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Bear Market Probability Model# Bear Market Probability Model: A Multi-Factor Risk Assessment Framework The Bear Market Probability Model represents a comprehensive quantitative framework for assessing systemic market risk through the integration of 13 distinct risk factors across four analytical categories: macroeconomic indicators, technical analysis factors, market sentiment measures, and market breadth metrics. This indicator synthesizes established financial research methodologies to provide real-time probabilistic assessments of impending bear market conditions, offering institutional-grade risk management capabilities to retail and professional traders alike. ## Theoretical Foundation ### Historical Context of Bear Market Prediction Bear market prediction has been a central focus of financial research since the seminal work of Dow (1901) and the subsequent development of technical analysis theory. The challenge of predicting market downturns gained renewed academic attention following the market crashes of 1929, 1987, 2000, and 2008, leading to the development of sophisticated multi-factor models. Fama and French (1989) demonstrated that certain financial variables possess predictive power for stock returns, particularly during market stress periods. Their three-factor model laid the groundwork for multi-dimensional risk assessment, which this indicator extends through the incorporation of real-time market microstructure data. ### Methodological Framework The model employs a weighted composite scoring methodology based on the theoretical framework established by Campbell and Shiller (1998) for market valuation assessment, extended through the incorporation of high-frequency sentiment and technical indicators as proposed by Baker and Wurgler (2006) in their seminal work on investor sentiment. The mathematical foundation follows the general form: Bear Market Probability = Σ(Wi × Ci) / ΣWi × 100 Where: - Wi = Category weight (i = 1,2,3,4) - Ci = Normalized category score - Categories: Macroeconomic, Technical, Sentiment, Breadth ## Component Analysis ### 1. Macroeconomic Risk Factors #### Yield Curve Analysis The inclusion of yield curve inversion as a primary predictor follows extensive research by Estrella and Mishkin (1998), who demonstrated that the term spread between 3-month and 10-year Treasury securities has historically preceded all major recessions since 1969. The model incorporates both the 2Y-10Y and 3M-10Y spreads to capture different aspects of monetary policy expectations. Implementation: - 2Y-10Y Spread: Captures market expectations of monetary policy trajectory - 3M-10Y Spread: Traditional recession predictor with 12-18 month lead time Scientific Basis: Harvey (1988) and subsequent research by Ang, Piazzesi, and Wei (2006) established the theoretical foundation linking yield curve inversions to economic contractions through the expectations hypothesis of the term structure. #### Credit Risk Premium Assessment High-yield credit spreads serve as a real-time gauge of systemic risk, following the methodology established by Gilchrist and Zakrajšek (2012) in their excess bond premium research. The model incorporates the ICE BofA High Yield Master II Option-Adjusted Spread as a proxy for credit market stress. Threshold Calibration: - Normal conditions: < 350 basis points - Elevated risk: 350-500 basis points - Severe stress: > 500 basis points #### Currency and Commodity Stress Indicators The US Dollar Index (DXY) momentum serves as a risk-off indicator, while the Gold-to-Oil ratio captures commodity market stress dynamics. This approach follows the methodology of Akram (2009) and Beckmann, Berger, and Czudaj (2015) in analyzing commodity-currency relationships during market stress. ### 2. Technical Analysis Factors #### Multi-Timeframe Moving Average Analysis The technical component incorporates the well-established moving average convergence methodology, drawing from the work of Brock, Lakonishok, and LeBaron (1992), who provided empirical evidence for the profitability of technical trading rules. Implementation: - Price relative to 50-day and 200-day simple moving averages - Moving average convergence/divergence analysis - Multi-timeframe MACD assessment (daily and weekly) #### Momentum and Volatility Analysis The model integrates Relative Strength Index (RSI) analysis following Wilder's (1978) original methodology, combined with maximum drawdown analysis based on the work of Magdon-Ismail and Atiya (2004) on optimal drawdown measurement. ### 3. Market Sentiment Factors #### Volatility Index Analysis The VIX component follows the established research of Whaley (2009) and subsequent work by Bekaert and Hoerova (2014) on VIX as a predictor of market stress. The model incorporates both absolute VIX levels and relative VIX spikes compared to the 20-day moving average. Calibration: - Low volatility: VIX < 20 - Elevated concern: VIX 20-25 - High fear: VIX > 25 - Panic conditions: VIX > 30 #### Put-Call Ratio Analysis Options flow analysis through put-call ratios provides insight into sophisticated investor positioning, following the methodology established by Pan and Poteshman (2006) in their analysis of informed trading in options markets. ### 4. Market Breadth Factors #### Advance-Decline Analysis Market breadth assessment follows the classic work of Fosback (1976) and subsequent research by Brown and Cliff (2004) on market breadth as a predictor of future returns. Components: - Daily advance-decline ratio - Advance-decline line momentum - McClellan Oscillator (Ema19 - Ema39 of A-D difference) #### New Highs-New Lows Analysis The new highs-new lows ratio serves as a market leadership indicator, based on the research of Zweig (1986) and validated in academic literature by Zarowin (1990). ## Dynamic Threshold Methodology The model incorporates adaptive thresholds based on rolling volatility and trend analysis, following the methodology established by Pagan and Sossounov (2003) for business cycle dating. This approach allows the model to adjust sensitivity based on prevailing market conditions. Dynamic Threshold Calculation: - Warning Level: Base threshold ± (Volatility × 1.0) - Danger Level: Base threshold ± (Volatility × 1.5) - Bounds: ±10-20 points from base threshold ## Professional Implementation ### Institutional Usage Patterns Professional risk managers typically employ multi-factor bear market models in several contexts: #### 1. Portfolio Risk Management - Tactical Asset Allocation: Reducing equity exposure when probability exceeds 60-70% - Hedging Strategies: Implementing protective puts or VIX calls when warning thresholds are breached - Sector Rotation: Shifting from growth to defensive sectors during elevated risk periods #### 2. Risk Budgeting - Value-at-Risk Adjustment: Incorporating bear market probability into VaR calculations - Stress Testing: Using probability levels to calibrate stress test scenarios - Capital Requirements: Adjusting regulatory capital based on systemic risk assessment #### 3. Client Communication - Risk Reporting: Quantifying market risk for client presentations - Investment Committee Decisions: Providing objective risk metrics for strategic decisions - Performance Attribution: Explaining defensive positioning during market stress ### Implementation Framework Professional traders typically implement such models through: #### Signal Hierarchy: 1. Probability < 30%: Normal risk positioning 2. Probability 30-50%: Increased hedging, reduced leverage 3. Probability 50-70%: Defensive positioning, cash building 4. Probability > 70%: Maximum defensive posture, short exposure consideration #### Risk Management Integration: - Position Sizing: Inverse relationship between probability and position size - Stop-Loss Adjustment: Tighter stops during elevated risk periods - Correlation Monitoring: Increased attention to cross-asset correlations ## Strengths and Advantages ### 1. Comprehensive Coverage The model's primary strength lies in its multi-dimensional approach, avoiding the single-factor bias that has historically plagued market timing models. By incorporating macroeconomic, technical, sentiment, and breadth factors, the model provides robust risk assessment across different market regimes. ### 2. Dynamic Adaptability The adaptive threshold mechanism allows the model to adjust sensitivity based on prevailing volatility conditions, reducing false signals during low-volatility periods and maintaining sensitivity during high-volatility regimes. ### 3. Real-Time Processing Unlike traditional academic models that rely on monthly or quarterly data, this indicator processes daily market data, providing timely risk assessment for active portfolio management. ### 4. Transparency and Interpretability The component-based structure allows users to understand which factors are driving risk assessment, enabling informed decision-making about model signals. ### 5. Historical Validation Each component has been validated in academic literature, providing theoretical foundation for the model's predictive power. ## Limitations and Weaknesses ### 1. Data Dependencies The model's effectiveness depends heavily on the availability and quality of real-time economic data. Federal Reserve Economic Data (FRED) updates may have lags that could impact model responsiveness during rapidly evolving market conditions. ### 2. Regime Change Sensitivity Like most quantitative models, the indicator may struggle during unprecedented market conditions or structural regime changes where historical relationships break down (Taleb, 2007). ### 3. False Signal Risk Multi-factor models inherently face the challenge of balancing sensitivity with specificity. The model may generate false positive signals during normal market volatility periods. ### 4. Currency and Geographic Bias The model focuses primarily on US market indicators, potentially limiting its effectiveness for global portfolio management or non-USD denominated assets. ### 5. Correlation Breakdown During extreme market stress, correlations between risk factors may increase dramatically, reducing the model's diversification benefits (Forbes and Rigobon, 2002). ## References Akram, Q. F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838-851. Ang, A., Piazzesi, M., & Wei, M. (2006). What does the yield curve tell us about GDP growth? Journal of Econometrics, 131(1-2), 359-403. Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680. Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636. Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261-292. Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16-24. Bekaert, G., & Hoerova, M. (2014). The VIX, the variance premium and stock market volatility. Journal of Econometrics, 183(2), 181-192. Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764. Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of Empirical Finance, 11(1), 1-27. Campbell, J. Y., & Shiller, R. J. (1998). Valuation ratios and the long-run stock market outlook. The Journal of Portfolio Management, 24(2), 11-26. Dow, C. H. (1901). Scientific stock speculation. The Magazine of Wall Street. Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45-61. Fama, E. F., & French, K. R. (1989). Business conditions and expected returns on stocks and bonds. Journal of Financial Economics, 25(1), 23-49. Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: measuring stock market comovements. The Journal of Finance, 57(5), 2223-2261. Fosback, N. G. (1976). Stock market logic: A sophisticated approach to profits on Wall Street. The Institute for Econometric Research. Gilchrist, S., & Zakrajšek, E. (2012). Credit spreads and business cycle fluctuations. American Economic Review, 102(4), 1692-1720. Harvey, C. R. (1988). The real term structure and consumption growth. Journal of Financial Economics, 22(2), 305-333. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. Magdon-Ismail, M., & Atiya, A. F. (2004). Maximum drawdown. Risk, 17(10), 99-102. Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175-220. Pagan, A. R., & Sossounov, K. A. (2003). A simple framework for analysing bull and bear markets. Journal of Applied Econometrics, 18(1), 23-46. Pan, J., & Poteshman, A. M. (2006). The information in option volume for future stock prices. The Review of Financial Studies, 19(3), 871-908. Taleb, N. N. (2007). The black swan: The impact of the highly improbable. Random House. Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105. Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research. Zarowin, P. (1990). Size, seasonality, and stock market overreaction. Journal of Financial and Quantitative Analysis, 25(1), 113-125. Zweig, M. E. (1986). Winning on Wall Street. Warner Books.
Pine Script® indicator
by EdgeTools
17
5:30 AM IST Close + Offset Lines + TablesDescription: This script captures the 5:30 AM IST close price and plots it on the chart along with dynamic offset levels above and below (±5, ±20, ±40, ±60, ±80 points). It also displays these levels in neatly organized tables at the top-right and bottom-right corners for quick reference. 🔹 Timezone: Asia/Kolkata (IST) 🔹 Useful for: Intraday traders who reference early morning levels 🔹 Visual aids: Orange line for 5:30 AM close Green lines for points above Red lines for points below Tables summarizing all levels This tool helps identify key early-morning reference zones that can act as support/resistance or breakout targets.
Pine Script® indicator
by sayedquadri190
MFI + RSI + EMA Dynamic SignalsThe MFI + RSI + EMA Dynamic Signals is a designed to combine with widened criteria to capture more trading opportunities, it balances momentum, trend, and flexibility, making it suitable for trading on timeframes like 15-minute to 4-hour charts. How It Works The indicator uses three technical components with relaxed criteria to produce signals: Money Flow Index (MFI) for Momentum Extremes: The MFI, calculated over a 14-period length, measures buying and selling pressure using price and volume. A buy signal can trigger when MFI crosses above the oversold level (default: 30, widened from 20), indicating potential buying pressure, while a sell signal can occur when MFI crosses below the overbought level (default: 70, widened from 80), suggesting selling pressure. Relative Strength Index (RSI) for Momentum Confirmation: The RSI, calculated over a 14-period length, confirms momentum strength. Bullish momentum is confirmed when RSI is above a buy threshold (default: 45, relaxed from 50), and bearish momentum when below a sell threshold (default: 55, relaxed from 50), allowing more signals near neutral momentum levels. Exponential Moving Average (EMA) for Trend Sensitivity: The indicator uses a fast EMA (default: 9 periods) and a slow EMA (default: 21 periods) to detect trend direction and crossovers. Signals can trigger when the fast EMA crosses the slow EMA, or when the fast EMA is within a proximity threshold (default: 0.5%) of the slow EMA, capturing early trend changes and increasing signal frequency. Signal Generation Signals are generated using the previous bar’s values to prevent repainting, with widened criteria for more frequent triggers: Buy Signal: Either the MFI crosses above the oversold level or the fast EMA crosses above the slow EMA, and either RSI confirms bullish momentum (above 45) or the EMAs are near a crossover (within 0.5%). Displayed as a green upward triangle below the bar. Sell Signal: Either the MFI crosses below the overbought level or the fast EMA crosses below the slow EMA, and either RSI confirms bearish momentum (below 55) or the EMAs are near a crossover (within 0.5%). Displayed as a red downward triangle above the bar.
Pine Script® indicator
by Raisontgh
Dual Stochastic Enhanced (with Presets giua64)Script Title: Dual Stochastic Enhanced (with Presets giua64) Overview: This indicator enhances the traditional Dual Stochastic strategy, aiming to provide more filtered and potentially reliable trading signals. By integrating dynamic overbought/oversold levels via Bollinger Bands on the slow stochastic, a trend filter based on a moving average, momentum confirmation via RSI, and user-friendly selectable presets, "Dual Stochastic Enhanced" seeks to offer a more robust approach to identifying potential entry points. Key Features: Dual Stochastics: Utilizes a slow stochastic (configurable, e.g., 14 periods) as a context filter and a fast stochastic (configurable, e.g., 5 periods) as a signal trigger. Bollinger Bands on Slow Stochastic: Instead of fixed overbought/oversold levels (80/20), Bollinger Bands are applied to the %K line of the slow stochastic. This creates dynamic zones that adapt to the stochastic's own volatility. Trend Filter: A moving average (configurable type and length, e.g., EMA 100 as seen in the example chart for general context) on the price helps filter signals, allowing only trades aligned with the prevailing trend. RSI Confirmation: An RSI oscillator (configurable length, e.g., 14 periods) is used to confirm momentum. Signals require the RSI to cross certain thresholds to validate the strength of the move. User Presets: Includes presets for "Scalping," "Intraday," and "Swing trading," which quickly set all key parameters to suit different styles and timeframes. A "Custom" option is also available for full manual configuration. Clear Visual Signals: Long (green) and Short (red) arrows appear on the chart when all entry conditions are met. Active Zone Highlighting: The background of the indicator panel changes color (green or red) when "active zone" conditions (a combination of stochastics, trend, and RSI) are favorable. Information Panel: A table in the top-right corner of the indicator panel displays the current status of the selected preset, trend filter, RSI value, and stochastic levels. Signal Logic: A LONG signal is generated when: The fast stochastic %K crosses above its %D line. The slow stochastic %K line is below its lower Bollinger Band (dynamic oversold condition). The fast stochastic %K line is also in a low area (e.g., <25) to confirm the trigger is not premature. The closing price is above the trend moving average (uptrend). The RSI is above its long confirmation level (e.g., >40), indicating sufficient bullish momentum. A SHORT signal is generated when: The fast stochastic %K crosses below its %D line. The slow stochastic %K line is above its upper Bollinger Band (dynamic overbought condition). The fast stochastic %K line is also in a high area (e.g., >75). The closing price is below the trend moving average (downtrend). The RSI is below its short confirmation level (e.g., <60), indicating sufficient bearish momentum. How to Use: Select a Preset suitable for your trading style and the timeframe you are analyzing (e.g., Scalping for M1-M15, Intraday for M5-H1, Swing for H4-D1). Alternatively, choose "Custom" and manually adjust all parameters (stochastic lengths, smoothing, Bollinger Bands, Moving Average, RSI, confirmation thresholds). Observe the Information Panel for a quick understanding of the current conditions. Evaluate the arrow signals, always considering the broader market context, price action, and any other confluences (supports/resistances, chart patterns). The background highlighting can help quickly identify periods where conditions are aligned for potential trades. Disclaimer: This script is provided for educational and informational purposes only. Trading involves significant risk, and past performance is not indicative of future results. Always thoroughly test any strategy or indicator on historical data and on a demo account before risking real capital. The author assumes no responsibility for any losses incurred from the use of this script. Author: giua64
Pine Script® indicator
by giua64
2
Stochastic RSI with Alerts# Stochastic RSI with Alerts - User Manual ## 1. Overview This enhanced Stochastic RSI indicator identifies overbought/oversold conditions with visual signals and customizable alerts. It features: - Dual-line Stoch RSI (K & D) - Threshold-based buy/sell signals - Configurable alert system - Customizable parameters ## 2. Installation 1. Open TradingView chart 2. Open Pine Editor (📈 icon at bottom) 3. Copy/paste the full code 4. Click "Add to Chart" ## 3. Input Parameters ### 3.1 Core Settings | Parameter | Default | Description | |-----------|---------|-------------| | K | 3 | Smoothing period for %K line | | D | 3 | Smoothing period for %D line | | RSI Length | 14 | RSI calculation period | | Stochastic Length | 14 | Lookback period for Stoch calculation | | RSI Source | Close | Price source for RSI calculation | ### 3.2 Signal Thresholds | Parameter | Default | Description | |-----------|---------|-------------| | Upper Limit | 80 | Sell signal threshold (overbought) | | Lower Limit | 20 | Buy signal threshold (oversold) | ### 3.3 Alert Settings | Parameter | Default | Description | |-----------|---------|-------------| | Enable Buy Alerts | True | Toggle buy notifications | | Enable Sell Alerts | True | Toggle sell notifications | | Custom Alert Message | Empty | Additional text for alerts | ## 4. Signal Logic ### 4.1 Buy Signal (Green ▲) Triggers when: \text{%K crossover %D} \quad AND \quad (\text{%K ≤ Lower Limit} \quad OR \quad \text{%D ≤ Lower Limit}) ### 4.2 Sell Signal (Red ▼) Triggers when: \text{%K crossunder %D} \quad AND \quad (\text{%K ≥ Upper Limit} \quad OR \quad \text{%D ≥ Upper Limit}) ## 5. Alert System ### 5.1 Auto-Generated Alerts The script automatically creates these alert conditions: - **Buy Signal Alert**: Triggers on valid buy signals - **Sell Signal Alert**: Triggers on valid sell signals Alert messages include: - Signal type (Buy/Sell) - Current %K and %D values - Custom message (if configured) ### 5.2 Alert Configuration **Method 1: Script-Generated Alerts** 1. Hover over any signal marker 2. Click the 🔔 icon 3. Select trigger conditions: - "Buy Signal Alert" - "Sell Signal Alert" **Method 2: Manual Setup** 1. Open Alert creation window 2. Condition: Select "Stoch RSI Alerts" 3. Choose: - "Buy Signal Alert" for long entries - "Sell Signal Alert" for exits/shorts ## 6. Customization Tips ### 6.1 Threshold Adjustment // For day trading (tighter ranges) upperLimit = 75 lowerLimit = 25 // For swing trading (wider ranges) upperLimit = 85 lowerLimit = 15 ### 6.2 Visual Modifications Change signal markers via: - `style=` : Try `shape.labelup`, `shape.flag`, etc. - `color=` : Use hex codes (#FF00FF) or named colors - `size=` : `size.tiny` to `size.huge` ## 7. Recommended Use Cases 1. **Mean Reversion Strategies**: Pair with support/resistance levels 2. **Trend Confirmation**: Filter with 200EMA direction 3. **Divergence Trading**: Compare with price action ## 8. Limitations - Works best in ranging markets - Combine with volume analysis for confirmation - Not recommended as standalone strategy --- This documentation follows technical writing best practices with: - Clear parameter tables - Mathematical signal logic - Visual hierarchy - Practical examples - Usage recommendations
Pine Script® indicator
by OxJohannWu
Open-Based Adjustable LevelsThis indicator gives signals for levels where the buy or sell volume is above adjustable levels (ex, volume at 100,000). And these levels will only signal after the price has gone above/below a certain 'adjustable' percentage of the stocks opening price. Example: Signal sell when the price action is 0.7% above market opening price and when sell volume is above 120,000 or Signal buy when buy volume is above 80,000 and the price is 0.5% below market opening price. Great for day trading and detecting potential swings in the market. Above image is on a 3min chart. Doesn't work as well on daily time frames or above. Should be combined with other indicators like buy/sell channels, for the best confirmations
Pine Script® indicator
by parkerberlinger
MFI Candle Trend🎯 Purpose: The MFI Candle Trend is a custom TradingView indicator that transforms the Money Flow Index (MFI) into candle-style visuals using various smoothing and transformation techniques. Rather than displaying MFI as a line, this script generates synthetic candles from MFI values, helping traders visualize money flow trends, strength, and potential reversals with more clarity. 📌 Trend strength can be analyzed based on buying and selling pressures in the trend direction. 🧩 How It Works: Calculates MFI values for open, high, low, and close prices. Applies optional smoothing using the user-selected moving average (EMA, SMA, WMA, etc.). Transforms the smoothed MFI data into synthetic candles using a selected method: Normal: Uses raw MFI data Heikin-Ashi: Applies HA transformation to MFI Linear: Uses linear regression on MFI values Rational Quadratic: Applies advanced rational quadratic filtering via an external kernel library Colors candles based on MFI momentum: Cyan: Strong positive MFI movement Red: Strong negative MFI movement ⚙️ Key Inputs: Method: The type of smoothing method to apply to MFI Options: None, EMA, SMA, SMMA (RMA), WMA, VWMA, HMA, Mode Length: Period for both the MFI and smoothing calculation Candle: Selects the transformation mode for generating synthetic candles Options: Normal, Heikin-Ashi, Linear, Rational Quadratic Rational Quadratic: Adjusts the depth of smoothing for the Rational Quadratic filter (applies only if selected) 📊 Outputs: Synthetic MFI Candlesticks: Plotted using the smoothed and transformed MFI values. Dynamic Coloring: Cyan when MFI momentum is increasing Red when MFI momentum is decreasing Horizontal Lines: 80: Overbought zone 20: Oversold zone 🧠 Why Use This Indicator? Unlike traditional MFI indicators that use a line plot, this tool gives traders: A candle-based visualization of money flow momentum Enhanced trend and reversal detection using color-coded MFI candles A choice of smoothing filters and transformations for noise reduction A powerful combination of momentum and structure-based analysis To combine volume and price strength into a single chart element ❗Important Note: This indicator is for educational and analytical purposes only. It does not constitute financial advice. Always use proper risk management and validate with additional tools or analysis.
Pine Script® indicator
by erdas0
Hurst Exponent Oscillator [PhenLabs]📊 Hurst Exponent Oscillator - Version: PineScript™ v5 📌 Description The Hurst Exponent Oscillator (HEO) by PhenLabs is a powerful tool developed for traders who want to distinguish between trending, mean-reverting, and random market behaviors with clarity and precision. By estimating the Hurst Exponent—a statistical measure of long-term memory in financial time series—this indicator helps users make sense of underlying market dynamics that are often not visible through traditional moving averages or oscillators. Traders can quickly know if the market is likely to continue its current direction (trending), revert to the mean, or behave randomly, allowing for more strategic timing of entries and exits. With customizable smoothing and clear visual cues, the HEO enhances decision-making in a wide range of trading environments. 🚀 Points of Innovation Integrates advanced Hurst Exponent calculation via Rescaled Range (R/S) analysis, providing unique market character insights. Offers real-time visual cues for trending, mean-reverting, or random price action zones. User-controllable EMA smoothing reduces noise for clearer interpretation. Dynamic coloring and fill for immediate visual categorization of market regime. Configurable visual thresholds for critical Hurst levels (e.g., 0.4, 0.5, 0.6). Fully customizable appearance settings to fit different charting preferences. 🔧 Core Components Log Returns Calculation: Computes log returns of the selected price source to feed into the Hurst calculation, ensuring robust and scale-independent analysis. Rescaled Range (R/S) Analysis: Assesses the dispersion and cumulative deviation over a rolling window, forming the core statistical basis for the Hurst exponent estimate. Smoothing Engine: Applies Exponential Moving Average (EMA) smoothing to the raw Hurst value for enhanced clarity. Dynamic Rolling Windows: Utilizes arrays to maintain efficient, real-time calculations over user-defined lengths. Adaptive Color Logic: Assigns different highlight and fill colors based on the current Hurst value zone. 🔥 Key Features Visually differentiates between trending, mean-reverting, and random market modes. User-adjustable lookback and smoothing periods for tailored sensitivity. Distinct fill and line styles for each regime to avoid ambiguity. On-chart reference lines for strong trending and mean-reverting thresholds. Works with any price series (close, open, HL2, etc.) for versatile application. 🎨 Visualization Hurst Exponent Curve: Primary plotted line (smoothed if EMA is used) reflects the ongoing estimate of the Hurst exponent. Colored Zone Filling: The area between the Hurst line and the 0.5 reference line is filled, with color and opacity dynamically indicating the current market regime. Reference Lines: Dash/dot lines mark standard Hurst thresholds (0.4, 0.5, 0.6) to contextualize the current regime. All visual elements can be customized for thickness, color intensity, and opacity for user preference. 📖 Usage Guidelines Data Settings Hurst Calculation Length Default: 100 Range: 10-300 Description: Number of bars used in Hurst calculation; higher values mean longer-term analysis, lower values for quicker reaction. Data Source Default: close Description: Select which data series to analyze (e.g., Close, Open, HL2). Smoothing Length (EMA) Default: 5 Range: 1-50 Description: Length for smoothing the Hurst value; higher settings yield smoother but less responsive results. Style Settings Trending Color (Hurst > 0.5) Default: Blue tone Description: Color used when trending regime is detected. Mean-Reverting Color (Hurst < 0.5) Default: Orange tone Description: Color used when mean-reverting regime is detected. Neutral/Random Color Default: Soft blue Description: Color when market behavior is indeterminate or shifting. Fill Opacity Default: 70-80 Range: 0-100 Description: Transparency of area fills—higher opacity for stronger visual effect. Line Width Default: 2 Range: 1-5 Description: Thickness of the main indicator curve. ✅ Best Use Cases Identifying if a market is regime-shifting from trending to mean-reverting (or vice versa). Filtering signals in automated or systematic trading strategies. Spotting periods of randomness where trading signals should be deprioritized. Enhancing mean-reversion or trend-following models with regime-awareness. ⚠️ Limitations Not predictive: Reflects current and recent market state, not future direction. Sensitive to input parameters—overfitting may occur if settings are changed too frequently. Smoothing can introduce lag in regime recognition. May not work optimally in markets with structural breaks or extreme volatility. 💡 What Makes This Unique Employs advanced statistical market analysis (Hurst exponent) rarely found in standard toolkits. Offers immediate regime visualization through smart dynamic coloring and zone fills. 🔬 How It Works Rolling Log Return Calculation: Each new price creates a log return, forming the basis for robust, non-linear analysis. This ensures all price differences are treated proportionally. Rescaled Range Analysis: A rolling window maintains cumulative deviations and computes the statistical “range” (max-min of deviations). This is compared against the standard deviation to estimate “memory”. Exponent Calculation & Smoothing: The raw Hurst value is translated from the log of the rescaled range ratio, and then optionally smoothed via EMA to dampen noise and false signals. Regime Detection Logic: The smoothed value is checked against 0.5. Values above = trending; below = mean-reverting; near 0.5 = random. These control plot/fill color and zone display. 💡 Note: Use longer calculation lengths for major market character study, and shorter ones for tactical, short-term adaptation. Smoothing balances noise vs. lag—find a best fit for your trading style. Always combine regime awareness with broader technical/fundamental context for best results.
Pine Script® indicator
by PhenLabs
2
Money Flow Index + VWAP Trend FilterThis indicator combines the volume-weighted momentum analysis of the Money Flow Index (MFI) with the trend-filtering capabilities of the Volume Weighted Average Price (VWAP) to generate reliable buy and sell signals. By requiring MFI overbought/oversold conditions to align with the trend direction relative to VWAP, this indicator reduces false signals, making it ideal for trading on timeframes like 5-minute to 4-hour charts. How It Works The indicator uses two technical components to produce signals: Money Flow Index (MFI) for Momentum Extremes: The MFI, calculated over a default 14-period length, measures buying and selling pressure using price and volume data. A buy signal is triggered when MFI crosses above the oversold level (default: 20), indicating potential buying pressure, while a sell signal occurs when MFI crosses below the overbought level (default: 80), suggesting selling pressure. Volume Weighted Average Price (VWAP) for Trend Direction: The VWAP calculates the average price of an asset, weighted by volume, resetting at the start of each trading session (e.g., daily for stocks). It acts as a dynamic support/resistance level. A bullish trend is confirmed when the price is above the VWAP, and a bearish trend when the price is below the VWAP. This ensures MFI signals are filtered to align with the broader trend direction, plotted as a purple line on the chart. Signal Generation Signals are generated using the previous bar’s values to prevent repainting: Buy Signal: The MFI crosses above the oversold level, and the price is above the VWAP (bullish trend). Displayed as a green upward triangle below the bar. Sell Signal: The MFI crosses below the overbought level, and the price is below the VWAP (bearish trend). Displayed as a red downward triangle above the bar.
Pine Script® indicator
by Raisontgh
Supertrend + Stochastic RSIThe Supertrend + Stochastic RSI indicator is designed for scalping and short-term trading, combining the trend-following power of the Supertrend with the momentum insights of the Stochastic RSI to generate reliable buy and sell signals. This indicator aims to reduce false signals by requiring confirmation from both trend direction and momentum, making it suitable for traders targeting quick, high-probability trades in fast-moving markets on lower timeframes (e.g., 1-minute to 15-minute charts). How It Works The indicator integrates two technical components to produce actionable signals: Supertrend for Trend Direction: The Supertrend, calculated with a default length of 10 and a factor of 3.0, identifies the prevailing trend. It plots a line above or below the price, turning green when the trend is bullish (price above Supertrend) and red when bearish (price below Supertrend). This helps traders stay aligned with the market’s direction, reducing trades against the trend. Stochastic RSI for Momentum Confirmation: The Stochastic RSI, computed over a 14-period RSI with 3-period smoothing for %K and %D lines, measures momentum. A buy signal is generated when the %K line crosses above the oversold level (default: 20), indicating potential upward momentum, while a sell signal occurs when %K crosses below the overbought level (default: 80), suggesting downward momentum. Signal Generation Signals are produced only when both conditions align, using the previous bar’s values to prevent repainting: Buy Signal: The Stochastic RSI %K crosses above the oversold level, and the Supertrend confirms a bullish trend (price above Supertrend). Displayed as a green upward triangle below the bar. Sell Signal: The Stochastic RSI %K crosses below the overbought level, and the Supertrend confirms a bearish trend (price below Supertrend). Displayed as a red downward triangle above the bar.
Pine Script® indicator
by Raisontgh
1
Adaptive Volume-Weighted RSI (AVW-RSI)Concept Summary The AVW-RSI is a modified version of the Relative Strength Index (RSI), where each price change is weighted by the relative trading volume for that period. This means periods of high volume (typically driven by institutions or “big money”) have a greater influence on the RSI calculation than periods of low volume. Why AVW-RSI Helps Traders Avoids Weak Signals During Low Volume Standard RSI may show overbought/oversold zones even during low-volume periods (e.g., during lunch hours or after news). AVW-RSI gives less weight to these periods, avoiding misleading signals. Amplifies Strong Momentum Moves If RSI is rising during high volume, it's more likely driven by institutional buying—AVW-RSI reflects that stronger by weighting the RSI component. Filters Out Retail Noise By prioritizing high-volume candles, it naturally discounts fakeouts caused by thin markets or retail-heavy moves. Highlights Institutional Entry/Exit Useful for spotting hidden accumulation/distribution that classic RSI would miss. How It Works (Calculation Logic) Traditional RSI Formula Recap RSI = 100 - (100 / (1 + RS)) RS = Average Gain / Average Loss (over N periods) Modified Step – Apply Volume Weight For each period Gain_t = max(Close_t - Close_{t-1}, 0) Loss_t = max(Close_{t-1} - Close_t, 0) Weight_t = Volume_t / AvgVolume(N) WeightedGain_t = Gain_t * Weight_t WeightedLoss_t = Loss_t * Weight_t Weighted RSI AvgWeightedGain = SMA(WeightedGain, N) AvgWeightedLoss = SMA(WeightedLoss, N) RS = AvgWeightedGain / AvgWeightedLoss AVW-RSI = 100 - (100 / (1 + RS)) Visual Features on Chart Line Color Gradient Color gets darker as volume weight increases, signaling stronger conviction. Overbought/Oversold Zones Traditional: 70/30 Suggested AVW-RSI zones: Use dynamic thresholds based on historical volatility (e.g., 80/20 for high-volume coins). Volume Spike Flags Mark RSI turning points that occurred during volume spikes with a special dot/symbol. Trading Strategies with AVW-RSI 1. Weighted RSI Divergence Regular RSI divergence becomes more powerful when volume is high. AVW-RSI divergence with volume spike is a strong signal of reversal. 2. Trend Confirmation RSI crossing above 50 during rising volume is a good entry signal. RSI crossing below 50 with high volume is a strong exit or short trigger. 3. Breakout Validation Price breaking resistance + AVW-RSI > 60 with volume = Confirmed breakout. Price breaking but AVW-RSI < 50 or on low volume = Potential fakeout. Example Use Case Stock XYZ is approaching a resistance zone. A trader sees: Standard RSI: 65 → suggests strength. Volume is 3x the average. AVW-RSI: 78 → signals strong momentum with institutional backing. The trader enters confidently, knowing this isn't just low-volume hype. Limitations / Tips Works best on liquid assets (Forex majors, large-cap stocks, BTC/ETH). Should be used alongside price action and volume analysis—not standalone. Periods of extremely high volume (news events) might need smoothing to avoid spikes.
Pine Script® indicator
by SupertradeOfficial
2
ETI IndicatorThe Ensemble Technical Indicator (ETI) is a script that combines multiple established indicators into one single powerful indicator. Specifically, it takes a number of technical indicators and then converts them into +1 to represent a bullish trend, or a -1 to represent a bearish trend. It then adds these values together and takes the running sum over the past 20 days. The ETI is composed of the following indicators and converted to +1 or -1 using the following criteria: Simple Moving Average (10 days) : When the price is above the 10-day simple moving averaging, +1, when below -1 Weighted Moving Average (10 days) : Similar to the SMA 10, when the the price is above the 10-day weighted moving average, +1, when below -1 Stochastic K% : If the current Stochastic K% is greater than the previous value, then +1, else -1. Stochastic D% : Similar to the Stochastic K%, when the current Stochastic D% is greater than the previous value, +1, else -1. MACD Difference : First subtract the MACD signal (i.e. the moving average) from the MACD value and if the current value is higher than the previous value, then +1, else -1. William's R% : If the current William's R% is greater than the previous one, then +1, else -1. William's Accumulation/Distribution : If the current William's AD value is greater than the previous value, then +1, else -1. Commodity Channel Index : If the Commodity Channel Index is greater than 200 (overbought), then -1, if it is less than -200 (oversold) then +1. When it is between those values, if the current value is greater than the previous value then +1, else -1. Relative Strength Index : If the Relative Strength Index is over 70 (overbought) then -1 and if under 30 (oversold) then +1. If the Relative Strength Indicator is between those values then if the current value is higher than the previous value +1, else -1. Momentum (9 days) : If the momentum value is greater than 0, then +1, else -1. Again, once these values have been calculated and converted, they are added up to produce a single value. This single value is then summed across the previous 20 candles to produce a running sum. By coalescing multiple technical indicators into a single value across time, traders can better understand how multiple inter-related indicators are behaving at once; high scores indicate that numerous indicators are showing bullish signals indicating a potential or ongoing uptrend (and vice-versa with low scores). Additional Features Numerous smoothing transformations have also been added (e.g. gaussian smoothing) to remove some of the noise might exist. Suggested Use It is recommended that stocks are shorted when the cross below 0, and are bought when the ETI crosses above -40. Arrows can be shown on the indicator to show these points. However feel free to use levels that work best for you. Traditionally, I have treated values above +50 as overbought and below -40 as undersold (with -80 indicating extremely oversold); however these levels could also indicate either upwards and downwards momentum so taking a position based on where the ETI is (rather than crossing levels) should be done with caution.
Pine Script® indicator
by ExpertCBCD
Machine Learning: ARIMA + SARIMADescription The ARIMA (Autoregressive Integrated Moving Average) and SARIMA (Seasonal ARIMA) are advanced statistical models that use machine learning to forecast future price movements. It uses autoregression to find the relationship between observed data and its lagged observations. The data is differenced to make it more predictable. The MA component creates a dependency between observations and residual errors. The parameters are automatically adjusted to market conditions. Differences ARIMA - This excels at identifying trends in the form of directions SARIMA - Incorporates seasonality. It's better at capturing patterns previously seen How To Use 1. Model: Determine if you want to use ARIMA (better for direction) or SARIMA (better for overall prediction). You can click on the 'Show Historic Prediction' to see the direction of the previous candles. Green = forecast ending up, red = forecast ending down 2. Metrics: The RMSE% and MAPE are 10 day moving averages of the first 10 predictions made at candle close. They're error metrics that compare the observed data with the predicted data. It is better to use them when they're below 8%. Higher timeframes will be higher, as these models are partly mean-reverting and higher TFs tend to trend more. Better to compare RMSE% and MAPE with similar timeframes. They naturally lag as data is being collected 3. Parameter selection: The simpler, the better. Both are used for ARIMA(1,1,1) and SARIMA(1,1,1)(1,1,1)5. Increasing may cause overfitting 4. Training period: Keep at 50. Because of limitations in pine, higher values do not make for more powerful forecasts. They will only criminally lag. So best to keep between 20 and 80
Pine Script® indicator
by stormeta
6
S&P 500 Top 25 - EPS AnalysisEarnings Surprise Analysis Framework for S&P 500 Components: A Technical Implementation The "S&P 500 Top 25 - EPS Analysis" indicator represents a sophisticated technical implementation designed to analyze earnings surprises among major market constituents. Earnings surprises, defined as the deviation between actual reported earnings per share (EPS) and analyst estimates, have been consistently documented as significant market-moving events with substantial implications for price discovery and asset valuation (Ball and Brown, 1968; Livnat and Mendenhall, 2006). This implementation provides a comprehensive framework for quantifying and visualizing these deviations across multiple timeframes. The methodology employs a parameterized approach that allows for dynamic analysis of up to 25 top market capitalization components of the S&P 500 index. As noted by Bartov et al. (2002), large-cap stocks typically demonstrate different earnings response coefficients compared to their smaller counterparts, justifying the focus on market leaders. The technical infrastructure leverages the TradingView Pine Script language (version 6) to construct a real-time analytical framework that processes both actual and estimated EPS data through the platform's request.earnings() function, consistent with approaches described by Pine (2022) in financial indicator development documentation. At its core, the indicator calculates three primary metrics: actual EPS, estimated EPS, and earnings surprise (both absolute and percentage values). This calculation methodology aligns with standardized approaches in financial literature (Skinner and Sloan, 2002; Ke and Yu, 2006), where percentage surprise is computed as: (Actual EPS - Estimated EPS) / |Estimated EPS| × 100. The implementation rigorously handles potential division-by-zero scenarios and missing data points through conditional logic gates, ensuring robust performance across varying market conditions. The visual representation system employs a multi-layered approach consistent with best practices in financial data visualization (Few, 2009; Tufte, 2001). The indicator presents time-series plots of the four key metrics (actual EPS, estimated EPS, absolute surprise, and percentage surprise) with customizable color-coding that defaults to industry-standard conventions: green for actual figures, blue for estimates, red for absolute surprises, and orange for percentage deviations. As demonstrated by Padilla et al. (2018), appropriate color mapping significantly enhances the interpretability of financial data visualizations, particularly for identifying anomalies and trends. The implementation includes an advanced background coloring system that highlights periods of significant earnings surprises (exceeding ±3%), a threshold identified by Kinney et al. (2002) as statistically significant for market reactions. Additionally, the indicator features a dynamic information panel displaying current values, historical maximums and minimums, and sample counts, providing important context for statistical validity assessment. From an architectural perspective, the implementation employs a modular design that separates data acquisition, processing, and visualization components. This separation of concerns facilitates maintenance and extensibility, aligning with software engineering best practices for financial applications (Johnson et al., 2020). The indicator processes individual ticker data independently before aggregating results, mitigating potential issues with missing or irregular data reports. Applications of this indicator extend beyond merely observational analysis. As demonstrated by Chan et al. (1996) and more recently by Chordia and Shivakumar (2006), earnings surprises can be successfully incorporated into systematic trading strategies. The indicator's ability to track surprise percentages across multiple companies simultaneously provides a foundation for sector-wide analysis and potentially improves portfolio management during earnings seasons, when market volatility typically increases (Patell and Wolfson, 1984). References: Ball, R., & Brown, P. (1968). An empirical evaluation of accounting income numbers. Journal of Accounting Research, 6(2), 159-178. Bartov, E., Givoly, D., & Hayn, C. (2002). The rewards to meeting or beating earnings expectations. Journal of Accounting and Economics, 33(2), 173-204. Bernard, V. L., & Thomas, J. K. (1989). Post-earnings-announcement drift: Delayed price response or risk premium? Journal of Accounting Research, 27, 1-36. Chan, L. K., Jegadeesh, N., & Lakonishok, J. (1996). Momentum strategies. The Journal of Finance, 51(5), 1681-1713. Chordia, T., & Shivakumar, L. (2006). Earnings and price momentum. Journal of Financial Economics, 80(3), 627-656. Few, S. (2009). Now you see it: Simple visualization techniques for quantitative analysis. Analytics Press. Gu, S., Kelly, B., & Xiu, D. (2020). Empirical asset pricing via machine learning. The Review of Financial Studies, 33(5), 2223-2273. Johnson, J. A., Scharfstein, B. S., & Cook, R. G. (2020). Financial software development: Best practices and architectures. Wiley Finance. Ke, B., & Yu, Y. (2006). The effect of issuing biased earnings forecasts on analysts' access to management and survival. Journal of Accounting Research, 44(5), 965-999. Kinney, W., Burgstahler, D., & Martin, R. (2002). Earnings surprise "materiality" as measured by stock returns. Journal of Accounting Research, 40(5), 1297-1329. Livnat, J., & Mendenhall, R. R. (2006). Comparing the post-earnings announcement drift for surprises calculated from analyst and time series forecasts. Journal of Accounting Research, 44(1), 177-205. Padilla, L., Kay, M., & Hullman, J. (2018). Uncertainty visualization. Handbook of Human-Computer Interaction. Patell, J. M., & Wolfson, M. A. (1984). The intraday speed of adjustment of stock prices to earnings and dividend announcements. Journal of Financial Economics, 13(2), 223-252. Skinner, D. J., & Sloan, R. G. (2002). Earnings surprises, growth expectations, and stock returns or don't let an earnings torpedo sink your portfolio. Review of Accounting Studies, 7(2-3), 289-312. Tufte, E. R. (2001). The visual display of quantitative information (Vol. 2). Graphics Press.
Pine Script® indicator
by EdgeTools
Relative Volume CandlesVisualizes candlesticks with transparency based on volume relative to a moving average. Higher-than-average volume makes candles more opaque, while lower volume increases transparency—helping you spot significant price movements at a glance! Features: Customizable up/down candle colors (default: green/red) Adjustable lookback period for volume averaging (default: 21) Fine-tune transparency with base transparency (default: 80) and scale (default: 2.0) Overlay directly on your chart for seamless analysis
Pine Script® indicator
by Syck0
1
Stochastic Strategy Table with Trend (1m–4H) + Toggle📊 Multi-Timeframe Stochastic Strategy Table with Trend Detection This script is designed for intraday and swing traders who want to monitor Stochastic momentum across multiple timeframes in real-time — all directly on the main chart. 🔎 What This Script Does This script builds a compact, color-coded table that displays: ✅ %K and %D values of the Stochastic oscillator ✅ Cross direction (K > D or K < D) ✅ Overbought/Oversold zone conditions ✅ Short-term trend detection via %K movement It covers ten timeframes: 1m, 2m,3m,5m, 15m, 30m, 1H, 2H, 3H, 4H 🟩 How to Use It Trend colors in header: 🟢 Green = %K is rising (uptrend) 🔴 Red = %K is falling (downtrend) ⚪ Gray = flat or neutral Cross Row: Green background = Bullish (%K > %D) Red background = Bearish (%K < %D) Zone Row: Green = Oversold (%K and %D below 20) Red = Overbought (%K and %D above 80) Gray = Neutral zone Use Case: Look for multiple timeframes aligning in trend Enter trades on short timeframes (e.g. 5m) when HTFs confirm direction Especially powerful when used with price action on 5m/15m candles ⚙️ Configurable Inputs %K Length %K Smoothing %D Length Table location Table size 💡 Why This Script Is Unique Shows true higher timeframe Stochastic values (not interpolated from current chart) Works in real-time with consistent updates Trend direction is visualized without needing extra space Built for serious intraday traders who rely on clean data and signal alignment 🙏 Credits & Notes This tool was created to solve a real problem: getting accurate HTF stochastic data in a clean, real-time, decision-friendly format. I built it for my own use — and now I'm sharing it for luck, and for anyone else looking to trade more clearly and confidently. Feel free to fork, customize, or build upon it. Good luck, and trade safe! 🍀💹
Pine Script® indicator
by seanpark0828
SPY Trend-Based Buy Signals🔹 Overview This indicator identifies potential buy signals on any asset by combining MACD and Stochastic Oscillator crossovers, while using the SPY’s trend (via exponential moving averages) as a broader market filter. It helps traders stay aligned with macro momentum and avoid counter-trend entries. 🔍 How it works SPY Trend Filter (Daily Timeframe): Pulls SPY (S&P 500 ETF) data using EMAs (5, 20, 80) Categorizes SPY market trend with color codes: 🟢 Green: Strong uptrend (EMA5 > EMA20 > EMA80) 🟡 Yellow: Potential uptrend / early momentum (EMA5 < EMA20 > EMA80) 🔴 Red: Downtrend (EMA5 < EMA20 < EMA80) 🔵 Blue: Possible trend reversal or mixed trend (EMA5 > EMA20 < EMA80) Buy Signal Conditions (Combined Logic): A signal is only triggered when: - SPY trend is either yellow or blue (indicating a neutral-to-bullish or early recovery environment) -The Stochastic Oscillator's %D line is below 50, showing possible upside - A bullish MACD crossover occurs on the current symbol 🟢 Green signal: MACD crossover occurs below 0 (early reversal) 🟠 Orange signal: MACD crossover occurs above 0 (momentum continuation) 📈 Visual Output 🟢 Green label below the bar when an early reversal setup occurs 🟠 Orange label above the bar when a trend continuation signal appears ✅ Best Use Case Ideal for: Swing traders and position traders LEAPS (long-term options) traders aligning entries with SPY trend Anyone seeking clean, contextual entries filtered by market momentum ⚠️ Note: This indicator is most effective when used on fundamentally strong stocks that are sector leaders with solid earnings growth and market presence. Use technical signals as a complement to quality fundamentals. ℹ️ Clarification: The moving averages displayed on the chart (e.g., on QQQ) are for visual reference only, to help users understand the color logic of the SPY trend filter. The actual logic and signals are based on SPY’s moving averages, regardless of the charted symbol.
Pine Script® indicator
by Max-o-Flex
Aesthetic RSI [AlchimistOfCrypto]🌌 Aesthetic RSI – Unveiling the Fractal Forces of Markets 🌌 Category: Momentum Indicators 📈 "The RSI oscillator, formalized through an advanced mathematical prism, reveals the underlying fractal structures of price movements. This indicator draws inspiration from quantum principles of divergence-convergence where the probability of a return to equilibrium increases proportionally to the distance from the median point. Our implementation employs sophisticated algorithmic smoothing to filter out the stochastic noise inherent in financial markets, allowing visualization of the true momentum forces according to thermodynamic entropy principles applied to trading systems." 📊 Professional Trading Application The Aesthetic RSI is a visually stunning and mathematically refined take on the classic Relative Strength Index. With customizable settings, advanced smoothing, and eight unique visual palettes, it empowers traders to detect momentum shifts and divergences with unparalleled clarity. ⚙️ Indicator Configuration - Length 📏 The core parameter (default: 20) that determines the calculation period. - Lower values (8-14): Increase sensitivity for short-term trading. - Higher values (21-34): Provide stronger signals for position trading. - OverBought/OverSold Thresholds 🎯 Customizable boundaries (default: 75/25) to identify extreme market conditions. - Calibrate based on asset volatility: Higher volatility assets may need wider thresholds (80/20) to reduce false signals. - Style 🎨 Eight meticulously crafted visual palettes optimized for pattern recognition: - Miami Vice (default): High-contrast cyan/magenta scheme for spotting divergences. - Cyberpunk: Yellow/purple combo to highlight momentum shifts. - Classic: Traditional green/red for conventional analysis. - High Contrast: Maximum visual separation for traders with visual impairments. - Specialized palettes (Forest, Ocean, Fire, Monochrome): Tailored for diverse market conditions. - Mode Selection 🔄 - Full: Displays a complete gradient spectrum across the RSI range, emphasizing momentum transitions between 35-65. - OverZone: Focuses on actionable extreme zones, reducing noise in ranging markets. 🚀 How to Use 1. Adjust Length ⏰: Set the period based on your trading style (short-term or long-term). 2. Fine-Tune Thresholds 🎚️: Customize overbought/oversold levels to match the asset’s volatility. 3. Select a Palette 🌈: Choose a visual style that enhances your pattern recognition. 4. Choose Mode 🔍: Use "Full" for detailed momentum analysis or "OverZone" for extreme zone focus. 5. Spot Divergences ✅: Look for price-RSI divergences to anticipate reversals. 6. Trade with Precision 🛡️: Combine with other indicators for high-probability setups. 📅 Release Notes (April 2025) Aesthetic RSI blends quantum-inspired mathematics with artistic visualization, redefining momentum analysis. Stay tuned for future enhancements! ✨ 🏷️ Tags #Trading #TechnicalAnalysis #RSI #Momentum #Divergence #MultiTimeframe #TradingStrategy #RiskManagement #Forex #Stocks #Crypto #Bitcoin #AlgoTrading #DayTrading #SwingTrading #TheAlchimist #QuantumTrading #VisualTrading #PatternRecognition
Pine Script® indicator
by AlchimistOfCrypto
Oath KeeperOath Keeper - Advanced Money Flow & Market Dynamics Indicator A sophisticated indicator that analyzes market dynamics through money flow patterns, volume analysis, and liquidation detection to identify high-probability trading opportunities. Core Features: • Smart Money Flow Analysis: Proprietary calculation of institutional money movement • Volume-Enhanced Signals: Multi-timeframe volume confirmation • Liquidation Detection: Identifies potential forced liquidation events • Advanced Signal Classification: Regular, Super, and Fakeout signals Signal Types: 1. Regular Signals (Green/Purple Circles) • Volume-confirmed momentum shifts • Money flow threshold breaches • Institutional participation confirmation 2. Super Signals (Green/Purple Squares) • Deep oversold/overbought reversals • High-volume rejection patterns • Liquidation event confirmation 3. Fakeout Signals (Red X) • Rapid sentiment shifts • Trap detection • False breakout warnings Visual Components: • Dynamic Money Flow Line (White/Purple) • Order Flow Clouds (Green/Red with high transparency) • Reference Levels (20, 50, 80) • Multi-type Signal Markers • Color-coded momentum visualization Interpretation Guide: • Green Cloud: Bullish money flow dominance • Red Cloud: Bearish money flow dominance • Circle Markers: Standard reversals • Square Markers: High-conviction moves • X Markers: Potential trap zones Best Practices: • Most effective on 1H+ timeframes • Use with major trading pairs • Wait for candle close confirmation • Combine with support/resistance levels • Monitor volume confirmation • Use multiple timeframe analysis This indicator helps traders identify institutional money flow, potential liquidation events, and market reversals by analyzing volume patterns and money flow dynamics, providing multiple confirmation layers for trade decisions. Note: Performance varies with market conditions and timeframes. Always employ proper risk management.
Pine Script® indicator
by RickyTSpanish
Stochastic with 4 %K LinesQuad Rotation Stochastic Strategy – Indicator Description The Quad Rotation Strategy is a momentum-based technical analysis tool that overlays four distinct Stochastic %K lines on a single chart. Each line is calculated using a unique set of parameters, allowing traders to visualize and compare momentum signals across varying sensitivities — from fast-reacting setups to slower, trend-confirming ones. This multi-speed stochastic view is designed to help traders: Identify rotation points where shorter-term stochastic lines cross faster than longer-term lines, signaling early reversals or trend continuation. Confirm strength or weakness in price action by observing alignment or divergence among the %K lines. Fine-tune entries and exits by using fast %K lines for timing and slower ones for confirmation. 🔍 How It Works: Four separate %K lines are plotted, each with configurable Length and Smoothing. All lines are calculated using the standard Stochastic formula: (%K = SMA of (Close - Low) / (High - Low) over period) No %D lines are included to keep the focus on %K behavior across different speeds. Standard overbought (80), oversold (20), and midline (50) levels are provided for context. This indicator is best used in: Trend continuation setups where faster stochastics pull back to oversold while slower ones remain bullish. Reversal zones where all four %K lines converge or cross in extreme levels. Range-bound environments where confluence of extremes offers swing trade opportunities.
Pine Script® indicator
by JonathanVasquez
1
Reversal Strength Meter – Adib NooraniThe Reversal Strength Meter is an oscillator designed to identify potential reversal zones based on supply and demand dynamics. It uses smoothed stochastic logic to reduce noise and highlight areas where momentum may be weakening, signaling possible market turning points. 🔹 Smooth, noise-reduced stochastic oscillator 🔹 Custom zones to highlight potential supply and demand imbalances 🔹 Non-repainting, compatible across all timeframes and assets 🔹 Visual-only tool — intended to support discretionary trading decisions This oscillator assists scalpers and intraday traders in tracking subtle shifts in momentum, helping them identify when a market may be preparing to reverse — always keeping in mind that trading is based on probabilities, not certainties. 📘 How to Use the Indicator Efficiently For Reversal Trading: Buy Setup – When the blue line dips below the 20 level, wait for it to re-enter above 20. – Look for reversal candlestick patterns (e.g., bullish engulfing, hammer, or morning star). – Enter above the pattern’s high, with a stop loss below its low. Sell Setup – When the blue line rises above the 80 level, wait for it to re-enter below 80. – Look for bearish candlestick patterns (e.g., bearish engulfing, inverted hammer, or evening star). – Enter below the pattern’s low, with a stop loss above its high. 🛡 Risk Management Guidelines Risk only 0.5% of your capital per trade Book 50% profits at a 1:1 risk-reward ratio Trail the remaining 50% using price action or other supporting indicators
Pine Script® indicator
by GlobalMarketWizard
3
RSI VWAP POC [Uncle Sam Trading]Category: Oscillators, Volume, Market Profile Timeframe: Suitable for all timeframes Markets: Crypto, Forex, Stocks, Commodities Overview The RSI VWAP POC indicator is a powerful and innovative oscillator that combines the Relative Strength Index (RSI), Volume-Weighted Average Price (VWAP), and Point of Control (POC) from market profile analysis. Designed to provide traders with clear, high-probability trading signals, this indicator helps you identify key market levels, spot overbought/oversold conditions, and time your entries and exits with precision. Whether you’re a day trader, swing trader, or scalper, this free tool adds significant value to your trading strategy by offering a unique blend of momentum, volume, and market profile insights. How It Works This indicator integrates three core components to deliver actionable insights: RSI (Relative Strength Index): Measures momentum to identify overbought (above 70) and oversold (below 30) conditions, helping you anticipate potential reversals. VWAP (Volume-Weighted Average Price): Calculates a volume-weighted price benchmark, which is used to compute a more accurate, volume-sensitive RSI. This ensures the indicator reflects true market dynamics. POC (Point of Control): Derived from market profile analysis, the POC represents the price level with the highest traded volume in a session, acting as a critical support or resistance level. The indicator plots a smoothed RSI based on VWAP, overlaid with market profile data on a user-defined higher timeframe (default: 4H). The POC is displayed as a red line, with aqua bars indicating the value area where the majority of trading volume occurred. When the RSI crosses the POC, the indicator generates clear buy and sell signals: Strong Buy (SBU): RSI crosses above the POC in an oversold zone. Strong Sell (SBD): RSI crosses below the POC in an overbought zone. Additional features include: Background colors to highlight bullish (green) or bearish (red) trends. Shaded zones for overbought (70/60) and oversold (30/40) levels. Customizable settings to fit your trading style and timeframe. How This Indicator Adds Value The RSI VWAP POC indicator offers several key benefits that enhance your trading performance: High-Probability Signals: By combining RSI, VWAP, and POC, this indicator identifies trades at key market levels where price is likely to react, increasing your win rate. Improved Timing: Clear buy and sell signals, such as ‘SBU’ and ‘SBD’, help you enter and exit trades at optimal points, maximizing profitability. Risk Management: Overbought/oversold zones and trend confirmation via background colors help you avoid false signals, protecting your capital. Versatility: Suitable for all markets (crypto, forex, stocks) and timeframes, making it a valuable tool for traders of all experience levels. Time Efficiency: The indicator does the heavy lifting by analyzing momentum, volume, and market profile data, allowing you to focus on executing trades. Real-World Performance Example: On a 1-hour Bitcoin chart with a 4-hour higher timeframe, this indicator identified a strong sell signal on April 6th at 12:00 ($82,000), leading to a 9% drop to $74,600. A subsequent strong buy signal on April 7th at 04:00 ($76,200) captured a 6% rise to $81,200 – a potential 25% profit with 5x leverage if exited at 5%. How to Use Add the Indicator: Search for “RSI VWAP POC ” in TradingView’s indicator library and add it to your chart. Set Your Timeframe: The indicator works on any timeframe but is optimized for a 1-hour chart with a 4-hour higher timeframe (set in the settings). Interpret Signals: Look for ‘SBU’ (strong buy) labels when the RSI crosses above the POC in an oversold zone, indicating a potential buying opportunity. Look for ‘SBD’ (strong sell) labels when the RSI crosses below the POC in an overbought zone, signaling a potential selling opportunity. Use the background colors (green for bullish, red for bearish) to confirm the trend. Combine with Your Strategy: Use the indicator alongside your existing analysis (e.g., support/resistance, candlestick patterns) for best results. Settings and Customization The indicator is highly customizable to suit your trading needs: RSI Length (Default: 14): Adjust the sensitivity of the RSI. Use a shorter length (e.g., 10) for scalping, or a longer length (e.g., 20) for smoother signals. EMA Smoothing Length (Default: 3): Smooths the RSI line. Increase to 5 or 7 for less choppy signals in volatile markets. Higher Timeframe (Default: 240 minutes): Set to 240 (4 hours) for a 1-hour chart. Adjust based on your chart’s timeframe (e.g., 60 minutes for a 15-minute chart). Value Area Percentage (Default: 100%): Defines the size of the value area around the POC. Lower to 70% for a tighter focus on key levels. Overbought/Oversold Thresholds (Defaults: 70/30): Adjust these levels to match market conditions (e.g., 80/20 for trending markets). Show POC Line (Default: True): Toggle the red POC line on or off. Show Buy/Sell Signals: Enable ‘Show Strong Breakup Signals’ and ‘Show Strong Breakdown Signals’ to focus on high-probability trades. Why Choose This Indicator? The RSI VWAP POC indicator stands out by offering a unique combination of momentum, volume, and market profile analysis in a single, easy-to-use tool. It’s designed to help traders of all levels make informed decisions, reduce risk, and increase profitability. Whether you’re trading Bitcoin, forex pairs, or stocks, this indicator provides the clarity and precision you need to succeed.
Pine Script® indicator
by UncleSamTrading
1
Multi Oscillator OB/OS Signals v3 - Scope TestIndicator Description: Multi Oscillator OB/OS Signals Purpose: The "Multi Oscillator OB/OS Signals" indicator is a TradingView tool designed to help traders identify potential market extremes and momentum shifts by monitoring four popular oscillators simultaneously: RSI, Stochastic RSI, CCI, and MACD. Instead of displaying these oscillators in separate panes, this indicator plots distinct visual symbols directly onto the main price chart whenever specific predefined conditions (typically related to overbought/oversold levels or line crossovers) are met for each oscillator. This provides a consolidated view of potential signals from these different technical tools. How It Works: The indicator calculates the values for each of the four oscillators based on user-defined settings (like length periods and price sources) and then checks for specific signal conditions on every bar: Relative Strength Index (RSI): It monitors the standard RSI value. When the RSI crosses above the user-defined Overbought (OB) level (e.g., 70), it plots an "Overbought" symbol (like a downward triangle) above that price bar. When the RSI crosses below the user-defined Oversold (OS) level (e.g., 30), it plots an "Oversold" symbol (like an upward triangle) below that price bar. Stochastic RSI: This works similarly to RSI but is based on the Stochastic calculation applied to the RSI value itself (specifically, the %K line of the Stoch RSI). When the Stoch RSI's %K line crosses above its Overbought level (e.g., 80), it plots its designated OB symbol (like a downward arrow) above the bar. When the %K line crosses below its Oversold level (e.g., 20), it plots its OS symbol (like an upward arrow) below the bar. Commodity Channel Index (CCI): It tracks the CCI value. When the CCI crosses above its Overbought level (e.g., +100), it plots its OB symbol (like a square) above the bar. When the CCI crosses below its Oversold level (e.g., -100), it plots its OS symbol (like a square) below the bar. Moving Average Convergence Divergence (MACD): Unlike the others, MACD signals here are not based on fixed OB/OS levels. It identifies when the main MACD line crosses above its Signal line. This is considered a bullish crossover and is indicated by a specific symbol (like an upward label) plotted below the price bar. It also identifies when the MACD line crosses below its Signal line. This is a bearish crossover, indicated by a different symbol (like a downward label) plotted above the price bar. Visualization: All these signals appear as small, distinct shapes directly on the price chart at the bar where the condition occurred. The shapes, their colors, and their position (above or below the bar) are predefined for each signal type to allow for quick visual identification. Note: In the current version of the underlying code, the size of these shapes is fixed (e.g., tiny) and not user-adjustable via the settings. Configuration: Users can access the indicator's settings to customize: The calculation parameters (Length periods, smoothing, price source) for each individual oscillator (RSI, Stoch RSI, CCI, MACD). The specific Overbought and Oversold threshold levels for RSI, Stoch RSI, and CCI. The colors associated with each type of signal (OB, OS, Bullish Cross, Bearish Cross). (Limitation Note: While settings exist to toggle the visibility of signals for each oscillator individually, due to a technical workaround in the current code, these toggles may not actively prevent the shapes from plotting if the underlying condition is met.) Alerts: The indicator itself does not automatically generate pop-up alerts. However, it creates the necessary "Alert Conditions" within TradingView's alert system. This means users can manually set up alerts for any of the specific signals generated by the indicator (e.g., "RSI Overbought Enter," "MACD Bullish Crossover"). When creating an alert, the user selects this indicator, chooses the desired condition from the list provided by the script, and configures the alert actions. Intended Use: This indicator aims to provide traders with convenient visual cues for potential over-extension in price (via OB/OS signals) or shifts in momentum (via MACD crossovers) based on multiple standard oscillators. These signals are often used as potential indicators for: Identifying areas where a trend might be exhausted and prone to a pullback or reversal. Confirming signals generated by other analysis methods or trading strategies. Noting shifts in short-term momentum. Disclaimer: As with any technical indicator, the signals generated should not be taken as direct buy or sell recommendations. They are best used in conjunction with other forms of analysis (price action, trend analysis, volume, fundamental analysis, etc.) and within the framework of a well-defined trading plan that includes risk management. Market conditions can change, and indicator signals can sometimes be false or misleading.
Pine Script® indicator
by ozgurzari
2