Cyber Monday高達80%折扣

指標和策略

FVG + Bollinger + Toggles + Swing H&L (Taken/Close modes)This indicator combines multiple advanced market-structure tools into one unified system. It detects A–C Fair Value Gaps (FVG) and plots them as dynamic boxes projected a fixed number of bars forward. Each bullish or bearish FVG updates in real time and “closes” once price breaks through the opposite boundary. The indicator also includes Bollinger Bands based on EMA-50 with adjustable deviation settings for volatility context. Swing Highs and Swing Lows are identified using pivot logic and are drawn as dynamic lines that change color once taken out. You can choose whether swings end on a close break or on any touch/violation of the level. All visual elements—FVGs, Bollinger Bands, and Swing Lines—can be individually toggled on or off from the settings panel. A time-window session box is included, allowing you to highlight a custom intraday window based on your selected timezone. The session box automatically tracks the high and low of the window and locks the final range once the window closes. Overall, the tool is designed for traders who want a structured, multi-layered view of liquidity, volatility, and intraday timing.
Pine Script®指標
由Menash100提供
Volume Profile S/R + OB/OS + BreaksAs a support resistance trader I have created this indicator that shows SR lines. RSI over bought and over sold. I also added momentum candle. It's easy to use. The arrows show over bought and over sold, that's where I start to be interested. Confirmation is if we are near a support/resistance area. shown as a red/green line. Don't just trade the RSI, Be patient and only take the perfekt setups. I't clean, it's simple it works.
Pine Script®指標
由TheHeikinAshitrader提供
Equal Highs/Lows Multi-Pivot [Julio]Equal Highs/Lows Multi-Pivot Description A sophisticated multi-timeframe pivot analysis tool that detects and highlights equal highs and equal lows across four different pivot lengths simultaneously. This indicator identifies price levels where the market creates identical extremes, a powerful signal of institutional support/resistance and potential reversal or breakout zones. How It Works Four Independent Pivot Streams Pivot 1 (Intraday - 2 bars): Ultra-fast level detection for scalpers Pivot 2 (Session - 4 bars): Short-term swing levels Pivot 3 (Daily - 6 bars): Medium-term structural levels Pivot 4 (Weekly - 9 bars): Long-term institutional levels Equal High (EQH) Detection Compares consecutive swing highs and draws a line when two highs are nearly identical within a defined threshold. The indicator uses ATR-based confluence to determine "equality," filtering out noise while catching true market structure. Equal Low (EQL) Detection Same logic applied to swing lows, identifying support zones where price repeatedly fails to break below previous lows. Key Features Four Simultaneous Timeframes: Analyze intraday, session, daily, and weekly structures all on one chart ATR-Based Confluence Threshold: Automatically adjusts sensitivity based on current volatility (no fake signals) Color-Coded Levels: Each pivot length has distinct colors for instant visual identification Highs: Red, Orange, Yellow, Fuchsia Lows: Green, Blue, Aqua, Purple Confirmation Mode: Optional setting to wait for full pivot confirmation before marking levels Customizable Alert Zones: Toggle individual pivot lengths on/off to reduce clutter Smart Label Positioning: Labels auto-center between the two equal pivots for clarity Ideal For Swing traders tracking support/resistance across multiple timeframes Scalpers identifying micro-structure for quick entries and exits Market structure analysts studying institutional price action patterns Multi-timeframe traders needing confluence from intraday to weekly levels Anyone trading 1-minute to 4-hour charts Trading Applications Identify strong support/resistance zones: Equal levels = confirmed institutional levels Confirm trend reversals: Multiple equal lows = strong accumulation zone; multiple equal highs = distribution Plan entries with precision: Enter near equal levels for higher probability setups Detect liquidity concentration: Where price repeatedly tests the same level Multi-timeframe confluence: Look for equal levels across multiple pivot lengths for ultra-strong zones How to Use Identify the equal levels: Color-coded lines instantly show where price creates matching extremes Check for confluence: Strong setups occur where multiple pivot lengths align Wait for price action: Watch for breakouts through equal levels or reversals at these zones Enter with structure: Use equal levels as entry/exit triggers combined with your trading methodology Manage with confidence: These levels mark institutional decision points Customization Options Adjust pivot lengths to match your preferred timeframe structure Set ATR threshold sensitivity (lower = stricter equality, higher = more signals) Toggle confirmation mode for additional filter Enable/disable individual pivot streams to reduce visual clutter Customize colors to match your chart theme Default Settings Optimized For NASDAQ futures and liquid forex pairs Intraday and swing trading (1-minute to 4-hour charts) Smart Money / ICT trading methodologies Volatility-adjusted confluence detection
Pine Script®指標
由julioperez75955提供
ADX Forecast Colorful [DiFlip]ADX Forecast Colorful Introducing one of the most advanced ADX indicators available — a fully customizable analytical tool that integrates forward-looking forecasting capabilities. ADX Forecast Colorful is a scientific evolution of the classic ADX, designed to anticipate future trend strength using linear regression. Instead of merely reacting to historical data, this indicator projects the future behavior of the ADX, giving traders a strategic edge in trend analysis. ⯁ Real-Time ADX Forecasting For the first time, a public ADX indicator incorporates linear regression (least squares method) to forecast the future behavior of ADX. This breakthrough approach enables traders to anticipate trend strength changes based on historical momentum. By applying linear regression to the ADX, the indicator plots a projected trendline n periods ahead — helping users make more accurate and timely trading decisions. ⯁ Highly Customizable The indicator adapts seamlessly to any trading style. It offers a total of 26 long entry conditions and 26 short entry conditions, making it one of the most configurable ADX tools on TradingView. Each condition is fully adjustable, enabling the creation of statistical, quantitative, and automated strategies. You maintain full control over the signals to align perfectly with your system. ⯁ Innovative and Science-Based This is the first public ADX indicator to apply least-squares predictive modeling to ADX dynamics. Technically, it embeds machine learning logic into a traditional trend-strength indicator. Using linear regression as a predictive engine adds powerful statistical rigor to the ADX, turning it into an intelligent, forward-looking signal generator. ⯁ Scientific Foundation: Linear Regression Linear regression is a fundamental method in statistics and machine learning used to model the relationship between a dependent variable y and one or more independent variables x. The basic formula for simple linear regression is: y = β₀ + β₁x + ε Where: y  = predicted value (e.g., future ADX) x  = explanatory variable (e.g., bar index or time) β₀ = intercept β₁ = slope (rate of change) ε   = random error term The goal is to estimate β₀ and β₁ by minimizing the sum of squared errors. This is achieved using the least squares method, ensuring the best linear fit to historical data. Once the coefficients are calculated, the model extends the regression line forward, generating the ADX projection based on recent trends. ⯁ Least Squares Estimation To minimize the error, the regression coefficients are calculated as: β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²) β₀ = ȳ - β₁x̄ Where: Σ = summation x̄ and ȳ = means of x and y i ranges from 1 to n (number of data points) These formulas provide the best linear unbiased estimator under Gauss-Markov conditions — assuming constant variance and linearity. ⯁ Linear Regression in Machine Learning Linear regression is a foundational algorithm in supervised learning. Its power in producing quantitative predictions makes it essential in AI systems, predictive analytics, time-series forecasting, and automated trading. Applying it to the ADX essentially places an intelligent forecasting engine inside a classic trend tool. ⯁ Visual Interpretation Imagine an ADX time series like this: Time → ADX  → The regression line smooths these values and projects them n periods forward, creating a predictive trajectory. This forecasted ADX line can intersect with the actual ADX, offering smarter buy and sell signals. ⯁ Summary of Scientific Concepts Linear Regression: Models variable relationships with a straight line. Least Squares: Minimizes prediction errors for best fit. Time-Series Forecasting: Predicts future values using historical data. Supervised Learning: Trains models to predict outcomes from inputs. Statistical Smoothing: Reduces noise and highlights underlying trends. ⯁ Why This Indicator Is Revolutionary Scientifically grounded: Based on rigorous statistical theory. Unprecedented: First public ADX using least-squares forecast modeling. Smart: Uses machine learning logic. Forward-Looking: Generates predictive, not just reactive, signals. Customizable: Flexible for any strategy or timeframe. ⯁ Conclusion By merging ADX and linear regression, this indicator enables traders to predict market momentum rather than merely follow it. ADX Forecast Colorful is not just another indicator — it’s a scientific leap forward in technical analysis. With 26 fully configurable entry conditions and smart forecasting, this open-source tool is built for creating cutting-edge quantitative strategies. ⯁ Example of simple linear regression with one independent variable This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables. ⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x) This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component. ⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models. ⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model. ⯁ Result of fitting a set of data points with a quadratic function This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line. ⯁ What is the ADX? The Average Directional Index (ADX) is a technical analysis indicator developed by J. Welles Wilder. It measures the strength of a trend in a market, regardless of whether the trend is up or down. The ADX is an integral part of the Directional Movement System, which also includes the Plus Directional Indicator (+DI) and the Minus Directional Indicator (-DI). By combining these components, the ADX provides a comprehensive view of market trend strength. ⯁ How to use the ADX? The ADX is calculated based on the moving average of the price range expansion over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and has three main zones: Strong Trend: When the ADX is above 25, indicating a strong trend. Weak Trend: When the ADX is below 20, indicating a weak or non-existent trend. Neutral Zone: Between 20 and 25, where the trend strength is unclear. ⯁ Entry Conditions Each condition below is fully configurable and can be combined to build precise trading logic. 📈 BUY 🅰️  Signal Validity: The signal will remain valid for X bars . 🅰️  Signal Sequence: Configurable as AND or OR . 🅰️ +DI > -DI 🅰️ +DI < -DI 🅰️ +DI > ADX 🅰️ +DI < ADX 🅰️ -DI > ADX 🅰️ -DI < ADX 🅰️ ADX > Threshold 🅰️ ADX < Threshold 🅰️ +DI > Threshold 🅰️ +DI < Threshold 🅰️ -DI > Threshold 🅰️ -DI < Threshold 🅰️ +DI (Crossover) -DI 🅰️ +DI (Crossunder) -DI 🅰️ +DI (Crossover) ADX 🅰️ +DI (Crossunder) ADX 🅰️ +DI (Crossover) Threshold 🅰️ +DI (Crossunder) Threshold 🅰️ -DI (Crossover) ADX 🅰️ -DI (Crossunder) ADX 🅰️ -DI (Crossover) Threshold 🅰️ -DI (Crossunder) Threshold 🔮 +DI (Crossover) -DI Forecast 🔮 +DI (Crossunder) -DI Forecast 🔮 ADX (Crossover) +DI Forecast 🔮 ADX (Crossunder) +DI Forecast 📉 SELL 🅰️  Signal Validity: The signal will remain valid for X bars . 🅰️  Signal Sequence: Configurable as AND or OR . 🅰️ +DI > -DI 🅰️ +DI < -DI 🅰️ +DI > ADX 🅰️ +DI < ADX 🅰️ -DI > ADX 🅰️ -DI < ADX 🅰️ ADX > Threshold 🅰️ ADX < Threshold 🅰️ +DI > Threshold 🅰️ +DI < Threshold 🅰️ -DI > Threshold 🅰️ -DI < Threshold 🅰️ +DI (Crossover) -DI 🅰️ +DI (Crossunder) -DI 🅰️ +DI (Crossover) ADX 🅰️ +DI (Crossunder) ADX 🅰️ +DI (Crossover) Threshold 🅰️ +DI (Crossunder) Threshold 🅰️ -DI (Crossover) ADX 🅰️ -DI (Crossunder) ADX 🅰️ -DI (Crossover) Threshold 🅰️ -DI (Crossunder) Threshold 🔮 +DI (Crossover) -DI Forecast 🔮 +DI (Crossunder) -DI Forecast 🔮 ADX (Crossover) +DI Forecast 🔮 ADX (Crossunder) +DI Forecast 🤖 Automation All BUY and SELL conditions are compatible with TradingView alerts, making them ideal for fully or semi-automated systems. ⯁ Unique Features Linear Regression: (Forecast) Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Condition Table: BUY/SELL Condition Labels: BUY/SELL Plot Labels in the Graph Above: BUY/SELL Automate and Monitor Signals/Alerts: BUY/SELL Background Colors: "bgcolor" Background Colors: "fill" Linear Regression (Forecast) Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Table of Conditions: BUY/SELL Conditions Label: BUY/SELL Plot Labels in the graph above: BUY/SELL Automate & Monitor Signals/Alerts: BUY/SELL Background Colors: "bgcolor" Background Colors: "fill"
Pine Script®指標
由DiFlip提供
US Sessions R4D1🇬🇧 English US Sessions R4D1 - Market Session Highlighter Visualize US market sessions directly on your chart with beautiful color overlays and an interactive dashboard. 🎯 FEATURES: - Automatic session detection based on New York time - Color-coded background for each session - Session start labels with customizable size - Real-time dashboard showing current session status - Fully customizable colors and settings 📊 SESSIONS: - 🌙 Premarket: 4:00-9:30 NY - 🔔 US Open: 9:30-11:30 NY (Power Hour!) - 🍔 Lunch: 11:30-13:30 NY (Low Volume) - 📈 Afternoon: 13:30-16:00 NY - 🌃 After Hours: 16:00-20:00 NY ⚙️ SETTINGS: - Toggle each session on/off - Customize all colors - Label size: tiny to huge - Dashboard position: any corner - Show/hide labels and dashboard Perfect for day traders who want to track market sessions at a glance. Know exactly when the US market opens, when volume typically drops during lunch, and when the afternoon push begins. Works on all timeframes and instruments.
Pine Script®指標
由AL_R4D1提供
Expected Move BandsExpected move is the amount that an asset is predicted to increase or decrease from its current price, based on the current levels of volatility. In this model, we assume asset price follows a log-normal distribution and the log return follows a normal distribution. Note: Normal distribution is just an assumption, it's not the real distribution of return Settings: "Estimation Period Selection" is for selecting the period we want to construct the prediction interval. For "Current Bar", the interval is calculated based on the data of the previous bar close. Therefore changes in the current price will have little effect on the range. What current bar means is that the estimated range is for when this bar close. E.g., If the Timeframe on 4 hours and 1 hour has passed, the interval is for how much time this bar has left, in this case, 3 hours. For "Future Bars", the interval is calculated based on the current close. Therefore the range will be very much affected by the change in the current price. If the current price moves up, the range will also move up, vice versa. Future Bars is estimating the range for the period at least one bar ahead. There are also other source selections based on high low. Time setting is used when "Future Bars" is chosen for the period. The value in time means how many bars ahead of the current bar the range is estimating. When time = 1, it means the interval is constructing for 1 bar head. E.g., If the timeframe is on 4 hours, then it's estimating the next 4 hours range no matter how much time has passed in the current bar. Note: It's probably better to use "probability cone" for visual presentation when time > 1 Volatility Models : Sample SD: traditional sample standard deviation, most commonly used, use (n-1) period to adjust the bias Parkinson: Uses High/ Low to estimate volatility, assumes continuous no gap, zero mean no drift, 5 times more efficient than Close to Close Garman Klass: Uses OHLC volatility, zero drift, no jumps, about 7 times more efficient Yangzhang Garman Klass Extension: Added jump calculation in Garman Klass, has the same value as Garman Klass on markets with no gaps. about 8 x efficient Rogers: Uses OHLC, Assume non-zero mean volatility, handles drift, does not handle jump 8 x efficient EWMA: Exponentially Weighted Volatility. Weight recently volatility more, more reactive volatility better in taking account of volatility autocorrelation and cluster. YangZhang: Uses OHLC, combines Rogers and Garmand Klass, handles both drift and jump, 14 times efficient, alpha is the constant to weight rogers volatility to minimize variance. Median absolute deviation: It's a more direct way of measuring volatility. It measures volatility without using Standard deviation. The MAD used here is adjusted to be an unbiased estimator. Volatility Period is the sample size for variance estimation. A longer period makes the estimation range more stable less reactive to recent price. Distribution is more significant on a larger sample size. A short period makes the range more responsive to recent price. Might be better for high volatility clusters. Standard deviations: Standard Deviation One shows the estimated range where the closing price will be about 68% of the time. Standard Deviation two shows the estimated range where the closing price will be about 95% of the time. Standard Deviation three shows the estimated range where the closing price will be about 99.7% of the time. Note: All these probabilities are based on the normal distribution assumption for returns. It's the estimated probability, not the actual probability. Manually Entered Standard Deviation shows the range of any entered standard deviation. The probability of that range will be presented on the panel. People usually assume the mean of returns to be zero. To be more accurate, we can consider the drift in price from calculating the geometric mean of returns. Drift happens in the long run, so short lookback periods are not recommended. Assuming zero mean is recommended when time is not greater than 1. When we are estimating the future range for time > 1, we typically assume constant volatility and the returns to be independent and identically distributed. We scale the volatility in term of time to get future range. However, when there's autocorrelation in returns( when returns are not independent), the assumption fails to take account of this effect. Volatility scaled with autocorrelation is required when returns are not iid. We use an AR(1) model to scale the first-order autocorrelation to adjust the effect. Returns typically don't have significant autocorrelation. Adjustment for autocorrelation is not usually needed. A long length is recommended in Autocorrelation calculation. Note: The significance of autocorrelation can be checked on an ACF indicator. ACF The multimeframe option enables people to use higher period expected move on the lower time frame. People should only use time frame higher than the current time frame for the input. An error warning will appear when input Tf is lower. The input format is multiplier * time unit. E.g. : 1D Unit: M for months, W for Weeks, D for Days, integers with no unit for minutes (E.g. 240 = 240 minutes). S for Seconds. Smoothing option is using a filter to smooth out the range. The filter used here is John Ehler's supersmoother. It's an advance smoothing technique that gets rid of aliasing noise. It affects is similar to a simple moving average with half the lookback length but smoother and has less lag. Note: The range here after smooth no long represent the probability Panel positions can be adjusted in the settings. X position adjusts the horizontal position of the panel. Higher X moves panel to the right and lower X moves panel to the left. Y position adjusts the vertical position of the panel. Higher Y moves panel up and lower Y moves panel down. Step line display changes the style of the bands from line to step line. Step line is recommended because it gets rid of the directional bias of slope of expected move when displaying the bands. Warnings: People should not blindly trust the probability. They should be aware of the risk evolves by using the normal distribution assumption. The real return has skewness and high kurtosis. While skewness is not very significant, the high kurtosis should be noticed. The Real returns have much fatter tails than the normal distribution, which also makes the peak higher. This property makes the tail ranges such as range more than 2SD highly underestimate the actual range and the body such as 1 SD slightly overestimate the actual range. For ranges more than 2SD, people shouldn't trust them. They should beware of extreme events in the tails. Different volatility models provide different properties if people are interested in the accuracy and the fit of expected move, they can try expected move occurrence indicator. (The result also demonstrate the previous point about the drawback of using normal distribution assumption). Expected move Occurrence Test The prediction interval is only for the closing price, not wicks. It only estimates the probability of the price closing at this level, not in between. E.g., If 1 SD range is 100 - 200, the price can go to 80 or 230 intrabar, but if the bar close within 100 - 200 in the end. It's still considered a 68% one standard deviation move.
Pine Script®指標
由Motgench提供
Psychological levelsADVANCED PSYCHOLOGICAL LEVELS - PROFESSIONAL FOREX INDICATOR This highly customizable indicator automatically identifies and visualizes all major psychological price levels across any Forex chart. Psychological levels represent critical price zones where traders naturally congregate their orders due to human psychology's attraction to round numbers. These levels consistently act as powerful support and resistance zones in the market. 🎯 KEY FEATURES: ✅ Four Distinct Level Types - Choose from 100-pip, 50-pip, 25-pip, and 10-pip psychological levels ✅ Individual Color Customization - Each level type has its own customizable zone and line colors ✅ Separate Zone Width Control - Adjust zone width independently for each level type ✅ Universal Forex Compatibility - Automatically adapts to JPY pairs and all other currency pairs ✅ Extended Coverage - Displays levels far beyond the visible chart area for comprehensive analysis ✅ Fixed Positioning - Levels remain stationary when scrolling or zooming ✅ Fully Customizable Styling - Choose between solid, dashed, or dotted line styles 📊 LEVEL TYPES EXPLAINED: 🔴 100-pip Levels (e.g., EUR/USD: 1.1000, 1.1100, 1.1200 | USD/JPY: 150.00, 151.00, 152.00) The most significant psychological barriers in Forex trading Major round numbers where institutional traders place large orders Strongest support and resistance zones with highest reaction probability Essential for swing trading and position trading strategies Default color: Red (highest importance) 🟠 50-pip Levels (e.g., EUR/USD: 1.1050, 1.1150, 1.1250 | USD/JPY: 150.50, 151.50, 152.50) Secondary psychological levels positioned midway between 100-pip levels Important intermediate zones for profit-taking and order clustering Highly effective for day trading strategies Reliable targets for partial profit exits Default color: Orange (medium-high importance) 🔵 25-pip Levels (e.g., EUR/USD: 1.1025, 1.1075, 1.1125 | USD/JPY: 150.25, 150.75, 151.25) Quartile levels providing granular market structure Perfect for scalping and short-term trading approaches Excellent confluence zones with technical indicators Ideal for tight stop-loss placement Default color: Blue (medium importance) 🟢 10-pip Levels (e.g., EUR/USD: 1.1010, 1.1020, 1.1030 | USD/JPY: 150.10, 150.20, 150.30) Most detailed psychological levels for precision trading Optimal for micro scalping and high-frequency strategies Provides fine-grained market structure analysis Useful for optimizing entry and exit timing Default color: Green (detailed analysis) ⚙️ CUSTOMIZATION OPTIONS: Color Settings (Individual for Each Level): Zone Color - Customize fill color with adjustable transparency Line Color - Set center line color independently Default color scheme uses traffic light logic (Red → Orange → Blue → Green) Zone Width Settings (Separate for Each Level): 100-pip Levels: Default 10 pips (wider zones for major levels) 50-pip Levels: Default 7 pips (medium zones) 25-pip Levels: Default 5 pips (smaller zones) 10-pip Levels: Default 3 pips (narrowest zones for precision) Display Settings: Line Style: Choose between Solid, Dashed, or Dotted Line Thickness: Adjustable from 1 to 5 pixels Level Selection: Toggle each level type on/off independently 💡 TRADING APPLICATIONS: 📈 Support & Resistance Identification Instantly recognize where price is likely to react Identify key reversal zones before they occur Combine with price action for high-probability setups 🎯 Optimal Entry & Exit Points Enter trades at psychological support/resistance Set realistic profit targets at the next psychological level Improve win rate by trading with market psychology 🛡️ Strategic Stop-Loss Placement Position stops just beyond psychological levels to avoid stop hunts Reduce premature stop-outs by understanding where others place stops Protect profits by moving stops to psychological levels 💰 Profit Target Optimization Set take-profit orders at psychological levels where profit-taking occurs Scale out positions at multiple psychological levels Maximize gains by understanding where demand/supply shifts 📊 Breakout Trading Identify when price decisively breaks through major psychological barriers Trade momentum when psychological levels are breached Confirm breakouts using multiple level types as confluence ⚖️ Risk Management Enhancement Calculate better risk-reward ratios using psychological levels Size positions based on distance to next psychological level Improve overall trading consistency 🔬 WHY PSYCHOLOGICAL LEVELS WORK: Psychological levels are self-fulfilling prophecies in financial markets. Because thousands of traders worldwide monitor the same round numbers, these levels naturally attract significant order flow: Order Clustering: Pending buy/sell orders accumulate at round numbers Profit Taking: Traders instinctively close positions at psychological levels Stop Hunts: Market makers often push price to psychological levels to trigger stops Institutional Activity: Banks and funds use round numbers for large order placement Pattern Recognition: Human brains naturally gravitate toward simple, round numbers 📋 TECHNICAL SPECIFICATIONS: ✓ Pine Script Version 6 (latest) ✓ Compatible with all Forex pairs (majors, minors, exotics) ✓ Works on all timeframes (M1 to Monthly) ✓ Automatic JPY pair detection and adjustment ✓ Maximum 500 lines and 500 boxes for optimal performance ✓ Levels extend infinitely across the chart ✓ No repainting - levels are fixed once drawn ✓ Efficient calculation prevents performance issues ✓ Clean visualization without chart clutter 👥 IDEAL FOR: Day Traders: Use 100-pip and 50-pip levels for intraday setups Swing Traders: Focus on major 100-pip levels for multi-day positions Scalpers: Enable 25-pip and 10-pip levels for precision entries Position Traders: Use 100-pip levels for long-term support/resistance analysis Beginner Traders: Learn to recognize important market structure easily Algorithm Developers: Incorporate psychological levels into automated strategies 🚀 HOW TO USE: Add the indicator to any Forex chart Select which level types you want to display (100, 50, 25, 10) Customize colors to match your chart theme Adjust zone widths based on your trading style and timeframe Choose line style (solid, dashed, or dotted) Watch for price reactions at the highlighted psychological zones Use the levels to plan entries, exits, and stop-loss placement 💎 BEST PRACTICES: ✓ Combine with candlestick patterns for confirmation signals ✓ Wait for price action confirmation before entering trades ✓ Use multiple timeframes to identify the most significant levels ✓ Disable 10-pip levels on higher timeframes to reduce visual noise ✓ Enable only 100-pip levels for clean, uncluttered analysis on Daily/Weekly charts ✓ Adjust zone widths based on pair volatility (wider for volatile pairs) ✓ Use color coding to instantly recognize level importance ⚡ PERFORMANCE OPTIMIZED: This indicator is engineered for maximum efficiency: Smart calculation only within visible price range Duplicate prevention system avoids overlapping levels Optimized loops with early break conditions Extended coverage (500 bars) without performance degradation Handles thousands of levels across all timeframes smoothly 🎨 VISUAL DESIGN: The default color scheme follows intuitive importance levels: Red (100-pip): Highest importance - major barriers Orange (50-pip): Medium-high importance - secondary levels Blue (25-pip): Medium importance - tertiary levels Green (10-pip): Detailed analysis - precision levels This traffic-light inspired system allows instant visual recognition of level significance. 📚 EDUCATIONAL VALUE: Beyond being a trading tool, this indicator serves as an excellent educational resource for understanding market psychology and how professional traders think. It visually demonstrates where the "crowd" is likely to place orders, helping you develop better market intuition. 🔄 CONTINUOUS UPDATES: This indicator displays levels dynamically based on the current price range, ensuring you always see relevant psychological levels no matter where price moves on the chart. ✨ WHAT MAKES THIS INDICATOR UNIQUE: Unlike simple horizontal line indicators, this advanced tool offers: Individual customization for each level type (colors, widths) Automatic currency pair detection and adjustment Visual zones (not just lines) for better support/resistance visualization Extended coverage ensuring levels are always visible Professional color-coding system for instant level importance recognition Performance-optimized for handling hundreds of levels simultaneously ⭐ PERFECT FOR ALL TRADING STYLES: Whether you're a conservative position trader looking at weekly charts or an aggressive scalper on 1-minute timeframes, this indicator adapts to your needs. Simply enable the appropriate level types and adjust the visualization to match your strategy.
Pine Script®指標
由Nickpalm提供
Hurst Exponent - Detrended Fluctuation AnalysisIn stochastic processes, chaos theory and time series analysis, detrended fluctuation analysis (DFA) is a method for determining the statistical self-affinity of a signal. It is useful for analyzing time series that appear to be long-memory processes and noise. █ OVERVIEW We have introduced the concept of Hurst Exponent in our previous open indicator Hurst Exponent (Simple). It is an indicator that measures market state from autocorrelation. However, we apply a more advanced and accurate way to calculate Hurst Exponent rather than simple approximation. Therefore, we recommend using this version of Hurst Exponent over our previous publication going forward. The method we used here is called detrended fluctuation analysis. (For folks that are not interested in the math behind the calculation, feel free to skip to "features" and "how to use" section. However, it is recommended that you read it all to gain a better understanding of the mathematical reasoning). █ Detrend Fluctuation Analysis Detrended Fluctuation Analysis was first introduced by by Peng, C.K. (Original Paper) in order to measure the long-range power-law correlations in DNA sequences . DFA measures the scaling-behavior of the second moment-fluctuations, the scaling exponent is a generalization of Hurst exponent. The traditional way of measuring Hurst exponent is the rescaled range method. However DFA provides the following benefits over the traditional rescaled range method (RS) method:  • Can be applied to non-stationary time series. While asset returns are generally stationary, DFA can measure Hurst more accurately in the instances where they are non-stationary.  • According the the asymptotic distribution value of DFA and RS, the latter usually overestimates Hurst exponent (even after Anis- Llyod correction) resulting in the expected value of RS Hurst being close to 0.54, instead of the 0.5 that it should be. Therefore it's harder to determine the autocorrelation based on the expected value. The expected value is significantly closer to 0.5 making that threshold much more useful, using the DFA method on the Hurst Exponent (HE).  • Lastly, DFA requires lower sample size relative to the RS method. While the RS method generally requires thousands of observations to reduce the variance of HE, DFA only needs a sample size greater than a hundred to accomplish the above mentioned. █ Calculation DFA is a modified root-mean-squares (RMS) analysis of a random walk. In short, DFA computes the RMS error of linear fits over progressively larger bins (non-overlapped “boxes” of similar size) of an integrated time series. Our signal time series is the log returns. First we subtract the mean from the log return to calculate the demeaned returns. Then, we calculate the cumulative sum of demeaned returns resulting in the cumulative sum being mean centered and we can use the DFA method on this. The subtraction of the mean eliminates the “global trend” of the signal. The advantage of applying scaling analysis to the signal profile instead of the signal, allows the original signal to be non-stationary when needed. (For example, this process converts an i.i.d. white noise process into a random walk.) We slice the cumulative sum into windows of equal space and run linear regression on each window to measure the linear trend. After we conduct each linear regression. We detrend the series by deducting the linear regression line from the cumulative sum in each windows. The fluctuation is the difference between cumulative sum and regression. We use different windows sizes on the same cumulative sum series. The window sizes scales are log spaced. Eg: powers of 2, 2,4,8,16... This is where the scale free measurements come in, how we measure the fractal nature and self similarity of the time series, as well as how the well smaller scale represent the larger scale. As the window size decreases, we uses more regression lines to measure the trend. Therefore, the fitness of regression should be better with smaller fluctuation. It allows one to zoom into the “picture” to see the details. The linear regression is like rulers. If you use more rulers to measure the smaller scale details you will get a more precise measurement. The exponent we are measuring here is to determine the relationship between the window size and fitness of regression (the rate of change). The more complex the time series are the more it will depend on decreasing window sizes (using more linear regression lines to measure). The less complex or the more trend in the time series, it will depend less. The fitness is calculated by the average of root mean square errors (RMS) of regression from each window. Root mean Square error is calculated by square root of the sum of the difference between cumulative sum and regression. The following chart displays average RMS of different window sizes. As the chart shows, values for smaller window sizes shows more details due to higher complexity of measurements. The last step is to measure the exponent. In order to measure the power law exponent. We measure the slope on the log-log plot chart. The x axis is the log of the size of windows, the y axis is the log of the average RMS. We run a linear regression through the plotted points. The slope of regression is the exponent. It's easy to see the relationship between RMS and window size on the chart. Larger RMS equals less fitness of the regression. We know the RMS will increase (fitness will decrease) as we increases window size (use less regressions to measure), we focus on the rate of RMS increasing (how fast) as window size increases. If the slope is < 0.5, It means the rate of of increase in RMS is small when window size increases. Therefore the fit is much better when it's measured by a large number of linear regression lines. So the series is more complex. (Mean reversion, negative autocorrelation). If the slope is > 0.5, It means the rate of increase in RMS is larger when window sizes increases. Therefore even when window size is large, the larger trend can be measured well by a small number of regression lines. Therefore the series has a trend with positive autocorrelation. If the slope = 0.5, It means the series follows a random walk. █ FEATURES  • Sample Size is the lookback period for calculation. Even though DFA requires a lower sample size than RS, a sample size larger > 50 is recommended for accurate measurement.  • When a larger sample size is used (for example = 1000 lookback length), the loading speed may be slower due to a longer calculation. Date Range is used to limit numbers of historical calculation bars. When loading speed is too slow, change the data range "all" into numbers of weeks/days/hours to reduce loading time. (Credit to allanster)  • “show filter” option applies a smoothing moving average to smooth the exponent.  • Log scale is my work around for dynamic log space scaling. Traditionally the smallest log space for bars is power of 2. It requires at least 10 points for an accurate regression, resulting in the minimum lookback to be 1024. I made some changes to round the fractional log space into integer bars requiring the said log space to be less than 2. • For a more accurate calculation a larger "Base Scale" and "Max Scale" should be selected. However, when the sample size is small, a larger value would cause issues. Therefore, a general rule to be followed is: A larger "Base Scale" and "Max Scale" should be selected for a larger the sample size. It is recommended for the user to try and choose a larger scale if increasing the value doesn't cause issues. The following chart shows the change in value using various scales. As shown, sometimes increasing the value makes the value itself messy and overshoot. When using the lowest scale (4,2), the value seems stable. When we increase the scale to (8,2), the value is still alright. However, when we increase it to (8,4), it begins to look messy. And when we increase it to (16,4), it starts overshooting. Therefore, (8,2) seems to be optimal for our use. █ How to Use Similar to Hurst Exponent (Simple). 0.5 is a level for determine long term memory.  • In the efficient market hypothesis, market follows a random walk and Hurst exponent should be 0.5. When Hurst Exponent is significantly different from 0.5, the market is inefficient.  • When Hurst Exponent is > 0.5. Positive Autocorrelation. Market is Trending. Positive returns tend to be followed by positive returns and vice versa.  • Hurst Exponent is < 0.5. Negative Autocorrelation. Market is Mean reverting. Positive returns trends to follow by negative return and vice versa. However, we can't really tell if the Hurst exponent value is generated by random chance by only looking at the 0.5 level. Even if we measure a pure random walk, the Hurst Exponent will never be exactly 0.5, it will be close like 0.506 but not equal to 0.5. That's why we need a level to tell us if Hurst Exponent is significant. So we also computed the 95% confidence interval according to Monte Carlo simulation. The confidence level adjusts itself by sample size. When Hurst Exponent is above the top or below the bottom confidence level, the value of Hurst exponent has statistical significance. The efficient market hypothesis is rejected and market has significant inefficiency. The state of market is painted in different color as the following chart shows. The users can also tell the state from the table displayed on the right. An important point is that Hurst Value only represents the market state according to the past value measurement. Which means it only tells you the market state now and in the past. If Hurst Exponent on sample size 100 shows significant trend, it means according to the past 100 bars, the market is trending significantly. It doesn't mean the market will continue to trend. It's not forecasting market state in the future. However, this is also another way to use it. The market is not always random and it is not always inefficient, the state switches around from time to time. But there's one pattern, when the market stays inefficient for too long, the market participants see this and will try to take advantage of it. Therefore, the inefficiency will be traded away. That's why Hurst exponent won't stay in significant trend or mean reversion too long. When it's significant the market participants see that as well and the market adjusts itself back to normal. The Hurst Exponent can be used as a mean reverting oscillator itself. In a liquid market, the value tends to return back inside the confidence interval after significant moves(In smaller markets, it could stay inefficient for a long time). So when Hurst Exponent shows significant values, the market has just entered significant trend or mean reversion state. However, when it stays outside of confidence interval for too long, it would suggest the market might be closer to the end of trend or mean reversion instead. Larger sample size makes the Hurst Exponent Statistics more reliable. Therefore, if the user want to know if long term memory exist in general on the selected ticker, they can use a large sample size and maximize the log scale. Eg: 1024 sample size, scale (16,4). Following Chart is Bitcoin on Daily timeframe with 1024 lookback. It suggests the market for bitcoin tends to have long term memory in general. It generally has significant trend and is more inefficient at it's early stage.
Pine Script®指標
由Motgench提供
Psychological LevelsADVANCED PSYCHOLOGICAL LEVELS - PROFESSIONAL FOREX INDICATOR This highly customizable indicator automatically identifies and visualizes all major psychological price levels across any Forex chart. Psychological levels represent critical price zones where traders naturally congregate their orders due to human psychology's attraction to round numbers. These levels consistently act as powerful support and resistance zones in the market. 🎯 KEY FEATURES: ✅ Four Distinct Level Types - Choose from 1000-pip, 100-pip, 50-pip, 25-pip, and 10-pip psychological levels ✅ Individual Color Customization - Each level type has its own customizable zone and line colors ✅ Separate Zone Width Control - Adjust zone width independently for each level type ✅ Universal Forex Compatibility - Automatically adapts to JPY pairs and all other currency pairs ✅ Extended Coverage - Displays levels far beyond the visible chart area for comprehensive analysis ✅ Fixed Positioning - Levels remain stationary when scrolling or zooming ✅ Fully Customizable Styling - Choose between solid, dashed, or dotted line styles 📊 LEVEL TYPES EXPLAINED: 🟣 1000-pip Levels (e.g., EUR/USD: 1.0000, 2.0000 | USD/JPY: 100.00, 110.00, 120.00) The strongest macro-level psychological barriers in the Forex market Represent massive institutional, long-term price zones Extremely important for position traders, swing traders, and macro analysis Used by hedge funds, banks, and large liquidity providers for major order placement Ideal for identifying long-term support/resistance, trend reversals, and market structure shifts Default color: Purple (highest, macro-level importance) 🔴 100-pip Levels (e.g., EUR/USD: 1.1000, 1.1100, 1.1200 | USD/JPY: 150.00, 151.00, 152.00) The most significant psychological barriers in Forex trading Major round numbers where institutional traders place large orders Strongest support and resistance zones with highest reaction probability Essential for swing trading and position trading strategies Default color: Red (highest importance) 🟠 50-pip Levels (e.g., EUR/USD: 1.1050, 1.1150, 1.1250 | USD/JPY: 150.50, 151.50, 152.50) Secondary psychological levels positioned midway between 100-pip levels Important intermediate zones for profit-taking and order clustering Highly effective for day trading strategies Reliable targets for partial profit exits Default color: Orange (medium-high importance) 🔵 25-pip Levels (e.g., EUR/USD: 1.1025, 1.1075, 1.1125 | USD/JPY: 150.25, 150.75, 151.25) Quartile levels providing granular market structure Perfect for scalping and short-term trading approaches Excellent confluence zones with technical indicators Ideal for tight stop-loss placement Default color: Blue (medium importance) 🟢 10-pip Levels (e.g., EUR/USD: 1.1010, 1.1020, 1.1030 | USD/JPY: 150.10, 150.20, 150.30) Most detailed psychological levels for precision trading Optimal for micro scalping and high-frequency strategies Provides fine-grained market structure analysis Useful for optimizing entry and exit timing Default color: Green (detailed analysis) ⚙️ CUSTOMIZATION OPTIONS: Color Settings (Individual for Each Level): Zone Color - Customize fill color with adjustable transparency Line Color - Set center line color independently Default color scheme uses traffic light logic (Purple → Red → Orange → Blue → Green) Zone Width Settings (Separate for Each Level): 1000-pip Levels: Default 15 pips (widest zones for long-term significance) 100-pip Levels: Default 8 pips (wider zones for major levels) 50-pip Levels: Default 5 pips (medium zones) 25-pip Levels: Default 3 pips (smaller zones) 10-pip Levels: Default 2 pips (narrowest zones for precision) Display Settings: Line Style: Choose between Solid, Dashed, or Dotted Line Thickness: Adjustable from 1 to 5 pixels Level Selection: Toggle each level type on/off independently 💡 TRADING APPLICATIONS: 📈 Support & Resistance Identification Instantly recognize where price is likely to react Identify key reversal zones before they occur Combine with price action for high-probability setups 🎯 Optimal Entry & Exit Points Enter trades at psychological support/resistance Set realistic profit targets at the next psychological level Improve win rate by trading with market psychology 🛡️ Strategic Stop-Loss Placement Position stops just beyond psychological levels to avoid stop hunts Reduce premature stop-outs by understanding where others place stops Protect profits by moving stops to psychological levels 💰 Profit Target Optimization Set take-profit orders at psychological levels where profit-taking occurs Scale out positions at multiple psychological levels Maximize gains by understanding where demand/supply shifts 📊 Breakout Trading Identify when price decisively breaks through major psychological barriers Trade momentum when psychological levels are breached Confirm breakouts using multiple level types as confluence ⚖️ Risk Management Enhancement Calculate better risk-reward ratios using psychological levels Size positions based on distance to next psychological level Improve overall trading consistency 🔬 WHY PSYCHOLOGICAL LEVELS WORK: Psychological levels are self-fulfilling prophecies in financial markets. Because thousands of traders worldwide monitor the same round numbers, these levels naturally attract significant order flow: Order Clustering: Pending buy/sell orders accumulate at round numbers Profit Taking: Traders instinctively close positions at psychological levels Stop Hunts: Market makers often push price to psychological levels to trigger stops Institutional Activity: Banks and funds use round numbers for large order placement Pattern Recognition: Human brains naturally gravitate toward simple, round numbers 📋 TECHNICAL SPECIFICATIONS: ✓ Pine Script Version 6 (latest) ✓ Compatible with all Forex pairs (majors, minors, exotics) ✓ Works on all timeframes (M1 to Monthly) ✓ Automatic JPY pair detection and adjustment ✓ Maximum 500 lines and 500 boxes for optimal performance ✓ Levels extend infinitely across the chart ✓ No repainting - levels are fixed once drawn ✓ Efficient calculation prevents performance issues ✓ Clean visualization without chart clutter 👥 IDEAL FOR: Day Traders: Use 100-pip and 50-pip levels for intraday setups Swing Traders: Focus on major 100-pip levels for multi-day positions Scalpers: Enable 25-pip and 10-pip levels for precision entries Position Traders: Use 100-pip levels for long-term support/resistance analysis Beginner Traders: Learn to recognize important market structure easily Algorithm Developers: Incorporate psychological levels into automated strategies 🚀 HOW TO USE: Add the indicator to any Forex chart Select which level types you want to display (100, 50, 25, 10) Customize colors to match your chart theme Adjust zone widths based on your trading style and timeframe Choose line style (solid, dashed, or dotted) Watch for price reactions at the highlighted psychological zones Use the levels to plan entries, exits, and stop-loss placement 💎 BEST PRACTICES: ✓ Combine with candlestick patterns for confirmation signals ✓ Wait for price action confirmation before entering trades ✓ Use multiple timeframes to identify the most significant levels ✓ Disable 10-pip levels on higher timeframes to reduce visual noise ✓ Enable only 100-pip levels for clean, uncluttered analysis on Daily/Weekly charts ✓ Adjust zone widths based on pair volatility (wider for volatile pairs) ✓ Use color coding to instantly recognize level importance ⚡ PERFORMANCE OPTIMIZED: This indicator is engineered for maximum efficiency: Smart calculation only within visible price range Duplicate prevention system avoids overlapping levels Optimized loops with early break conditions Extended coverage (500 bars) without performance degradation Handles thousands of levels across all timeframes smoothly 🎨 VISUAL DESIGN: The default color scheme follows intuitive importance levels: Purple (1000-pip): Macro-level, highest significance Red (100-pip): Highest importance - major barriers Orange (50-pip): Medium-high importance - secondary levels Blue (25-pip): Medium importance - tertiary levels Green (10-pip): Detailed analysis - precision levels This traffic-light inspired system allows instant visual recognition of level significance. 📚 EDUCATIONAL VALUE: Beyond being a trading tool, this indicator serves as an excellent educational resource for understanding market psychology and how professional traders think. It visually demonstrates where the "crowd" is likely to place orders, helping you develop better market intuition. 🔄 CONTINUOUS UPDATES: This indicator displays levels dynamically based on the current price range, ensuring you always see relevant psychological levels no matter where price moves on the chart. ✨ WHAT MAKES THIS INDICATOR UNIQUE: Unlike simple horizontal line indicators, this advanced tool offers: Individual customization for each level type (colors, widths) Automatic currency pair detection and adjustment Visual zones (not just lines) for better support/resistance visualization Extended coverage ensuring levels are always visible Professional color-coding system for instant level importance recognition Performance-optimized for handling hundreds of levels simultaneously ⭐ PERFECT FOR ALL TRADING STYLES: Whether you're a conservative position trader looking at weekly charts or an aggressive scalper on 1-minute timeframes, this indicator adapts to your needs. Simply enable the appropriate level types and adjust the visualization to match your strategy. Transform your Forex trading with professional-grade psychological level analysis. Add this indicator to your chart today and start trading with the market psychology on your side!
Pine Script®指標
由Nickpalm提供
MACD Ultimate MTF [Radisa] MACD Ultimate MTF - Enhanced MACD with Beautiful Fills Based on the legendary CM_MacD_Ult_MTF by ChrisMoody - upgraded to Pine Script v5 with beautiful gradient fills and an informative dashboard. 🎯 FEATURES: - Multi-timeframe support (MTF) - view higher timeframe MACD on any chart - Beautiful fill between MACD & Signal line - 4-color histogram (strong/weak bull & bear) - Smooth lines on current timeframe (no stepping) - Cross signals with dot markers - Real-time info dashboard - Fully customizable colors 📊 SIGNALS: - 🟢 Bullish Cross: MACD crosses above Signal - 🔴 Bearish Cross: MACD crosses below Signal - Histogram color intensity shows momentum strength 📈 HISTOGRAM COLORS: - Bright Green: Above zero + rising (strong bullish) - Dark Green: Above zero + falling (weakening bullish) - Bright Red: Below zero + falling (strong bearish) - Dark Red: Below zero + rising (weakening bearish) ⚙️ SETTINGS: - Fast/Slow/Signal Length (default: 12/26/9) - Use current or custom timeframe - Toggle MACD line, Signal line, Histogram - Toggle fills and color changes - Customizable colors for all elements 💡 DASHBOARD SHOWS: - MACD value with colored background - Signal value - Histogram value - Trend direction (Bullish/Bearish) - Momentum strength (Strong/Fading) - Current timeframe Perfect for trend-following strategies. Combine with RSI or Supertrend for confirmation. Works on Crypto, Forex, Stocks - all timeframes.
Pine Script®指標
由AL_R4D1提供
6x EMA Set (5/20/50/100/200/300)This Pine Script indicator utilizes six Exponential Moving Averages (5, 20, 50, 100, 200, and 300 EMA) to visualize market trends and support/resistance levels across multiple timeframes on a single chart. The code is highly customizable, allowing the user to input and adjust the period length and color for each EMA directly within the indicator settings. The calculation engine uses Pine Script v5's optimized ta.ema() function to compute each average based on the closing price, with the EMA formula naturally weighting recent price action more heavily. This multi-layered structure enables the trader to quickly compare short-term momentum (Fast EMAs) against long-term structural trends (Slow EMAs).
Pine Script®指標
由mhakany提供
NIFTY Weekly Option Seller DirectionalHere’s a straight description you can paste into the TradingView “Description” box and tweak if needed: --- ### NIFTY Weekly Option Seller – Regime + Score + Management (Single TF) This indicator is built for **weekly option sellers** (primarily NIFTY) who want a **structured regime + scoring framework** to decide: * Whether to trade **Iron Condor (IC)**, **Put Credit Spread (PCS)** or **Call Credit Spread (CCS)** * How strong that regime is on the current timeframe (score 0–5) * When to **DEFEND** existing positions and when to **HARVEST** profits > **Note:** This is a **single timeframe** tool. The original system uses it on **4H and 1D separately**, then combines scores manually (e.g., using `min(4H, 1D)` for conviction and lot sizing). --- ## Core logic The script classifies the market into 3 regimes: * **IC (Iron Condor)** – range/mean-reversion conditions * **PCS (Put Credit Spread)** – bullish/trend-up conditions * **CCS (Call Credit Spread)** – bearish/trend-down conditions For each regime, it builds a **0–5 score** using: * **EMA stack (8/13/34)** – trend structure * **ADX (custom DMI-based)** – trend strength vs range * **Previous-day CPR** – in CPR vs break above/below * **VWAP (session)** – near/far value * **Camarilla H3/L3** – for IC context * **RSI (14)** – used as a **brake**, not a primary signal * **Daily trend / Daily ADX** – used as **hard gates**, not double-counted as extra points Then: * Scores for PCS / CCS / IC are **cross-penalised** (they pull each other down if conflicting) * Final scores are **smoothed** (current + previous bar) to avoid jumpy signals The **background colour** shows the current regime and conviction: * Blue = IC * Green = PCS * Red = CCS * Stronger tint = higher regime score --- ## Scoring details (per timeframe) **PCS (uptrend, bullish credit spreads)** * +2 if EMA(8) > EMA(13) > EMA(34) * +1 if ADX > ADX_TREND * +1 if close > CPR High * +1 if close > VWAP * RSI brake: * If RSI < 50 → PCS capped at 2 * If RSI > 75 → PCS capped at 3 * Daily gating: * If daily EMA stack is **not** uptrend → PCS capped at 2 **CCS (downtrend, bearish credit spreads)** * +2 if EMA(8) < EMA(13) < EMA(34) * +1 if ADX > ADX_TREND * +1 if close < CPR Low * +1 if close < VWAP * RSI brake: * If RSI > 50 → CCS capped at 2 * If RSI < 25 → CCS capped at 3 * Daily gating: * If daily EMA stack is **not** downtrend → CCS capped at 2 **IC (range / mean-reversion)** * +2 if ADX < ADX_RANGE (low trend) * +1 if close inside CPR * +1 if near VWAP * +0.5 if inside Camarilla H3–L3 * +1 if daily ADX < ADX_RANGE (daily also range-like) * +0.5 if RSI between 45 and 55 (classic balance zone) * Daily gating: * If daily ADX ≥ ADX_TREND → IC capped at 2 (no “strong IC” in strong trends) **Cross-penalty & smoothing** * Each regime’s raw score is reduced by **0.5 × max(other two scores)** * Final IC / PCS / CCS scores are then **smoothed** with previous bar * Scores are always clipped to ** ** --- ## Regime selection * If one regime has the highest score → that regime is selected. * If there is a tie or close scores: * When ADX is high, trend regimes (PCS/CCS) are preferred in the direction of the EMA stack. * When ADX is low, IC is preferred. The selected regime’s score is used for: * Background colour intensity * Minimum score gate for alerts * Display in the info panel --- ## DEFEND / HARVEST / REGIME alerts The script also defines **management signals** using ATR-based buffers and Camarilla breaks: * **DEFEND** * Price moving too close to short strikes (PCS/CCS/IC) relative to ATR, or * Trend breaks through Camarilla with ADX strong → Suggests rolling away / widening / converting to reduce risk. * **HARVEST** * Price has moved far enough from your short strikes (in ATR multiples) and market is still range-compatible → Suggests booking profits / rolling closer / reducing risk. * **REGIME CHANGED** * Regime flips (IC ↔ PCS/CCS) with cooldown and minimum score gate → Suggests switching playbook (range vs trend) for new entries. Each of these has a plotshape label plus an `alertcondition()` for TradingView alerts. --- ## UI / Panel The **top-right panel** (optional) shows: * Strategy + final regime score (IC / PCS / CCS, x/5) * ADX / RSI values * CPR status (Narrow / Normal / Wide + %) * EMA Stack (Up / Down / Mixed) and EMA tightness * VWAP proximity (Near / Away) * Final **IC / PCS / CCS** scores (for this timeframe) * H3/L3, H4/L4, CPR Low/High and VWAP levels (rounded) These values are meant to be **read quickly at the decision time** (e.g. near the close of the 4H bar or daily bar). --- ## Intended workflow 1. Run the script on **4H** and **1D** charts separately. 2. For each timeframe, read the panel’s **IC / PCS / CCS scores** and regime. 3. Decide: * Final regime (IC vs PCS vs CCS) * Combined score (e.g. `AlignScore = min(Score_4H, Score_1D)`) 4. Map that combined score to **your own lot-size buckets** and trade rules. 5. During the life of the position, use **DEFEND / HARVEST / REGIME** alerts to adjust. The script does **not** auto-calculate lot size or P&L. It focuses on giving a structured, consistent **market regime + strength + levels + management** layer for weekly option selling. --- ## Disclaimer This is a discretionary **decision-support tool**, not a guarantee of profit or a replacement for risk management. No performance is implied or promised. Always size positions and manage risk according to your own capital, rules, and regulations.
Pine Script®指標
由distinctSeahor20287提供