Multiple Time Series Ising Model for Financial Market Simulations

TL;DR

This paper introduces a multi-time series Ising model that captures volatility clustering and cross-correlations in financial markets, providing a new tool for simulating complex market behaviors.

Contribution

It presents a novel Ising model that simulates multiple financial time series with inter-system interactions, capturing realistic market phenomena.

Findings

Model reproduces volatility clustering observed in real markets.

Simulates non-zero cross correlations between stock volatilities.

Demonstrates mutual correlation of volatilities in simulated stock markets.

Abstract

In this paper we propose an Ising model which simulates multiple financial time series. Our model introduces the interaction which couples to spins of other systems. Simulations from our model show that time series exhibit the volatility clustering that is often observed in the real financial markets. Furthermore we also find non-zero cross correlations between the volatilities from our model. Thus our model can simulate stock markets where volatilities of stocks are mutually correlated.