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A semiparametric conditional capital asset pricing model |
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| Affiliation: | 1. Dipartimento di Scienze Economiche e Aziendali, University of Pavia, Italy;2. School of Economics, University of Notthingham, Nottingham, UK;1. Graduate School of Economics and Business Administration, Hokkaido University, Kita 9, Nishi 7, Kita-ku, Sapporo 060–0809, Japan;2. Graduate School of Economics, Hitotsubashi University. Naka 2-1, Kunitachi, Tokyo 186-8601, Japan;3. Department of Industrial Administration, Tokyo University of Science, 2641 Yamazaki, Noda-shi, Chiba 278–8510, Japan |
| Abstract: | This paper proposes using a functional coefficient regression technique to estimate time-varying betas and alpha in the conditional capital asset pricing model (CAPM). Functional coefficient representation relaxes the strict assumptions regarding the structure of betas and alpha by combining the predictors into an index. Appropriate index variables are selected by applying the smoothly clipped absolute deviation penalty. In such a way, estimation and variable selection can be done simultaneously. Based on the empirical studies, the proposed model performs better than the alternatives in explaining asset returns and we find no strong evidence to reject the conditional CAPM. |
| Keywords: | Conditional capital asset pricing model Functional coefficient regression Smoothly clipped absolute deviation penalty Variable selection C13 C52 G12 |
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