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Financial Markets Analysis by Probabilistic Fuzzy Modelling

Author

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  • van den Berg, J.H.
  • van den Bergh, W.-M.
  • Kaymak, U.

Abstract

For successful trading in financial markets, it is important to develop financial models where one can identify different states of the market for modifying one???s actions. In this paper, we propose to use probabilistic fuzzy systems for this purpose. We concentrate on Takagi???Sugeno (TS) probabilistic fuzzy systems that combine interpretability of fuzzy systems with the statistical properties of probabilistic systems. We start by recapitulating the general architecture of TS probabilistic fuzzy rule-based systems and summarize the corresponding reasoning schemes. We mention how probabilities can be estimated from a given data set and how a probability distribution can be approximated by a fuzzy histogram. We apply our methodology for financial time series analysis and demonstrate how a probabilistic TS fuzzy system can be identified, assuming that a linguistic term set is given. We illustrate the interpretability of such a system by inspecting the rule bases of our models.

Suggested Citation

  • van den Berg, J.H. & van den Bergh, W.-M. & Kaymak, U., 2003. "Financial Markets Analysis by Probabilistic Fuzzy Modelling," ERIM Report Series Research in Management ERS-2003-036-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    • Handle: RePEc:ems:eureri:323
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    References listed on IDEAS

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    1. Kroon, L.G. & Zuidwijk, R.A., 2003. "Mathematical models for planning support," ERIM Report Series Research in Management ERS-2003-032-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. van den Berg, J.H. & van den Bergh, W.-M. & Kaymak, U., 2001. "Probabilistic and Statistical Fuzzy Set Foundations of Competitive Exception Learning," ERIM Report Series Research in Management ERS-2001-40-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Pau, L-F. & Oremus, M.H.P., 2003. "WLAN Hot Spot services for the automotive and oil industries :a business analysis Or : "Refuel the car with petrol and information, both ways at the gas station"," ERIM Report Series Research in Management ERS-2003-039-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
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    Citations

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    Cited by:

    1. von Corswant, F. & Wynstra, J.Y.F. & Wetzels, M., 2003. "In Chains? Automotive Suppliers and Their Product Development Activities," ERIM Report Series Research in Management ERS-2003-027-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. R. J. Almeida & U. Kaymak, 2009. "Probabilistic fuzzy systems in value‐at‐risk estimation," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 16(1‐2), pages 49-70, January.
    3. Iris Lucas & Michel Cotsaftis & Cyrille Bertelle, 2017. "Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems," Post-Print hal-02114933, HAL.

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    More about this item

    Keywords

    data-driven design; fuzzy reasoning; fuzzy rule base; probabilistic fuzzy systems; time series analysis;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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