Gaussian Tests of "Extremal White Noise" for Dependent, Heterogeneous, Heavy Tailed Time Series with an Application
AbstractWe develop asymptotically chi-squared tests of tail specific extremal serial dependence for possibly heavy-tailed time series, including infinite variance and infinite mean processes. Our test statistics have a chi-squared limit distribution under the null of "extremal white-noise" for processes near-epoch-dependent on a mixing process; and obtain a power of one for extremal dependent processes under general conditions. We restrict the NED property to hold only in the extreme support of the distribution, and characterize a broad array of linear and GARCH processes with geometric or hypoberbolic memory that are extremal NED. We apply one-tailed, two-tailed, and difference in tails tests to stock market and exchange rate returns data, and find low levels of significant, persistent, symmetric extremal dependence in the Yen and British Pound, and except for the Shanghai Stock Exchange we find no evidence of extremal dependence in any absolute returns series. A limited study of bivariate volatility spillover in exchange rates reveals extremes in the daily returns of the Yen symmetrically spillover briefly into the Euro after a four day delay, and positive extreme returns in the Euro immediately, and persistently, spillover into the Yen. //
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 0411014.
Length: 54 pages
Date of creation: 18 Nov 2004
Date of revision: 09 Dec 2004
Note: Type of Document - pdf; pages: 54
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extremal dependence; white-noise; volatility spillover; near-epoch-dependence; regular variation; infinite variance; portmanteau test; exchange rates.;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-11-22 (All new papers)
- NEP-ECM-2004-11-22 (Econometrics)
- NEP-ETS-2004-11-22 (Econometric Time Series)
- NEP-FIN-2004-11-22 (Finance)
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