MSc in Mathematical and Computational Finance

at University of Oxford

The course lays the foundation for further research in academia or for a career as a quantitative analyst in a financial or other institution.

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 focuses 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)

The second term will be a combination of core material, offering 48 hours of lectures (18 hours of classes) and 48 hours of electives (students will choose four 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
 

• Stochastic Volatility (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 Numerical Methods (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)
• Optimisation (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)

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.

Proven and potential academic excellence

Degree-level qualifications

As a minimum, applicants should hold or be predicted to achieve the following UK qualifications or their equivalent:
 

• a first-class or strong upper second-class undergraduate degree with honours in mathematics or a related discipline. 

Applicants should have a background in probability, statistics, ordinary and partial differential equations, linear algebra and analysis. They must demonstrate their aptitude for, and knowledge of, mathematics, particularly in the area of real analysis, through their performance at interview. Applicants with undergraduate degrees that are not purely mathematical will still be expected to demonstrate they have sufficient knowledge to perform well on the course.

For applicants with a degree from the USA, the minimum GPA sought is 3.6 out of 4.0.

GRE General Test scores

No Graduate Record Examination (GRE) or GMAT scores are sought.

Other qualifications, evidence of excellence and relevant experience

Publications are not expected.

English language proficiency

Minimum scores required to meet the University's higher level requirement

IELTS Academic

 7.5  

TOEFL iBT, including the 'Home Edition'

110

Home    
£39,280

Overseas    
£39,280

MSc graduates have been recruited by prominent investment banks and hedge funds. Many past students have also progressed to PhD-level studies at leading universities in Europe and elsewhere.