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Automated Variable Selection in Vector Multiplicative Error Models

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Abstract

Multiplicative Error Models (MEM) can be used to trace the dynamics of non–negative valued processes. Interactions between several such processes are accommodated by the vector MEM and estimated by maximum likelihood (Gamma marginals with copula functions) or by Generalized Method of Moments. In choosing the relevant variables one can follow an automated procedure where the full specification is successively pruned in a general–to–specific approach. An efficient and fast algorithm is presented in this paper and evaluated by means of a simulation and a real world example of volatility spillovers in European markets.

Suggested Citation

  • Fabrizio Cipollini & Giampiero M. Gallo, 2009. "Automated Variable Selection in Vector Multiplicative Error Models," Econometrics Working Papers Archive wp2009_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  • Handle: RePEc:fir:econom:wp2009_02
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    Cited by:

    1. Karanasos, Menelaos & Xu, Yongdeng & Yfanti, Stavroula, 2017. "Constrained QML Estimation for Multivariate Asymmetric MEM with Spillovers: The Practicality of Matrix Inequalities," Cardiff Economics Working Papers E2017/14, Cardiff University, Cardiff Business School, Economics Section.
    2. Cipollini, Fabrizio & Gallo, Giampiero M., 2025. "Multiplicative Error Models: 20 years on," Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
    3. Hautsch, Nikolaus & Okhrin, Ostap & Ristig, Alexander, 2012. "Modeling time-varying dependencies between positive-valued high-frequency time series," SFB 649 Discussion Papers 2012-054, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. repec:hum:wpaper:sfb649dp2013-041 is not listed on IDEAS
    5. Wang, Yanfeng & Ke, Rui & Yang, Dong, 2024. "Modeling dynamic higher-order comoments for portfolio selection based on copula approach," International Review of Economics & Finance, Elsevier, vol. 96(PB).
    6. Zhang, Shulin & Okhrin, Ostap & Zhou, Qian M. & Song, Peter X.-K., 2016. "Goodness-of-fit test for specification of semiparametric copula dependence models," Journal of Econometrics, Elsevier, vol. 193(1), pages 215-233.
    7. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula–Based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics, MDPI, vol. 5(2), pages 1-24, April.
    8. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    9. repec:hum:wpaper:sfb649dp2012-054 is not listed on IDEAS

    More about this item

    Keywords

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    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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