Measuring price impact and information content of trades in a time-varying setting

TL;DR

This paper introduces a non-linear, dynamic model to measure how trades impact prices and contain information, revealing intraday patterns and the influence of liquidity and recent trades on impact.

Contribution

It develops a novel non-linear, observation-driven model for dynamic estimation of trade impact and information content, extending Hasbrouck's framework.

Findings

Market impact shows intraday patterns with large fluctuations.

Trade information content depends on liquidity and recent price/trade history.

The model enables dynamic estimation of permanent impact for transaction cost analysis.

Abstract

We propose a non-linear observation-driven version of the Hasbrouck (1991) model for dynamically estimating trades' market impact and information content. We find that market impact displays an intraday pattern superimposed with large fluctuations. Some of them are exogenous, and, as an example, we investigate market impact dynamics around FOMC announcements. Contrary to Hasbrouck (1991), we find that the information content of trades depends on the local liquidity level and the recent history of prices and trades. Finally, we use the model to estimate the time-varying permanent impact parameter, which allows performing a dynamic transaction cost analysis.