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From Minority Games to real markets

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Author Info
D. Challet
A. Chessa
M. Marsili
Y. -C. Zhang

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Abstract

We address the question of market efficiency using the Minority Game (MG) model. First we show that removing unrealistic features of the MG leads to models which reproduce a scaling behavior close to what is observed in real markets. In particular we find that i) fat tails and clustered volatility arise at the phase transition point and that ii) the crossover to random walk behavior of prices is a finite size effect. This, on one hand, suggests that markets operate close to criticality, where the market is marginally efficient. On the other it allows one to measure the distance from criticality of real market, using cross-over times. The artificial market described by the MG is then studied as an ecosystem with different_species_ of traders. This clarifies the nature of the interaction and the particular role played by the various populations.

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File URL: http://arxiv.org/abs/cond-mat/0011042
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Paper provided by arXiv.org in its series Quantitative Finance Papers with number cond-mat/0011042.

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Date of creation: Nov 2000
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Handle: RePEc:arx:papers:cond-mat/0011042

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  1. Luca Grilli & Angelo Sfrecola, 2005. "Neural Networks to Predict Financial Time Series in a Minority Game Context," Quaderni DSEMS 14-2005, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia. [Downloadable!]
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