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Unbiased weighted variance and skewness estimators for overlapping returns

Stephen Taylor () and Ming Fang ()
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Stephen Taylor: Martin Tuchman School of Management at the New Jersey Institute of Technology
Ming Fang: Martin Tuchman School of Management at the New Jersey Institute of Technology

Swiss Journal of Economics and Statistics, 2018, vol. 154, issue 1, 1-8

Abstract: Abstract This article develops unbiased weighted variance and skewness estimators for overlapping return distributions. These estimators extend the variance estimation methods constructed in Bod et. al. (Applied Financial Economics 12:155-158, 2002) and Lo and MacKinlay (Review of Financial Studies 1:41-66, 1988). In addition, they may be used in overlapping return variance or skewness ratio tests as in Charles and Darné (Journal of Economic Surveys 3:503-527, 2009) and Wong (Cardiff Economics Working Papers, 2016). An example using synthetic overlapping returns from a model fit to data from the SPY S&P 500 exchange traded fund is given in order to demonstrate under which circumstances the unbiased correction becomes significant in skewness estimation. Finally, we compare the effect of the HAC weighting schemes of Andrews (Econometrica 53:817-858, 1991) as a function of sample size and overlapping return window length.

Keywords: Overlapping returns; Variance and skewness estimation; Asset returns; Weighted estimators (search for similar items in EconPapers)
Date: 2018
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