The volatility smile changed drastically around the crash of 1987 and new option pricing models have been proposed in order to accommodate that change. Deterministic volatility models allow for more flexible volatility surfaces but refrain from introducing additional risk-factors. Thus, options...

This paper documents large micro-heterogeneity and forecasting skill in the cross-section of survey based bond risk premia. We reject informationally constrained rational expectations but show a learning model distorted by sentiment is consistent with the data. Aggregating, we propose a belief...

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...

Conventional tests of present-value models over-reject the null of no predictability. In order to better account for the intrinsic probability of detecting predictive relations by chance alone, we develop a new nonparametric Monte Carlo testing method, which does not rely on distributional...

Asymptotic tests over-reject the null of no predictability in present-value models. We develop a nonparametric testing approach in state space models, implying reliable finite sample inference under weak assumptions on price-dividend ratio and dividend shocks. We find sharp evidence of return...

Asymptotic tests over-reject the null of no predictability in present-value models. We develop a nonparametric testing approach in state space models, implying reliable finite sample inference under weak assumptions on price-dividend ratio and dividend shocks. We find sharp evidence of return...