Agent-Based Market Models of Bubbles, Crashes, and Intermittency

Summary

This study examines a market model inspired by the Santa Fe artificial market and the Minority Game. Agents can select among strategies according to relative profitability or stay out of the market. Prices respond to excess demand, while agent wealth is tracked. The model’s behavior depends chiefly on price impact and the balance between trend-following and contrarian behavior.

Varying those parameters produces oscillating markets with bubbles and crashes, intermittent markets, and a stable rational regime. In the intermittent phase, price changes resemble observed financial data through small linear correlations, fat tails, and persistent volatility clustering. The authors also analyze how parameter changes can move the system into that phase and how random shifts in strategy may explain long-range activity correlations. These are results from a modeled market, not evidence that the same mechanisms fully explain real markets. The study also considers transaction costs and wealth distribution.

Key ideas

• Agent participation and strategy choice depend on relative profitability, with the option to stay out of the market.
• Price impact and the balance between trend-following and contrarian behavior shape the model’s regimes.
• The model produces oscillating, intermittent, and stable market phases.
• Intermittent simulated returns exhibit fat tails, weak linear correlation, and clustered volatility.
• Random strategy shifts are proposed as an explanation for long-range activity correlations.

Tags

# Bubbles, crashes and intermittency in agent based market models


# Bubbles, crashes and intermittency in agent based market models









We define and study a rather complex market model, inspired from the Santa Fe artificial market and the Minority Game. Agents have different strategies among which they can choose, according to their relative profitability, with the possibility of not participating to the market. The price is updated according to the excess demand, and the wealth of the agents is properly accounted for. Only two parameters play a significant role: one describes the impact of trading on the price, and the other describes the propensity of agents to be trend following or contrarian. We observe three different regimes, depending on the value of these two parameters: an oscillating phase with bubbles and crashes, an intermittent phase and a stable `rational' market phase. The statistics of price changes in the intermittent phase resembles that of real price changes, with small linear correlations, fat tails and long range volatility clustering. We discuss how the time dependence of these two parameters spontaneously drives the system in the intermittent region. We analyze quantitatively the temporal correlation of activity in the intermittent phase, and show that the `random time strategy shift' mechanism that we proposed earlier allows one to understand the observed long ranged correlations. Other mechanisms leading to long ranged correlations are also reviewed. We discuss several other issues, such as the formation of bubbles and crashes, the influence of transaction costs and the distribution of agents wealth.

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