Core modules
Programming for Quantitative Finance
Develop and support the skills required for practical applications of theoretical concepts in the MSc Mathematical Finance course.
Stochastic Calculus for Finance
Get a thorough introduction into discrete-time martingale theory, Brownian motion, and stochastic calculus, illustrated by examples from Mathematical Finance.
Financial Statistics
Discover the main approaches to statistical inference and financial time series.
Simulation & Machine Learning for Finance
Gain a theoretical and practical understanding of numerical methods in finance.
Asset Pricing & Risk
An introduction to modern theories of Asset Pricing and Portfolio Theory in both static and dynamic settings.
Financial Econometrics
Get an introduction to the main tools and approaches to estimation and inference of financial and economic models.
Applications of Stochastic Calculus in Finance
Gain a thorough understanding of how stochastic calculus is used in continuous time finance. You will also develop an in-depth understanding of models used for various asset classes.
Dissertation
The 10,000 word dissertation allows you to synthesise, apply and extend the knowledge you have gained in the taught component of the programme, and to demonstrate mastery of some elements of financial mathematics.
Optional modules
Optional modules can vary from year to year. Example optional modules may include:
Statistical Learning & Big Data
Cover a range of theories in statistical learning and big data and big model related issues and solutions.
Advanced Trading Strategies
Get an introduction to three advanced topics in Mathematical Finance, computing and explaining key variables, applying appropriate techniques, and analysing and comparing different modelling approaches between the three.
Partial Differential Equations in Finance
Gain a theoretical and practical understanding of partial differential equations.
Brownian Motion
Learn how to construct Brownian motion and study its path properties, how to use stochastic calculus for manipulations, and about differential equations.
Read the module descriptions for this course on the Warwick Business School website.
