Dynamic Trade Informativeness
60 Pages Posted: 1 Oct 2018 Last revised: 5 Jan 2020
Date Written: January 5, 2020
This paper develops a structural model to examine high-frequency price dynamics. The key innovation is to allow trades’ permanent price impact to be time-varying—dynamic trade informativeness. A distribution-free ﬁltering technique pins the real-world data to the model. The ﬁltered series signiﬁcantly recover the eﬃcient price innovation through the dynamics of trade informativeness, improve trades’ explanatory power for future returns, distinguish informativeness from trades’ aggressiveness, gauge informed investors’ patience, and capture systematic patterns around scheduled and unscheduled events, as well as general intraday trends. The framework contributes to the better utilization of high-frequency trading data.
Keywords: trade informativeness, price impact, ﬁltering, high-frequency data
JEL Classification: C13, G10
Suggested Citation: Suggested Citation