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GARCH-based identification of triangular systems with an application to the CAPM: still living with the roll critique

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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 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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  • Todd Prono, 2006. "GARCH-based identification of triangular systems with an application to the CAPM: still living with the roll critique," Working Papers 07-1, Federal Reserve Bank of Boston.
    • Handle: RePEc:fip:fedbwp:07-1
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    Cited by:

    1. Michael Nwogugu, 2020. "Regret Theory And Asset Pricing Anomalies In Incomplete Markets With Dynamic Un-Aggregated Preferences," Papers 2005.01709, arXiv.org.
    2. Michael C. Nwogugu, 2020. "Decision-Making, Sub-Additive Recursive "Matching" Noise And Biases In Risk-Weighted Stock/Bond Index Calculation Methods In Incomplete Markets With Partially Observable Multi-Attribute Pref," Papers 2005.01708, arXiv.org.

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    capital asset pricing model; time series analysis;

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