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Diffusive Market Impact: A Consistent Microfoundation

Julius Bonart · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.11691 · cited by 0 works (OpenAlex) · open-access PDF

Russian

Диффузионный эффект может объяснить многие эмпирические регулярности рыночного влияния, включая «закон квадратного корня» и его кроссовер до достаточно линейного режима для низких торговых ставок. Один из его центральных предсказаний заключается в том, что информация-нейтральная торговая стратегия генерирует диффузионное состояние влияния. Мы микрофинансируем этот результат в экономике с трейдером и многими арбитражами, которые постепенно устраняют предсказуемые доходы. Каждый арбитраж наблюдает реализованные доходы и частный сигнал одного компонента фундаментального дохода. Поскольку совокупная частная торговая стратегия становится полной и под соответствующим сближением к стационарному пределу, закон влияния трейдера является формой $j

Machine translation (Meta M2M100); the English original follows.

Abstract

Structural price diffusivity explains many empirical regularities of market impact including the ``square-root law'' and its crossover to a linear regime for low trading rates \citep{bonart2026diffusive}. One of its central predictions is that an information-neutral trading strategy generates a diffusive impact state. We microfound this result in an economy with a trader and many arbitrageurs who progressively eliminate predictable returns. Each arbitrageur observes realized returns and a private signal of one component of the fundamental return. As aggregate private information becomes complete and under suitable convergence to a stationary limit, the trader's impact law is of the form $j=U\cdot w$, where $w$ is the innovation in the trading schedule and $U$ is causal all-pass. Impact returns are therefore white, even though no individual arbitrageur can reconstruct the underlying trading strategy. We then investigate the economic meaning of the impact phase. We argue that the $U$ which has minimum distance from the filter $L$ generating the trade flow is an especially interesting candidate: Trade flow is then minimally distorted under impact and arbitrage, and it always guarantees positive impact costs. Under a trader flow generated by a biexponential $L$ (the simplest form allowed in our model) an interesting result emerges: Impact decline is confined to a narrow band of $50\%$--$60\%$, lower than some empirical estimates and quite consistent with others. More complicated flow models can lead to different decays. Finally, we argue that in real markets, the impact phase is probably somewhat ``distorted'' in its long-term tails which allows for a full relaxation of the impact propagator. The effect is weak, long-term mean-reversion of the impact state.

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Topics: Economics, Econometrics, Flow (mathematics), Arbitrage, Filter (signal processing), Aggregate (composite)

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