We examine the predictability of expected stock returns across horizons using machine learning. We use neural networks, and gradient boosted regression trees on the U.S. and international equity datasets. We find that predictability of returns using neural networks models decreases with longer...

The paper explores the link between financial sentiment and private debt, using Keynes’s A Treatise on Money as a conceptual backdrop. In responding to his critics after the publication of his General Theory Keynes famously talked about unexpected, violent changes in conventional asset...

It is widely acknowledged that many financial markets exhibit a considerably greater degree of kurtosis (and sometimes also skewness) than is consistent with the Geometric Brownian Motion model of Black and Scholes (1973). Among the many alternative models that have been proposed in this...

We use a unique dataset of corporate bonds guaranteed by the full faith and credit of the U.S. to test a number of recent theories about why asset prices may diverge from fundamental values. These models emphasize the role of funding liquidity, slow-moving capital, the leverage of financial...