Zhiliang Ying (Chair)

Abstract

This paper relates jumps in high frequency stock prices to firm-level, industry and macroeconomic news, in the form of machine-readable releases from Thomson Reuters News Analytics. We begin by examining the relationship from news to price jumps. We find that relevant new information, both idiosyncratic and systematic, gets incorporated quickly into prices, as economic theory suggests. However, in the reverse direction, from price jumps to news, the situation changes. Whereas we found that most relevant news lead to a jump, the vast majority of price jumps do not have identifiable public news that can explain them. We then analyze the various market microstructure features that lead to jumps without news (joint with Chenxu Li)