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Determining risk model confidence sets

Author

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  • Cummins, Mark
  • Dowling, Michael
  • Esposito, Francesco

Abstract

Two alternative approaches to identifying a model confidence set (MCS) are contrasted. Together with a specification of the established MCS test, we present a new version of a test that identifies a model set satisfying the MCS requirements and is characterised by an alternative model ranking p-value. We also contrast the two MCS approaches empirically, constructing a market risk model selection exercise for the Dow Jones Industrial Average. Our adapted MCS method is shown to lead to a smaller MCS, nested within the MCS determined by the popular MCS method, and allows greater distinction between models.

Suggested Citation

  • Cummins, Mark & Dowling, Michael & Esposito, Francesco, 2017. "Determining risk model confidence sets," Finance Research Letters, Elsevier, vol. 22(C), pages 169-174.
    • Handle: RePEc:eee:finlet:v:22:y:2017:i:c:p:169-174
    DOI: 10.1016/j.frl.2017.02.005
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    References listed on IDEAS

    as
    1. Peter R. Hansen & Asger Lunde & James M. Nason, 2011. "The Model Confidence Set," Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
    2. Francesco P. Esposito & Mark Cummins, 2016. "Multiple Hypothesis Testing of Market Risk Forecasting Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(5), pages 381-399, August.
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