Stochastic Volatility Modeling in Derivative Pricing with Python
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Stochastic Volatility Modeling in Derivative Pricing with Python: Advanced Quantitative Techniques for Options and Risk Management

Stochastic Volatility Modeling in Derivative Pricing with Python: Advanced Quantitative Techniques for Options and Risk Management


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About the Book

Reactive PublishingTraditional financial models like Black-Scholes assume constant volatility, but real-world markets exhibit stochastic and dynamic volatility patterns that significantly impact derivative pricing and risk management. Stochastic Volatility Models (SVMs)-such as the Heston, SABR, and GARCH models-offer a more accurate framework for pricing options, managing volatility risk, and improving portfolio hedging strategies. This book provides a comprehensive, Python-driven approach to implementing stochastic volatility models in quantitative finance, algorithmic trading, and derivative pricing. Readers will explore mathematical foundations, model calibration techniques, and practical Python implementations for modern risk analysis. Key Topics Covered: Introduction to Stochastic Volatility Models - Why standard models fail and the need for advanced volatility modeling Heston Model Implementation - Simulating stochastic volatility and calibrating Heston's model to market data SABR Model for Interest Rate Derivatives - Understanding the stochastic alpha-beta-rho framework for options pricing GARCH & EGARCH Models - Modeling volatility clustering and leverage effects in financial time series Monte Carlo & PDE Methods - Using numerical techniques to solve complex derivative pricing models Python Implementation & Optimization - Hands-on coding with NumPy, SciPy, and TensorFlow for scalable computations Designed for quants, algorithmic traders, and risk analysts, this book bridges the gap between theoretical finance and real-world implementation with detailed explanations, step-by-step coding tutorials, and case studies using real market data. Master the power of stochastic volatility modeling-Get your copy today!


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Product Details
  • ISBN-13: 9798314073650
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 229 mm
  • No of Pages: 414
  • Returnable: N
  • Sub Title: Advanced Quantitative Techniques for Options and Risk Management
  • Width: 152 mm
  • ISBN-10: 8314073652
  • Publisher Date: 14 Mar 2025
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Spine Width: 22 mm
  • Weight: 603 gr


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Stochastic Volatility Modeling in Derivative Pricing with Python: Advanced Quantitative Techniques for Options and Risk Management
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