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	Testing covariance stationarity
	Xiao, Zhijie ; Lima, Luiz Renato
	2010-05-11 ; 2010-05-11
关键词	asymptotic theory KPSS stationarity testing time-varying variance TIME-SERIES REGRESSION STOCK-MARKET PRICES UNIT-ROOT TESTS CONDITIONAL HETEROSKEDASTICITY MATRIX ESTIMATION LINEAR-PROCESSES NULL HYPOTHESIS LONG MEMORY VOLATILITY VARIANCE Economics Mathematics, Interdisciplinary Applications Social Sciences, Mathematical Methods Statistics & Probability
中文摘要	In this paper, we show that the widely used stationarity tests such as the Kwiatkowski Phillips, Schmidt, and Shin (KPSS) test have power close to size in the presence of time-varying unconditional variance. We propose a new test as a complement of the existing tests. Monte Carlo experiments show that the proposed test possesses the following characteristics: (i) in the Presence of unit root or a structural change in the mean, the proposed test is as powerful as the KPSS and other tests, (ii) in the presence of a changing variance, the traditional tests Perform badly whereas the proposed test has high power comparing to the existing tests; (iii) the proposed test has the same size as traditional stationarity tests under the null hypothesis of stationarity. An application to daily observations of return on U.S. Dollar/Euro exchange rate reveals the existence of instability in the unconditional variance when the entire sample is considered, but stability is found in subsamples.
语种	英语 ; 英语
出版者	TAYLOR & FRANCIS INC ; PHILADELPHIA ; 325 CHESTNUT ST, SUITE 800, PHILADELPHIA, PA 19106 USA
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/26199]
专题	清华大学
推荐引用方式 GB/T 7714	Xiao, Zhijie,Lima, Luiz Renato. Testing covariance stationarity[J],2010, 2010.
APA	Xiao, Zhijie,&Lima, Luiz Renato.(2010).Testing covariance stationarity..
MLA	Xiao, Zhijie,et al."Testing covariance stationarity".(2010).

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