Connor, Gregory, Hagmann, Matthias and Linton, Oliver (2007) Efficient estimation of a semiparametric characteristic-based factor model of security returns. Financial Markets Group Discussion Papers (599). Financial Markets Group, The London School of Economics and Political Science, London, UK.
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Abstract
This paper develops a new estimation procedure for characteristic-based factor models of security returns. We treat the factor model as a weighted additive nonparametric regression model, with the factor returns serving as time-varying weights, and a set of univariate non-parametric functions relating security characteristic to the associated factor betas. We use a time-series and cross-sectional pooled weighted additive nonparametric regression methodology to simultaneously estimate the factor returns and characteristic-beta functions. By avoiding the curse of dimensionality our methodology allows for a larger number of factors than existing semiparametric methods. We apply the technique to the three-factor Fama-French model, Carhart’s four-factor extension of it adding a momentum factor, and a five-factor extension adding an own-volatility factor. We .nd that momentum and own-volatility factors are at least as important if not more important than size and value in explaining equity return comovements. We test the multifactor beta pricing theory against the Capital Asset Pricing model using a standard test, and against a general alternative using a new nonparametric test.
| Item Type: | Monograph (Discussion Paper) |
|---|---|
| Official URL: | https://www.fmg.ac.uk/ |
| Additional Information: | © 2007 The Authors |
| Divisions: | Financial Markets Group |
| Subjects: | H Social Sciences > HG Finance H Social Sciences > HB Economic Theory |
| JEL classification: | G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing; Trading volume; Bond Interest Rates C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods |
| Date Deposited: | 16 Jul 2009 13:57 |
| Last Modified: | 11 Dec 2024 18:49 |
| URI: | http://eprints.lse.ac.uk/id/eprint/24504 |
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