Quantitativeanalysis — Indicators and Strategies

S&P 500 & Normalized CAPE Z-Score Analyzer This macro-focused indicator visualizes the historical valuation of the U.S. equity market using the CAPE ratio (Shiller P/E), normalized over its long-term average and standard deviations. It helps traders and investors identify overvaluation and undervaluation zones over time, combining both statistical signals and historical context. 💡 Why It’s Useful This indicator is ideal for macro traders and long-term investors looking to contextualize equity valuations across decades. It helps identify statistical extremes in valuation by referencing the standard deviation of the CAPE ratio relative to its long-term mean. The overlay of S&P 500 price with valuation zones provides a visual confirmation tool for macro decisions or timing insights. It includes: ✅ Three display modes: -S&P 500 (color-coded by CAPE valuation zone) -Normalized CAPE (vs. long-term mean) -CAPE Z-Score (standardized measure) 🎯 How to Interpret Dynamic coloring of the S&P 500 price based on CAPE valuation: 🔴 Z > +2σ → Highly Overvalued 🟠 Z > +1σ → Overvalued ⚪ -1σ < Z < +1σ → Neutral 🟢 Z < -1σ → Undervalued ✅ Z < -2σ → Strong Buy Zone -Live valuation label showing the current CAPE, Z-score, and zone. -Macro event shading: major historical events (e.g. Great Depression, Oil Crisis, Dot-com Bubble, COVID Crash) are shaded on the chart for context. ✅ Built-in alerts: CAPE > +2σ → Potential risk zone CAPE < -2σ → Potential opportunity zone 📊 Use Cases This indicator is ideal for: 🧠 Macro traders seeking long-term valuation extremes. 📈 Portfolio managers monitoring systemic valuation risk. 🏛️ Long-term investors timing strategic allocation shifts. 🧪 How It Works CAPE ratio (Shiller PE) is retrieved from Quandl (MULTPL/SHILLER_PE_RATIO_MONTH). The script calculates the long-term average and standard deviation of CAPE. The Z-score is computed as: (CAPE - Mean) / Standard Deviation Users can switch between: S&P 500 chart, color-coded by CAPE valuation zones. Normalized CAPE, centered around zero (historic mean). CAPE Z-score, showing statistical positioning directly. Visual bands represent +1σ, +2σ, -1σ, -2σ thresholds. You can switch between modes using the “Display” dropdown in the settings panel. 📊 Data Sources CAPE: MULTPL/SHILLER_PE_RATIO_MONTH via Quandl S&P 500: Monthly close prices of SPX (TradingView data) All data updated on monthly resolution This is not a repackaged built-in or autogenerated script. It’s a custom-built and interactive indicator designed for educational and analytical use in macroeconomic valuation studies.

Advanced Volume-Driven Breakout Signals The "Advanced Volume-Driven Breakout Signals" indicator is a cutting-edge tool designed to help traders identify high-potential trading opportunities through sophisticated volume analysis techniques. This indicator integrates volume flow analysis, moving averages, and Relative Volume (RVOL) to provide a comprehensive view of market conditions, going beyond traditional Volume Spread Analysis (VSA) methods. Key Features: Volume Flow Analysis: Distinguishes bullish and bearish volume flows with distinct colors, making it easier to visualize market sentiment and potential breakout points. Volume Flow Moving Averages: Calculates moving averages for volume using various methods (SMA, EMA, WMA, HMA, VWMA), accommodating different trading strategies. This includes settings for adjusting the type of moving average and its period, as well as thresholds for high, medium, and low volume levels. Volume Spikes Detection: Identifies significant volume spikes based on user-defined multipliers and moving averages, highlighting unusual trading activity. Volume MA Cloud Settings: Computes general moving averages of volume to track trends and detect deviations. This feature includes options to select different moving average types and adjust thresholds for detecting high volume activity. Relative Volume (RVOL): Measures current volume relative to historical averages, triggering signals when RVOL exceeds predefined thresholds, indicating notable changes in trading activity. Entry Conditions: Provides clear long and short entry signals based on combined volume flow conditions and RVOL, offering actionable trading opportunities. Volume Visualization: — Bullish Volume Flow: Light and dark green bars indicate bullish volume flow. — Bearish Volume Flow: Light and dark red bars denote bearish volume flow. — High Volume Bars: Highlighted in yellow, and extreme volume bars in orange for additional context. These bars are plotted for visual aid and do not directly influence trade signals, focusing instead on the quality and strength of the volume flow. Alerts: Allows users to create alert notifications for long and short entry signals when the criteria are met, enabling traders to respond promptly to trading opportunities. Usage: Overlay: Apply the indicator directly to your price chart to visualise real-time signals and volume conditions. Customisable: Adjust settings for moving averages, RVOL, and other parameters to match your trading strategy and preferences. Comparison to VSA Scripts: The "Advanced Volume-Driven Breakout Signals" indicator extends beyond traditional VSA scripts by incorporating a wider range of analytical features. While VSA primarily focuses on volume spread patterns and price action, this indicator offers enhanced functionality with advanced RVOL metrics, customizable moving averages, and detailed volume spike detection, making it a more versatile tool for identifying breakout opportunities and managing trades. It is particularly effective when used alongside key levels and order blocks. Acknowledgements: Special thanks to @oh92 and @goofoffgoose for their invaluable scripts, which served as inspiration in the development of this advanced trading indicator. Notes: The script is continually evolving, with ongoing refinements aimed at enhancing accuracy and performance.

GARCH Volatility Estimation - The Quant Science The GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model is a statistical model used to forecast the volatility of a financial asset. This model takes into account the fluctuations in volatility over time, recognizing that volatility can vary in a heteroskedastic (i.e., non-constant variance) manner and can be influenced by past events. The general formula of the GARCH model is: σ²(t) = ω + α * ε²(t-1) + β * σ²(t-1) where: σ²(t) is the conditional variance at time t (i.e., squared volatility) ω is the constant term (intercept) representing the baseline level of volatility α is the coefficient representing the impact of the squared lagged error term on the conditional variance ε²(t-1) is the squared lagged error term at the previous time period β is the coefficient representing the impact of the lagged conditional variance on the current conditional variance In the context of financial forecasting, the GARCH model is used to estimate the future volatility of the asset. HOW TO USE This quantitative indicator is capable of estimating the probable future movements of volatility. When the GARCH increases in value, it means that the volatility of the asset will likely increase as well, and vice versa. The indicator displays the relationship of the GARCH (bright red) with the trend of historical volatility (dark red). USER INTERFACE Alpha: select the starting value of Alpha (default value is 0.10). Beta: select the starting value of Beta (default value is 0.80). Lenght: select the period for calculating values within the model such as EMA (Exponential Moving Average) and Historical Volatility (default set to 20). Forecasting: select the forecasting period, the number of bars you want to visualize data ahead (default set to 30). Design: customize the indicator with your preferred color and choose from different types of charts, managing the design settings.