Abstract

http://ssrn.com/abstract=1354528
 
 

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Semiparametric Vector MEM


Fabrizio Cipollini


Universita di Firenze, DiSIA (Dipartimento di Statistica, Informatica, Applicazioni)

Robert F. Engle


New York University - Leonard N. Stern School of Business - Department of Economics; New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER)

Giampiero M. Gallo


Universita' di Firenze - Dipartimento di Statistica, Informatica, Applicazioni "G.Parenti"

February 2009

NYU Working Paper No. FIN-08-041

Abstract:     
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: amore 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.

Number of Pages in PDF File: 21

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Date posted: March 9, 2009  

Suggested Citation

Cipollini, Fabrizio and Engle, Robert F. and Gallo, Giampiero M., Semiparametric Vector MEM (February 2009). NYU Working Paper No. FIN-08-041. Available at SSRN: http://ssrn.com/abstract=1354528

Contact Information

Fabrizio Cipollini
Universita di Firenze, DiSIA (Dipartimento di Statistica, Informatica, Applicazioni) ( email )
Viale Morgagni, 59
Florence, Florence 50134
Italy
+39 055 2751592 (Phone)
+39 055 4223560 (Fax)
Robert F. Engle (Contact Author)
New York University - Leonard N. Stern School of Business - Department of Economics ( email )
269 Mercer Street
New York, NY 10003
United States
New York University (NYU) - Department of Finance
Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Giampiero M. Gallo
Universita' di Firenze - Dipartimento di Statistica, Informatica, Applicazioni "G.Parenti" ( email )
Viale G.B. Morgagni, 59
Florence, 50134
Italy
0039 055 2751 591 (Phone)
0039 055 4223560 (Fax)
HOME PAGE: http://www.disia.unifi.it/gallog
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