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Open AccessArticle

Copula–Based vMEM Specifications versus Alternatives: The Case of Trading Activity

1
Dipartimento di Statistica, Informatica, Applicazioni “G. Parenti”, Università di Firenze, 50134 Firenze, Italy
2
Department of Finance, Stern School of Business, New York University, New York, 10012 NY, USA
3
NYU Florence, Villa La Pietra, 50139 Firenze, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Nikolaus Hautsch
Econometrics 2017, 5(2), 16; https://doi.org/10.3390/econometrics5020016
Received: 4 March 2016 / Revised: 3 March 2017 / Accepted: 5 April 2017 / Published: 12 April 2017
(This article belongs to the Special Issue Financial High-Frequency Data)
We discuss several multivariate extensions of the Multiplicative Error Model to take into account dynamic interdependence and contemporaneously correlated innovations (vector MEM or vMEM). We suggest copula functions to link Gamma marginals of the innovations, in a specification where past values and conditional expectations of the variables can be simultaneously estimated. Results with realized volatility, volumes and number of trades of the JNJ stock show that significantly superior realized volatility forecasts are delivered with a fully interdependent vMEM relative to a single equation. Alternatives involving log–Normal or semiparametric formulations produce substantially equivalent results. View Full-Text
Keywords: GARCH; MEM; realized volatility; trading volume; trading activity; trades; copula; volatility forecasting GARCH; MEM; realized volatility; trading volume; trading activity; trades; copula; volatility forecasting
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Cipollini, F.; Engle, R.F.; Gallo, G.M. Copula–Based vMEM Specifications versus Alternatives: The Case of Trading Activity. Econometrics 2017, 5, 16.

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