Artículo de revista
Portfolio performance of linear SDF models: an out-of-sample assessment
Fecha
2018Registro en:
Quantitative Finance, Volumen 18, Issue 8, 2018, Pages 1425-1436
14697696
14697688
10.1080/14697688.2018.1429646
Autor
Guidolin, Massimo
Hansen Silva, Erwin
Lozano Banda, Martín
Institución
Resumen
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 onemonth 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.