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Efficient Estimation of a Semiparametric Characteristic- Based Factor Model of Security Returns

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Author Info
Gregory Connor (The London School of Economics)
Matthias Hagmann (Concordia Advisors and Swiss Finance Institute)
Oliver Linton (The London School of Economics)

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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 nonparametric 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 find 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.

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Publisher Info
Paper provided by Swiss Finance Institute in its series Swiss Finance Institute Research Paper Series with number 07-26.

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Length: 63 pages
Date of creation: Sep 2007
Date of revision:
Handle: RePEc:chf:rpseri:rp0726

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Web page: http://www.SwissFinanceInstitute.ch
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Related research
Keywords: Additive Models; Arbitrage pricing theory; Factor model; Fama-French; Kernel estimation; Nonparametric regression; Panel data.;

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Find related papers by JEL classification:
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods

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