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Tests for m-dependence Based on Sample Splitting Methods

  • Seongman Moon

    ()

    (Universidad Carlos III de Madrid)

  • Carlos Velasco

    ()

    (Universidad Carlos III de Madrid)

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.

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Paper provided by Research Institute for Market Economy, Sogang University in its series Working Papers with number 1108.

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Length: 51 pages
Date of creation: Aug 2011
Date of revision:
Handle: RePEc:sgo:wpaper:1108
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