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13.341 Articles in journals published by the UPC
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Modelling stock returns with AR-GARCH processes

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Ferenstein, Elzbieta
Gasowski, Miroslaw
Document typeArticle
Defense date2004
PublisherInstitut d'Estadística de Catalunya
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 2.5 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 2.5 Spain
Abstract
Financial returns are often modelled as autoregressive time series with random disturbances having conditional heteroscedastic variances, especially with GARCH type processes. GARCH processes have been intensely studying in financial and econometric literature as risk models of many financial time series. Analyzing two data sets of stock prices we try to fit AR(1) processes with GARCH or EGARCH errors to the log returns. Moreover, hyperbolic or generalized error distributions occur to be good models of white noise distributions.
CitationFerenstein, Elzbieta; Gasowski, Miroslaw. "Modelling stock returns with AR-GARCH processes". SORT, 2004, Vol. 28, núm. 1 
URIhttp://hdl.handle.net/2099/3744
ISSN1696-2281
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  • SORT (Statistics and Operations Research Transactions) - 2004, Vol. 28, Núm. 1 [7]
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