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A small-sample overlapping variance-ratio test

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  • Y. K. Tse
  • K. W. Ng
  • Xibin Zhang

Abstract

The null distribution of the overlapping variance-ratio (OVR) test of the random-walk hypothesis is known to be downward biased and skewed to the right in small samples. As shown by Lo and MacKinlay (1989), the test under-rejects the null on the left tail seriously when the sample size is small. This property adversely affects the applicability of the OVR test to macroeconomic time series, which usually have rather small samples. In this paper, we propose a modified overlapping variance-ratio statistic and derive its exact mean under the normality assumption. We propose to approximate the small-sample distribution of the modified statistic using a beta distribution that matches the (exact) mean and the (asymptotic) variance. A Monte Carlo experiment shows that the beta approximation performs well in small samples. Copyright 2004 Blackwell Publishing Ltd.

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Bibliographic Info

Article provided by Wiley Blackwell in its journal Journal of Time Series Analysis.

Volume (Year): 25 (2004)
Issue (Month): 1 (01)
Pages: 127-135

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Handle: RePEc:bla:jtsera:v:25:y:2004:i:1:p:127-135

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Cited by:
  1. Amélie Charles & Olivier Darne, 2009. "Variance ratio tests of random walk: An overview," Post-Print hal-00771078, HAL.
  2. Azad, A.S.M. Sohel, 2009. "Random walk and efficiency tests in the Asia-Pacific foreign exchange markets: Evidence from the post-Asian currency crisis data," Research in International Business and Finance, Elsevier, vol. 23(3), pages 322-338, September.

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