Functional gradient descent for financial time series with an application to the measurement of market risk
Journal
Journal of Banking & Finance
ISSN
0378-4266
ISSN-Digital
1872-6372
Type
journal article
Date Issued
2005-04-01
Author(s)
Abstract
The estimation and forecast of the volatility matrix are two of the main tasks of financial econometrics since they are essential ingredients in many practical applications. Unfortunately the use of classical multivariate methods in large dimensions is difficult because of the curse of dimensionality. We present a general semiparametric technique, based on functional gradient descent (FGD) and able to overcome most problems associated with a multivariate GARCH-type estimation. By testing the accuracy of the volatility estimates for the measurement of market risk on real data we provide empirical evidence of the strong predictive potential of the FGD approach, also in comparison to other standard methods.
Language
English
HSG Classification
not classified
Refereed
Yes
Publisher
Elsevier
Publisher place
Amsterdam
Volume
29
Number
4
Start page
959
End page
977
Pages
19
Subject(s)
Eprints ID
32647