Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/191546 
Erscheinungsjahr: 
2019
Schriftenreihe/Nr.: 
KIT Working Paper Series in Economics No. 122
Verlag: 
Karlsruher Institut für Technologie (KIT), Institut für Volkswirtschaftslehre (ECON), Karlsruhe
Zusammenfassung: 
An accurate assessment of tail inequalities and tail asymmetries of financial returns is key for risk management and portfolio allocation. We propose a new test procedure for detecting the full extent of such structural differences in the dependence of bivariate extreme returns. We decompose the testing problem into piecewise multiple comparisons of Cramér-von Mises distances of tail copulas. In this way, tail regions that cause differences in extreme dependence can be located and consequently be targeted by financial strategies. We derive the asymptotic properties of the test and provide a bootstrap approximation for finite samples. Moreover, we account for the multiplicity of the piecewise tail copula comparisons by adjusting individual p-values according to multiple testing techniques. Monte Carlo simulations demonstrate the test's superior finite-sample properties for common financial tail risk models, both in the i.i.d. and the sequentially dependent case. During the last 90 years in US stock markets, our test detects up to 20% more tail asymmetries than competing tests. This can be attributed to the presence of non-standard tail dependence structures. We also find evidence for diminishing tail asymmetries during every major financial crisis - except for the 2007-09 crisis - reflecting a risk-return trade-off for extreme returns.
Schlagwörter: 
tail dependence
tail copulas
tail asymmetry
tail inequality
extreme values
multiple testing
JEL: 
C12
C53
C58
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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