A Distance Test of Normality for a Wide Class of Stationary Processes

Zacharias Psaradakis and Marián Vávra
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Marián Vávra: National Bank of Slovakia
Authors registered in the RePEc Author Service: Marian Vavra ()

No 1513, Birkbeck Working Papers in Economics and Finance from Birkbeck, Department of Economics, Mathematics & Statistics

Abstract: This paper considers a distance test for normality of the one-dimensional marginal distribution of stationary fractionally integrated processes. The test is implemented by using an autoregressive sieve bootstrap approximation to the null sampling distribution of the test statistic. The bootstrap-based test does not require knowledge of either the dependence parameter of the data or of the appropriate norming factor for the test statistic. The small-sample properties of the test are examined by means of Monte Carlo experiments. An application to real-world data is also presented.

Keywords: Distance test; fractionally integrated process; Sieve bootstrap; normality. (search for similar items in EconPapers)
JEL-codes: C12 C22 (search for similar items in EconPapers)
Date: 2015-09
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https://eprints.bbk.ac.uk/id/eprint/15266 First version, 2015 (application/pdf)

Related works:
Journal Article: A distance test of normality for a wide class of stationary processes (2017)
Working Paper: Testing for normality with applications (2015)
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