Stochastic Calculus & Brownian Motion in Quant Finance: A Practical Guide to Option Pricing, Volatility Modeling, and

Reactive Publishing
This book delivers the mathematical foundations of modern quantitative finance with a direct, applied focus. Built around stochastic calculus and Brownian motion, it shows how continuous-time models underpin option pricing, risk management, and trading strategies used on today’s desks.

You’ll move from first principles to advanced applications, learning not only the theory but also how to implement it in practice. Each chapter connects core concepts to real trading problems, so the math isn’t just abstract, it’s actionable.


What You’ll Learn
Construction and properties of Wiener processes and Ito integrals

Application of Ito’s Lemma in derivatives pricing

Stochastic differential equations (SDEs) and their financial interpretation

How stochastic calculus powers the Black-Scholes model, Greeks, and hedging

Practical approaches to volatility modeling and path-dependent options

Python-based Monte Carlo methods and algorithmic trading applications


Who It’s For
Quantitative analysts, traders, and risk managers

Financial engineers and graduate students in finance

Python developers working in quantitative modeling

Professionals seeking a practical, mathematically rigorous guide

This is not a “light” introduction, it’s a practical reference for people serious about quant finance.