Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/55634
Authors: 
Prono, Todd
Year of Publication: 
2007
Series/Report no.: 
Working paper series // Federal Reserve Bank of Boston 07-1
Abstract: 
This paper presents a new method for identifying triangular systems of time-series data. Identification is the product of a bivariate GARCH process. Relative to the literature on GARCH-based identification, this method distinguishes itself both by allowing for a timevarying covariance and by not requiring a complete estimation of the GARCH parameters. Estimation follows OLS and standard univariate GARCH and ARMA techniques, or GMM. A Monte Carlo study of the GMM estimator is provided. The identification method is then applied in testing a conditional version of the CAPM.
Subjects: 
Triangular systems
endogeneity
identification
conditional heteroskedasticity
generalized method of moments
GARCH
GMM
CAPM
JEL: 
C13
C32
G12
Document Type: 
Working Paper

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