Connor, Gregory and Hagmann, Matthias and Linton, Oliver (2012) Efficient Semiparametric Estimation of the Fama–French Model and Extensions. Econometrica , 80 (2). pp. 713-754. ISSN 0012-9682

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Abstract

This paper develops a new estimation procedure for characteristic-based factor models of stock 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 that adds a momentum factor, and a five-factor extension that adds 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 a general alternative using a new nonparametric test

Item Type:	Article
Keywords:	Additive models; arbitrage pricing theory; characteristic-based factor model; kernel estimation; nonparametric regression;
Academic Unit:	Faculty of Social Sciences > Economics, Finance and Accounting
Item ID:	3579
Depositing User:	Gregory Connor
Date Deposited:	17 Apr 2012 15:33
Journal or Publication Title:	Econometrica
Publisher:	Econometric Society
Refereed:	Yes
URI:
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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