Replicating financial market dynamics with a simple self-organized critical lattice model

TL;DR

This paper presents a simple lattice model that self-organizes into a critical state, reproducing key statistical features of high-frequency financial market data without parameter tuning.

Contribution

It introduces a minimalistic lattice model exhibiting self-organized criticality that accurately mimics real market statistical properties.

Findings

Model produces time series similar to real market data

GARCH(1,1) fits on the model match NASDAQ data

Model demonstrates scale invariance and criticality

Abstract

We explore a simple lattice field model intended to describe statistical properties of high frequency financial markets. The model is relevant in the cross-disciplinary area of econophysics. Its signature feature is the emergence of a self-organized critical state. This implies scale invariance of the model, without tuning parameters. Prominent results of our simulation are time series of gains, prices, volatility, and gains frequency distributions, which all compare favorably to features of historical market data. Applying a standard GARCH(1,1) fit to the lattice model gives results that are almost indistinguishable from historical NASDAQ data.