Average skewness, which is defined as the average of monthly skewness values across firms, performs well at predicting future market returns. This result still holds after controlling for the size or liquidity of the firms or for current business cycle conditions. We also find that average...

We build a macroeconomic model for Switzerland, the Euro Area, and the USA that drives the dynamics of several asset classes and the liabilities of a representative Swiss (defined-contribution) pension fund. This encompassing approach allows us to generate correlations between returns on assets...

In this paper, we document evidence that downside betas tend to comove more than upside betas during a financial crisis, but upside betas tend to comove more than the downside betas during financial booms. We find that the asymmetry between Downside-Beta Comovement and Upside-Beta Comovement is...

We find that investors are fixated on analysts' consensus outputs (earnings forecasts, recommendations, and forecast dispersion), which can be inferior signals compared to the corresponding outputs provided by high-quality analysts, especially when a large number of high-quality analysts follow...

Recent literature suggests that trading by institutional investors may affect the first and second moments of returns. Elaborating on this intuition, we conjecture that arbitrageurs can propagate liquidity shocks between related markets. The paper provides evidence in this direction by studying...

We develop statistical methods to detect informed trading in options markets. We apply these methods to 31 companies from various sectors over 14 years analyzing approximately 9.6 million option prices. We find that option informed trading tends to cluster prior to certain events, takes place...

This appendix extends the empirical results in Chesney, Crameri, and Mancini (2011). Informed trading activities on put and call options are analyzed for 19 companies in the banking and insurance sectors from January 1996 to September 2009. Our empirical findings suggest that certain events such...

We propose a nonparametric Bayesian approach for the estimation of the pricing kernel. Historical stock returns and option market data are combined through the Dirichlet Process (DP) to construct an option-adjusted physical measure. The precision parameter of the DP process is calibrated to the...

In this paper, we examine the performance of three DeMark indicators (Sequential, Combo and Setup trend), which constitute specific implementations of technical analysis often used by practitioners, over twenty-one commodity futures markets and ten years of daily data. Our work addresses price...

Prediction (or information) markets are markets where participants trade contracts whose payoff depends on unknown future events. Studying prediction markets allows to avoid many problems, which arise in some artificially designed behavioral experiments investigating collective decision making...