Power-law tails in the distribution of order imbalance

TL;DR

This paper analyzes the distribution of order imbalance in Chinese stock market data, revealing power-law tails and significant variability across stocks, with implications for understanding market microstructure.

Contribution

It provides the first comprehensive analysis of order imbalance distributions across multiple stocks and timescales, highlighting power-law behavior and asymmetry.

Findings

Order imbalance distributions have power-law tails.

Tail index varies significantly across stocks.

Distributions are asymmetric and show no clear trend with timescale.

Abstract

We investigate the probability distribution of order imbalance calculated from the order flow data of 43 Chinese stocks traded on the Shenzhen Stock Exchange. Two definitions of order imbalance are considered based on the order number and the order size. We find that the order imbalance distributions of individual stocks have power-law tails. However, the tail index fluctuates remarkably from stock to stock. We also investigate the distributions of aggregated order imbalance of all stocks at different timescales $\Delta{t}$. We find no clear trend in the tail index with respect $\Delta{t}$. All the analyses suggest that the distributions of order imbalance are asymmetric.