Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10261/1838
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dc.creatorLopes Moreira da Veiga, Maria Helena-
dc.date2007-11-05T13:03:49Z-
dc.date2007-11-05T13:03:49Z-
dc.date2003-09-21-
dc.date.accessioned2017-01-31T00:58:00Z-
dc.date.available2017-01-31T00:58:00Z-
dc.identifierhttp://hdl.handle.net/10261/1838-
dc.identifier.urihttp://dspace.mediu.edu.my:8181/xmlui/handle/10261/1838-
dc.descriptionThis paper provides empirical evidence that continuous time models with one factor of volatility, in some conditions, are able to fit the main characteristics of financial data. It also reports the importance of the feedback factor in capturing the strong volatility clustering of data, caused by a possible change in the pattern of volatility in the last part of the sample. We use the Efficient Method of Moments (EMM) by Gallant and Tauchen (1996) to estimate logarithmic models with one and two stochastic volatility factors (with and without feedback) and to select among them.-
dc.languageeng-
dc.relationUFAE and IAE Working Papers-
dc.relation585.03-
dc.rightsopenAccess-
dc.subjectEfficient Method of Moments-
dc.subjectMean-Reversion-
dc.subjectPersistent Volatility-
dc.titleAre One Factor Logarithmic Volatility Models Useful to Fit the Features of Financial Data? An Application to Microsoft Data-
dc.typeDocumento de trabajo-
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