T ChenY1 he Financial Statistics stream of the MSc Statistics programme is mainly intended for students wishing to pursue careers in the finance industry or as a stepping stone towards PhD study in statistics for finance.

Students will receive a thorough grounding in the theory and methods of statistical inference and the statistical analysis of time series, as well as a selection of important concepts in statistical finance, such as financial time series, asset pricing and portfolio choice, and some aspects of continuous-time finance. Students will also learn to code in the R statistical computing environment. Optional modules from the Statistics, Finance and Economics departments (among others) are available.

The research branch of the Financial Statistics programme is open to students wishing to take the dissertation option.

Dr Yining Chen
MSc Statistics (Financial Statistics) Programme Director

Entry Requirements

The normal entry requirement is an upper second class honours degree, or equivalent, with a significant mathematical content. Well-qualified applicants who do not meet this requirement will be considered on merit.

Details of how to apply

For further practical details on how to submit an application, including the word limit on your personal statement, please see our MSc FAQs (Frequently Asked Questions). To submit your application please visit our Graduate Admissions website here.

Course Structure

Our taught postgraduate courses are based around lectures, with problem classes and computer workshops. Most courses are assessed by a two-hour exam in the summer term although some contain an element of course work.

The courses in the programme are divided into two categories: compulsory courses and optional courses. Students must take courses to the value of four full units.

Compulsory courses and options

i. Three compulsory courses:

ST422 Time Series (H)
ST425 Statistical Inference: Principles, Methods and Computation (F) (Lent Term Week 0 Exam)
ST436 Financial Statistics (H)

ii. Optional courses to the value of two full units from the following:

ST405 Multivariate Methods (H)
ST409 Stochastic Processes (H)
ST411 Generalised Linear Modelling and Survival Analysis (H)
ST416 Multilevel Modelling (H)
ST418 Nonlinear Dynamics and the Analysis of Real Time Series (H)
ST421 Developments in Statistical Methods (H)
ST426 Applied Stochastic Processes (H)
ST427 Insurance Mathematics (H) (Lent Term Week 0 Exam)
ST429 Probabilistic Methods in Risk Management and Insurance (H)
ST433 Computational Methods in Finance and Insurance (H)
ST435 Advanced Probability Theory (H) (Lent Term Week 0 Exam)
ST439 Stochastics for Derivatives Modelling (H)
ST440 Recent Developments in Finance and Insurance (H)
ST441Introduction to Markov Processes and Their Applications (H)*
ST442 Longitudinal Data Analysis (H)
ST443 Machine Learning and Data Mining (H)
ST444 Statistical Computing (H)
MY456 Survey Methodology (H) (Department of Methodology)
MY457 Causal Inference for Observational and Experimental Studies (H) (Department of Methodology)

Note: *ST441 is not available in the 2015/16 academic session.

Non-statistics and non-methodology courses:

EC484 Econometric Analysis (F) (Department of Economics)
Statistics students taking EC484 will be required to register in early September in order to attend the econometrics component of the pre-sessional course EC451. Students must pass an exam taken at the end of the pre-sessional in order to proceed to EC484. In addition, please note that there will be a mid-term exam in Lent Term Week 0.
FM402 Financial Risk Analysis (H) (Department of Finance)
FM404 Forecasting Financial Time Series (H) (Department of Finance)
FM413 Fixed Income Markets (H) (Department of Finance)
FM429 Asset Markets A (H) (Department of Finance)
FM441 Derivatives (H) (Department of Finance)
MA407 Algorithms and Computation (H) (Department of Mathematics)
MA415 The Mathematics of the Black and Scholes Theory (H) (Department of Mathematics)
MA416 The Foundations of Interest Rate and Credit Risk Theory (H) (Department of Mathematics)
MA420 Quantifying Risk Modelling and Alternative Markets (H) (Department of Mathematics)
MG4C6 Mathematical Programming: Theory and Algorithms (H) (Department of Management)

Please note: The maximum of one unit's worth of non-ST courses is permitted. Other non-ST course(s) may be taken, with permission. H = Half Unit; F = Full Unit.

Compulsory courses and options (research branch)

MSc in Statistics (Financial Statistics) (Research) is similar to the MSc in Statistics (Financial Statistics) nine-month programme but involves a compulsory dissertation (ST499) which replaces one unit’s worth of optional courses.

i. Four compulsory courses (equivalent to three full units):

ST422 Time Series (H)
ST425 Statistical Inference: Principles, Methods and Computation (F) (Lent Term Week 0 Exam)
ST436 Financial Statistics (H)
ST499 Dissertation (F)

ii. Optional courses to the value of one full unit, as listed above for the MSc in Statistics (Financial Statistics).

Programme Regulations

MSc Statistics (Financial Statistics)

MSc Statistics (Financial Statistics) (Research)

Winton
MSc Prizes

Two prizes sponsored by Winton Capital are awarded to MSc students each year.

Winton Prize for Academic Excellence in MSc Statistics/MSc Statistics (Financial Statistics)

Awarded to the MSc Statistics or MSc Statistics (Financial Statistics) student with the highest overall marks in their exams. One prize of £500 awarded.

Winton Prize for Best Dissertation in MSc Statistics/MSc Statistics (Financial Statistics)

Awarded to the MSc Statistics or MSc Statistics (Financial Statistics) student with the highest mark on their dissertation. One prize of £500 awarded.

This agreement is applicable until 2017.