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Autoregressive Conditional Skewness

Published online by Cambridge University Press:  06 April 2009

Campbell R. Harvey
Affiliation:
Duke University, Durham, NC 27708 and National Bureau of Economic Research, Cambridge, MA 02138
Akhtar Siddique
Affiliation:
Georgetown University, Washington, DC 20057.

Abstract

We present a new methodology for estimating time-varying conditional skewness. Our model allows for changing means and variances, uses a maximum likelihood framework with instruments, and assumes a non-central t distribution. We apply this method to daily, weekly, and monthly stock returns, and find that conditional skewness is important. In particular, we show that the evidence of asymmetric variance is consistent with conditional skewness. Inclusion of conditional skewness also impacts the persistence in conditional variance.

Type
Research Article
Copyright
Copyright © School of Business Administration, University of Washington 1999

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