GARCH-based identification of triangular systems with an application to the CAPM: still living with the roll critique
AbstractThis 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 time-varying 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. ; Quantitative Analysis Unit Working Paper QAU07-2
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Bibliographic InfoPaper provided by Federal Reserve Bank of Boston in its series Working Papers with number 07-1.
Date of creation: 2006
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-03-03 (All new papers)
- NEP-ECM-2007-03-03 (Econometrics)
- NEP-ETS-2007-03-03 (Econometric Time Series)
- NEP-FMK-2007-03-03 (Financial Markets)
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