Using the correlation exponent to decide whether an economic series is chaotic
作者:
T. Liu,
C. W. J. Granger,
W. P. Heller,
期刊:
Journal of Applied Econometrics
(WILEY Available online 1992)
卷期:
Volume 7,
issue S1
页码: 25-39
ISSN:0883-7252
年代: 1992
DOI:10.1002/jae.3950070504
出版商: Wiley Subscription Services, Inc., A Wiley Company
数据来源: WILEY
摘要:
AbstractWe consider two ways of distinguishing deterministic time‐series from stochastic white noise; the Grassberger—Procaccia correlation exponent test and the Brock, Dechert, Scheinkman (or BDS) test. Using simulated data to test the power of these tests, the correlation exponent test can distinguish white noise from chaos. It cannot distinguish white noise from chaos mixed with a small amount of white noise. With i.i.d. as the null, the BDS correctly rejects the null when the data are deterministic chaos. Although the BDS test may also reject the null even when the data are stochastic, it may be useful in distinguishing between linear and nonlinear stochastic proces
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