- Students understand some of the core principles and quantitative techniques involved in risk management and supervision of financial institutions.
- Students are able to apply the techniques, working with Excel, VBA, and additional tools that may vary from year to year.
- Students understand how to interpret the outcome of risk models and their limitations, from a manager’s perspective. They understand the role of additional stress testing in coping with model uncertainty.
- Students learn how to interpret recent or historical financial events from a risk management perspective
We give an introduction to risk management, with a focus on the quantitative tools used by financial institutions and their regulators. Most aspects, however, are directly applicable for financial risk management in non-financial corporations as well.
As compared to the trading perspective, which is the classical viewpoint in Financial Engineering, in risk management the emphasis shifts to extremer levels of risk, and higher levels of aggregation: portfolio level, company level, and systemic effects for the financial system. This naturally gives rise to the concept of Value-at-Risk (VaR), which plays a central role in the field, despite some shortcomings that we will address. We discuss several methods and models for determining VaR, for three main risk categories, market risk (the risk of adverse price movements on assets) credit risk (the risk of default of a debtor), and operational risk (due to e.g. failure of systems, fraud). Some of these methods make use of option theory. We also pay attention to Asset & Liability Management methods for managing the exposure to interest rate risk (banks) and the coverage ratio (pension funds) at balance sheet level. Limitations of risk models are emphasized, and it is discussed how stress testing may mitigate the effects of model uncertainty. Students participate in presentations on linking the theory to financial disasters in the past and recent events.
Mandatory: Mathematical Finance.(2130006)
Recommended: Statistics and Probability, Corporate Finance