PT - JOURNAL ARTICLE AU - Lars Kaiser AU - Marco J. Menichetti AU - Aron Veress TI - Enhanced Mean–Variance Portfolios:<br/> <em>A Controlled Integration of Quantitative Predictors</em> AID - 10.3905/jpm.2014.40.4.028 DP - 2014 Jul 31 TA - The Journal of Portfolio Management PG - 28--41 VI - 40 IP - 4 4099 - https://pm-research.com/content/40/4/28.short 4100 - https://pm-research.com/content/40/4/28.full AB - The intuitiveness and practicality of mean–variance portfolios largely depend on the accuracy of moment estimates, which are subject to large estimation errors and are conditional on time. The authors propose a model that accounts for factor dynamics in a Bayesian setting, in which they endogenously derive the effect of estimation accuracy on the posterior distribution from a linear predictive regression model. By doing so, they capture upside return potential for periods of high factor-explained variance, while constraining downside risk for periods of low predictive quality. Results are robust in a simulation and an empirical setting.TOPICS: Portfolio construction, statistical methods, performance measurement