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...

After showing that the distribution of the S&P 500's distortion, i.e. the log difference between its real stock market index and its real fundamental value, is bimodal, we demonstrate that agentbased financial market models may explain this puzzling observation. Within these models, speculators...

Tests of excessive volatility along the lines of Shiller (1981) and Leroy and Porter (1981) count among the most convincing pieces of evidence against the validity of the time-honored efficient market hypothesis. Recently, using Shiller s distinction between ex-ante rational (fundamental) price...

We study whether prices of traded options contain information about future extreme market events. Our option-implied conditional expectation of market loss due to tail events, or tail loss measure, predicts future market returns, magnitude, and probability of the market crashes, beyond and above...

We report strong evidence that changes of momentum, i.e. "acceleration", defined as the first difference of successive returns, provide better performance and higher explanatory power than momentum. The corresponding Γ-factor explains the momentum-sorted portfolios entirely but not the reverse....

Many asset pricing theories treat the cross-section of returns volatility and correlations as two intimately related quantities driven by common factors, which hinders achieving a neat definition of a correlation premium. We formulate a model without factors, but with a continuum of securities...

Models based on factors such as size, value, or momentum are ubiquitous in asset pricing. Therefore, portfolio allocation and risk management require estimates of the volatility of these factors. While realized volatility has become a standard tool for liquid individual assets, this measure is...

We merge the literature on downside return risk and liquidity risk and introduce the concept of extreme downside liquidity (EDL) risks. The cross-section of stock returns reflects a premium if a stock's return (liquidity) is lowest at the same time when the market liquidity (return) is lowest....

We develop a four-factor model intended to capture size, value, and credit rating transition patterns in excess returns for a panel of predominantly mid- and large-cap entities. Using credit transition matrices and rating histories from 48 US issuers, we provide evidence to support a...

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...