Portfolio performance of linear SDF models: an out-of-sample assessment |
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Authors: | Massimo Guidolin Martín Lozano-Banda |
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Institution: | 1. Department of Finance, CAREFIN, and IGIER, Bocconi University , Milan, Italy.;2. Departamento de Contabilidad y Finanzas, Universidad de Monterrey , México. |
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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. |
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Keywords: | Linear asset pricing models Stochastic discount factor Portfolio selection Out-of-sample performance |
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