Testing for Sign and Amplitude Asymmetries Using Threshold Autoregressions

Posted: 30 Mar 2006

See all articles by Ana-Maria Fuertes

Ana-Maria Fuertes

Cass Business School, City University of London

Jerry Coakley

University of Essex - Essex Business School

Abstract

This paper uses threshold autoregressions to characterize asymmetries in adjustment dynamics and develops likelihood ratio tests to detect them. A robust bootstrap technique is proposed to circumvent the problem that the asymptotic distribution of the test statistics is non-standard. Monte Carlo simulations show that the bootstrap tests are correctly sized and are robust to near-unit roots and non-Gaussian errors. Their power is reasonable, improves sharply with the time series length and remains satisfactory for smooth transition autoregressions. Our approach combined with nonparametric tests can discriminate between asymmetries in adjustment dynamics and in innovations. An application to four monthly US dollar spot returns provides evidence of amplitude asymmetry.

Keywords: Regime-switching, LR test, Bootstrap, Subsampling, Monte Carlo

JEL Classification: C22, C15, C52

Suggested Citation

Fuertes, Ana-Maria and Coakley, Jerry, Testing for Sign and Amplitude Asymmetries Using Threshold Autoregressions. Journal of Economic Dynamics and Control, Vol. 30, No. 4, pp. 623-654, 2006; Cass Business School Research Paper. Available at SSRN: https://ssrn.com/abstract=892589

Ana-Maria Fuertes

Cass Business School, City University of London ( email )

Faculty of Finance
106 Bunhill Row
London, EC1Y 8TZ
United Kingdom
+44 207 477 0186 (Phone)
+44 207 477 8881 (Fax)

HOME PAGE: http://www.city.ac.uk/people/academics/ana-maria-fuertes

Jerry Coakley (Contact Author)

University of Essex - Essex Business School ( email )

Wivenhoe Park
Colchester, CO4 3SQ
United Kingdom
+44 1206 872455 (Phone)
+44 1206 873429 (Fax)

HOME PAGE: http://www.essex.ac.uk/afm/staff/coakley.shtm

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