  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.
