Dynamic Trade Informativeness

45 Pages Posted: 1 Oct 2018 Last revised: 21 Nov 2018

Date Written: November 18, 2018

Abstract

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 (November 18, 2018). 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

Register to save articles to
your library

Register

Paper statistics

Downloads
31
Abstract Views
555
PlumX Metrics