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Semiparametric vector MEM

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In financial time series analysis we encounter several instances of non–negative valued processes (volumes, trades, durations, realized volatility, daily range, and so on) which exhibit clustering and can be modeled as the product of a vector of conditionally autoregressive scale factors and a multivariate iid innovation process (vector Multiplicative Error Model). Two novel points are introduced in this paper relative to previous suggestions: a more general specification which sets this vector MEM apart from an equation by equation specification; and the adoption of a GMM-based approach which bypasses the complicated issue of specifying a general multivariate non–negative valued innovation process. A vMEM for volumes, number of trades and realized volatility reveals empirical support for a dynamically interdependent pattern of relationships among the variables on a number of NYSE stocks.

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  • Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2009. "Semiparametric vector MEM," Econometrics Working Papers Archive wp2009_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    • Handle: RePEc:fir:econom:wp2009_03
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    1. Manganelli, Simone, 2005. "Duration, volume and volatility impact of trades," Journal of Financial Markets, Elsevier, vol. 8(4), pages 377-399, November.
    2. Bera, Anil K. & Bilias, Yannis, 2002. "The MM, ME, ML, EL, EF and GMM approaches to estimation: a synthesis," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 51-86, March.
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    11. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2007. "A Model for Multivariate Non-negative Valued Processes in Financial Econometrics," Econometrics Working Papers Archive wp2007_16, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
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    More about this item

    Keywords

    Multiplicative Error Model; GMM; Simultaneous Equations; Volatility; Market Activity;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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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