Cookies?
Library Header Image
LSE Research Online LSE Library Services

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

Connor, Gregory, Hagmann, Matthias and Linton, Oliver (2007) Efficient estimation of a semiparametric characteristic-based factor model of security returns. . Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.

[img]
Preview
PDF
Download (933kB) | Preview

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 characteristicbeta 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 found that momentum and ownvolatility 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: http://sticerd.lse.ac.uk/
Additional Information: © 2007 the authors
Divisions: Economics
STICERD
Subjects: 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: 10 Mar 2008 11:49
Last Modified: 15 Sep 2023 23:10
URI: http://eprints.lse.ac.uk/id/eprint/3775

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics