Risk Management

Course Director: Tobias Sichert

Content
The measurement and management of financial risk is of utmost importance for financial institutions (including banks, insurance companies, mutual funds and hedge funds) and corporations. The objective of the course is to provide students with advanced skills and knowledge on quantifying and managing risks of financial assets. We will study econometric techniques and statistical tools commonly employed in the area of finance and risk management and practice their implementation. The quantitative methods studied in this course are particularly useful for students interested in a career in investment management.

The course will cover the following topics:

1. Volatility modelling and forecasting
2. Value-at-Risk and expected shortfall
3. Historical simulation
4. Nonnormal distributions and Extreme Value Theory
5. Monte Carlo simulation and varinace reduction
6. Modelling correlations

Format & Structure

Class will meet twice a week for eight weeks. The course will be based on slide presentations and readings. All material will be posted on the course page. Students are required to read the assigned material before each lecture. There will be 1-2 guest lectures by people from the financial industry. There will be two HW assignments to be completed in groups of 2-3 students and a final take home project. Moreover, students will have access to courses on the Datacamp platform to learn Python

Course Administrator: Kirandeep.Saini@hhs.se

After completing this course, students should be able to:

1. Explain the defining risk characteristics of various types of financial assets.
2. Identify and estimate the appropriate time series and variance model for a given data series, produce forecasts and evaluate the accuracy of the predictions using various metrics.
3. Motivate the use of generalized autoregressive conditional heteroscedasticity (GARCH) models, estimate and produce forecasts from GARCH models and contrast various models from the GARCH family.
4. Quantify various aspect of risks of financial assets.
5. Explain how deviations normal distribution is important for risk management.
6. Model assets returns and run large-scale simulations of portfolios of assets.
7. Apply appropriate variance reduction techniques in simulations.

This is an elective course. Students are assumed to have a good knowledge of finance and statistics/econometrics, and should be able to manipulate data using Python. This course is highly recommended to finance students who wants to specialize in Investment Management. Students who are not enrolled in the Master of Finance must obtain prior approval to attend the course. The purpose is to ascertain that students from other programs satisfy the course prerequisites. These students must provide relevant information about previously taken statistics/finance courses to the course administrator well before the end of the registration period. The student will then be notified whether they indeed meets the course requirements and can enrol in the course.

The course is based on the book "Elements of Financial Risk Management", 2nd edition, by Peter Christoffersen (ISBN 9780128102350).

I plan to switch to the 3rd edition as soon as it is available.

Grading will be based on two homework assignment, to be carried out in groups of 2-3 students, and a final take home project (individual). The final grade will be calculated as follows:

• Homework 1 (10%)
• Homework 2 (10%)
• Final take home project (80%)

Find the course schedule in TimeEdit

Have you been granted educational support because of a documented disability? If so, please contact the course director as soon as possible so that adequate accommodations can be made.

Contact specialneeds@hhs.se if you have questions about being granted educational support or need a copy of your educational support certificate.

For more information, visit the Specific Educational Needs page on the Student Hub (login required).