IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v295y2020i1d10.1007_s10479-020-03757-8.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-020-03757-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-020-03757-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. David Colander (ed.), 2000. "The Complexity Vision and the Teaching of Economics," Books, Edward Elgar Publishing, number 1955.
    3. 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).
    4. Mohamed Zouaoui & G. Nouyrigat & F. Beer, 2011. "How Does Investor Sentiment Affect StockMarket Crises? Evidence from Panel Data," Post-Print halshs-00785809, HAL.
    5. 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.
    6. 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.
    7. Camelia Kuhnen & Brian Knutson, 2005. "The Neural Basis of Financial Risk Taking," Experimental 0509001, University Library of Munich, Germany.
    8. Ardalan, Kavous, 2018. "Neurofinance versus the efficient markets hypothesis," Global Finance Journal, Elsevier, vol. 35(C), pages 170-176.
    9. 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.
    10. 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.
    11. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Xiaoxiao & Yu, Hao & Sun, Qiuwen & Tam, Vivian W.Y., 2023. "A critical review of occupant energy consumption behavior in buildings: How we got here, where we are, and where we are headed," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    2. Nafisa Mahbub & Anh Le & Jun Zhuang, 2022. "Online crowd-funding strategy: a game-theoretical approach to a Kickstarter case study," Annals of Operations Research, Springer, vol. 315(2), pages 1019-1036, August.
    3. Caginalp, Carey & Caginalp, Gunduz & Swigon, David, 2021. "Stochastic asset flow equations: Interdependence of trend and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    4. Ayşe Özmen & Yuriy Zinchenko & Gerhard-Wilhelm Weber, 2023. "Robust multivariate adaptive regression splines under cross-polytope uncertainty: an application in a natural gas market," Annals of Operations Research, Springer, vol. 324(1), pages 1337-1367, May.
    5. Qi, Yue & Liao, Kezhi & Liu, Tongyang & Zhang, Yu, 2022. "Originating multiple-objective portfolio selection by counter-COVID measures and analytically instigating robust optimization by mean-parameterized nondominated paths," Operations Research Perspectives, Elsevier, vol. 9(C).
    6. Wang, Xiaolong & Feng, Jing & Liu, Qi & Li, Yongge & Xu, Yong, 2022. "Neural network-based parameter estimation of stochastic differential equations driven by Lévy noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hela Namouri & Fredj Jawadi & Zied Ftiti & Néjib Hachicha, 2018. "Threshold effect in the relationship between investor sentiment and stock market returns: a PSTR specification," Applied Economics, Taylor & Francis Journals, vol. 50(5), pages 559-573, January.
    2. Nawaf Almaskati & Ron Bird & Yue Lu & Danny Leung, 2019. "Corporate Governance, Information Uncertainty and Market Reaction to Information Signals," Working Papers in Economics 19/15, University of Waikato.
    3. Wang, Wenzhao & Duxbury, Darren, 2021. "Institutional investor sentiment and the mean-variance relationship: Global evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 415-441.
    4. Tingqiang Chen & Binqing Xiao & Haifei Liu, 2018. "Credit Risk Contagion in an Evolving Network Model Integrating Spillover Effects and Behavioral Interventions," Complexity, Hindawi, vol. 2018, pages 1-16, March.
    5. Bildirici, Melike E. & Badur, Mesut M., 2019. "The effects of oil and gasoline prices on confidence and stock return of the energy companies for Turkey and the US," Energy, Elsevier, vol. 173(C), pages 1234-1241.
    6. Daniel Perez-Liston & Daniel Huerta-Sanchez & Juan Gutierrez, 2018. "Do Domestic Sentiment and the Spillover of US Investor Sentiment Impact Mexican Stock Market Returns?," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2_suppl), pages 185-212, August.
    7. Fang, Libing & Yu, Honghai & Huang, Yingbo, 2018. "The role of investor sentiment in the long-term correlation between U.S. stock and bond markets," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 127-139.
    8. Anand, Abhinav & Basu, Sankarshan & Pathak, Jalaj & Thampy, Ashok, 2021. "The impact of sentiment on emerging stock markets," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 161-177.
    9. Ahmed Salhin & Mo Sherif & Edward Jones, 2016. "Investor Sentiment and Sector Returns," CFI Discussion Papers 1602, Centre for Finance and Investment, Heriot Watt University.
    10. Mehwish Aziz Khan & Eatzaz Ahmad, 2018. "Measurement of Investor Sentiment and Its Bi-Directional Contemporaneous and Lead–Lag Relationship with Returns: Evidence from Pakistan," Sustainability, MDPI, vol. 11(1), pages 1-20, December.
    11. Reis, Pedro Manuel Nogueira & Pinho, Carlos, 2020. "A new European investor sentiment index (EURsent) and its return and volatility predictability," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    12. Wu, Qinqin & Hao, Ying & Lu, Jing, 2017. "Investor sentiment, idiosyncratic risk, and mispricing of American Depository Receipt," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 1-14.
    13. Hu, May & Chao, Chi-Chur & Lim, Jin Hao, 2016. "Another explanation of the mutual fund fee puzzle," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 134-152.
    14. Wang, Wenzhao & Su, Chen & Duxbury, Darren, 2021. "Investor sentiment and stock returns: Global evidence," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 365-391.
    15. Tihana Škrinjarić, 2021. "Profiting on the Stock Market in Pandemic Times: Study of COVID-19 Effects on CESEE Stock Markets," Mathematics, MDPI, vol. 9(17), pages 1-20, August.
    16. Kamini Solanki & Yudhvir Seetharam, 2014. "Is consumer confidence an indicator of JSE performance?," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 8(3), September.
    17. Mariano González-Sánchez & M. Encina Morales de Vega, 2021. "Influence of Bloomberg’s Investor Sentiment Index: Evidence from European Union Financial Sector," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
    18. Economou, Fotini & Panagopoulos, Yannis & Tsouma, Ekaterini, 2018. "Uncovering asymmetries in the relationship between fear and the stock market using a hidden co-integration approach," Research in International Business and Finance, Elsevier, vol. 44(C), pages 459-470.
    19. Agoraki, Maria-Eleni K. & Aslanidis, Nektarios & Kouretas, Georgios P., 2022. "U.S. banks’ lending, financial stability, and text-based sentiment analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 73-90.
    20. Deven Bathia & Don Bredin & Dirk Nitzsche, 2016. "International Sentiment Spillovers in Equity Returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(4), pages 332-359, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:295:y:2020:i:1:d:10.1007_s10479-020-03757-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.