Semiparametric and Nonparametric Testing for Long Memory. A Monte Carlo Study.

Hauser, Michael A. (1997) Semiparametric and Nonparametric Testing for Long Memory. A Monte Carlo Study. Preprint Series / Department of Applied Statistics and Data Processing, 16. Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, Vienna.


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The finite sample properties of three semiparametric estimators, several versions of the modified rescaled range, MMR, and three versions of the GHURST estimator are investigated. Their power and size for testing for long memory under short-run effects, joint short and long-run effects, heteroscedasticity and t-distributions are given using Monte Carlo methods. The MMR with the Barlett window is generally robust with the disadvantage of a relatively small power. The trimmed Whittle likelihood has high power in general and is robust expect for large short-run effects. The tests are applied to chandes in exchange rate series (daily data) of 6 major countries. The hypothesis of no fractional integration is rejected for none of the series. (author's abstract)

Item Type: Paper
Additional Information: published in: Empirical Economics 22, 1997, pp. 247-271
Classification Codes: JEL C14, G15
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 10 Jul 2006 10:10
Last Modified: 22 Oct 2019 00:41


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