Open AccessThe Relation Between Conditionally Heteroskedastic Factor Models and Factor GARCH Models
Author(s) -
Sentana Enrique
Publication year - 1998
Publication title -
the econometrics journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.861
H-Index - 36
eISSN - 1368-423X
pISSN - 1368-4221
DOI - 10.1111/1368-423x.12014
Subject(s) - heteroscedasticity , autoregressive conditional heteroskedasticity , econometrics , factor (programming language) , economics , mathematics , computer science , volatility (finance) , programming language
The factor GARCH model of Engle (1987) and the latent factor ARCH model of Diebold and Nerlove (1989) have become rather popular multivariate volatility parametrizations due to their parsimony, and the commonality in volatility movements across different financial series. Nevertheless, there is some confusion in the literature between them. The purpose of this paper is to make clear their similarities and differences by providing a formal nesting of the two models, which can be exploited to analyse their statistical features in a more general context. At the same time, their differences may be important in the interpretation of empirical results.