Mathematical Trading and Finance MSc

This module focuses on the introduction of pricing financial securities, which forms the basis for understanding asset pricing behaviour and the cornerstone of many asset pricing models. The focus is on spot securities, mainly equities and debt instruments.

This module introduces to derivatives instruments and derivatives markets in the context of financial risk management. Focus is specifically given to the identification of the risks inherent in derivative securities.

The course provides the essential statistical and econometric techniques needed to conduct quantitative research in finance and economics.

The module provides the necessary mathematical tools on which the entire programme is based. Specifically, the module offers a rigorous introduction to Brownian motions and stochastic calculus.

This module provides on overview of machine learning concepts, techniques and algorithms used in practice to describe and analyse complex data and design predictive analytics methods. You should expect to engage with the main idea and intuition behind modern machine learning tools from a practical perspective.

This trading focused module introduces students to the world of computer-based trading and dealing with high frequency data.

Financial debacles are a constant reminder of the relationship between financial risk and reward. The quantitative approach to this relationship is ever more dominant in the market and subject to constant innovation.

The module provides a thorough introduction to the market of fixed income securities, such as bonds, swaps and interest rate options. Furthermore, the module covers the main modelling requirements used in fixed income securities. It also offers insights in current issues of fixed income market, such as multicurve rates and counterparty credit risk.

Students need to study optional modules in this year.