This paper shows a strong link between granular information contained in individual stock prices and sectoral movements. Using machine learning algorithms, we find that a predictor that aggregates the price movements of a broad cross-section of individual stocks predicts sector ETF returns...

This paper examines the impact of sentiment in an online message forum on stock returns. Using a novel controlled experiment, we collect a large panel of messages with no fundamental information but strong sentiment and stock return data. We find a significant causal effect of social media...

I discover that investors' preferences for gambling mainly involve stocks that have performed poorly in the past three months, as lottery-like stocks with poor performance are much more likely to generate large payoffs than those with good performance (61.53% vs. 40.17%). Furthermore, lotto...

Based on intraday data for a large cross section of individual stocks, we find that the risk component of stock returns exhibits strong intraday momentum, and this pattern holds from previous market close to 10:00, and every half hour since then until market close at 16:00. Strikingly, the...

In this paper, we uncover the first momentum pattern of corporate bonds. In contrast to the popular stock momentum, originated by Jegadeesh and Titman (1993) but unextendable to bonds, our momentum is based on the risk components of the bonds rather than past returns. We find that bonds with...

This paper shows a strong link between granular information contained in individual stock prices and sectoral movements. Based on high-frequency data, we find that a simple LASSO predictor that aggregates high-frequency price movements of a broad universe of individual stocks predicts sector ETF...

We document that the first and third cross-sectional moments of corporate bond returns significantly and positively predict future stock market returns both in- and out-of-sample. The predictability emerges from informed bond trading and gradual diffusion of information. Particularly, the...