Mathematical Risk Management
EMMS013S7 (30 credits)
Full-time and Part-time year 2
Autumn and Spring Terms, over 20 weeks
Lecturers: Simon Hubbert, and Steve Satchell
Aims
The course provides an introduction to modern risk management theory and practice. Students will develop problem-solving skills in risk management applications and become conversant with up-to-date techniques employed by financial institutions.
Objectives
- To develop knowledge of statistical techniques applicable to measuring risk in portfolios.
- To learn how to apply these techniques in practice.
- To become acquainted with standard risk models and to have a thorough critical understanding of the strengths and weaknesses of these models.
Topics
- Introduction to key concepts of risk v reward.
- Utility Theory.
- The optimal portfolio problem.
- The Capital Asset Pricing Model.
- Arbitrage pricing theorem and factor models.
- Statistical properties of financial returns.
- Loss distribution risk measures such as VaR and TVaR.
- VaR with derivative portfolios.
- Extreme Value Theory techniques applied to VaR measurement.
- The Basel proposals for bank capital requirements.
- Backtesting Risk Models.
- Credit risk modeling including Credit-VaR.
- Modeling Volatility and Correlation using GARCH techniques.
- Strategic Asset Allocation.
- Tactical asset allocation.
- Performance measurement.
- Hedge fund risk.
- Risks associated to the choice of model and the liquidity of the market.
Course Assessment
The final grade is determined through a three-hour exam in June and a take-home exercise in the Easter vacation.
Textbooks
Lecture notes will be distributed.