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Enhanced evolving participatory learning fuzzy modeling: an application for asset returns volatility forecasting

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Abstract

Evolving participatory learning (ePL) modeling joins the concepts of participatory learning and evolving fuzzy systems. It uses data streams to continuously adapt the structure and functionality of fuzzy models. This paper suggests an enhanced version of the ePL approach, called ePL+, which includes both an utility measure to shrink rule bases, and a variable cluster radius mechanism to improve the cluster structure. These features are useful in adaptive fuzzy rule-based modeling to recursively construct local fuzzy models with variable zone of influence. Moreover, ePL+ extends ePL to multi-input, multi-output fuzzy system modeling. Computational experiments considering financial returns volatility modeling and forecasting are conducted to compare the performance of the ePL+ approach with state of the art fuzzy modeling methods and with GARCH modeling. The experiments use actual data of S&P 500 and Ibovespa stock market indexes. The results suggest that the ePL+ approach is highly capable to model volatility dynamics, in a robust, flexible, parcimonious, and autonomous way.

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Notes

  1. One must note that ePL considers MISO models whereas ePL+ concerns MIMO models. This difference appears in consequent parameters learning, as will be described in the Subsect. 2.5.

  2. The database was provided by Bloomberg.

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Acknowledgements

The authors thank the Brazilian Ministry of Education (CAPES), the Brazilian National Research Council (CNPq) Grants 304596/2009-4 and 306343/2011-8, and the Research Foundation of the State of São Paulo (FAPESP) Grant 13851-3/2011, for their support.

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Authors and Affiliations

  1. School of Electrical and Computer Engineering, University of Campinas, Campinas, 13083-852, Brazil

    Leandro Maciel & Fernando Gomide

  2. Institute of Economics, University of Campinas, Campinas, 13083-857, Brazil

    Rosangela Ballini

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  1. Leandro Maciel
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  2. Fernando Gomide
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  3. Rosangela Ballini
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Correspondence to Rosangela Ballini.

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Maciel, L., Gomide, F. & Ballini, R. Enhanced evolving participatory learning fuzzy modeling: an application for asset returns volatility forecasting. Evolving Systems 5, 75–88 (2014). https://doi.org/10.1007/s12530-013-9099-0

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