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Carte Stochastic Volatility Mastery Danny Munrow

Stochastic Volatility Mastery

From Heston to SABR in Python: Calibrate, Simulate, and Price Options with Heston, SABR, and Bates Models Using Production-Ready Python

Autor: Danny Munrow, James Preston
Limbă: engleză
Legare: Carte broșată
Editura: Independently published
Disponibilitate: În depozitul extern
Expediem în 10-18 zile
184.05 lei
Reactive PublishingVolatility isn't constant, and if your models assume it is, your PnL will suffer....

Informații despre carte

Autor
Danny Munrow, James Preston
Limbă
engleză
Legare
Carte - Carte broșată
Publicat
2025
Pagini
628
EAN
9798266142534
Enbook ID
53226331
Editura
Independently published
Greutate
748
Dimensiuni
152 x 229 x 40

Descriere completă

Reactive Publishing

Volatility isn't constant, and if your models assume it is, your PnL will suffer. Stochastic Volatility Mastery is the definitive guide to building, calibrating, and deploying realistic volatility models that match how markets actually behave.

This book takes you beyond Black-Scholes, showing you how to implement Heston, SABR, and Bates models step-by-step in Python, calibrate them to market smiles, and use them to price options and manage risk at scale.

Inside, you'll master:

  • Heston Model Foundations - Closed-form solutions, Monte Carlo simulation, and Greeks.

  • SABR Calibration & Pricing - Fitting skew/smile and handling extreme strikes.

  • Bates Model with Jumps - Capturing jump risk for better crisis scenario pricing.

  • FFT and Monte Carlo Methods - Fast, accurate option pricing approaches.

  • Practical Calibration Workflows - Optimize parameters with least-squares, MLE, and global search.

  • Speed Optimization - Use Numba, JAX, and vectorization for real-time execution.

Complete with production-quality Python code and calibration examples, this book bridges theory and practice, giving quants, traders, and developers a toolkit for robust, market-consistent option pricing that holds up under stress.