As a consequence of recent technological advances and the proliferation of algorithmic and high frequency trading, the cost of trading in financial markets has irrevocably changed. One important change relates to how trading affects prices; known as price impact. Price impact represents the...

Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...

Whether idiosyncratic volatility has increased over time and whether it is a good predictor of future returns is a matter of active debate. We show formally through central limit arguments that there is a direct relationship between the dynamics of the cross-sectional variance of realized...

This paper provides global evidence supporting the hypothesis that expected return models are enhanced by the inclusion of variables that describe the evolution of book-to-market-changes in book value, changes in price, and net share issues. This conclusion is supported using data representing...

This paper examines the time-series predictability of aggregate stock returns in 20 emerging markets. In contrast to the aggregate-level findings in US, earnings yield forecasts the time-series of aggregate stock returns in emerging markets. We consider aggregate earnings not as normalizing...

We identify all return leader-follower pairs among individual stocks using Granger causality regressions. Thus-identified leaders can reliably predict their followers' returns out of sample, and the return predictability works at the level of individual stocks rather than industries. Our results...

We show that news stories contain information about economic linkages between firms and document that information diffuses slowly across linked stocks. Specifically, we identify linked stocks from co-mentions in news stories and find that linked stocks cross-predict one another's returns in the...

In this paper, we extend the literature on crash prediction models in three main ways. First, we explicitly relate crash prediction measures and asset pricing models. Second, we present a simple, effective statistical significance test for crash prediction models. Finally, we propose a...

Data on individual trades in prediction markets relating to the 2008 and 2012 US Presidential elections reveal that traders vary enormously in their behavior. This contrasts with the standard prediction-market models, which assume relatively homogeneous participants who differ only in their...