Bootstrap-Assisted Tests for Skewness, Kurtosis, and Normality Under Unknown Dependence

Charisios Grivas (), Zacharias Psradakis () and Marian Vavra ()
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Charisios Grivas: Aalborg University
Zacharias Psradakis: Birkbeck Business School
Marian Vavra: National Bank of Slovakia

No WP 10/2026, Working and Discussion Papers from Research Department, National Bank of Slovakia

Abstract: This paper considers tests for skewness, kurtosis and normality of the one-dimensional marginal distribution of a stationary fractional process, which may exhibit short memory, antipersistence or long memory. The autoregressive-sieve bootstrap is used to obtain Pvalues and critical values for tests based on studentized empirical coefficients of skewness and kurtosis. These studentized coefficients are constructed using variance estimators obtained by the same bootstrap procedure. Notably, such tests, as well as variants based on non-studentized statistics, can be implemented in a straightforward manner without requiring knowledge or estimation of the memory parameter of the process. Monte Carlo simulations show that the bootstrap-assisted tests perform well for sample sizes that are typical in applied settings. The methodology is further illustrated through an application to realized measures of stock-return volatility.

JEL-codes: C12 C22 C63 (search for similar items in EconPapers)
Pages: 57 pages
Date: 2026-09
New Economics Papers: this item is included in nep-ets
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