Using Triples to Assess Symmetry Under Weak Dependence

Zacharias Psaradakis and Marián Vávra

Journal of Business & Economic Statistics, 2022, vol. 40, issue 4, 1538-1551

Abstract: The problem of assessing symmetry about an unspecified center of the one-dimensional marginal distribution of a strictly stationary random process is considered. A well-known U-statistic based on data triples is used to detect deviations from symmetry, allowing the underlying process to satisfy suitable mixing or near-epoch dependence conditions. We suggest using subsampling for inference on the target parameter, establish the asymptotic validity of the method in our setting, and discuss data-driven rules for selecting the size of subsamples. The small-sample properties of the proposed inferential procedures are examined by means of Monte Carlo simulations. Applications to time series of output growth and stock returns are also presented.

Date: 2022
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Working Paper: On Using Triples to Assess Symmetry Under Weak Dependence (2020)
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DOI: 10.1080/07350015.2021.1939037

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