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Theory and Applications of TAR Model with Two Threshold Variables

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  • Chen, Haiqiang
  • Chong, Terence Tai Leung
  • Bai, Jushan

Abstract

A growing body of threshold models has been developed over the past two decades to capture the nonlinear movement of financial time series. Most of these models, however, contain a single threshold variable only. In many empirical applications, models with two or more threshold variables are needed. This paper develops a new threshold autoregressive model which contains two threshold variables. A likelihood ratio test is proposed to determine the number of regimes in the model. The finite-sample performance of the estimators is evaluated and an empirical application is provided.

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File URL: http://mpra.ub.uni-muenchen.de/54527/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 54527.

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Date of creation: 01 Jan 2012
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Publication status: Published in Econometric Reviews 31.2(2012): pp. 142-170
Handle: RePEc:pra:mprapa:54527

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Related research

Keywords: Threshold Autoregressive Model; Misspecification; Likelihood Ratio Test; Bootstrapping.;

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References

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  5. Chong, Terence Tai-Leung, 2001. "Structural Change In Ar(1) Models," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 17(01), pages 87-155, February.
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Cited by:
  1. Haiqiang Chen & Terence Tai Leung Chong & Yingni She, 2014. "A principal component approach to measuring investor sentiment in China," Quantitative Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 14(4), pages 573-579, April.
  2. Chong, Terence Tai Leung & Yan, Isabel K., 2014. "Estimating and Testing Threshold Regression Models with Multiple Threshold Variables," MPRA Paper 54732, University Library of Munich, Germany.
  3. repec:wyi:journl:002214 is not listed on IDEAS

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