Explore our Mathematical Finance taught Master's degree.

P-N3G2

MSc

1 year full-time

23 September 2024

Warwick Business School

University of Warwick

Join our challenging MSc Mathematical Finance taught by three of Warwick's top departments; Mathematics, Statistics and Warwick Business School. With expert supervision, this mathematically rigorous course will develop and apply the quantitative skills in machine learning, computational statistics and mathematical finance used in the financial markets and the finance industry.

This unique course provides training from three top departments at the University of Warwick: Mathematics, Statistics and Warwick Business School. Building on your strong mathematical background, you will develop and apply the quantitative skills in machine learning, computational statistics and mathematical finance that are used within the financial markets and finance industry.

Our core modules focus on the four elements of the core skill set needed for careers in finance: Financial Statistics, Financial Mathematics, Asset Pricing and Risk, and Simulation and Machine Learning for Finance. In line with these modules, you will also learn programming for Quantitative Finance, focusing on C++, Python, and R.

Skills from this degree

• Teaching by three world-leading academic departments helps you to gain a deep insight into mathematical finance
• Uncover the newest quantitative theory and practice through specialist modules
• Develop your industry acumen by accessing our CareersPlus service with specialist careers coaches.

Modules are taught by staff from WBS, Statistics, and Mathematics, through a combination of lectures, classes, and computer lab sessions.

Seven core modules cover the four key pillars of the core skill set you will need for a career in the finance industry: Financial Statistics, Financial Mathematics, Asset Pricing and Risk, and Simulation and Machine Learning for Finance.

Our optional modules help you to personalise the course to focus in on your own interests and future career path.

The typical class size for this course is around 20 students.

Students on this MSc will typically receive between 26 and 30 contact hours per module.

Assessment is a mix of exams and coursework with your dissertation bringing all of your learning together at the end.

Your timetable

Your personalised timetable will be complete when you are registered for all modules, core and optional, and you have been allocated to your lectures, seminars and other small group classes. Your core modules will be registered for you and you will be able to choose your optional modules when you join us.

There may be events taking place in the evenings. Classes may run up to 7pm and other events, such as careers presentations may take place later or on Saturdays. Occasionally, classes and exams may be held on Saturdays. We will notify you in advance if this is the case.

This is a full-time course, so there are no holidays as such. However, the two weeks covering Christmas and New Year are guaranteed to be free from lectures. There may also be weeks free over the Easter period (check with your programme team). Resit exams may take place outside of standard teaching periods.

A high 2:1 or First (or equivalent) in a Mathematics, Statistics, Physics or another relevant quantitatively-focused undergraduate degree. You will need strong ability in mathematics and finance, and some experience in statistics or econometrics.

• Band B
• IELTS overall score of 7.0, minimum component scores of two at 6.0/6.5 and the rest at 7.0 or above.

We accept a range of language tests. Please refer to our website for more details.

There are no additional entry requirements for this course.

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.

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.

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