Semiparametric Estimation of a Characteristic-Based Factor Model of Stock Returns
AbstractThis paper develops a new estimation procedure for characteristic-based factor models of stock returns. It describes a factor model in which the factor betas are smooth nonlinear functions of observed security characteristics. It develops an estimation procedure that combines nonparametric kernel methods for constructing mimicking portfolios with parametric nonlinear regression to estimate factor returns and factor betas. Factor models are estimated for UK and US common stocks using book-to-price ratio, market capitalizations, and dividend yield.
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Bibliographic InfoPaper provided by Financial Markets Group in its series FMG Discussion Papers with number dp346.
Date of creation: Mar 2000
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- Matthias Fengler & Wolfgang Härdle & Enno Mammen, 2005. "A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics," SFB 649 Discussion Papers SFB649DP2005-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Gregory Connor & Matthias Hagmann & Oliver Linton, 2007.
"Efficient Estimation of a Semiparametric Characteristic- Based Factor Model of Security Returns,"
Swiss Finance Institute Research Paper Series
07-26, Swiss Finance Institute.
- Gregory Connor & Oliver Linton & Matthias Hagmann, 2007. "Efficient Estimation of a Semiparametric Characteristic-Based Factor Model of Security Returns," FMG Discussion Papers dp599, Financial Markets Group.
- Gregory Connor & Matthias Hagmann & Oliver Linton, 2007. "Efficient Estimation of a SemiparametricCharacteristic-Based Factor Model of Security Returns," STICERD - Econometrics Paper Series /2007/524, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
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