VOLATILITY CLUSTERING IN FINANCIAL MARKETS: A MICROSIMULATION OF INTERACTING AGENTS

TLDR

Clustered volatility and ARCH effects are ubiquitous in financial data and can be interpreted as on‑off intermittency, a dynamic behaviour known from physics. The paper proposes a multi‑agent speculative‑activity framework to explain clustered volatility. The model includes chartist and fundamentalist agents who switch strategies based on payoff differences, with price changes driven by a market maker reacting to demand‑supply imbalances. Simulations show a generally stable, efficient market punctuated by brief destabilising phases when chartist agents exceed a threshold, yet volatility is quickly dampened, reproducing stylised facts such as unit roots, heteroscedasticity, and leptokurtic returns.

Abstract

The finding of clustered volatility and ARCH effects is ubiquitous in financial data. This paper presents a possible explanation for this phenomenon within a multi-agent framework of speculative activity. In the model, both chartist and fundamentalist strategies are considered with agents switching between both behavioural variants according to observed differences in pay-offs. Price changes are brought about by a market maker reacting to imbalances between demand and supply. Most of the time, a stable and efficient market results. However, its usual tranquil performance is interspersed by sudden transient phases of destabilisation. An outbreak of volatility occurs if the fraction of agents using chartist techniques surpasses a certain threshold value, but such phases are quickly brought to an end by stabilising tendencies. Formally, this pattern can be understood as an example of a new type of dynamic behaviour known as "on-off intermittency" in physics literature. Statistical analysis of simulated time series shows that the main stylised facts (unit roots in levels together with heteroscedasticity and leptokurtosis of returns) can be found in this "artificial" market.