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Volatility is not just a byproduct of options, it's an asset class in its own right. Successful traders know how to analyze, forecast, and trade volatility to build portfolios that thrive in both calm and chaotic markets.
Volatility Trading Strategies with Python gives you a complete framework for mastering volatility. From the VIX index to vega-neutral hedging, you'll learn how to design, test, and execute strategies that capture opportunities hidden in the volatility surface.
Understanding Volatility: Historical vs. implied volatility, term structure, and skew.
VIX and Volatility Indices: How they're built, traded, and used in hedging.
Portfolio Construction: Delta-hedged, vega-neutral, and gamma-neutral strategies.
Trading Strategies: Straddles, strangles, calendar spreads, and dispersion trades.
Forecasting Models: GARCH, stochastic volatility, and machine learning approaches.
Python Implementation: Build volatility forecasting models and trading systems step-by-step.
Python (Pandas, NumPy, SciPy, Statsmodels)
Options data structures and volatility surfaces
GARCH and stochastic volatility models
Backtesting engines for volatility-driven strategies
Options traders seeking to specialize in volatility
Quants and analysts designing risk-hedged strategies
Data scientists expanding into financial markets
Python developers applying quantitative methods in trading
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