Risk Management
People
Course director
Assistant
Description
We begin by defining the various types of financial risks and stress the need for their management through the analysis of losses and defaults of financial institutions in the recent past. We next turn to the computation of Value-at-Risk measures for portfolios of equity, bond, and option positions. We discuss the estimation of the main inputs surrounding the calculation of VaR, and elaborate on models for time-varying volatility and correlations. We cover both local-valuation models based on derivatives, as well as full-valuation models such as historical simulation and Monte Carlo methods. We also discuss alternative metrics to VaR and Extreme Value Theory. Finally, we examine models for liquidity and operational risk management.
Lecture notes will be made available on the course website. The recommended textbook for the course is “Risk Management and Financial Institutions” by John Hull.
Objectives
The course aims at providing the main tools for measuring and managing financial risks, with a particular focus on market risk.
Teaching mode
In presence
Learning methods
Lectures will alternate between discussion of theoretical material and exercise sessions.
Examination information
The course grade is based on:
80% in-class, closed-book final.
20% take-home group assignments. The group must prepare a short (max 2 pages single-sided) executive summary of the analysis addressing the questions that are given, an Excel file with the solution, and a PPT presentation. Files should be uploaded in the system no later than midnight of the due date in order to be considered for grading. The group members are also required to attend the class where the case will be discussed, when randomly picked group(s) will be required to present their solution. Not showing up in class for discussion, or delivering only a subset of the cases will result in losing the corresponding 20% of the grade.
Bibliography
Education
- Master of Science in Economics in Finance, Lecture, 1st year
- Master of Science in Financial Technology and Computing, Lecture, SFI accreditation (min 45 ECTS), 1st year