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Portmanteau Model Diagnostics and Tests for Nonlinearity: A Comparative Monte Carlo Study of Two Alternative Methods

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  • Brooks, Chris

Abstract

This paper employs an extensive Monte Carlo study to test the size and power of the BDS and close return methods of testing for departures from independent and identical distribution. It is found that the finite sample properties of the BDS test are far superior and that the close return method cannot be recommended as a model diagnostic. Neither test can be reliably used for very small samples, while the close return test has low power even at large sample sizes. Citation Copyright 1999 by Kluwer Academic Publishers.

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File URL: http://journals.kluweronline.com/issn/0927-7099/contents
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Bibliographic Info

Article provided by Society for Computational Economics in its journal Computational Economics.

Volume (Year): 13 (1999)
Issue (Month): 3 (June)
Pages: 249-63

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Handle: RePEc:kap:compec:v:13:y:1999:i:3:p:249-63

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Web page: http://www.springerlink.com/link.asp?id=100248
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Cited by:
  1. Evzen Kocenda & Lubos Briatka, 2004. "Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power," CERGE-EI Working Papers wp235, The Center for Economic Research and Graduate Education - Economic Institute, Prague.
  2. Brooks, Chris & Henry, Olan T., 2000. "Linear and non-linear transmission of equity return volatility: evidence from the US, Japan and Australia," Economic Modelling, Elsevier, vol. 17(4), pages 497-513, December.
  3. Mariano Matilla-García & Manuel Ruiz Marín & Mohammed Dore & Rina Ojeda, 2014. "Nonparametric correlation integral–based tests for linear and nonlinear stochastic processes," Decisions in Economics and Finance, Springer, vol. 37(1), pages 181-193, April.

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