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Are One Factor Logarithmic Volatility Models Useful to Fit the Features of Financial Data? An Application to Microsoft Data

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dc.creator Lopes Moreira da Veiga, Maria Helena
dc.date 2007-11-05T13:03:49Z
dc.date 2007-11-05T13:03:49Z
dc.date 2003-09-21
dc.date.accessioned 2017-01-31T00:58:00Z
dc.date.available 2017-01-31T00:58:00Z
dc.identifier http://hdl.handle.net/10261/1838
dc.identifier.uri http://dspace.mediu.edu.my:8181/xmlui/handle/10261/1838
dc.description This 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.language eng
dc.relation UFAE and IAE Working Papers
dc.relation 585.03
dc.rights openAccess
dc.subject Efficient Method of Moments
dc.subject Mean-Reversion
dc.subject Persistent Volatility
dc.title Are One Factor Logarithmic Volatility Models Useful to Fit the Features of Financial Data? An Application to Microsoft Data
dc.type Documento de trabajo


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