MSc Financial and Computational Mathematics
Course Overview
This rigorous course equips students with the advanced mathematical and computational techniques required for modern quantitative finance. It delves into complex topics like measure-theoretic probability, stochastic calculus, and partial differential equations to model markets, price derivatives, and manage risk. The curriculum is heavily computational, providing hands-on experience with essential programming languages and the option to study cutting-edge machine learning applications.
Key Program Highlights
- Rigorous grounding in measure-theoretic probability and stochastic processes
- Advanced computational methods using industry-relevant software (Python, R, C#)
- Elective option to study machine learning for financial applications
- Focus on real-world problems like derivative pricing and algorithmic trading
- Designed for those with strong prior knowledge of mathematics and programming
Course Overview
This rigorous course equips students with the advanced mathematical and computational techniques required for modern quantitative finance. It delves into complex topics like measure-theoretic probability, stochastic calculus, and partial differential equations to model markets, price derivatives, and manage risk. The curriculum is heavily computational, providing hands-on experience with essential programming languages and the option to study cutting-edge machine learning applications.
Key Program Highlights
- Rigorous grounding in measure-theoretic probability and stochastic processes
- Advanced computational methods using industry-relevant software (Python, R, C#)
- Elective option to study machine learning for financial applications
- Focus on real-world problems like derivative pricing and algorithmic trading
- Designed for those with strong prior knowledge of mathematics and programming
