GARCH-type Models with Generalized Secant Hyperbolic Innovations

Verfasser / Beitragende:
[Paola Palmitesta, Corrado Provasi]
Ort, Verlag, Jahr:
2004
Enthalten in:
Studies in Nonlinear Dynamics & Econometrics, 8/2(2004-05-18)
Format:
Artikel (online)
ID: 378929828
LEADER caa a22 4500
001 378929828
003 CHVBK
005 20180305123626.0
007 cr unu---uuuuu
008 161128e20040518xx s 000 0 eng
024 7 0 |a 10.2202/1558-3708.1212  |2 doi 
035 |a (NATIONALLICENCE)gruyter-10.2202/1558-3708.1212 
245 0 0 |a GARCH-type Models with Generalized Secant Hyperbolic Innovations  |h [Elektronische Daten]  |c [Paola Palmitesta, Corrado Provasi] 
520 3 |a GARCH-type models have been analyzed assuming various nongaussian distributions of errors. In general, the asymmetric generalized Student-t random variable seems to be the distribution which better captures the nonnormality features of financial data. However, a drawback of this distribution is represented by the technical dificulties due to the evaluation of moments, especially in the case of fractional degrees of freedom. In this paper we propose to model high frequency time series returns using GARCH-type models with a generalized secant hyperbolic (GSH) distribution. The main advantage of the GSH distribution over the Student-t distribution is that all the moments are finite for each value of the shape parameter. The distribution is symmetric with respect to the mean, but we show that it is still possible to obtain the density in a closed form introducing a skewness parameter according to the method proposed by Fernandez and Steel. We use a Monte Carlo experiment to validate this distribution in the context of GARCH models with maximum likelihood estimates of parameters. Finally, we show an application to log returns of a stock index. 
540 |a ©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston 
700 1 |a Palmitesta  |D Paola  |u University of Siena, Italy, palmitesta@unisi.it  |4 aut 
700 1 |a Provasi  |D Corrado  |u University of Padua, provasi@stat.unipd.it  |4 aut 
773 0 |t Studies in Nonlinear Dynamics & Econometrics  |d De Gruyter  |g 8/2(2004-05-18)  |q 8:2  |1 2004  |2 8  |o snde 
856 4 0 |u https://doi.org/10.2202/1558-3708.1212  |q text/html  |z Onlinezugriff via DOI 
908 |D 1  |a research article  |2 jats 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.2202/1558-3708.1212  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Palmitesta  |D Paola  |u University of Siena, Italy, palmitesta@unisi.it  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Provasi  |D Corrado  |u University of Padua, provasi@stat.unipd.it  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Studies in Nonlinear Dynamics & Econometrics  |d De Gruyter  |g 8/2(2004-05-18)  |q 8:2  |1 2004  |2 8  |o snde 
900 7 |b CC0  |u http://creativecommons.org/publicdomain/zero/1.0  |2 nationallicence 
898 |a BK010053  |b XK010053  |c XK010000 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-gruyter