Course content

Five core modules cover key material in finance, statistics, and maths. You will also choose three elective modules to allow you to focus on your personal interests. Assessment is a mix of exams and coursework, both individual and group. A dissertation completes the course. The programme starts in September 2012, and extends beyond the normal undergraduate term dates.

The course is delivered through a combination of lectures, classes, and computer lab sessions to ensure you have the right theoretical and technical skills. The modules are taught by staff from WBS, Warwick Mathematics Institute, and the Department of Statistics.

Fundamental Tools

The course begins with a one-week induction module, run by Warwick Mathematics Institute. This refresher module ensures you have the mathematical foundations for the course.

Core modules

C++ Modelling in Asset Pricing
An introduction to the valuation of risky assets together with sufficient C++ expertise to apply numerical techniques of asset pricing to practical market problems. Gain transferable skills applicable to other problems in the domain of finance.
Continuous Time Finance for Interest Rate Models
Further your understanding of how stochastic calculus is used in continuous time finance and gain an in-depth understanding of models used for interest rates. Topics include mathematical foundations, option pricing in continuous time, and term structure models, continuous local martingales, Girsanov's Theorem, pricing, completeness for the Black-Scholes economy, implied volatility, market implied distributions, stochastic volatility and incomplete markets, multi-currency economy, short rate models, market models, and Markov functional models. Department of Statistics
Derivative Securities
Study various types of derivative instruments traded in financial markets, the concepts of no-arbitrage pricing and hedging, and the mathematics of the discrete-time binomial models used to price derivatives.
Numerical Methods
Gain a theoretical and practical understanding of numerical methods in finance, in particular those related to simulations of stochastic processes. Topics include the basics of linear models, GARCH and ARCH, Markov model, Monte Carlo methods, numerical methods for differential and stochastic differential equations, and the CRR model of binomial options pricing. Warwick Mathematics Institute
Probability and Stochastic Processes
Probability theory provides the language and the key technical concepts and tools for the study of financial mathematics. Explore ideas from probability and develop the tools required to exploit them. Topics include events and random variables, stochastic processes, and calculus for continuous time processes. Department of Statistics

Dissertation

An individual, practical, technical project will form the basis of your 10-12,000 word dissertation. You will usually submit your dissertation in early September.

Some of our students undertake this as a sponsored piece of work for an external organisation. Through careful matching of students' strengths to sponsors' requirements we are usually able to partner about a third of our students to client projects. You will be supervised and supported throughout by one of our academic staff.

Recent sponsors

  • Barclays Global Investors
  • BP
  • Duff & Phelps
  • F&C Investments
  • HSBC
  • JP Morgan
  • LDFM
  • Lloyds Banking Group
  • Nomura
  • Numerical Algorithms Group
  • Old Mutual Asset Managment.

Recent external projects offered to students of our finance masters courses include:

  • Corporate ALM project
  • Relative Volatility Heatmap
  • Can drivers of credit curves be parameterised?
  • Is the single name CDS v index CDS basis a useful trading indicator?
  • Assessing the importance of volatility estimation in portfolio design and risk management
  • Assessing the role of statistical learning algorithms and directional prediction in asset allocation
  • Optimisation of the NBS balance sheet
  • Risk Aggregation in Nationwide
  • Capital impacts of Sovereign Swap Spread Risk
  • Pricing multi-asset options using PDE methods
  • Review of the NAG Library
  • Annual vs Quarterly reporting: timeliness vs level of detail
  • What factor distributions are most effective in predicting future performance?
  • Modelling Market Level Volatility
  • Evaluation of a proprietary dataset of style equity flows
  • Value investment strategies for sector/industry selection
  • Quantitative analysis of fundamental news on the markets - Foreign Exchange
  • Quantitative analysis of fundamental news on the markets - Euro & US Fixed Income
  • The effect of interest rates and foreign exchange on stock index valuations across regions and in comparison to the greater world
  • The effects of Libor shocks on companies profitability and stock price
  • The liquidity effect of algorithmic trading
  • Cyclicality of credit ratings

Many of our students prefer to undertake research under the supervision of a faculty member from one of the three departments. This gives you the opportunity to really hone and practise your technical skills.

You may be offered the opportunity to undertake a project for an external organisation.

Elective modules

Choose three modules. In previous years we have offered the following electives:

Behavioural Finance
Explore the role of psychological and social forces that apply to decision-making in financial markets.
Empirical Finance
Study the theories and tools used in financial econometrics, including prediction, quantitative methods of asset allocation, volatility, risk modelling, and quantitative asset pricing.
Financial Engineering & Structured Products
Explore recent developments in financial engineering and structuring, and consider the rationale and benefits of financial innovation to the various parties to a transaction.
Financial Risk Management
Discover how financial organisations identify, quantify, manage, and control risk.
Financial Time Series
Gain practical experience of specialised time series software. Model and analyse financial time series data. Extend and develop the methodology and critically evaluate time series developments in the finance area. Topics include prices and return; time series volatility, directionality, forecasting; linear models of financial time series, autoregressive and random walk models, detailed developments and derivations of autoregressive models including: combining ARMA and ARCH models, GARCH models, and financial illustrations and stochastic volatility models, interest rate models, and financial applications. Department of Statistics
Fixed Income & Credit Risk
Explore the basic financial instruments for managing interest rate and credit risk before progressing to value and hedge with more complex tools.
Investment Management
Review modern portfolio theory and investment analysis. Explore the issues involved in combining securities to construct an optimum investment portfolio, and the nature and role of derivatives in managing risk. Consider how to evaluate a portfolio, and adjust its composition, to ensure optimal performance.
Partial Differential Equations in Finance
Explore the benefits and shortcomings of various methods for solving problems and appreciate the importance of program reliability testing. Topics include basics of parabolic PDEs including PDEs in finance; finite difference approximation of parabolic PDEs; treatment of general boundary conditions; nonlinearity and difficulties of nonlinear equations; parabolic equations in higher dimensions; free boundary problem in option pricing and American options; and Monte Carlo methods of pricing options. Warwick Mathematics Institute