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...

The intuitiveness and practicability of mean-variance portfolios largely depends on the accuracy of moment estimates, which are subject to large estimation errors and conditional on time. We propose a model accounting for factor dynamics in a Bayesian setting, in which the impact of estimation...

A model of portfolio return dynamics is considered in which the price of risk is permitted to be heterogeneous. In doing this, a novel method is proposed that delivers improved out-of-sample forecasts of portfolio returns. The main innovation is the use of a set of predictors that account for...

We quantify disagreement about the economy with ex-ante measures of divergence of opinion among economic forecasters and investigate if economic disagreement has a significant impact on the cross-sectional pricing of individual stocks. We find a significant disagreement premium of 7.2% per...

A single macroeconomic factor based on growth in the capital share of aggregate income exhibits significant explanatory power for expected returns across a range of equity characteristic portfolios and non-equity asset classes, with risk price estimates that are of the same sign and similar in...

Due to arbitrage risk asymmetries, the relationship between idiosyncratic risk and expected returns is positive (negative) among overpriced (underpriced) stocks. We offer a new active anomaly-selection strategy that capitalizes on this effect. To this end, we consider eleven equity anomalies in...

This paper examines the lead/lag relations between size-sorted portfolio returns through the lens of financial cycles governing these returns using a novel econometric methodology. Specifically, we develop a Markov-switching vector autoregressive model that allows for imperfect synchronization...

This paper presents a forward looking model for selection of hedge fund investment strategies. Given excess skewness observed in hedge funds' return distributions, we assume that the historical returns have a skew student t distribution. We implement a Bayesian framework to derive the parameters...

Present market instabilities have prompted great interest on the characteristics of specific portfolios such as minimum variance and equally- weighted risk contribution portfolios as these portfolios do not rely on the estimate of expected returns. Indeed, in turmoil periods traditional market...

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...