"This paper proposes a new tractable approach to solving multi-period asset allocation problems. We assume that investor preferences are defined over moments of the terminal wealth distribution such as its skew and kurtosis. Time-variations in investment opportunities are driven by a regime...

"This paper finds strong evidence of time-variations in the joint distribution of returns on a stock market portfolio and portfolios tracking size--and value effects. Mean returns, volatilities and correlations between these equity portfolios are found to be driven by underlying regimes that...

"This paper characterizes equilibrium asset prices under adaptive, rational and Bayesian learning schemes in a model where dividends evolve on a binomial lattice. The properties of equilibrium stock and bond prices under learning are shown to differ significantly compared with prices under full...

This paper conducts a broad-based comparison of iterated and direct multi-period forecasting approaches applied to both univariate and multivariate models in the form of parsimonious factor-augmented vector autoregressions. To account for serial correlation in the residuals of the multi-period...

Existing results on the properties and performance of forecast combinations have been derived in the context of mean squared error loss. Under this loss function empirical studies have generally found that estimates of optimal forecast combination weights lead to higher losses than...

Studies of bond return predictability find a puzzling disparity between strong statistical evidence of return predictability and the failure to convert return forecasts into economic gains. We show that resolving this puzzle requires accounting for important features of bond return models such...

We study daily money market mutual fund flows at the individual share class level during September 2008. This fine granularity of data facilitates new insights into investor and portfolio holding characteristics conducive to run risk in cash-like asset pools. Empirically, we find that...

We propose a new approach to forecasting stock returns in the presence of structural breaks that simultaneously affect the parameters of multiple portfolios. Exploiting information in the cross-section increases our ability to identify breaks in return prediction models and enables us to detect...