A New Bootstrap Test for Multiple Assets Joint Risk Testing

Journal of Risk, 2017, Volume 19, Issue 4, pages 1-22

Posted: 19 Aug 2013 Last revised: 14 Nov 2017

See all articles by David Ardia

David Ardia

HEC Montreal - Department of Decision Sciences

Lukasz T. Gatarek

Erasmus University Rotterdam (EUR) - Erasmus School of Economics (ESE); Tinbergen Institute

Lennart F. Hoogerheide

VU University Amsterdam

Multiple version iconThere are 2 versions of this paper

Date Written: July 18, 2016

Abstract

A novel simulation-based methodology is proposed to test the validity of a set of marginal time series models, where the dependence structure between the time series is taken ‘directly’ from the observed data. The procedure is useful when one wants to summarize the test results for several time series in one joint test statistic and p-value. The proposed test method can have higher power than a test for a univariate time series, especially for short time series. Therefore our test for multiple time series is particularly useful if one wants to assess Value-at-Risk (or Expected Shortfall) predictions over a small time frame (e.g., a crisis period). We apply our method to test GARCH model specifications for a large panel data set of stock returns.

Keywords: Bootstrap test, GARCH, marginal models, multiple time series, Value-at-Risk

JEL Classification: C1, C12, C22, C44

Suggested Citation

Ardia, David and Gatarek, Lukasz T. and Hoogerheide, Lennart F., A New Bootstrap Test for Multiple Assets Joint Risk Testing (July 18, 2016). Journal of Risk, 2017, Volume 19, Issue 4, pages 1-22 , Available at SSRN: https://ssrn.com/abstract=2312007 or http://dx.doi.org/10.2139/ssrn.2312007

David Ardia (Contact Author)

HEC Montreal - Department of Decision Sciences ( email )

3000 Côte-Sainte-Catherine Road
Montreal, QC H2S1L4
Canada

Lukasz T. Gatarek

Erasmus University Rotterdam (EUR) - Erasmus School of Economics (ESE) ( email )

Tinbergen Institute

Burg. Oudlaan 50
Rotterdam, 3062 PA
Netherlands

Lennart F. Hoogerheide

VU University Amsterdam ( email )

De Boelelaan 1105
Amsterdam, ND North Holland 1081 HV
Netherlands

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