Course summary

The information provided on this page was correct at the time of publication (November 2024). For complete and up-to-date information about this course, please visit the relevant University of Oxford course page via www.graduate.ox.ac.uk/ucas. The MSc in Mathematical and Computational Finance provides you with a strong mathematical background and the skills necessary to apply your expertise to the solution of problems. You will develop skills to formulate mathematical problems that are based on the needs of the financial industry. You will carry out relevant mathematical and financial analysis, develop and implement appropriate tools to present and interpret model results. The course lays the foundation for further research in academia or for a career as a quantitative analyst in a financial or other institution. Structure and content Term one You will take four introductory courses in the first week. The introductory courses cover partial differential equations, probability and statistics, financial markets and instruments, and Python. The first term will then focus on compulsory core material, offering 64 hours of lectures and 24 hours of classes, plus one compulsory computing course offering 16 hours of lectures. Core courses Stochastic Calculus (16 lectures, and 4 classes of 1.5 hours each) Financial Derivatives (16 lectures, and 4 classes of 1.5 hours each) Numerical Methods (16 lectures, and 4 classes of 1.5 hours each) Statistics and Financial Data Analysis (16 lectures, and 4 classes of 1.5 hours each) Computing course Financial computing with C++ I (16 hours of lectures, plus 4 classes of 2 hours each over weeks 1-9) Term two The second term will be a combination of core material, offering 48 hours of lectures (18 hours of classes) and 48 hours of electives. Core courses Deep Learning (16 lectures, and 4 classes of 1.5 hours each) Quantitative Risk Management (8 lectures, and 2 classes of 1.5 hours each) Stochastic Control (8 lectures, and 2 classes of 1.5 hours each) Fixed Income (16 lectures, and 4 classes of 1.5 hours each) Elective courses A number of elective courses will be offered, of which you will choose four options. Courses usually offered include: Advanced Volatility Modelling (8 lectures, and 2 classes of 1.5 hours each) Advanced Monte Carlo Methods (8 lectures, and 2 classes of 1.5 hours each) Advanced Topics in Computational Finance (8 lectures, and 2 classes of 1.5 hours each) Asset Pricing (8 lectures, and 2 classes of 1.5 hours each) Market Microstructure and Algorithmic Trading (8 lectures, and 2 classes of 1.5 hours each) Decentralised Finance (8 lectures, and 2 classes of 1.5 hours each) Computing course Financial computing with C++ II (24 hours of lectures and classes) Term three The third term is mainly dedicated to a dissertation project which is to be written on a topic chosen in consultation with your supervisor. This may be prepared in conjunction with an industry internship.