Welcome to the GitHub repository for "Stochastic Calculus for Quants - A Simplified Guide". This comprehensive document aims to break down the complexities of stochastic calculus, making it accessible for students, professionals, and anyone interested in quantitative finance.
This guide dives deep into the core concepts of stochastic calculus as applied in quantitative finance. By simplifying complex terminologies and providing real-world analogies, the guide ensures an intuitive understanding of the subject.
- Simplified Explanations: Each topic is broken down in layman's terms to ensure clarity.
- Visual Representations: Detailed graphs and plots to illustrate concepts.
- Relevant Examples: Real-world examples from the financial domain to provide context.
- Probability & Random Walks
- Sigma Algebra & Filtrations
- Wiener Process & Martingales
- Ito's Lemma & P-Q Measures
- Geometric Brownian Motion
- Black-Scholes Model
- Monte Carlo Simulations ... and more!
The guide is available as a PDF in this repository. Simply navigate to the file named Stochastic_Calculus_for_Quants.pdf and download it.
Your feedback is invaluable! If you have suggestions, corrections, or want to contribute to this guide, feel free to raise an issue or submit a pull request. """