Universal scaling and nonlinearity of aggregate price impact in financial markets

TL;DR

This paper uncovers a universal non-linear pattern in how aggregated trades impact stock prices across intra-day timescales, revealing that price movements depend on complex correlations and order flow balance rather than simple linear effects.

Contribution

It demonstrates the universal non-linear shape of price impact across instruments and links it to Hurst exponents, challenging the assumption of linear impact and highlighting the role of order flow balance.

Findings

Price impact has a universal non-linear shape across instruments.

Extreme order flow imbalance correlates with price pinning, not large returns.

The probability of a trade changing the mid-price decreases with order-sign bias.

Abstract

How and why stock prices move is a centuries-old question still not answered conclusively. More recently, attention shifted to higher frequencies, where trades are processed piecewise across different timescales. Here we reveal that price impact has a universal non-linear shape for trades aggregated on any intra-day scale. Its shape varies little across instruments, but drastically different master curves are obtained for order-volume and -sign impact. The scaling is largely determined by the relevant Hurst exponents. We further show that extreme order flow imbalance is not associated with large returns. To the contrary, it is observed when the price is "pinned" to a particular level. Prices move only when there is sufficient balance in the local order flow. In fact, the probability that a trade changes the mid-price falls to zero with increasing (absolute) order-sign bias along an arc-shaped curve for all intra-day scales. Our findings challenge the widespread assumption of linear aggregate impact. They imply that market dynamics on all intra-day timescales are shaped by correlations and bilateral adaptation in the flows of liquidity provision and taking.