Abstract
In 1997, a minority game (MG) was proposed as a non-cooperative iterated game with an odd population of agents who make bids whether to buy or sell. Since then, many variants of the MG have been proposed. However, the common disadvantage in their characteristics is to ignore the past actions beyond a constant memory. So it is difficult to simulate actual payoffs of agents if the past price behavior has a significant influence on the current decision. In this paper we present a new variant of the MG, called an asset value game (AG), and its extension, called an extended asset value game (ExAG). In the AG, since every agent aims to decrease the mean acquisition cost of his asset, he automatically takes the past actions into consideration. The AG, however, is too simple to reproduce the complete market dynamics, that is, there may be some time lag between the price and his action. So we further consider the ExAG by using probabilistic actions, and compare them by simulation.
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Andersen, J.V., Sornette, D.: The $-game. The European Physical Journal B 31(1), 141–145 (2003)
Araujo, R.M., Lamb, L.C.: Towards understanding the role of learning models in the dynamics of the minority game. In: Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2004), pp. 727–731 (2004)
Araujo, R.M., Lamb, L.C.: On the use of memory and resources in minority games. ACM Transactions on Autonomous and Adaptive Systems 4(2), 2 (2009)
Challet, D.: Inter-pattern speculation: beyond minority, majority and $-games. Journal of Economic Dynamics and Control (2007)
Challet, D., Marsili, M., Zhang, Y.-C.: Stylized facts of financial markets and market crashes in minority games. Physica A 294, 514–524 (2001)
Challet, D., Marsili, M., Zhang, Y.-C.: Minority games — interacting agents in financial markets. Oxford University Press (2005)
Challet, D., Zhang, Y.-C.: Emergence of cooperation and organization in an evolutionary game. Physica A 246, 407–418 (1997)
Coolen, A.C.C.: The mathematical theory of minority games. Oxford University Press (2005)
Ferreira, F.F., Marsili, M.: Real payoffs and virtual trading in agent based market models. Physica A 345, 657–675 (2005)
Ferreira, F.F., de Oliveira, V.M., Crepaldi, A.F., Campos, P.R.A.: Agent-based model with heterogeneous fundamental prices. Physica A 357, 534–542 (2005)
Giardina, I., Bouchaud, J.-P., Meźard, M.: Microscopic models for long ranged volatility correlations. Physica A 299, 28–39 (2001)
Kiniwa, J., Koide, T., Sandoh, H.: Analysis of price behavior in lazy $-game. Physica A 388(18), 3879–3891 (2009)
Liu, X., Liang, X., Tang, B.: Minority game and anomalies in financial markets. Physica A 333, 343–352 (2004)
Marsili, M.: Market mechanism and expectations in minority and majority games. Physica A 299, 93–103 (2001)
De Martino, A., Giardina, I., Mosetti, G.: Statistical mechanics of the mixed majority-minority game with random external information. Journal of Physics A: Mathematical and General 36, 8935–8954 (2003)
Takayasu, H., Miura, T., Hirabayashi, T., Hamada, K.: Statistical properties of deterministic threshold elements — the case of market price. Physica A 184(1-2), 127–134 (1992)
Tedeschi, A., De Martino, A., Giardina, I.: Coordination, intermittency and trends in generalized minority games. Physica A 358, 529–544 (2005)
Yamada, K., Takayasu, H., Takayasu, M.: Characterization of foreign exchange market using the threshold-dealer-model. Physica A 382(1), 340–346 (2007)
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Kiniwa, J., Koide, T., Sandoh, H. (2013). Asset Value Game and Its Extension: Taking Past Actions into Consideration. In: Filipe, J., Fred, A. (eds) Agents and Artificial Intelligence. ICAART 2012. Communications in Computer and Information Science, vol 358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36907-0_21
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DOI: https://doi.org/10.1007/978-3-642-36907-0_21
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