Evaluating Value-at-Risk Forecasts: A New Set of Multivariate Backtests

38 Pages Posted: 13 Apr 2015 Last revised: 6 Dec 2015

See all articles by Dominik Wied

Dominik Wied

University of Cologne

Gregor N. F. Weiss

University of Leipzig - Faculty of Economics and Management Science

Daniel Ziggel

Ruhr University of Bochum

Date Written: December 4, 2015

Abstract

We propose two new tests for detecting clustering in multivariate Value-at-Risk (VaR) forecasts. First, we consider CUSUM-tests to detect first-order instationarities in the matrix of VaR-violations. Second, we propose x2-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 backtests of multivariate conditional coverage. In all cases, a bootstrap approximation is possible, but not mandatory in terms of empirical size and power.

Keywords: Model Risk, Multivariate Backtesting, Value-at-Risk

JEL Classification: C52, C53, C58

Suggested Citation

Wied, Dominik and Weiss, Gregor N. F. and Ziggel, Daniel, Evaluating Value-at-Risk Forecasts: A New Set of Multivariate Backtests (December 4, 2015). Available at SSRN: https://ssrn.com/abstract=2593526 or http://dx.doi.org/10.2139/ssrn.2593526

Dominik Wied

University of Cologne ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

Gregor N. F. Weiss (Contact Author)

University of Leipzig - Faculty of Economics and Management Science ( email )

Grimmaische Str. 12
Leipzig, 04109
Germany
+49 341 97 33821 (Phone)
+49 341 97 33829 (Fax)

HOME PAGE: http://www.wifa.uni-leipzig.de/nfdl

Daniel Ziggel

Ruhr University of Bochum ( email )

Universitätsstraße 150
Bochum, NRW 44780
Germany

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