Financial Markets Can Be at Sub-optimal Equilibria
AbstractWe use game theory and Santa Fe Artificial Stock Market, an agent-based model of an evolving stock market, to study the optimal frequency for traders to revise their market forecasting rules. We discover two things: There is a unique strategic Nash equilibrium in the game of choosing forecast revision rates, and this equilibrium is sub-optimal in the sense that traders' earnings are not maximized an the market is inefficient. This strategic equilibrium is due to an analogue of the prisoner's dilemma; the optimal global state is unstable because each trader has too much incentive to "defect" and use forecasting rules that pull the market into the sub-optimal equilibrium. Copyright 2002 by Kluwer Academic Publishers
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Bibliographic InfoArticle provided by Society for Computational Economics in its journal Computational Economics.
Volume (Year): 19 (2002)
Issue (Month): 1 (February)
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- Norman Ehrentreich, 2002. "The Santa Fe Artificial Stock Market Re-Examined - Suggested Corrections," Computational Economics 0209001, EconWPA.
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