Do price trajectory data increase the efficiency of market impact estimation?

TL;DR

This paper investigates whether incorporating price trajectory data, especially early trade prices, improves the asymptotic efficiency of market impact estimation methods for large institutional investors.

Contribution

It demonstrates that using partial price trajectory data can asymptotically outperform traditional methods like VWAP-based estimation in market impact models.

Findings

Partial price trajectory data improves estimation efficiency.

Early trade prices are particularly valuable.

Theoretical and empirical benefits are discussed.

Abstract

Market impact is an important problem faced by large institutional investor and active market participant. In this paper, we rigorously investigate whether price trajectory data from the metaorder increases the efficiency of estimation, from an asymptotic view of statistical estimation. We show that, for popular market impact models, estimation methods based on partial price trajectory data, especially those containing early trade prices, can outperform established estimation methods (e.g., VWAP-based) asymptotically. We discuss theoretical and empirical implications of such phenomenon, and how they could be readily incorporated into practice.