Dynamic Trade Informativeness

60 Pages Posted: 1 Oct 2018 Last revised: 5 Jan 2020

Date Written: January 5, 2020

Abstract

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

Yueshen, Bart Zhou and Zhang, Jinyuan, Dynamic Trade Informativeness (January 5, 2020). Available at SSRN: https://ssrn.com/abstract=3119538 or http://dx.doi.org/10.2139/ssrn.3119538

Bart Zhou Yueshen

INSEAD - Finance ( email )

Boulevard de Constance
F-77305 Fontainebleau Cedex
France

Jinyuan Zhang (Contact Author)

INSEAD ( email )

INSEAD, Boulevard de Constance,
Fontainebleau, 77300
France

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