A NOTE ON THE LSE OF THREE-REGIME TAR MODEL WITH AN INFINITE VARIANCE

Yaxing Yang () and Shiqing Ling ()
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Yaxing Yang: Xiamen University and Hong Kong University of Science and Technology, P. R. China
Shiqing Ling: Xiamen University and Hong Kong University of Science and Technology, P. R. China

Annals of Financial Economics (AFE), 2018, vol. 13, issue 02, 1-13

Abstract: The least square estimator (LSE) of three-regime TAR models has been well developed when the noise has a finite variance. However, little is known about the asymptotic behavior of the LSE of three-regime threshold autoregressive (TAR) models in the heavy-tailed setting and neither theory nor methodology is available for model fitting in this case. In this paper, we use simulation method to study the asymptotic behavior of the LSE of infinite variance three-regime TAR models. A real example is given for the NASDAQ daily volume from the year 2012 to 2014. The results in this paper may provide an empirical insight for further theoretical research of the LSE of three-regime TAR models with heavy-tailed innovations.

Keywords: Least square estimation; infinite variance; threshold models; simulation (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1142/S2010495218500070

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