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An invariant sign test for random walks based on recursive median adjustment

Title
An invariant sign test for random walks based on recursive median adjustment
Authors
So B.S.Shin D.W.
Ewha Authors
소병수신동완
SCOPUS Author ID
소병수scopus; 신동완scopus
Issue Date
2001
Journal Title
Journal of Econometrics
ISSN
0304-4076JCR Link
Citation
vol. 102, no. 2, pp. 197 - 229
Indexed
SCIE; SSCI; SCOPUS WOS scopus
Abstract
We propose a new invariant sign test for random walks against general stationary processes and develop a theory for the test. In addition to the exact binomial null distribution of the test, we establish various important properties of the test: the consistency against a wide class of possibly nonlinear stationary autoregressive conditionally heteroscedastic processes and/or heavy-tailed errors; a local asymptotic power advantage over the classical Dickey-Fuller test; and invariance to monotone data transformations, to conditional heteroscedasticity and to heavy-tailed errors. Using the sign test, we also investigate various interrelated issues such as M-estimator, exact confidence interval, sign test for serial correlation, robust inference for a cointegration model, and discuss possible extensions to models with autocorrelated errors. Monte-Carlo experiments verify that the sign test has not only very stable sizes but also locally better powers than the parametric Dickey-Fuller test and the nonparametric tests of Granger and Hallman (1991. Journal of Time Series Analysis 12, 207-224) and Burridge and Guerre (1996. Econometric Theory 12, 705-719) for heteroscedastic and/or heavy tailed errors. © 2001 Elsevier Science S.A. All rights reserved.
DOI
10.1016/S0304-4076(01)00053-7
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자연과학대학 > 통계학전공 > Journal papers
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