Asset Allocation in the Chinese Stock Market:The Role of Return Predictability

Does Stock Return Predictability Imply Improved Asset Allocation and Performance?

Stock-Return Predictability and Asset Pricing Models

The regression of stock returns on predictive variables, such as dividend yield, has proven useful in optimal portfolio selection when investment opportunities are timevarying. Conditional versions of factor models impose a restriction on that regression, thereby implying a particular portfolio choice. The study examines several pricing models from a perspective of conditional mean-variance opt...

Dynamic asset allocation with ambiguous return predictability

We study an investor’s optimal consumption and portfolio choice problem when he confronts with two possibly misspecified submodels of stock returns: one with IID returns and the other with predictability. We adopt a generalized recursive ambiguity model to accommodate the investor’s aversion to model uncertainty. The investor deals with specification doubts by slanting his beliefs about submode...

Stock Return Predictability, Conditional Asset Pricing Models and Portfolio Selection

I examine an investor’s portfolio allocation problem across multiple risky assets in the presence of return predictability when, in addition to the predictability evidence, the investor uses conditional asset pricing models to guide him in the portfolio selection decision. I also explore how the uncertainty associated with the model dynamics affects the investor’s optimal portfolio. To analyze ...

The Limits to Stock Return Predictability∗

We examine predictive return regressions from a new angle. We ask what observable univariate properties of returns tell us about the “predictive space” that defines the true predictive model: the triplet ¡ λ,R2 x, ρ ¢ , where λ is the predictor’s persistence, R2 x is the predictive R-squared, and ρ is the "Stambaugh Correlation" (between innovations in the predictive system). When returns are n...