Stochastic Price Dynamics in Response to Order Flow Imbalance: Evidence from CSI 300 Index Futures

TL;DR

This paper models the impact of order flow imbalance on price dynamics in Chinese CSI 300 Index Futures using a novel Ornstein-Uhlenbeck process driven by a Lévy process, revealing horizon-dependent effects and regime-dependent dynamics.

Contribution

It introduces a new stochastic model for order flow impact using an Ornstein-Uhlenbeck process with memory, differing from traditional Hawkes process approaches.

Findings

Order flow imbalance acts as a market shock.

Horizon-dependent effects influence metric interactions.

Regime-dependent dynamics affect forecasting power.

Abstract

We conduct modeling of the price dynamics following order flow imbalance in market microstructure and apply the model to the analysis of Chinese CSI 300 Index Futures. There are three findings. The first is that the order flow imbalance is analogous to a shock to the market. Unlike the common practice of using Hawkes processes, we model the impact of order flow imbalance as an Ornstein-Uhlenbeck process with memory and mean-reverting characteristics driven by a jump-type L\'evy process. Motivated by the empirically stable correlation between order flow imbalance and contemporaneous price changes, we propose a modified asset price model where the drift term of canonical geometric Brownian motion is replaced by an Ornstein-Uhlenbeck process. We establish stochastic differential equations and derive the logarithmic return process along with its mean and variance processes under initial boundary conditions, and evolution of cost-effectiveness ratio with order flow imbalance as the trading trigger point, termed as the quasi-Sharpe ratio or response ratio. Secondly, our results demonstrate horizon-dependent heterogeneity in how conventional metrics interact with order flow imbalance. This underscores the critical role of forecast horizon selection for strategies. Thirdly, we identify regime-dependent dynamics in the memory and forecasting power of order flow imbalance. This taxonomy provides both a screening protocol for existing indicators and an ex-ante evaluation paradigm for novel metrics.