We propose three residual-based tests for conditional dynamic asymmetry. Estimation is performed under the null hypothesis of constant asymmetry of the innovations and, in a second step, the tests are performed either through a parametric model or a nonparametric method (runs). The working distribution is assumed to fall into the class of skewed distributions of Fernandez and Steel (1998) for which asymmetry is measured by the ratio between the probabilities of being larger and smaller than the mode. We derive the asymptotic distribution of the tests that incorporates the uncertainty of the estimated parameters in the first step. A Monte Carlo study shows that neglecting this uncertainty severely biases the tests and an empirical application on a basket of daily returns reveals that financial data often present dynamics in the conditional skewness.
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Paper provided by Université Libre de Bruxelles, Ecares in its series ECARES Working Papers with number
2008_009.
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Hansen, Bruce E, 1994.
"Autoregressive Conditional Density Estimation,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-30, August.
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