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Tests for m-dependence Based on Sample Splitting Methods

Author

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  • Seongman Moon

    (Universidad Carlos III de Madrid)

  • Carlos Velasco

    (Universidad Carlos III de Madrid)

Abstract

This paper develops new inference methods for m-dependent data. Our approach is based on sample splitting by regular sampling of original data at lower frequencies, so that standard techniques can be used for independent data in individual subsamples. We then explore several alternatives of aggregation across subsample statistics and investigate their asymptotic and finite sample properties. We apply our methods to nonparametric tests of the predictability of excess returns in the presence of m-dependence. We also illustrate how our serial dependence tests can provide valid information for identifying particular economic alternatives when testing the expectations hypothesis in foreign exchange markets.

Suggested Citation

  • Seongman Moon & Carlos Velasco, 2011. "Tests for m-dependence Based on Sample Splitting Methods," Working Papers 1108, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    • Handle: RePEc:sgo:wpaper:1108
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    Cited by:

    1. David Harris & Hsein Kew, 2014. "Portmanteau Autocorrelation Tests Under Q-Dependence And Heteroskedasticity," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(3), pages 203-217, May.

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    More about this item

    Keywords

    m-dependence; sample splitting; pooled method; Wald method; minimum/maximum/median method; expectations hypothesis.;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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