Stochastic Calculus for Finance A Practical Guide for Quantitative Analysts and Traders

This book covers:
Brownian motion & stochastic processes - The foundation of modern financial modeling
Itô calculus & stochastic differential equations (SDEs) - Key tools for derivative pricing
The Black-Scholes model & risk-neutral pricing - Understand the math behind options
Jump diffusion & mean-reverting models - Improve volatility forecasting
Numerical methods & Monte Carlo simulations - Real-world applications in Python
Heston model & stochastic volatility - More accurate option pricing strategies
Featuring real-world case studies, Python code examples, and step-by-step solutions, this book bridges the gap between theoretical concepts and practical implementation.
Who This Book is For:
Quantitative Analysts & Traders - Improve your models and trading algorithms
Financial Engineers & Risk Managers - Gain deeper insights into pricing and hedging
Students & Academics - A must-have resource for mastering stochastic calculus in finance
Take your financial modeling skills to the next level-get your copy today!