Cass Business School

City, University of London

Financial Mathematics

The MSc Financial Mathematics draws on tools from applied mathematics, computer science, statistics and economic theory to prepare you for roles in which you will combine in-depth knowledge of financial products and risk with sophisticated technical and programming skills. You will acquire solid knowledge of probability theory and stochastic processes, numerical analysis and programming languages, asset pricing theory and risk analysis, with special emphasis on valuation and risk management. Typical career paths of graduates from our MSc Financial Mathematics include research positions (in both financial and academic institutions), or roles involving the development, management and improvement of derivatives models using advanced programming languages, and model validation such as Equity/Equity Derivatives Quant, Quantitative Financial Engineer, or Quantitative Risk Analyst. This programme is rigorous with respect to the mathematics but also places great emphasis on linking theory with real world developments. You will often be exposed to the teaching of real world practitioners from the City of London.

Entry requirements

MSc: A UK 2.1 or above, or the equivalent from an overseas institution; and Previous degree must be in a highly quantitative subject such as mathematics, physics or engineering, having covered areas such as calculus, statistics, probability theory and linear algebra. Transcript/interim transcript; Current module list if still studying; CV; Personal statement (500-600 words); IELTS result, if report available; Confirmation of professional qualification examinations/exemptions/passes, if applicable; Two references; and Work experience is not a requirement of this course. For a successful application to receive an unconditional status all documents must be verified, so an original or certified copy of the degree transcript must be sent by post to Specialist Masters Programme Office, 106 Bunhill Row, London, EC1Y 8TZ, UK.

Course modules

Term 1: asset pricing; numerical methods 1: foundations; mathematical models for financial derivatives; stochastic calculus. Term 2: fixed income securities; numerical methods 2: applications in finance; risk analysis; advanced stochastic modelling methods in finance. Term 3: five electives or one elective and a business research project.

Assessment methods

To satisfy the requirements of the degree programme, students must complete: nine core courses and five electives; or one elective and a Business Research Project.

Sponsorship information

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Qualification Study mode Start month Fee Course duration
MSc Full-time September 2019 25,500 per Whole course (Northern Ireland) 1 Years
MSc Full-time September 2019 25,500 per Whole course (EU) 1 Years
MSc Full-time September 2019 25,500 per Whole course (Wales) 1 Years
MSc Full-time September 2019 25,500 per Whole course (Scotland) 1 Years
MSc Full-time September 2019 25,500 per Whole course (England) 1 Years
MSc Full-time September 2019 25,500 per Whole course (International) 1 Years

Campus details

Campus name Town Postcode Region Main campus Campus Partner
Cass Business School EC1Y 8TZ London

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