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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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Author Info
Maria Helena Lopes Moreira da Veiga ()
Abstract

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.

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Publisher Info
Paper provided by Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC) in its series UFAE and IAE Working Papers with number 585.03.

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Length: 29
Date of creation: 21 Sep 2003
Date of revision:
Handle: RePEc:aub:autbar:585.03

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Related research
Keywords: Efficient Method of Moments; One (Two) Factor Volatility Logarithmic Model; Mean-Reversion; Persistent Volatility; Feedback; Projection; Seminonparametric (SNP); Reprojection.;

Find related papers by JEL classification:
G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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