Alternative Models for Conditional Stock Volatility
Adrian R. Pagan
Australian National University
G. William Schwert
University of Rochester, Rochester, NY 14627
and National Bureau of Economic Research
Journal of Econometrics, 45 (July 1990) 267-290
Journal of Econometrics All Star
Paper
This paper compares several statistical models for monthly stock return volatility. The focus is on U.S. data from 1834-1925 because the post-1926 data have been analyzed in more detail by others. Also, the Great Depression had levels of stock volatility that are inconsistent with stationary models for conditional heteroskedasticity. We show the importance of nonlinearities in stock return behavior that are not captured by conventional ARCH or GARCH models. We also show the nonstationarity of stock volatility.
Key words: Volatility, Heteroskedasticity, Stock Market, ARCH, GARCH, Nonparametric, Kernel, Fourier
JEL Classifications: G14, C22
Cited 345 times in the SSCI and SCOPUS through 2008
© Copyright 1990, Elsevier
The following file contains the reprint of this paper in Acrobat's portable data format (.pdf). The file is about 994 KB and can only be viewed (and printed) using a copy of Acrobat Reader or Acrobat Exchange.
If you want the current version of the Adobe Acrobat Reader for other
platforms, visit Adobe's web page by clicking the image below.
Click here to download this paper in PDF format.
Return to Publications Page
© Copyright 1998-2009, G. William Schwert
Last Updated on 3/5/2009