Varianza condicional de medias móviles no-lineales
Daniel Ventosa-Santaulària (),
Alfonso Mendoza-Velázquez () and
Ensayos Revista de Economia, 2008, vol. XXVII, issue 2, 29-48
We present a new heteroskedastic conditional variance model using NonLinear Moving Average as the basis for this specification [NLMACH(q)]. The typical problem of this class of models-i.e., noninvertibility—is solved by means of an intuitive parametric restriction; this allows us to use Maximum Likelihood as the estimation procedure. The statistical properties of the new model are both simple and attractive for empirical purposes in finance: a natural fat-tailed distribution stands out. The Autocorrelation Function of the squared process allows us for identification of the number of lags to be included in the new specification. In addition, we present several Monte Carlo experiments where the properties of the model using finite samples are exhibited. Finally, an empirical application using exchange rates and capital market bonds is shown.
Keywords: Conditionally Heteroskedastic Models; NLMACH(q); Volatility; Fat-tailed Distributions (search for similar items in EconPapers)
JEL-codes: C12 C13 C22 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ere:journl:v:xxvii:y:2008:i:2:p:29-48
Ordering information: This journal article can be ordered from
Access Statistics for this article
Ensayos Revista de Economia is currently edited by Edgar Mauricio Luna Domínguez
More articles in Ensayos Revista de Economia from Universidad Autonoma de Nuevo Leon, Facultad de Economia Avenida Lazaro Cardenas 4600 Ote., Fraccionamiento Residencial Las Torres, C.P. 64930. Monterrey, Nuevo Leon. México.. Contact information at EDIRC.
Bibliographic data for series maintained by Dora María Vega Facio ().