Abstract
We use game theory and Santa Fe Artificial Stock Market, anagent-based model of an evolving stock market, to study theoptimal frequency for traders to revise their market forecastingrules. We discover two things: There is a unique strategic Nashequilibrium in the game of choosing forecast revision rates, andthis equilibrium is sub-optimal in the sense that traders'earnings are not maximized an the market is inefficient. Thisstrategic equilibrium is due to an analogue of the prisoner'sdilemma; the optimal global state is unstable because eachtrader has too much incentive to `defect' and use forecastingrules that pull the market into thesub-optimal equilibrium.
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Joshi, S., Parker, J. & Bedau, M.A. Financial Markets can be at Sub-Optimal Equilibria. Computational Economics 19, 5–23 (2002). https://doi.org/10.1023/A:1014988805326
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DOI: https://doi.org/10.1023/A:1014988805326