MURAL - Maynooth University Research Archive Library

    Efficient Semiparametric Estimation of the Fama–French Model and Extensions

    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

    [img] Download (880kB)

    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...

    Add this article to your Mendeley library


    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
      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

      Repository Staff Only(login required)

      View Item Item control page


      Downloads per month over past year

      Origin of downloads