This paper shows that the framework proposed by Barberis and Huang (2009) to incorporate narrow framing and loss aversion into dynamic models of portfolio choice and asset pricing can be extended to also account for probability weighting and for a value function that is convex on losses and...

We study optimal securitization of defaultable assets in a continuous time setting. A financial intermediary can create a portfolio of defaultable assets and then sell it to outside investors. The default risk of the assets in the portfolio is determined by the unobservable costly effort exerted...

Modern open economy macro models assume the continuous adjustment of international portfolio allocation. We introduce gradual portfolio adjustment into a global equity market model. Our approach differs from related literature in two key dimensions. First, the time interval between portfolio...

The aim of this study is to examine whether securitized real estate returns reflect direct real estate returns or general stock market returns using international data for the U.S., U.K., and Australia. In contrast to previous research, which has generally relied on overall real estate market...

Across numerous asset classes, momentum strategies have historically generated high Sharpe ratios and strong positive alphas relative to standard asset pricing models. However, the returns to momentum strategies are negatively skewed: they experience infrequent but strong and persistent strings...

Reference-dependent preference models assume that agents derive utility from deviations of consumption from benchmark levels, rather than from consumption levels. These references can be either backward-looking (as explicit in the Habit literature) or forward-looking (as implicitly suggested by...

This paper develops an optimal trading strategy explicitly linked to an agent's preferences and assessment of the distribution of asset returns. The price of this strategy is a portfolio of implied moments, and its expected excess returns naturally accommodate compensation for higher-order...

We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model is calibrated at a quarterly frequency for ten European countries. We also use maximum-likelihood estimates and Bayesian estimates to account for parameter uncertainty. We find...

We explore the performance of mixed-frequency predictive regressions for stock returns from the perspective of a Bayesian investor. We develop a constrained parameter learning approach for sequential estimation allowing for belief revisions. Empirically, we find that mixed-frequency models...