MSc Mathematical Finance

Challenge yourself with a high-level mix of mathematic and finance disciplines

This mathematically rigorous course is unique in providing training from three top departments at Warwick: Statistics, Mathematics and Warwick Business School. It enables you to develop and apply the quantitative skills in machine learning, computational statistics and mathematical finance used in the financial markets and the finance industry. 

Build on your strong mathematical background to gain both a deep theoretical and conceptual knowledge of finance, together with the requisite high-level probability, statistics and mathematics, to enable you to undertake advanced quantitative modelling. Lab work will give you hands-on experience of using software packages for simulations and time series analysis, as well as learning programming for quantitative finance in three core languages: Python, C++ and R. 

Our departments benefit from excellent links to key financial institutions and employers, and this course has benefited from industry recommendations. 

Discover more about our course structure on the Statistics Department website. 

Please note that this course was previously named MSc Financial Mathematics.

  • Application Deadline 2 August 2024
  • Start Date September 2024
  • Duration 1 year
  • Location Warwick Campus
  • Format Full-time
  • UK Fees £32,600 *
  • EU/International Fees £38,850 *

* See fees and funding for fees breakdown.

4 Nationalities (2023 cohort)
18 Cohort size
22 Average age


  • A unique chance to be taught by three leading academic departments to gain a deep insight into financial mathematics 

  • Uncover cutting-edge quantitative theory and practice with a range of specialist modules 

  • Dedicated careers coaching by specialists in the Finance industry and finance-related roles. 

What our graduates do
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My course gave me a foundation of financial knowledge which I've applied throughout my career at PwC."
Sofia Asatridi Management Consultant, PwC,
MSc Finance & Economics (2011 - 2012)
Student experiences
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