Semiparametric vector MEM
Fabrizio Cipollini (),
Robert Engle and
Giampiero Gallo ()
Econometrics Working Papers Archive from Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti"
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.
Keywords: Multiplicative Error Model; GMM; Simultaneous Equations; Volatility; Market Activity (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-mst
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Journal Article: SEMIPARAMETRIC VECTOR MEM (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:fir:econom:wp2009_03
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