Thumbnail - Request a copy

Asymptotics of Cholesky GARCH models and time-varying conditional betas

Darolles, Serge; Francq, Christian; Laurent, Sébastien (2018), Asymptotics of Cholesky GARCH models and time-varying conditional betas, Journal of Econometrics, 204, 2, p. 223-247. 10.1016/j.jeconom.2018.02.003

Type
Article accepté pour publication ou publié
Date
2018
Journal name
Journal of Econometrics
Volume
204
Number
2
Publisher
Elsevier
Pages
223-247
Publication identifier
Metadata
Show full item record
Author(s)
Darolles, Serge
Dauphine Recherches en Management [DRM]
Francq, Christian
Centre de Recherche en Économie et Statistique [CREST]
Laurent, Sébastien cc
Aix-Marseille Sciences Economiques [AMSE]
Abstract (EN)
This paper proposes a new model with time-varying slope coefficients. Our model, called CHAR, is a Cholesky-GARCH model, based on the Cholesky decomposition of the conditional variance matrix introduced by Pourahmadi (1999) in the context of longitudinal data. We derive stationarity and invertibility conditions and prove consistency and asymptotic normality of the Full and equation-by-equation QML estimators of this model. We then show that this class of models is useful to estimate conditional betas and compare it to the approach proposed by Engle (2016). Finally, we use real data in a portfolio and risk management exercise. We find that the CHAR model outperforms a model with constant betas as well as the dynamic conditional beta model of Engle (2016).
Subjects / Keywords
Multivariate-GARCH; Conditional betas; Covariance
JEL
C53 - Forecasting and Prediction Methods; Simulation Methods
C32 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
C13 - Estimation: General