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Wied, Dominik, Weiss, Gregor N. F. and Ziggel, Daniel (2016). Evaluating Value-at-Risk forecasts: A new set of multivariate backtests. J. Bank Financ., 72. S. 121 - 133. AMSTERDAM: ELSEVIER SCIENCE BV. ISSN 1872-6372

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Abstract

We propose two new tests for detecting clustering in multivariate Value-at-Risk (VaR) forecasts. First, we consider CUSUM-tests to detect non-constant expectations in the matrix of VaR-violations. Second, we propose chi(2)-tests for detecting cross-sectional and serial dependence in the VaR-forecasts. Moreover, we combine our new backtests with a test of unconditional coverage to yield two new back tests of multivariate conditional coverage. Results from a simulation study underline the usefulness of our new backtests for controlling portfolio risks across a bank's business lines. In an empirical study, we show how our multivariate backtests can be employed by regulators to backtest a banking system. (C) 2016 Elsevier B.V. All rights reserved.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Wied, Dominik UNSPECIFIED UNSPECIFIED UNSPECIFIED Weiss, Gregor N. F. UNSPECIFIED UNSPECIFIED UNSPECIFIED Ziggel, Daniel UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-256769
DOI:	10.1016/j.jbankfin.2016.07.014
Journal or Publication Title:	J. Bank Financ.
Volume:	72
Page Range:	S. 121 - 133
Date:	2016
Publisher:	ELSEVIER SCIENCE BV
Place of Publication:	AMSTERDAM
ISSN:	1872-6372
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language BOOTSTRAP Multiple languages Business, Finance; Economics Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/25676