COURSE CURRICULUM

The MSc in Financial Mathematics provides a rigorous foundation in quantitative finance, data analytics, and econometrics, preparing students for advanced roles in finance, banking, and data-driven industries. The program develops strong analytical and computational skills through a blend of mathematical theory and financial application. Core modules include Computing for Data Analytics and Finance, Financial Mathematics, Financial and Time Series Econometrics, and Financial Portfolio Analysis, enabling students to model financial data, evaluate risk, and optimise investment strategies. Throughout the year, students complete a Dissertation in Financial Mathematics, applying theoretical knowledge to independent research on real-world financial challenges. The course also offers a variety of optional modules that allow students to tailor their studies to specific interests. These include Advanced Numerical Analysis, Corporate Finance, Linear Statistical Models, Probability Models, Financial Investment and Corporate Risk Analysis, Machine Learning and Statistics for Health, Monte Carlo Simulations, and Statistical Inference. This flexibility ensures a balance between theoretical depth and practical skill development. By combining expertise from mathematics, statistics, and finance, the program cultivates quantitative reasoning, programming proficiency, and problem-solving ability. Graduates emerge well-equipped for analytical and research-based careers in finance, risk management, quantitative modelling, and academic or applied economic research.