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 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...

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...

Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models,...

We introduce a multivariate GARCH model that utilizes and models realized measures of volatility and covolatility. The realized measures extract information contained in high-frequency data that is particularly beneficial during periods with variation in volatility and covolatility. Applying the...

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...

This paper re-examines the joint distribution of equity and bond returns using high frequency data. In particular, we analyze the weekly realized stock bond correlation calculated from 5-minute returns of the futures prices of the S&P 500 and the 10-year Treasury Note. A potentially gradual...

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...