A New Bootstrap Test for Multiple Assets Joint Risk Testing

22 Pages Posted: 30 Mar 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: March 30, 2017

Abstract

In this paper, 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 statistical 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 within a small time frame (eg, a crisis period). We apply our method to test generalized autoregressive conditional heteroscedasticity (GARCH) model specifications for a large panel data set of stock returns.

Keywords: bootstrap test, generalized autoregressive conditional heteroscedasticity (GARCH), marginal models, multiple time series, value-at-risk (VaR)

Suggested Citation

Ardia, David and Gatarek, Lukasz T. and Hoogerheide, Lennart F., A New Bootstrap Test for Multiple Assets Joint Risk Testing (March 30, 2017). Journal of Risk, Vol. 19, No. 4, 2017, Available at SSRN: https://ssrn.com/abstract=2943439

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

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
0
Abstract Views
471
PlumX Metrics