MSc Financial Mathematics (MSc FM)
An 18-month master's with a core in computational methods, pricing and hedging, econometrics and fixed income, then a dissertation. Optional modules span portfolio theory, statistical learning, deep learning in finance and actuarial modelling.
What you’ll study
Core
- Computational Methods in Finance I
- Introduction to Pricing and Hedging
- Financial Econometrics
- Fixed Income Securities
- Computational Methods in Finance II
- Dissertation
Electives
- Portfolio Theory and Risk Management
- Mathematics and Statistics for Data Science
- Stochastic Modelling in Actuarial Science
- Statistical Methods in Finance
- Arbitrage, Equilibrium and Pricing
- Advanced Statistical Learning Theory
- Deep Learning in Finance
- Quantitative Finance with Applications
Source: xjtlu.edu.cn ↗
Before you apply
- Background
- Bachelor's in mathematics, statistics, physics, engineering, computer science, finance or an economics-related discipline
- English
- IELTS Academic 6.5 overall with at least 5.5 in each section (TOEFL iBT or PTE Academic accepted)
- Other
- Chinese applicants: WAM 75%+ from top-ranked institutions or 80-85% otherwise; UK 2:1; North America GPA 3.0
Source: xjtlu.edu.cn ↗
After graduation
- Typical first roles
- Quantitative analyst, Quantitative researcher, Risk manager, Data scientist, Algorithmic trading specialist
Source: xjtlu.edu.cn ↗
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Module list is for 2026-27 and may change. Page names employer types (investment banks, hedge funds, asset managers, insurers, fintech) but no outcome statistics. Top Deep Learning in Finance students may be offered internships at ForthTech's Shenzhen office. The Apply link on the page appears to point at a closed-applications URL.
Checked 6 November 2026 against the sources linked on this page. Fees, units and requirements change each year, so confirm them on the programme’s website before applying.