Portfolio Performance of Linear SDF Models: An Out-of-Sample Assessment
Erwin Hansen and
No 627, Working Papers from IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University
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 ?nd 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 signi?cant di¤erences in Sharpe ratios of up to 10 percent. Linear multifactor models that provide the best in-sample ?t also yield the highest realized Sharpe ratios. JEL classi?cation: G11, G12. Keywords: Linear asset pricing models, Stochastic discount factor, Portfolio selection, Out-of-sample performance.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
Journal Article: Portfolio performance of linear SDF models: an out-of-sample assessment (2018)
Working Paper: Portfolio Performance of Linear SDF Models: An Out-of-Sample Assessment (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:igi:igierp:627
Ordering information: This working paper can be ordered from
Access Statistics for this paper
More papers in Working Papers from IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University via Rontgen, 1 - 20136 Milano (Italy).
Bibliographic data for series maintained by ().