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Efficient estimation of a semiparametric characteristic-based factor model of security returns

  • Gregory Connor
  • Matthias Hagmann
  • Oliver Linton

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.

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File URL: http://eprints.lse.ac.uk/24504/
File Function: Open access version.
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Paper provided by London School of Economics and Political Science, LSE Library in its series LSE Research Online Documents on Economics with number 24504.

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Length: 61 pages
Date of creation: 17 Sep 2007
Date of revision:
Handle: RePEc:ehl:lserod:24504
Contact details of provider: Postal: LSE Library Portugal Street London, WC2A 2HD, U.K.
Phone: +44 (020) 7405 7686
Web page: http://www.lse.ac.uk/

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  1. M. Hashem Pesaran, 2004. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," CESifo Working Paper Series 1331, CESifo Group Munich.
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