A Model for Multivariate Non-Negative Valued Processes in Financial Econometrics
Universita di Firenze, DiSIA (Dipartimento di Statistica, Informatica, Applicazioni)
Robert F. Engle
New York University - Leonard N. Stern School of Business - Department of Economics; National Bureau of Economic Research (NBER); New York University (NYU) - Department of Finance
Giampiero M. Gallo
Universita' di Firenze - Dipartimento di Statistica
January, 27 2009
The Multiplicative Error Model for nonnegative valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation process with nonnegative support. A multivariate extension allows the innovations to be contemporaneously correlated. The estimation procedure is hindered by the lack of sufficiently flexible probability density functions for such processes. We adopt copula functions to be able to estimate the parameters of the scale factors and of the correlations of the innovation processes. We illustrate the feasibility of the procedure and the gains over the equation by equation approach using a model with different volatility measures.
Number of Pages in PDF File: 38
Keywords: GARCH, MEM, Volatility, Copula, financial time seriesworking papers series
Date posted: January 28, 2009
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