Time: 9.00am - 5.15pm
Venue: LSE (Room TBC)
Tutor: Prof Casper G. de Vries (Erasmus School of Economics, Rotterdam)
The course is now full.
Course Outline
The main objective of this course is to develop a coherent framework for evaluating market risk and systemic risk at the levels of individual asset, portfolio of assets, banks and insurers and at the level of the macro economy. The main tool that we exploit in devising this framework is the statistical and probability theory on tail risk derived from Extreme Value Theory (EVT) if the risk distribution has heavy tails. Standard concepts from, banking, finance and macroeconomics are evaluated within this novel framework.
In particular, the course offers different methods to manage financial market risk with special emphasis on downside risk measures such as Value-at-Risk (VAR), semi-variance, ES, Stress tests, worst case scenario analysis, etc. To this end, we analyze the implications of heavy-tailed risks, especially the convolution properties of distributions with heavy tails. The heavy-tail feature refers to the phenomenon that very bad outcomes occur way more frequently than the normal distribution predicts. We review estimation techniques of the downside risk, both at individual asset level and portfolio level. Given the link between individual risk management and stability of the financial system, we evaluate extensively how these techniques apply for to the risk management from a supervisory point of view. The framework explains the inherent fragility of the financial system and suggests tools for measuring systemic stability.
PC lab sessions implement the novel techniques using market data. The rigorous treatment of some of the techniques and their practical implementation enables students to analyze independently market and systemic risk after completing this crash course.
Prior to participating, students may want to study the review paper by Rocco from the Banca D’Italia.
Literature
Rocco, M., Extreme Value Theory for Finance: A Survey, Occasional Paper # 99, Banca D’Italia, 2011:
http://www.bancaditalia.it/pubblicazioni/qef/2011-0099/QEF_99.pdf
Background reading
Danielsson, J, and C.G. de Vries, Tail Index and Quantile Estimation with very High Frequency Data, Journal of Empirical Finance 4,1997, 241-257
Embrechts, P.C. Kluppelberg and T. Mikosch, Modelling Extremal Events for Insurance and Finance, Springer, 1997
Hartmann, P., S. Straetmans and C.G. de Vries, Asset Market Linkages in Crisis Periods, Review of Economics and Statistics 81, 2004, 313-326
Vries, C.G. de, The simple Economics of Bank Fragility,95, Journal of Banking & Finance 29, 2005, 803-825
Poon, S.H., M. Rockinger and J. Tawn, Extreme-value Dependence Measures in Financial Markets: Diagnostics, models and Financial Applications, The Review of Financial Studies 17, 2004, 581-610.
Slijkerman, J.F., D. Schoenmaker and C.G. de Vries, Systemic Risk & Diversification across European Banks and Insurers, Journal of Banking and Finance, 2013
Please note that participants are required to bring their own laptops for lab sessions with at least Excel installed and preferably Matlab or R / S-PLUS. The masterclass is free of charge.
