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A New Bootstrap Test for the Validity of a Set of Marginal Models for Multiple Dependent Time Series: An Application to Risk Analysis

Author

Listed:
  • David Ardia

    (Laval University, Quebec, Canada)

  • Lukasz Gatarek

    (Erasmus University Rotterdam)

  • Lennart F. Hoogerheide

    (VU University Amsterdam)

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.

Suggested Citation

  • David Ardia & Lukasz Gatarek & Lennart F. Hoogerheide, 2014. "A New Bootstrap Test for the Validity of a Set of Marginal Models for Multiple Dependent Time Series: An Application to Risk Analysis," Tinbergen Institute Discussion Papers 14-028/III, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20140028
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    References listed on IDEAS

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    4. Peter Christoffersen, 2004. "Backtesting Value-at-Risk: A Duration-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 84-108.
    5. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
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    More about this item

    Keywords

    Bootstrap test; GARCH; marginal models; multiple time series; Value-at-Risk;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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