This chapter surveys research on agent-based models used in finance. It will concentrate on models where the use of computational tools is critical for the process of crafting models which give insights into the importance and dynamics of investor heterogeneity in many financial settings.

Economies are complicated systems encompassing micro behaviors, interaction patterns, and global regularities. Whether partial or general in scope, studies of economic systems must consider how to handle difficult real-world aspects such as asymmetric information, imperfect competition,...

This paper uses an agent based financial market calibrated to aggregate data. It shows how these markets are able to magnify the volatility of fundamentals, and to create time series with persistent volatility. The mechanism for this persistence is explored using several of the time series...

Chaos theory has touched on such fields as biology, cognitive science, and physics. By providing a unified and complete explanation of new statistical methods that are useful for testing for chaos in data sets, Brock, Hsieh, and LeBaron show how the principles of chaos theory can be applied to...

We find a large positive correlation between daily trading volume in currency futures markets and foreign‐exchange intervention by the Federal Reserve over the period 1979 to 1996. Neither contemporaneous nor predicted volatility can fully account for the increases in trading activity. Whether...

Heterogeneous agent models for financial markets have provided explanations for many empirical regularities of relatively high frequency (hourly/daily) financial time series. They have been much quieter when it comes to longer range features. This paper examines a simplified computational...