TAILIEUCHUNG - Building the Santa Fe Artificial Stock Market

Much of my market design philosophy stems from a desire to understand the impact of agent interactions and group learning dynamics in a financial setting. While agent-based markets have many goals, I see their first scientific use as a tool for understanding the dynamics in relatively traditional economic models. It is these models for which economists often invoke the heroic assumption of convergence to rational expectations equilibrium where agents’ beliefs and behavior have converged to a self-consistent world view. Obviously, this would be a nice place to get to, but the dynamics of this journey are rarely spelled out. Given that financial markets appear to. | Building the Santa Fe Artificial Stock Market Blake LeBaron Brandeis University June 2002 Abstract This short summary presents an insider s look at the construction of the Santa Fe artificial stock market. The perspective considers the many design questions that went into building the market from the perspective of a decade of experience with agent-based financial markets. The market is assessed based on its overall strengths and weaknesses. Graduate School of International Economics and Finance Brandeis University 415 South Street Mailstop 32 Waltham MA 02453 - 2728 blebaron@ blebaron. The author is a research associate at the National Bureau of Economic Research and an external faculty member at the Santa Fe Institute. 1 1 Introduction Most social systems involve complex interactions among many individuals. Much of economics hopes both to greatly simplify human behavior and to do it in such a way that aggregate macro features can be easily characterized. The success of this traditional approach to describe human behavior has only had mixed success. One area where questions remain is finance where many empirical features are troubling for existing theories. Several of the foundations of the field are in a state of disarray and new radically different theories are One of the directions that researchers have been taking is the use of agent-based financial markets. These bottom-up models of financial markets start from first principals of agent behavior. Using either computational or more sophisticated mathematical tools they are able to describe macro features emerging from a soup of individual interacting strategies. Since the early 1990 s I ve been involved with one of the first agent-based financial market platforms The Santa Fe Artificial Stock Market. Now with nearly a decade of experience in looking at financial markets from an agent-based perspective I would like to turn my attention back to the SFI market. I will .

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