MSc in Mathematical and Computational Finance - Course components

• Introduction to Partial Differential Equations
• Introduction to Probability
• Introduction to Statistics
• Python
• Financial Markets and Instruments
• Markdown Reports 

• Stochastic Calculus
• Financial Derivatives
• Numerical Methods 
• Statistics and Financial Data Analysis

Computing Course

• Financial Computing with C++ 1 -16 hours of lectures in Michaelmas Term

• Fixed Income and Credit
• Stochastic Control
• Quantitative Risk Management
• Deep Learning

• Advanced Monte Carlo methods
• Advanced Numerical methods
• Advanced Volatility Modelling
• Asset Pricing
• Market Microstructure and Algorithmic Trading
• Decentralised Finance

• Financial Computing with C++ 2 - three week course at the end of Hilary Term (weeks 6, 7 and 8)

Following the second set of exams, students write a dissertation on a topic related to mathematical modelling and computational methods in finance.

MSc dissertations may be prepared in conjunction with an industry internship (possibly extending beyond the timeframe of the MSc dissertation) focused on quantitative modelling in finance.