Portfolio performance of linear SDF models: an out-of-sample assessment

Martín Carlos Lozano Banda, Edwin Hansen, Massimo Guidolin

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


We evaluate linear stochastic discount factor models using an ex-post portfolio metric: the realized out-of-sample Sharpe ratio of mean–variance portfolios backed by alternative linear factor models. Using a sample of monthly US portfolio returns spanning the period 1968–2016, we find evidence that multifactor linear models have better empirical properties than the CAPM, not only when the cross-section of expected returns is evaluated in-sample, but also when they are used to inform one-month ahead portfolio selection. When we compare portfolios associated to multifactor models with mean–variance decisions implied by the single-factor CAPM, we document statistically significant differences in Sharpe ratios of up to 10 percent. Linear multifactor models that provide the best in-sample fit also yield the highest realized Sharpe ratios.
Original languageEnglish
Pages (from-to)1425-1436
Number of pages12
JournalQuantitative Finance
Issue number8
Publication statusPublished - 3 Aug 2018

Bibliographical note

Funding Information:
Hansen acknowledges financial support from FONDECYT [grant number #11150693].

Publisher Copyright:
© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

Copyright 2018 Elsevier B.V., All rights reserved.

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics, Econometrics and Finance(all)


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