (ANN) algorithm in Lorentzian space. normalizeDeriv(src, quadraticMeanLength)   Returns the smoothed hyperbolic tangent of the input series.   Parameters:      src (float) : The input series (i.e., the first-order derivative for price).      quadraticMeanLength (int) : The length of the quadratic mean (RMS).   Returns: nDeriv The normalized derivative of the input series. normalize(src, min, max)   Rescales a source value with an unbounded range to a target range.   Parameters:      src (float) : The input series      min (float) : The minimum value of the unbounded range      max (float) : The maximum value of the unbounded range   Returns: The normalized series rescale(src, oldMin, oldMax, newMin, newMax)   Rescales a source value with a bounded range to anther bounded range   Parameters:      src (float) : The input series      oldMin (float) : The minimum value of the range to rescale from      oldMax (float) : The maximum value of the range to rescale from      newMin (float) : The minimum value of the range to rescale to      newMax (float) : The maximum value of the range to rescale to   Returns: The rescaled series getColorShades(color)   Creates an array of colors with varying shades of the input color   Parameters:      color (color) : The color to create shades of   Returns: An array of colors with varying shades of the input color getPredictionColor(prediction, neighborsCount, shadesArr)   Determines the color shade based on prediction percentile   Parameters:      prediction (float) : Value of the prediction      neighborsCount (int) : The number of neighbors used in a nearest neighbors classification      shadesArr (array) : An array of colors with varying shades of the input color   Returns: shade Color shade based on prediction percentile color_green(prediction)   Assigns varying shades of the color green based on the KNN classification   Parameters:      prediction (float) : Value (int|float) of the prediction   Returns: color color_red(prediction)   Assigns varying shades of the color red based on the KNN classification   Parameters:      prediction (float) : Value of the prediction   Returns: color tanh(src)   Returns the the hyperbolic tangent of the input series. The sigmoid-like hyperbolic tangent function is used to compress the input to a value between -1 and 1.   Parameters:      src (float) : The input series (i.e., the normalized derivative).   Returns: tanh The hyperbolic tangent of the input series. dualPoleFilter(src, lookback)   Returns the smoothed hyperbolic tangent of the input series.   Parameters:      src (float) : The input series (i.e., the hyperbolic tangent).      lookback (int) : The lookback window for the smoothing.   Returns: filter The smoothed hyperbolic tangent of the input series. tanhTransform(src, smoothingFrequency, quadraticMeanLength)   Returns the tanh transform of the input series.   Parameters:      src (float) : The input series (i.e., the result of the tanh calculation).      smoothingFrequency (int)      quadraticMeanLength (int)   Returns: signal The smoothed hyperbolic tangent transform of the input series. n_rsi(src, n1, n2)   Returns the normalized RSI ideal for use in ML algorithms.   Parameters:      src (float) : The input series (i.e., the result of the RSI calculation).      n1 (simple int) : The length of the RSI.      n2 (simple int) : The smoothing length of the RSI.   Returns: signal The normalized RSI. n_cci(src, n1, n2)   Returns the normalized CCI ideal for use in ML algorithms.   Parameters:      src (float) : The input series (i.e., the result of the CCI calculation).      n1 (simple int) : The length of the CCI.      n2 (simple int) : The smoothing length of the CCI.   Returns: signal The normalized CCI. n_wt(src, n1, n2)   Returns the normalized WaveTrend Classic series ideal for use in ML algorithms.   Parameters:      src (float) : The input series (i.e., the result of the WaveTrend Classic calculation).      n1 (simple int)      n2 (simple int)   Returns: signal The normalized WaveTrend Classic series. n_adx(highSrc, lowSrc, closeSrc, n1)   Returns the normalized ADX ideal for use in ML algorithms.   Parameters:      highSrc (float) : The input series for the high price.      lowSrc (float) : The input series for the low price.      closeSrc (float) : The input series for the close price.      n1 (simple int) : The length of the ADX. regime_filter(src, threshold, useRegimeFilter)   Parameters:      src (float)      threshold (float)      useRegimeFilter (bool) filter_adx(src, length, adxThreshold, useAdxFilter)   filter_adx   Parameters:      src (float) : The source series.      length (simple int) : The length of the ADX.      adxThreshold (int) : The ADX threshold.      useAdxFilter (bool) : Whether to use the ADX filter.   Returns: The ADX. filter_volatility(minLength, maxLength, useVolatilityFilter)   filter_volatility   Parameters:      minLength (simple int) : The minimum length of the ATR.      maxLength (simple int) : The maximum length of the ATR.      useVolatilityFilter (bool) : Whether to use the volatility filter.   Returns: Boolean indicating whether or not to let the signal pass through the filter. backtest(high, low, open, startLongTrade, endLongTrade, startShortTrade, endShortTrade, isEarlySignalFlip, maxBarsBackIndex, thisBarIndex, src, useWorstCase)   Performs a basic backtest using the specified parameters and conditions.   Parameters:      high (float) : The input series for the high price.      low (float) : The input series for the low price.      open (float) : The input series for the open price.      startLongTrade (bool) : The series of conditions that indicate the start of a long trade.      endLongTrade (bool) : The series of conditions that indicate the end of a long trade.      startShortTrade (bool) : The series of conditions that indicate the start of a short trade.      endShortTrade (bool) : The series of conditions that indicate the end of a short trade.      isEarlySignalFlip (bool) : Whether or not the signal flip is early.      maxBarsBackIndex (int) : The maximum number of bars to go back in the backtest.      thisBarIndex (int) : The current bar index.      src (float) : The source series.      useWorstCase (bool) : Whether to use the worst case scenario for the backtest.   Returns: A tuple containing backtest values init_table()   init_table()   Returns: tbl The backtest results. update_table(tbl, tradeStatsHeader, totalTrades, totalWins, totalLosses, winLossRatio, winrate, earlySignalFlips)   update_table(tbl, tradeStats)   Parameters:      tbl (table) : The backtest results table.      tradeStatsHeader (string) : The trade stats header.      totalTrades (float) : The total number of trades.      totalWins (float) : The total number of wins.      totalLosses (float) : The total number of losses.      winLossRatio (float) : The win loss ratio.      winrate (float) : The winrate.      earlySignalFlips (float) : The total number of early signal flips.   Returns: Updated backtest results table.
Pine Script® kütüphanesi
TFU_Tradewise tarafından
CEF (Chaos Theory Regime Oscillator)Chaos Theory Regime Oscillator This script is open to the community. What is it? The CEF (Chaos Entropy Fusion) Oscillator is a next-generation "Regime Analysis" tool designed to replace traditional, static momentum indicators like RSI or MACD. Unlike standard oscillators that only look at price changes, CEF analyzes the "character" of the market using concepts from Chaos Theory and Information Theory. It combines advanced mathematical engines (Hurst Exponent, Entropy, VHF) to determine whether a price movement is a real trend or just random noise. It uses a novel "Adaptive Normalization" technique to solve scaling problems common in advanced indicators, ensuring the oscillator remains sensitive yet stable across all assets (Crypto, Forex, Stocks). What It Promises: Intelligent Filtering: Filters out false signals in sideways (volatile) markets using the Hurst Base to measure trend continuity. Dynamic Adaptation: Automatically adapts to volatility. Thanks to trend memory, it doesn't get stuck at the top during uptrends or at the bottom during downtrends. No Repainting: All signals are confirmed at the close of the bar. They don't repaint or disappear. What It Doesn't Promise: Magic Wand: It's a powerful analytical tool, not a crystal ball. It determines the regime, but risk management is up to the investor. Late-Free Holy Grail: It deliberately uses advanced correction algorithms (WMA/SMA) to provide stability and filter out noise. Speed ​​is sacrificed for accuracy. Which Concepts Are Used for Which Purpose? CEF is built on proven mathematical concepts while creating a unique "Fusion" mechanism. These are not used in their standard forms, but are remixed to create a consensus engine: Hurst Exponent: Used to measure the "memory" of the time series. Tells the oscillator whether there is a probability of the trend continuing or reversing to the mean. Vertical Horizontal Filter (VHF): Determines whether the market is in a trend phase or a congestion phase. Shannon Entropy: Measures the "irregularity" or "unpredictability" of market data to adjust signal sensitivity. Adaptive Normalization (Key Innovation): Instead of fixed limits, the oscillator dynamically scales itself based on recent historical performance, solving the "flat line" problem seen in other advanced scripts. Original Methodology and Community Contribution This algorithm is a custom synthesis of public domain mathematical theories. The author's unique contribution lies in the "Adaptive Normalization Logic" and the custom weighting of Chaos components to filter momentum. Why Public Domain? Standard indicators (RSI, MACD) were developed for the markets of the 1970s. Modern markets require modern mathematics. This script is presented to the community to demonstrate how Regime Analysis can improve trading decisions compared to static tools. What Problems Does It Solve? Problem 1: The "Stagnant Market" Trap CEF Solution: While the RSI gives false signals in a sideways market, CEF's Hurst/VHF filter suppresses the signal, essentially making the histogram "off" (or weak) during noise. Problem 2: The "Overbought" Fallacy CEF Solution: In a strong trend (Pump/Dump), traditional oscillators get stuck at 100 or 0. CEF uses "Trend Memory" to understand that an overbought price is not a reversal signal but a sign of trend strength, and keeps the signal green/red instead of reversing it prematurely. Problem 3: Visual Confusion CEF Solution: Instead of multiple lines, it presents a single, color-coded histogram featuring only prominent "Smart Circles" at high-probability reversal points. Automation Ready: Custom Alerts CEF is designed for both manual trading and automation. Smart Buy/Sell Circles: Visual signals that only appear when trend filters are aligned with momentum reversals. Deviation Labels: Automatically detects and labels structural divergences between price and entropy. Disclaimer: This indicator is for educational purposes only. Past performance does not guarantee future results. Always practice appropriate risk management.
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