Evaluating Specification Tests for Markov-Switching Time-Series Models
AbstractWe evaluate the performance of several specification tests for Markov regime-switching time-series models. We consider the Lagrange multiplier (LM) and dynamic specification tests of Hamilton (1996) and Ljung-Box tests based on both the generalized residual and a standard-normal residual constructed using the Rosenblatt transformation. The size and power of the tests are studied using Monte Carlo experiments. We find that the LM tests have the best size and power properties. The Ljung-Box tests exhibit slight size distortions, though tests based on the Rosenblatt transformation perform better than the generalized residual-based tests. The tests exhibit impressive power to detect both autocorrelation and autoregressive conditional heteroscedasticity (ARCH). The tests are illustrated with a Markov-switching generalized ARCH (GARCH) model fitted to the US dollar-British pound exchange rate, with the finding that both autocorrelation and GARCH effects are needed to adequately fit the data. Copyright 2008 The Author. Journal compilation 2008 Blackwell Publishing Ltd
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Bibliographic InfoArticle provided by Wiley Blackwell in its journal Journal of Time Series Analysis.
Volume (Year): 29 (2008)
Issue (Month): 4 (07)
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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782
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- Chevallier, Julien, 2012.
"Global imbalances, cross-market linkages, and the financial crisis : a multivariate Markov-Switching analysis,"
Economics Papers from University Paris Dauphine
123456789/8773, Paris Dauphine University.
- Chevallier, Julien, 2012. "Global imbalances, cross-market linkages, and the financial crisis: A multivariate Markov-switching analysis," Economic Modelling, Elsevier, vol. 29(3), pages 943-973.
- Joanna Janczura & Rafał Weron, 2013. "Goodness-of-fit testing for the marginal distribution of regime-switching models with an application to electricity spot prices," AStA Advances in Statistical Analysis, Springer, vol. 97(3), pages 239-270, July.
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