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...

This paper estimates the probability of a “lost decade,” where equity investments lose value over a 10-year period. The findings are a reminder that equity investments are risky even over longer time periods, and investors should take this into consideration when making portfolio choices. It...

Evolutionary metaphors have been prominent in both economics and finance. They are often used as basic foundations for rational behavior and efficient markets. Theoretically, a mechanism which selects for rational investors requires many caveats, and is far from generic. This paper tests wealth...

This study discusses the potential applicability of Agent-based Computational Economics (ACE) for macroeconomic modeling, with a particular stress on the following three issues: (1) taxonomy - what types of agents for macroeconomic models?; (2) scale robustness - how many agents for...