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Robust Power Calculations with Tests for Serial Correlation in Stock Returns

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  • Matthew Richardson
  • Tom Smith
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    Abstract

    This paper provides an asymptotically most powerful test for a particular class of statistics which test the hypothesis of no serial correlation. This class includes many of the statistics employed in the recent finance and macroeconomics literature. Furthermore, with respect to a popular mean reversion alternative model, we show that the asymptotically most powerful test is quite robust to distributional specifications.

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    Bibliographic Info

    Paper provided by Wharton School Rodney L. White Center for Financial Research in its series Rodney L. White Center for Financial Research Working Papers with number 12-91.

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    Handle: RePEc:fth:pennfi:12-91

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    Cited by:
    1. Perron, Pierre & Vodounou, Cosme, 2004. "Tests of return predictability: an analysis of their properties based on a continuous time asymptotic framework," Journal of Empirical Finance, Elsevier, vol. 11(2), pages 203-230, March.
    2. Campbell, John, 2001. "Why Long Horizons? A Study of Power Against Persistent Alternatives," Scholarly Articles 3196341, Harvard University Department of Economics.

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