Volatility Trading Strategies with Python
Volatility Trading Strategies with Python: From VIX to Vega Neutral Portfolios: Master Implied Volatility, Forecasting, and Risk-Neutral Trading in Options Markets by Hayden Van Der Post, Alice Schwartz
English | October 2, 2025 | ISBN: N/A | ASIN: B0FTTBCSXH | 894 pages | EPUB | 0.76 Mb
English | October 2, 2025 | ISBN: N/A | ASIN: B0FTTBCSXH | 894 pages | EPUB | 0.76 Mb
Reactive Publishing
Master Implied Volatility, Forecasting, and Risk-Neutral Trading in Options Markets
Trade Volatility Like a Professional Quant
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.
What You’ll Learn
- 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