Extreme Value MSR
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Extreme Value MSR
This presentation explains how extreme value methods can be used to measure severe financial losses and improve risk assessment. It applies these methods to portfolio returns and evaluates Value-at-Risk estimates.
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- 0 Rating
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- 2 Students Enrolled
Requirements
- Statistics
General Overview
Description
The presentation provides a general introduction to extreme value analysis in financial risk management, focusing on the behaviour of unusually large losses that may not be well captured by standard statistical models. It discusses key approaches for identifying and modelling extreme observations, including block maxima and peaks-over-threshold methods, together with generalized extreme value and generalized Pareto distributions. Using historical return data for a portfolio composed of Bayer, BMW, and Siemens, it illustrates diagnostic tools, tail estimation techniques, and the estimation of Value-at-Risk through moving-window procedures. The presentation also introduces backtesting as a way to compare estimated risk levels with realised losses, highlighting the practical role of extreme-value methods in portfolio risk measurement.
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Meet the instructors !
Wolfgang Karl HÄRDLE attained his Dr. rer. nat. in Mathematics at Universität Heidelberg in 1982 and in 1988 his habilitation at Universität Bonn. He is Ladislaus von Bortkiewicz Professor of Statistics at Humboldt-Universität zu Berlin and the director of the Sino German Graduate School (洪堡大学 + 厦门大学) IRTG1792 on “High dimensional non stationary time series analysis”. He directs IDA Institute for Digital Assets,
University of Economic Studies, Bucharest, RO. His research focuses on data analytics, dimension reduction and quantitative finance. He has published over 30 books and more than 300 papers in top statistical, econometrics and finance journals. He is highly ranked and cited on Google Scholar, REPEC and SSRN. He has professional experience in financial engineering, S.M.A.R.T. (Specific, Measurable, Achievable, Relevant, Timely) data analytics, machine learning and cryptocurrency markets. He has created the www.quantlet.com platform, a cryptocurrency index, CRIX www.royalton-crix.com He is 玉山学者 （Yushan Scholar), web page hu.berlin/wkh