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Testing for marginal asymmetry of weakly dependent processes

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  • Marian Vavra

    (National Bank of Slovakia)

Abstract

This article addresses the issue of testing for asymmetry of the marginal law of weakly dependent processes. A modified quantile-based symmetry test is considered. The test has an intuitive interpretation, it is easy and fast to calculate, follows a standard limiting distribution, and much importantly, it is robust against weak dependence of observations and outliers. The finite sample performance of the robust test is examined via Monte Carlo experiments. An empirical application using economic indicators is provided as well.

Suggested Citation

  • Marian Vavra, 2013. "Testing for marginal asymmetry of weakly dependent processes," Working and Discussion Papers WP 1/2013, Research Department, National Bank of Slovakia.
    • Handle: RePEc:svk:wpaper:1022
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    File URL: http://www.nbs.sk/_img/Documents/PUBLIK/WP_1-2013.pdf
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    Cited by:

    1. Luke Hartigan, 2016. "Testing for Symmetry in Weakly Dependent Time Series," Discussion Papers 2016-18, School of Economics, The University of New South Wales.
    2. Marián Vávra, 2020. "Assessing distributional properties of forecast errors for fan-chart modelling," Empirical Economics, Springer, vol. 59(6), pages 2841-2858, December.
    3. Zacharias Psaradakis & Márian Vávra, 2018. "Bootstrap-Assisted Tests of Symmetry for Dependent Data," Birkbeck Working Papers in Economics and Finance 1806, Birkbeck, Department of Economics, Mathematics & Statistics.
    4. Zacharias Psaradakis & Marián Vávra, 2022. "Using Triples to Assess Symmetry Under Weak Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1538-1551, October.

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    More about this item

    Keywords

    marginal symmetry; sample quantiles; Monte Carlo experiments;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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