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Learning about beta: time-varying factor loadings, expected returns, and the conditional CAPM Author info | Abstract | Publisher info | Download info | Related research | Statistics Tobias Adrian
Francesco Franzoni
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We complement the conditional capital asset pricing model (CAPM) by introducing unobservable long-run changes in risk factor loadings. In this environment, investors rationally “learn” the long-run level of factor loading by observing realized returns. As a direct consequence of this assumption, conditional betas are modeled using the Kalman filter. Because of its focus on low-frequency variation in betas, our approach circumvents recent criticisms of the conditional CAPM. When tested on portfolios sorted by size and book-to-market ratio, our learning-augmented conditional CAPM fails to be rejected. ; Original title: Learning about beta: a new look at CAPM tests.
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Paper provided by Federal Reserve Bank of New York in its series Staff Reports with number
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Date of creation: 2008Date of revision:
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Keywords: Capital assets pricing model ; Investments ; Other versions of this item:
Article Adrian, Tobias & Franzoni, Francesco, 2009.
"Learning about beta: Time-varying factor loadings, expected returns, and the conditional CAPM ,"
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