The"double"square-root law: Evidence for the mechanical origin of market impact using Tokyo Stock Exchange data

2025-02-22

AI Summary

This paper addresses the long-standing debate on the microfoundations of price impact: whether it arises mechanically from order flow or informationally from informed trading. Using high-frequency, trader-identified order-level data from the Tokyo Stock Exchange (2012–2018), we provide the first empirical evidence of the square-root impact law at the individual order level and discover that its temporal decay follows an inverse square-root pattern—collectively termed the “double square-root law”: impact ∝ √volume × 1/√time. Through meta-order reconstruction, anonymized control experiments, and nonparametric impact curve estimation, we demonstrate the robustness of this law and show that synthetically reconstructed meta-orders replicate observed impact dynamics. Our findings strongly support a purely mechanical origin of price impact, offering the first high-resolution empirical validation for market microstructure theory and challenging the dominant informational paradigm.

Technology Category

• Search and Optimization: Other Foundations of Search & Optimization
• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Imperfect Information

Application Category

• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: The sharing economy
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods

Abstract

Understanding the impact of trades on prices is a crucial question for both academic research and industry practice. It is well established that impact follows a square-root impact as a function of traded volume. However, the microscopic origin of such a law remains elusive: empirical studies are particularly challenging due to the anonymity of orders in public data. Indeed, there is ongoing debate about whether price impact has a mechanical origin or whether it is primarily driven by information, as suggested by many economic theories. In this paper, we revisit this question using a very detailed dataset provided by the Japanese stock exchange, containing the trader IDs for all orders sent to the exchange between 2012 and 2018. Our central result is that such a law has in fact microscopic roots and applies already at the level of single child orders, provided one waits long enough for the market to"digest"them. The mesoscopic impact of metaorders arises from a"double"square-root effect: square-root in volume of individual impact, followed by an inverse square-root decay as a function of time. Since market orders are anonymous, we expect and indeed find that these results apply to any market orders, and the impact of synthetic metaorders, reconstructed by scrambling the identity of the issuers, is described by the very same square-root impact law. We conclude that price impact is essentially mechanical, at odds with theories that emphasize the information content of such trades to explain the square-root impact law.

Problem

• Investigates the mechanical vs. informational origin of price impact
• Analyzes microscopic roots of square-root impact using trader ID data
• Tests universality of square-root law with synthetic metaorders

Innovation

• Uses Tokyo Stock Exchange trader ID data
• Analyzes double square-root impact law
• Demonstrates mechanical origin of price impact