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A bootstrap approach to test the conditional symmetry in time series models

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  • Perez-Alonso, Alicia

Abstract

This paper discusses how to test for conditional symmetry in time seriesregression models. To that end, we utilize the Bai and Ng test. We also examinethe performance of some popular (unconditional) symmetry tests for observationswhen applied to regression residuals. The tests considered include the coeficientof skewness, a joint test of the third and fifth moments, the Runs test, the Wilcoxonsigned-rank test and the Triples test. An easy-to-implement symmetric bootstrapprocedure is proposed to calculate critical values for these tests. Consistency of thebootstrap procedure will be shown. A simple Monte Carlo experiment isconducted to explore the finite-sample properties of all the tests.
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  • Perez-Alonso, Alicia, 2007. "A bootstrap approach to test the conditional symmetry in time series models," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3484-3504, April.
    • Handle: RePEc:eee:csdana:v:51:y:2007:i:7:p:3484-3504
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    Cited by:

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    2. Bacci, Silvia & Bartolucci, Francesco, 2014. "Mixtures of equispaced normal distributions and their use for testing symmetry with univariate data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 262-272.
    3. Joseph Ngatchou-Wandji & Michel Harel, 2013. "A Cramér-von Mises test for symmetry of the error distribution in asymptotically stationary stochastic models," Statistical Inference for Stochastic Processes, Springer, vol. 16(3), pages 207-236, October.
    4. Henderson, Daniel J. & Parmeter, Christopher F., 2015. "A consistent bootstrap procedure for nonparametric symmetry tests," Economics Letters, Elsevier, vol. 131(C), pages 78-82.

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: 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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