Dr Philippe Mueller OLD M2.16

This course is available on the MSc in Accounting and Finance, MSc in Applicable Mathematics, MSc in Finance and Economics, MSc in Finance and Economics (Research), MSc in Financial Mathematics, MSc in Management and Regulation of Risk, MSc in Risk and Finance and MSc in Risk and Stochastics. This course is not available as an outside option.

A background in statistics and mathematics is required. No prior programming experience is necessary but students without programming experience are highly encouraged to concurrently take FM457 MATLAB for MSc Students.

This is a graduate level course on the quantitative and statistical tools that are important in applied finance. It studies financial markets and market risk from a quantitative point of view, focusing on understanding the relationship between risk and return and on models for managing financial risks. The course brings together three essential fields: finance, statistics and computer programming. Students will be exposed to the application of these tools and the key properties of financial data through a set of computer-based classes and exercises. The following key topics will be covered; review of statistics and introduction to time series econometrics; modeling of financial returns; introduction to the analysis of financial data using MATLAB; volatility models including GARCH type models and  the concept of implied volatility; risk measures and coherence; Value-at-Risk and Expected Shortfall; introduction to simulation-based methods and application to option pricing and risk management.

Implementing the models and tools in MATLAB is an essential part of the course and, consequently, all classes are computer-based. With regards to empirical work the students will learn how to deal with very practical problems such as locating financial data and processing the data to be able to analyze it in the first place. Through the computer-based exercises the students explore the data bases available at the LSE and they will become comfortable working with real data. Throughout the term the students will build their own toolbox of routines that can also be used outside the course.

20 hours of lectures and 10 hours of seminars in the MT.

Problem sets to be solved using MATLAB. In addition, students will have the opportunity to present the results of a problem set to the class.

The core text for this course is:

Jon Danielsson, Financial Risk Forecasting, John Wiley & Sons, 2011.

Extra readings will be assigned for selected topics.

Exam (75%, duration: 1 hour and 30 minutes) in the main exam period.
Project (20%, 2000 words) and presentation (5%) in the MT.