Tail Dependence MSR
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Tail Dependence MSR
This presentation examines tail dependence: the tendency of financial assets to experience extreme movements at the same time. It introduces copula models and applies them to stock returns and portfolio Value-at-Risk estimation.
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- 0 Rating
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- 1 Students Enrolled
Requirements
- Statistics
General Overview
Description
The presentation provides a general overview of dependence between financial assets, with particular attention to joint extreme events that can increase portfolio risk during stressed market conditions. It begins with common dependence measures, such as Pearson correlation, Kendall’s tau, and Spearman’s rho, and explains why standard correlation alone may not fully capture simultaneous large losses. It then introduces upper and lower tail dependence, elliptical distributions, and several copula models—including Gaussian, Student-t, Gumbel, Clayton, and Frank copulas—as flexible tools for modelling relationships among asset returns. Practical examples use daily returns for Bayer, BMW, Siemens, and Volkswagen to estimate tail dependence and compare alternative copula specifications. The presentation concludes by showing how copula-based simulations can be used to estimate and backtest portfolio Value-at-Risk over moving time windows.
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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