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Mutual relevance of investor sentiment and finance by modeling coupled stochastic systems with MARS

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  • Betül Kalaycı

    (Middle East Technical University)

  • Ayşe Özmen

    (Middle East Technical University)

  • Gerhard-Wilhelm Weber

    (Middle East Technical University
    Poznan University of Technology)

Abstract

Stochastic differential equations (SDEs) rapidly become one of the most well-known formats in which to express such diverse mathematical models under uncertainty such as financial models, neural systems, behavioral and neural responses, human reactions and behaviors. They belong to the main methods to describe randomness of a dynamical model today. In a financial system, different kinds of SDEs have been elaborated to model various financial assets. On the other hand, economists have conducted research on several empirical phenomena regarding the behaviour of individual investors, such as how their emotions and opinions influence their decisions. All those emotions and opinions are described by the word Sentiment. In finance, stochastic changes might occur according to investors’ sentiment levels. In our study, we aim to represent the mutual effects between some financial process and investors’ sentiment with constructing a coupled system of non-autonomous SDEs, evolving in time. These equations are hard to assess and solve. Therefore, we express them in a simplified manner by discretization and Multivariate Adaptive Regression Splines (MARS) model. MARS is a strong method for flexible regression and classification with interactive variables. Hereby, we treat time as another spatial variable. Eventually, we present a modern application with real-world data. This study finishes with a conclusion and an outlook towards future studies.

Suggested Citation

  • Betül Kalaycı & Ayşe Özmen & Gerhard-Wilhelm Weber, 2020. "Mutual relevance of investor sentiment and finance by modeling coupled stochastic systems with MARS," Annals of Operations Research, Springer, vol. 295(1), pages 183-206, December.
    • Handle: RePEc:spr:annopr:v:295:y:2020:i:1:d:10.1007_s10479-020-03757-8
    DOI: 10.1007/s10479-020-03757-8
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    References listed on IDEAS

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    1. David Colander (ed.), 2000. "The Complexity Vision and the Teaching of Economics," Books, Edward Elgar Publishing, number 1955.
    2. Bormann, Sven-Kristjan, 2013. "Sentiment indices on financial markets: What do they measure?," Economics Discussion Papers 2013-58, Kiel Institute for the World Economy (IfW Kiel).
    3. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    4. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    5. Mohamed Zouaoui & Geneviève Nouyrigat & Francisca Beer, 2011. "How does investor sentiment affect stock market crises?Evidence from panel data," Working Papers CREGO 1110304, Université de Bourgogne - CREGO EA7317 Centre de recherches en gestion des organisations.
    6. Ardalan, Kavous, 2018. "Neurofinance versus the efficient markets hypothesis," Global Finance Journal, Elsevier, vol. 35(C), pages 170-176.
    7. Mohamed Zouaoui & Geneviève Nouyrigat & Francisca Beer, 2011. "How Does Investor Sentiment Affect Stock Market Crises? Evidence from Panel Data," The Financial Review, Eastern Finance Association, vol. 46(4), pages 723-747, November.
    8. Alper Çevik & Gerhard-Wilhelm Weber & B. Murat Eyüboğlu & Kader Karlı Oğuz, 2017. "Voxel-MARS: a method for early detection of Alzheimer’s disease by classification of structural brain MRI," Annals of Operations Research, Springer, vol. 258(1), pages 31-57, November.
    9. Camelia Kuhnen & Brian Knutson, 2005. "The Neural Basis of Financial Risk Taking," Experimental 0509001, University Library of Munich, Germany.
    10. Mohamed Zouaoui & G. Nouyrigat & F. Beer, 2011. "How Does Investor Sentiment Affect StockMarket Crises? Evidence from Panel Data," Post-Print halshs-00785809, HAL.
    11. Pakize Taylan & Gerhard-Wilhelm Weber & Fatma Yerlikaya Özkurt, 2010. "A new approach to multivariate adaptive regression splines by using Tikhonov regularization and continuous optimization," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(2), pages 377-395, December.
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