• Media type: E-Book
  • Title: Bayesian Solutions for the Factor Zoo : We Just Ran Two Quadrillion Models
  • Contributor: Bryzgalova, Svetlana [Author]; Huang, Jiantao [Other]; Julliard, Christian [Other]
  • Published: [S.l.]: SSRN, [2020]
  • Extent: 1 Online-Ressource (61 p)
  • Language: English
  • DOI: 10.2139/ssrn.3481736
  • Identifier:
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments November 18, 2019 erstellt
  • Description: We propose a novel framework for analyzing linear asset pricing models: simple, robust, and applicable to high dimensional problems. For a (potentially misspecified) standalone model, it provides reliable risk premia estimates of both tradable and non-tradable factors, and detects those weakly identified. For competing factors and (possibly non-nested) models, the method automatically selects the best specification – if a dominant one exists – or provides a model averaging, if there is no clear winner given the data. We analyze 2.25 quadrillion models generated by a large set of existing factors, and gain novel insights on the empirical drivers of asset returns
  • Access State: Open Access