This paper estimates a structural times series model of return volatility. We argue that the structural time series approach to GARCH modelling first suggested by Engle and Lee, has the potential to improve the empirical reliability of GARCH models, and greatly enhance their interpretability. In its structural form, our model has tow parts, a short-memory GARCH model with a time-varying benchmark variance, and a longer-memory exponential smoothing model of benchmark variance. In its reduced for, the model is equivalent to a restricted-coefficient version of the GARCH (2,2) model. We apply the model to daily equity index returns from seven countries over the period January 1980 - April 1997. The model significantly outperform unstructured GARCH in its ability to capture short, medium and long-term memory in daily return volatility.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Publisher Info
Paper provided by Financial Markets Group in its series FMG Discussion Papers with number
dp370.