Dynamic Trade Informativeness

46 Pages Posted: 1 Oct 2018 Last revised: 12 Aug 2019

Date Written: August 9, 2019


This paper develops a structural model to examine 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; gauge informed investors’ patience; and capture the general intraday trend, as well as systematic patterns around specific events. 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 (August 9, 2019). 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

Jinyuan Zhang (Contact Author)

INSEAD ( email )

INSEAD, Boulevard de Constance,
Fontainebleau, 77300

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