FM442      Half Unit
Quantitative Methods for Finance and Risk Analysis

This information is for the 2020/21 session.

Teacher responsible

Prof Philippe Mueller


This course is available on the Global MSc in Management, MSc in Accounting and Finance, MSc in Applicable Mathematics, MSc in Econometrics and Mathematical Economics, MSc in Financial Mathematics, MSc in Quantitative Methods for Risk Management, MSc in Risk and Finance, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (LSE and Fudan) and MSc in Statistics (Financial Statistics) (Research). This course is not available as an outside option.

Global MSc in Management ('Accounting and Finance' and 'Finance' concentrations only).

This course is available to other students from the Departments of Economics, Mathematics, and Statistics where regulations permit. 


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

Course content

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, Factor Models, Principal Components Analysis, Options Pricing, Binomial Trees, Monte Carlo Simulations, and associated topics in Econometrics.  This list is meant to be representative, but topics may be added or removed.

Implementing the models and tools in R is an essential part of the course.  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.


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

Formative coursework

Six homework assignments to be solved using R.

Indicative reading

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; Ruey Tsay (2010), Analysis of Financial Time Series; Pietro Veronesi (2010), Fixed Income Securities: Valuation, Risk, and Risk Management.


Exam (30%, duration: 1 hour and 30 minutes, reading time: 10 minutes) in the summer exam period.
Project (70%) in the MT.

Important information in response to COVID-19

Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: Finance

Total students 2019/20: 68

Average class size 2019/20: 17

Controlled access 2019/20: Yes

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Problem solving
  • Application of information skills
  • Application of numeracy skills
  • Commercial awareness
  • Specialist skills