Please use this identifier to cite or link to this item: doi:10.22028/D291-26219
Title: A simple non-stationary model for stock returns
Author(s): Drees, Holger
Starica, Catalin
Language: English
Year of Publication: 2002
Free key words: distributional forecasts
GARCH process
DDC notations: 510 Mathematics
Publikation type: Other
Abstract: The aim of the present peper is to show the example of the S&P 500 return series that a simple non-stationary model seem to fit the data significantly better than conventional GARCH-type models outperforming them also in forecasting the distribution of tomorrow's return. Instead of a complex endogenous specification of the conditional variance, we assume that the volatility dynamics is exogenous. Since no obvious canadidates explanatory exogenous variables are at hand, we model the volatility as deterministic. This approach leads to a structurally simple regression-type model. Special attention is paid to the accurate descripion of the tails of the innovations.
Link to this record: urn:nbn:de:bsz:291-scidok-43946
Series name: Preprint / Fachrichtung Mathematik, Universität des Saarlandes
Series volume: 69
Date of registration: 2-Dec-2011
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Mathematik
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

Files for this record:
File Description SizeFormat 
preprint_69_02.pdf860,58 kBAdobe PDFView/Open

Items in SciDok are protected by copyright, with all rights reserved, unless otherwise indicated.