Portfolio Performance of Linear SDF Models: An Out-of-Sample Assessment

37 Pages Posted: 3 Aug 2018

See all articles by Massimo Guidolin

Massimo Guidolin

Bocconi University - Department of Finance

Erwin Hansen

University of Chile - Department of Business Administration

Martin Lozano

Independent

Date Written: February 5, 2018

Abstract

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.

Keywords: Linear asset pricing models, Stochastic discount factor, Portfolio selection, Out-of-sample performance

JEL Classification: G11, G12

Suggested Citation

Guidolin, Massimo and Hansen, Erwin and Lozano, Martin, Portfolio Performance of Linear SDF Models: An Out-of-Sample Assessment (February 5, 2018). BAFFI CAREFIN Centre Research Paper No. 2018-85. Available at SSRN: https://ssrn.com/abstract=3225610 or http://dx.doi.org/10.2139/ssrn.3225610

Massimo Guidolin (Contact Author)

Bocconi University - Department of Finance ( email )

Via Roentgen 1
Milano, MI 20136
Italy

Erwin Hansen

University of Chile - Department of Business Administration ( email )

Diagonal Paraguay 257
Santiago, 8330015
Chile

Martin Lozano

Independent ( email )

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