Dynamic Trade Informativeness

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