We study the evolution of the behavioral component of the financial market by estimating a Bayesian mixture model in which two types of investors coexist: one rational, with standard subjective expected utility theory (SEUT) preferences, and one behavioral, endowed with an S-shaped utility...

The VPIN, or Volume-synchronized Probability of INformed trading, metric is introduced by Easley, Lopez de Prado and O'Hara (ELO) as a real-time indicator of order flow toxicity. They find the measure useful in predicting return volatility and conclude it may help signal impending market...

Easley, Lopez de Prado and O'Hara introduce VPIN as a real-time indicator of order flow toxicity. They find it useful for monitoring order fl ow imbalances and signaling impending market turmoil, exemplified by the ash crash. They also deem VPIN a good forecaster of short-term volatility. In...

We estimate long-run consumption-based asset pricing models using a comprehensive set of international test assets, including broad equity market portfolios, international value/growth portfolios, and international bond portfolios. We find that differences in returns across assets within a...

What drives volatility on financial markets? This paper takes a comprehensive look at the predictability of financial market volatility by macroeconomic and financial variables. We go beyond forecasting stock market volatility (by large the focus in previous studies) and additionally investigate...

This paper adopts dynamic factor models with macro-fi?nance predictors to revisit the intertemporal risk-return relation in ?five large European stock markets. We identify country specifi?c, Euro area, and global factors to determine the conditional moments of returns considering the role of...

We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and study the realized moments? time-series and cross-sectional properties. We investigate if this week?'s realized moments are informative for the cross-section of next week'?s stock returns. We...

Yes. We use intraday data to compute weekly realized variance, skewness and kurtosis for individual equities and assess whether this week?s realized moments predict next week?s stock returns in the cross-section. We sort stocks each week according to their past realized moments, form decile...

This paper provides detailed insights into predictability of the entire stock and bond return distribution through the use of quantile regression. This allows us to examine speci?c parts of the return distribution such as the tails or the center, and for a suf?ciently ?ne grid of quantiles we...

In a framework of heterogeneous beliefs, I investigate a two-date consumption model with continuous trading over the interval [0; T], in which information on the aggregate consumption at time T is revealed by an Ornstein-Uhlenbeck Bridge. This information structure allows investors to speculate...