Abstract

http://ssrn.com/abstract=1492177
 
 

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Asymptotic Distribution-Free Diagnostic Tests for Heteroskedastic Time Series Models


Juan Carlos Escanciano


Indiana University Bloomington - Department of Economics

September 10, 2009

Center for Applied Economics and Policy Research Paper No. 019-2009

Abstract:     
This article investigates model checks for a class of possibly nonlinear heteroskedastic time series models, including but not restricted to ARMA-GARCH models. We propose omnibus tests based on functionals of certain weighted standardized residual empirical processes. The new tests are asymptotically distribution-free, suitable when the conditioning set is in…nite-dimensional, and consistent against a class of Pitman's local alternatives converging at the parametric rate n1=2; with n the sample size. A Monte Carlo study shows that the simulated level of the proposed tests is close to the asymptotic level already for moderate sample sizes and that tests have a satisfactory power performance. Finally, we illustrate our methodology with an application to the well-known S&P 500 daily stock index. The paper also contains an asymptotic uniform expansion for weighted residual empirical processes when initial conditions are considered, a result of independent interest.

Number of Pages in PDF File: 33

Keywords: Time series models, model speci…cation, ARMA-GARCH mod- els, S&P 500

JEL Classification: C12, C52

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Date posted: October 21, 2009  

Suggested Citation

Escanciano, Juan Carlos, Asymptotic Distribution-Free Diagnostic Tests for Heteroskedastic Time Series Models (September 10, 2009). Center for Applied Economics and Policy Research Paper No. 019-2009. Available at SSRN: http://ssrn.com/abstract=1492177 or http://dx.doi.org/10.2139/ssrn.1492177

Contact Information

Juan Carlos Escanciano (Contact Author)
Indiana University Bloomington - Department of Economics ( email )
Bloomington, IN 47405-6620
United States
812-855-7925 (Phone)
812-855-3736 (Fax)

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