A diffusion approximation for limit order book models

TL;DR

This paper develops a diffusion approximation for complex limit order book models, showing that under certain conditions, the discrete models converge to an infinite-dimensional stochastic differential equation, providing a new analytical framework.

Contribution

It introduces a diffusion approximation for non-linear, state-dependent limit order book models, establishing convergence to an infinite-dimensional SDE with unique solutions.

Findings

Discrete models are relatively compact and converge to an infinite-dimensional SDE.

Under specific assumptions, the limiting SDE has a unique solution.

The framework applies to models with complex dependence structures.

Abstract

This paper derives a diffusion approximation for a sequence of discrete-time one-sided limit order book models with non-linear state dependent order arrival and cancellation dynamics. The discrete time sequences are specified in terms of an $\R_+$-valued best bid price process and an $L^2_{loc}$-valued volume process. It is shown that under suitable assumptions the sequence of interpolated discrete time models is relatively compact in a localized sense and that any limit point satisfies a certain infinite dimensional SDE. Under additional assumptions on the dependence structure we construct two classes of models, which fit in the general framework, such that the limiting SDE admits a unique solution and thus the discrete dynamics converge to a diffusion limit in a localized sense.