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Testing For Zero Autocorrelation In The Presence Of Statistical Dependence

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Author Info

  • Lobato, I.N.
  • Nankervis, John C.
  • Savin, N.E.

Abstract

The problem addressed in this paper is to test the null hypothesis that a time series process is uncorrelated up to lag K in the presence of statistical dependence. We propose an extension of the Box Pierce Q-test that is asymptotically distributed as chi-square when the null is true for a very general class of dependent processes that includes non-martingale difference sequences. The test is based on a consistent estimator of the asymptotic covariance matrix of the sample autocorrelations under the null. The finite sample performance of this extension is investigated in a Monte Carlo study.

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Bibliographic Info

Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 18 (2002)
Issue (Month): 03 (June)
Pages: 730-743

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Handle: RePEc:cup:etheor:v:18:y:2002:i:03:p:730-743_18

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Cited by:
  1. Todea, Alexandru & Zoicas Ienciu, Adrian, 2011. "Technical Analysis and Stochastic Properties of Exchange Rate Movements: Empirical Evidence from the Romanian Currency Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 175-192, March.
  2. Chortareas, Georgios & Jiang, Ying & Nankervis, John C., 2011. "The random-walk behavior of the Euro exchange rate," Finance Research Letters, Elsevier, vol. 8(3), pages 158-162, September.
  3. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2012. "Exchange-rate return predictability and the adaptive markets hypothesis: Evidence from major foreign exchange rates," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1607-1626.
  4. Shao, Xiaofeng, 2011. "A bootstrap-assisted spectral test of white noise under unknown dependence," Journal of Econometrics, Elsevier, vol. 162(2), pages 213-224, June.
  5. Adrian Wai-Kong Cheung & Jen-Je Su & Astrophel Kim Choo, 2011. "Are Euro exchange rates markets efficient? New evidence from a large panel," Discussion Papers in Finance finance:201109, Griffith University, Department of Accounting, Finance and Economics.
  6. Peter C.B. Phillips & Sainan Jin, 2013. "Testing the Martingale Hypothesis," Cowles Foundation Discussion Papers 1912, Cowles Foundation for Research in Economics, Yale University.
  7. Marian Vavra, 2012. "Testing Non-linearity Using a Modified Q Test," Birkbeck Working Papers in Economics and Finance 1204, Birkbeck, Department of Economics, Mathematics & Statistics.
  8. Jen-Je Su, 2005. "On the size and power of testing for no autocorrelation under weak assumptions," Applied Financial Economics, Taylor & Francis Journals, vol. 15(4), pages 247-257.
  9. Carlos Velasco & Ignacio N. Lobato, 2004. "A simple and general test for white noise," Econometric Society 2004 Latin American Meetings 112, Econometric Society.
  10. Francq, Christian & Zakoïan, Jean-Michel, 2007. "HAC estimation and strong linearity testing in weak ARMA models," Journal of Multivariate Analysis, Elsevier, vol. 98(1), pages 114-144, January.
  11. Zhang, Jingsi & Jiang, Wenxin & Shao, Xiaofeng, 2013. "Bayesian model selection based on parameter estimates from subsamples," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 979-986.
  12. repec:ebl:ecbull:v:3:y:2004:i:46:p:1-9 is not listed on IDEAS
  13. Miguel A. Delgado & Carlos Velasco, 2010. "A distribution-free transform of the residuals sample autocorrelations with application to model checking," Economics Working Papers we101707, Universidad Carlos III, Departamento de Economía.
  14. Sant'Anna, Pedro H. C., 2013. "Testing for Uncorrelated Residuals in Dynamic Count Models with an Application to Corporate Bankruptcy," MPRA Paper 48376, University Library of Munich, Germany.
  15. Escanciano, J. Carlos & Lobato, Ignacio N., 2009. "An automatic Portmanteau test for serial correlation," Journal of Econometrics, Elsevier, vol. 151(2), pages 140-149, August.
  16. Guay, Alain & Guerre, Emmanuel & Lazarová, Štěpána, 2013. "Robust adaptive rate-optimal testing for the white noise hypothesis," Journal of Econometrics, Elsevier, vol. 176(2), pages 134-145.

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