A New Bootstrap Test for the Validity of a Set of Marginal Models for Multiple Dependent Time Series: an Application to Risk Analysis
Lukasz Gatarek and
Lennart F. Hoogerheide
Cahiers de recherche from CIRPEE
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 (search for similar items in EconPapers)
JEL-codes: C1 C12 C22 C44 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-ore and nep-rmg
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Working Paper: A New Bootstrap Test for the Validity of a Set of Marginal Models for Multiple Dependent Time Series: An Application to Risk Analysis (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:lvl:lacicr:1413
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