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An Object-Oriented Bayesian Framework for the Detection of Market Drivers

Author

Listed:
  • Maria Elena De Giuli

    (Department of Economics and Management, University of Pavia, 27100 Pavia PV, Italy)

  • Alessandro Greppi

    (Zurich Investment Life, 20159 Milan MI, Italy)

  • Marina Resta

    (School of Social Sciences, Department of Economics and Business Studies, University of Genova, 16126 Genova GE, Italy)

Abstract

We use Object Oriented Bayesian Networks (OOBNs) to analyze complex ties in the equity market and to detect drivers for the Standard & Poor’s 500 (S&P 500) index. To such aim, we consider a vast number of indicators drawn from various investment areas (Value, Growth, Sentiment, Momentum, and Technical Analysis), and, with the aid of OOBNs, we study the role they played along time in influencing the dynamics of the S&P 500. Our results highlight that the centrality of the indicators varies in time, and offer a starting point for further inquiries devoted to combine OOBNs with trading platforms.

Suggested Citation

  • Maria Elena De Giuli & Alessandro Greppi & Marina Resta, 2019. "An Object-Oriented Bayesian Framework for the Detection of Market Drivers," Risks, MDPI, vol. 7(1), pages 1-18, January.
  • Handle: RePEc:gam:jrisks:v:7:y:2019:i:1:p:8-:d:197533
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    References listed on IDEAS

    as
    1. Hillmer, S. C. & Yu, P. L., 1979. "The market speed of adjustment to new information," Journal of Financial Economics, Elsevier, vol. 7(4), pages 321-345, December.
    2. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
    3. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    4. Sun, Lili & Shenoy, Prakash P., 2007. "Using Bayesian networks for bankruptcy prediction: Some methodological issues," European Journal of Operational Research, Elsevier, vol. 180(2), pages 738-753, July.
    5. Julia Mortera & Paola Vicard & Cecilia Vergari, 2012. "Object-Oriented Bayesian Networks for a Decision Support System," Departmental Working Papers of Economics - University 'Roma Tre' 0144, Department of Economics - University Roma Tre.
    6. Fama, Eugene F, et al, 1969. "The Adjustment of Stock Prices to New Information," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 10(1), pages 1-21, February.
    7. Benjamin-Fink, Nicole & Reilly, Brian K., 2017. "A road map for developing and applying object-oriented bayesian networks to “WICKED” problems," Ecological Modelling, Elsevier, vol. 360(C), pages 27-44.
    8. Flaminia Musella & Paola Vicard, 2015. "Object-oriented Bayesian networks for complex quality management problems," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 115-133, January.
    9. Shanken, Jay & Weinstein, Mark I., 2006. "Economic forces and the stock market revisited," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 129-144, March.
    10. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
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    Keywords

    OOBN; Market Drivers; S&P 500;
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