The Physics of Price Discovery: Deconvolving Information, Volatility, and the Critical Breakdown of Signal during Retail Herding

TL;DR

This paper investigates how information transmission through prices breaks down during retail herding, revealing the roles of different investor types and firm sizes in market efficiency using advanced deconvolution and Hawkes process analysis.

Contribution

It introduces a novel combination of regularized deconvolution and Hawkes processes to analyze the impulse response of investor flows and their impact on price discovery during herding episodes.

Findings

Foreign and institutional flows drive permanent price discovery.

Individual flows are mainly panic-driven and self-exciting.

Institutional impact weakens in small-cap stocks during herding.

Abstract

How information transmits through prices -- and why this transmission breaks down -- remains poorly understood. We combine regularized deconvolution with Hawkes process analysis to study the impulse response structure of investor flows in the Korean equity market (January 2020 -- February 2025). Three findings emerge: foreign and institutional flows drive permanent price discovery while individual flows provide contrarian liquidity; individual investor surges are predominantly panic-driven and exhibit near-explosive self-excitation; and during herding episodes, institutional price impact deteriorates sharply in small-cap stocks while large-cap stocks maintain resilience. These results reframe market efficiency as a state variable -- conditional on both herding intensity and firm size -- rather than a structural constant.