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Multifractal regime transition in a modified minority game model

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  • Crepaldi, Antonio F.
  • Neto, Camilo Rodrigues
  • Ferreira, Fernando F.
  • Francisco, Gerson

Abstract

The search for more realistic modeling of financial time series reveals several stylized facts of real markets. In this work we focus on the multifractal properties found in price and index signals. Although the usual minority game (MG) models do not exhibit multifractality, we study here one of its variants that does. We show that the nonsynchronous MG models in the nonergodic phase is multifractal and in this sense, together with other stylized facts, constitute a better modeling tool. Using the structure function (SF) approach we detected the stationary and the scaling range of the time series generated by the MG model and, from the linear (non-linear) behavior of the SF we identified the fractal (multifractal) regimes. Finally, using the wavelet transform modulus maxima (WTMM) technique we obtained its multifractal spectrum width for different dynamical regimes.

Suggested Citation

  • Crepaldi, Antonio F. & Neto, Camilo Rodrigues & Ferreira, Fernando F. & Francisco, Gerson, 2009. "Multifractal regime transition in a modified minority game model," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1364-1371.
    • Handle: RePEc:eee:chsofr:v:42:y:2009:i:3:p:1364-1371
    DOI: 10.1016/j.chaos.2009.03.044
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    Cited by:

    1. Fernando F. Ferreira & A. Christian Silva & Ju-Yi Yen, 2019. "Detailed study of a moving average trading rule," Papers 1907.00212, arXiv.org.
    2. da Fonseca, Eder Lucio & Ferreira, Fernando F. & Muruganandam, Paulsamy & Cerdeira, Hilda A., 2013. "Identifying financial crises in real time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1386-1392.
    3. Lin, Hai & Yang, Dong-Ping & Shuai, J.W., 2011. "Cooperation among mobile individuals with payoff expectations in the spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 44(1), pages 153-159.
    4. Yuan, Ying & Zhang, Tonghui, 2020. "Forecasting stock market in high and low volatility periods: a modified multifractal volatility approach," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).

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