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Market and Systemic Risk Management

  • Teacher(s)
    Casper de Vries, Chen Zhou
  • Research field
    Finance, Finance
  • Dates
    Period 5 - Apr 24, 2023 to Jul 14, 2023
  • Course type
  • Program year
  • Credits

Course description

The main objective of this course is to develop a coherent framework for evaluating market risk at the levels of individual asset, portfolios of assets, banks and insurers and the systemic risk regarding the financial system and macro economy. The main tool that we exploit in devising this framework is the statistical theory about tail risk based on from Extreme Value Theory (EVT), in combination with standard concepts from finance and macroeconomics.

In particular, the course offers different methods to manage financial risk with special emphasis on downside risk measures such as Value-at-Risk (VAR), Expected Shortfall (ES), semi-variance, Stress tests, worst case scenario analysis, etc. Various statistical techniques are studied for analysing heavy-tailed distributions, especially their convolution properties. Subsequently, we investigate the EVT for the sake of stress testing and scenario analysis. Given the link between individual risk management and stability of the financial system, we also pay attention to various aspects of risk management from a supervisory point of view. The inherent fragility of the financial system is explained and tools for measuring systemic stability are developed.

Students have to submit empirical homework as well as addressing theoretical questions. The rigorous treatment of some of the techniques enables students to independently analysemarket and systemic risk.

Course literature

Primary reading
Lecture notes and research papers provided in lectures
Further reading
- Rocco, M. (2014) Extreme value theory in finance: a survey. Journal of Economic Surveys, 28(1), 82-108.
- Nolde, N. and Zhou, C. (2021). Extreme Value Analysis for Financial Risk Management. Annual Review of Statistics and Its Application, 8, 217-240.

Embrechts, P., Klüppelberg, C., and Mikosch, T. (1997). Modelling extremal events: for insurance and finance (Vol. 33). Springer Science & Business Media.