This paper introduces a non-parametric framework to statistically examine how news events, such as company or macroeconomic announcements, contribute to the pre- and post-event jump dynamics of stock prices under the intraday seasonality of the news and jumps. We demonstrate our framework, which...

Investors in stock markets face a huge amount of financial information. For that reason, they must decide how to distribute their trading effort across different securities. We propose a new measure of investor trade allocation between securities, called the trading signature . This measure,...

Recent studies using data on social media and stock markets have mainly focused on predicting stock returns. Instead of predicting stock price movements, we examine the relation between Facebook data and investors' decision making in stock markets with a unique data on investors' transactions on...

We introduce a novel method to identify information networks in stock markets, which explicitly accounts for the impact of public information on investor trading decisions. We show that public information has a clear effect on the empirical investor networks' topology. Most importantly, our...

The starting point of this paper is that neighboring investors may talk to each other sharing information about their transactions in stock markets, leading to similar trading behavior. We find that pairwise trade timing similarities between investor pairs are negatively associated to...

Investors in stock markets distribute their limited attention across different securities. Drawing on recent findings on social behavior, we ask whether there are persistent, characteristic patterns in how household investors distribute their attention. Our study builds on a large data set that...