RT Journal Article
T1 Data cloning estimation of GARCH and COGARCH models
A1 Marín, J.M.
A1 Rodríguez Bernal, Teresa
AB GARCH models include most of the stylized facts of financial time series and they have  been largely used to analyze discrete financial time series. In the last years, continuous time models based on discrete GARCH models have been also proposed to deal with  non-equally spaced observations, as COGARCH model based on Lévy processes. In this paper, we propose to use the data cloning methodology in order to obtain estimators of GARCH and COGARCH model parameters. Data cloning methodology uses a Bayesian approach to obtain approximate maximum likelihood estimators avoiding numerically maximization of the pseudo-likelihood function. After a simulation study for both GARCH and COGARCH models using data cloning, we apply this technique to model the behavior of some NASDAQ time series.
PB Taylor & Francis
SN 0094-9655
YR 2015
FD 2015-06
LK https://hdl.handle.net/20.500.14352/24109
UL https://hdl.handle.net/20.500.14352/24109
LA eng
DS Docta Complutense
RD 15 may 2024