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

Paper: arXiv 2212.12687

Authors: F. Campigli, G. Bormetti, F. Lillo

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.

Complexity vs Empirical Score

• Math Complexity: 7.5/10
• Empirical Rigor: 8.0/10
• Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper provides a strong theoretical extension to Hasbrouck’s foundational model by introducing a time-varying, non-linear observation-driven framework. Its empirical application to intraday dynamics and FOMC announcements demonstrates high practical rigor and market microstructure relevance.

Research Flowchart

  flowchart TD
    A[Research Goal: Estimate dynamic market impact & trade information content] --> B[Model Development: Non-linear observation-driven Hasbrouck model]
    B --> C[Inputs: High-frequency trade, price data & FOMC event timestamps]
    C --> D[Computational Estimation: Dynamic parameter estimation for local liquidity & trade history]
    D --> E[Finding 1: Intraday market impact shows large exogenous spikes e.g., FOMC]
    D --> F[Finding 2: Trade information content depends on local liquidity & recent history]
    D --> G[Outcome: Time-varying permanent impact parameter for dynamic TCA]