ABOUT
This is a course for advanced undergraduate and graduate students with an aptitude and interest in quantitative methods. The students will be exposed to no-arbitrage-based deep and beautiful ideas underlying mathematical finance. For this they will get an adequate exposure to stochastic calculus. Stochastic calculus is also relevant for the increasingly mainstream diffusion-based generative AI. Register here.
40 HOURS OF
RIGOROUS LECTURES +
STUDENT-LED PROJECTS
COURSE CONTENT 📚
- Review of Measure-Theoretic Probability
- Martingales & Brownian Motion
- Stochastic Calculus & Stochastic Integration
- Itô’s Formula & Girsanov’s Theorem
- Stochastic Differential Equations & PDE Connections
- Discrete & Continuous-Time Pricing Theory
- Stochastic Volatility Models & Interest Rate Models
- PDEs in Finance
ELIGIBILTY 👨🏻🎓
- Advanced undergraduates & master’s-level students
- Strong background in Probability, Linear Algebra, and Analysis
- Aptitude & interest in quantitative methods
LECTURES 🎥
- Lecture 1: Introduction to Derivatives (August 26, 2025)
- Lecture 2: Basic Probability & Discrete Finance (August 28, 2025)
- Lecture 3: Risk Neutral Measure & Complete Markets (September 2, 2025)
- Lecture 4: Measure Theory Overview: Sigma Algebras (September 4, 2025)
- Lecture 5: Lebesgue Integral and Convergence (September 9, 2025)