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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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  • 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.

Suggested Citation

  • Maria Helena Lopes Moreira da Veiga, 2003. "Are One Factor Logarithmic Volatility Models Useful to Fit the Features of Financial Data? An Application to Microsoft Data," UFAE and IAE Working Papers 585.03, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    • Handle: RePEc:aub:autbar:585.03
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    Keywords

    Efficient Method of Moments; One (Two) Factor Volatility Logarithmic Model; Mean-Reversion; Persistent Volatility; Feedback; Projection; Seminonparametric (SNP); Reprojection.;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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