This paper proposes output gap dispersion as a measure of economic synchronization patterns across the world economies. Utilizing a novel, multivariate quantile causality testing methodology and data from a set of 45 advanced and emerging nations, we present evidence of significant causal...

We study the predictability of stock returns using an iterative model-building approach known as quantile boosting. Examining alternative return quantiles that represent normal, bull and bear markets via recursive quantile regressions, we trace the predictive value of extensively studied...

In a novel take on the gradual information diffusion hypothesis of Hong et al. (2007), we examine the predictive role of industries over aggregate stock market volatility. Using high frequency data for U.S. industry indexes and various heterogeneous autoregressive (HAR) type and machine learning...