Author:
Ashley Richard A.,Patterson Douglas M.
Abstract
Daily financial returns (and daily stock returns, in particular) are commonly modeled as GARCH(1, 1) processes. Here we test this specification using new model evaluation technology developed by Ashley and Patterson that examines the ability of the estimated model to reproduce features of particular interest: various aspects of nonlinear serial dependence, in the present instance. Using daily returns to the CRSP equally weighted stock index, we find that the GARCH(1, 1) specification cannot be rejected; thus, this model appears to be reasonably adequate in terms of reproducing the kinds of nonlinear serial dependence addressed by the battery of nonlinearity tests used here.
Publisher
Cambridge University Press (CUP)
Subject
Economics and Econometrics
Reference27 articles.
1. Lagrange multiplier tests for testing nonlinearities in time series models;Saikkonen;Scandinavian Journal of Statistics,1988
2. Time Irreversibility and Business Cycle Asymmetry
3. Tests for specification errors in classical linear least squares regression analysis;Ramsey;Journal of the Royal Statistical Society B,1969
4. A Nonlinear Time Series Workshop
5. Mizrach B. (1991) A Simple Nonparametric Test for Independence. Unpublished manuscript, Department of Economics, Rutgers University.
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