FM442      Half Unit
Quantitative Methods for Finance and Risk Analysis

This information is for the 2025/26 session.

Course Convenor

Availability

Requisites

Additional requisites:

A strong background in statistics and quantitative methods at the undergraduate level is required.  Prior programming experience is helpful.  

This graduate-level course covers important quantitative and statistical tools in applied finance. It studies financial markets risk, with a particular focus on models for measuring, assessing and managing financial risk.  Students will be introduced to the application of these tools and the key properties of financial data through a set of computer-based homework assignments and classes.

The course aims to introduce quantitative concepts and techniques in many areas of finance. Sample topics include risk measures (e.g., Value-at-Risk and Expected Shortfall, including implementation and backtesting), univariate and multivariate volatility models, Monte Carlo Simulations, and associated topics in Econometrics.  This list is meant to be representative, but topics may be added or removed. Recent stress events, such as the global crisis in 2008, Covid-19 in 2020, Russia’s invasion of Ukraine, recent inflation, and the US tariffs are used to illustrate the various methodologies presented in the course.

An essential part of the course is implementing the models and tools in the programming language R. Further information on R as used in the course can be found in the R Notebook at  https://www.financialriskforecasting.com/notebook.

The homework assignments are designed to guide the students to all stages of the analytical process, from locating, downloading and processing financial data to the implementation of the tools and interpretation of results. Students will have the opportunity to explore the databases available at the LSE and to become comfortable working with real data.

30 hours of seminars in the Autumn Term.

This course is taught in the interactive lecturing format. There is no distinction between lectures and classes/seminars; there are “sessions” only, and the pedagogical approach in each session is interactive.

No single text covers the course material. The relevant sections of the following readings would be appropriate for individual topics: Jon Danielsson (2011), Financial Risk Forecasting; The lecture slides and supporting programming material can be found on www.financialriskforecasting.com/

Other background reading is Ruey Tsay (2010), Analysis of Financial Time Series; Peter Christoffersen (2003) Elements of Financial Risk Management; Alexander J. McNeil, Rüdiger Frey, et al. , (2015) Quantitative Risk Management: Concepts, Techniques and Tools.

Exam (50%), duration: 90 Minutes, reading time: 10 minutes in the Spring exam period

Continuous assessment (50%)