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 relationship between risk and return is one of the most studied topics in finance. The majority of the literature is based on a linear, parametric relationship between expected returns and conditional volatility. This paper models the contemporaneous relationship between market excess...

We embed a news shock, a noisy indicator of the future state, in a two-state Markovswitching growth model. Our framework, combined with parameter learning, features rich history-dependent uncertainty dynamics. We show that bad news that arrives during a prolonged economic boom can trigger a...

Using a latent variables approach, we estimate the dynamics of dividends and returns in a tractable present-value model with time-varying risks. Expected returns imply a similar return predictability as under homoskedasticity, while expected dividend growth is more persistent and explains a...

I provide evidence that risks in macroeconomic fundamentals contain valuable information about bond risk premia. I extract factors from a set of quantile-based risk measures estimated for US macroeconomic variables and document that they account for up to 31% of the variation in excess bond...

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...

Long-run risk models, a cornerstone in the macro-finance literature for their ability to capture key asset price phenomena, are known to entail implausibly high levels of timing and risk premia. Our paper resolves this puzzle by considering consumption of durable goods in addition to that of...

This paper shows how uncertainty about the type of return distribution (distribution uncertainty) can be incorporated in asset allocation decisions by using a novel, Bayesian semiparametric approach. To evaluate the economic importance of distribution uncertainty, the extent of changes in...