Suchergebnisse

"This review article describes recent literature on asset allocation, covering both static and dynamic models. The article focuses on the bond--stock decision and on the implications of return predictability. In the static setting, investors are assumed to be Bayesian, and the role of various prior beliefs and specifications of the likelihood are explored. In the dynamic setting, recursive utility is assumed, and attention is paid to obtaining analytical results when possible. Results under both full and limited-information assumptions are discussed"--National Bureau of Economic Research web site

"We develop a life-cycle consumption and portfolio choice model in which households have nonhomothetic utility over two types of goods, basic and luxury. We calibrate the model to match the cross-sectional and life-cycle variation in the basic expenditure share in the Consumer Expenditure Survey. The model explains the degree to which the portfolio share in risky assets rises in wealth in the cross-section of households in the Survey of Consumer Finances. For a given household, the portfolio share can fall in response to an increase in wealth, even though the model implies decreasing relative risk aversion"--National Bureau of Economic Research web site

Are excess returns predictable and if so, what does this mean for investors? Previous literature has tended toward two polar viewpoints: that predictability is useful only if the statistical evidence for it is incontrovertible, or that predictability should affect portfolio choice, even if the evidence is weak according to conventional measures. This paper models an intermediate view: that both data and theory are useful for decision-making. We investigate optimal portfolio choice for an investor who is skeptical about the amount of predictability in the data. Skepticism is modeled as an informative prior over the R^2 of the predictive regression. We find that the evidence is sufficient to convince even an investor with a highly skeptical prior to vary his portfolio on the basis of the dividend-price ratio and the yield spread. The resulting weights are less volatile and deliver superior out-of-sample performance as compared to the weights implied by an entirely model-based or data-based view.