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MSc Mathematical Finance

Covid 19 will - in all probability - affect the delivery of teaching and assessment in 21/22. The various Departments involved in MSMF are still developing their policies for 21/22, but the hope is to have (much) more face-to-face delivery than was possible in 20/21. However, these policies are continually evolving depending on the latest advice from the University, and indeed the UK government.
There are many benefits from being on campus, of which perhaps the most significant is the ability to interact in a meaningful way with your peers. Although it is likely that the University will allow remote study for the first few weeks at least, the best experience will be available to those who are physically present at the University.
The Warwick MSc in Mathematical Finance (MSMF) builds on the success of the long-running Financial Mathematics course which was one of the first of its kind in the UK and occupied a leading position in the sector. The MSc in Mathematical Finance reflects the dramatic changes in the nature of the Quantitative Finance industry in recent years, with the introduction of new financial instruments & markets, technological innovation and the changes in the regulatory framework.
 
This mathematically rigorous course is aimed at candidates wishing to either
  • pursue a career in the mathematically intensive segment of the Quantitative Finance sector or
  • do a quantitative PhD in the area of Financial Mathematics broadly understood, including Algorithmic Computational Methods (such as Machine Learning) in Finance.

One of the unique features of MSMF at Warwick is that it is taught as a collaborative effort by three world-leading departments, giving the students unique access to the experts in relevant areas of this multifaceted masters programme:

      Structure of the course: four pillars representing the areas of expertise required for our students' future employment and three stages of development: “foundations” (prerequisite skills in the core areas), “specialisation” (bundles of electives to match interest and career destination), and finally "application" of acquired skills and knowledge (dissertation):

      • The three stages broadly follow the three academic terms:
        • Term 1 (Autumn): lays down the foundational skills in the “4 Pillars”
        • Term 2 (Spring): provides specialisation and “pathway”-specific skills
        • Term 3 (Summer): assurance of learning by applying skills to your dissertation
        • A “Backbone” (spanning all terms) develops Programming / Data skills
      • The 4 “Pillars” correspond to the core modules in Term 1 and Term 2 (see Course Structure for details):
        • Financial Statistics
        • Financial Mathematics
        • Asset Pricing and Risk
        • Simulation and Machine Learning for Finance

      Generous scholarship programme: many students in the MSc in Financial Mathematics have in the last few years received scholarships worth between 25% to 50% of the fee. See the Fees and Funding section for more details.

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