We propose a non-parametric method based on a model-free formula to evaluate the tails of a risk-neutral distribution using the full cross-section of option prices at a fixed horizon. The method leads to the joint estimation of risk-neutral tail probabilities and tail expectations beyond the...

We propose a novel method to estimate risk-neutral quantiles that uses sorting to minimize an objective function given by a convex combination of call and put option prices over the range of available strike prices. We demonstrate that this new method significantly improves the accuracy of...

We examine the return information conveyed by a firm’s dividend surprise, defined as the difference between a firm’s actual dividend per share (DPS) and investors’ expected DPS. We find that negative-surprise stocks (i.e., stocks in the lowest dividend surprise quintile) provide 5.64% more...

This paper provides a framework for obtaining the estimator of expected asset returns for portfolio selection. The framework relies on a linear model where the expected returns are the coefficients to be estimated. The model is fitted to a synthetic dataset by Bayesian regression. The estimator...