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A Novel Method of Modeling Dynamic Evolutionary Game with Rational Agents for Market Forecasting

Author

Listed:
  • Narges TALEBIMOTLAGH
  • Farzad HASHEMZADEH
  • Amir RIKHTEHGAR GHIASI
  • Sehraneh GHAEMI

    (Control Engineering Department Faculty of Electrical and Computer Engineering: University of Tabriz, Tabriz, Iran)

Abstract

Gold price modeling and prediction is a difficult problem and drastic changes of the price causes nonlinear dynamic that makes the price prediction one of the most challenging tasks for economists. Since gold market always has been interesting for traders, many of traders with various beliefs were highly active in gold market. The competition among two agents of traders, namely trend followers and rational agents, to gain the highest profit in gold market is formulated as a dynamic evolutionary game, where, the evolutionary equilibrium is considered to be the solution to this game. Furthermore, genetic algorithm is being used to find the unknown parameters of the model, so that we could maximize the fitness of the proposed multi agent model and the gold market daily price data. Besides the evolutionary game dynamic, we proposed a new method for modeling rational expectations using recurrent neural network. The evolutionarily stable strategies is proven despite the prediction error of the expectation. The empirical results show the high efficiency of the proposed method which could forecast future gold price precisely.

Suggested Citation

  • Narges TALEBIMOTLAGH & Farzad HASHEMZADEH & Amir RIKHTEHGAR GHIASI & Sehraneh GHAEMI, 2017. "A Novel Method of Modeling Dynamic Evolutionary Game with Rational Agents for Market Forecasting," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(1), pages 281-302.
    • Handle: RePEc:cys:ecocyb:v:50:y:2017:i:1:p:281-302
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    References listed on IDEAS

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    1. Schipper, Burkhard C., 2008. "On An Evolutionary Foundation Of Neuroeconomics," Economics and Philosophy, Cambridge University Press, vol. 24(03), pages 495-513, November.
    2. Araujo, Ricardo Azevedo & de Souza, Nathalia Almeida, 2010. "An evolutionary game theory approach to the dynamics of the labour market: A formal and informal perspective," Structural Change and Economic Dynamics, Elsevier, vol. 21(2), pages 101-110, May.
    3. Schipper, Burkhard C., 2008. "On An Evolutionary Foundation Of Neuroeconomics," Economics and Philosophy, Cambridge University Press, vol. 24(3), pages 495-513, November.
    4. Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2008. "Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm," Energy Economics, Elsevier, vol. 30(5), pages 2623-2635, September.
    5. Mauricio G. Villena & Marcelo J. Villena, 2004. "Evolutionary Game Theory and Thorstein Veblen’s Evolutionary Economics: Is EGT Veblenian?," Journal of Economic Issues, Taylor & Francis Journals, vol. 38(3), pages 585-610, September.
    6. Hanauske, Matthias & Kunz, Jennifer & Bernius, Steffen & König, Wolfgang, 2009. "Doves and hawks in economics revisited [An evolutionary quantum game theory-based analysis of financial crises]," MPRA Paper 14680, University Library of Munich, Germany.
    7. Ricardo Azevedo Araujo & Helmar Nunes Moreira, 2014. "Lyapunov stability in an evolutionary game theory model of the labour market," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 15(1), pages 41-53.
    8. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    9. Elvio Accinelli Gamba & Edgar J. Sánchez Carrera, 2010. "The Evolutionary Processes for the Populations of Firms and Workers," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 39-68, May.
    10. Agnés d’Artigues & Thierry Vignolo, 2004. "An evolutionary theory of the convergence towards low inflation rates," Journal of Evolutionary Economics, Springer, vol. 15(1), pages 51-64, January.
    11. Brock, W.A. & Hommes, C.H. & Wagener, F.O.O., 2009. "More hedging instruments may destabilize markets," Journal of Economic Dynamics and Control, Elsevier, vol. 33(11), pages 1912-1928, November.
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    More about this item

    Keywords

    Evolutionary Game Theory · Rational Agent · Evolutionary Stable State · Recurrent Neural Network · Two Step Ahead Prediction · Reinforcement Learning · Gold Market.;

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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