Ledoit, OlivierSanta Clara, PedroWolf, MichaelUniversitat Pompeu Fabra. Departament d'Economia i Empresa2017-07-262017-07-262001-10-01Review of Economics and Statistics 85, 735-747, 2003http://hdl.handle.net/10230/892The goal of this paper is to estimate time-varying covariance matrices. Since the covariance matrix of financial returns is known to change through time and is an essential ingredient in risk measurement, portfolio selection, and tests of asset pricing models, this is a very important problem in practice. Our model of choice is the Diagonal-Vech version of the Multivariate GARCH(1,1) model. The problem is that the estimation of the general Diagonal-Vech model model is numerically infeasible in dimensions higher than 5. The common approach is to estimate more restrictive models which are tractable but may not conform to the data. Our contribution is to propose an alternative estimation method that is numerically feasible, produces positive semi-definite conditional covariance matrices, and does not impose unrealistic a priori restrictions. We provide an empirical application in the context of international stock markets, comparing the new estimator to a number of existing ones.application/pdfengL'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commonsinfo:eu-repo/semantics/workingPaperdiagonal-vech model multivariate garchunrestricted estimationFinance and Accountinginfo:eu-repo/semantics/openAccess