IDEAS home Printed from https://ideas.repec.org/a/spr/fininn/v6y2020i1d10.1186_s40854-020-00211-3.html
   My bibliography  Save this article

Opinion dynamics in finance and business: a literature review and research opportunities

Author

Listed:
  • Quanbo Zha

    (School of Management Science and Real Estate, Chongqing University)

  • Gang Kou

    (School of Business Administration, Southwestern University of Finance and Economics)

  • Hengjie Zhang

    (Business School, Hohai University)

  • Haiming Liang

    (Center for Network Big Data and Decision-Making, Business School, Sichuan University)

  • Xia Chen

    (Center for Network Big Data and Decision-Making, Business School, Sichuan University)

  • Cong-Cong Li

    (School of Economics and Management, Southwest Jiaotong University)

  • Yucheng Dong

    (Center for Network Big Data and Decision-Making, Business School, Sichuan University)

Abstract

Opinion dynamics is an opinion evolution process of a group of agents, where the final opinion distribution tends to three stable states: consensus, polarization, and fragmentation. At present, the opinion dynamics models have been extensively studied in differrent fields. This paper provides a review of opinion dynamics in finance and business, such as, finance, marketing, e-commerce, politics, and group decision making. Furthermore, identified research challenges have been proposed to promote the future research of this topic.

Suggested Citation

  • Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    • Handle: RePEc:spr:fininn:v:6:y:2020:i:1:d:10.1186_s40854-020-00211-3
    DOI: 10.1186/s40854-020-00211-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s40854-020-00211-3
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1186/s40854-020-00211-3?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
    ---><---

    References listed on IDEAS

    as
    1. Karl B. Diether & Kuan-Hui Lee & Ingrid M. Werner, 2009. "Short-Sale Strategies and Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 22(2), pages 575-607, February.
    2. Luo, Gui-Xun & Liu, Yun & Zeng, Qing-An & Diao, Su-Meng & Xiong, Fei, 2014. "A dynamic evolution model of human opinion as affected by advertising," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 254-262.
    3. Vilela, André L.M. & Wang, Chao & Nelson, Kenric P. & Stanley, H. Eugene, 2019. "Majority-vote model for financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 762-770.
    4. C. J. Tessone & R. Toral, 2004. "Neighborhood models of minority opinion spreading," Computing in Economics and Finance 2004 206, Society for Computational Economics.
    5. M. C. González & A. O. Sousa & H. J. Herrmann, 2004. "Opinion Formation On A Deterministic Pseudo-Fractal Network," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 45-57.
    6. Yan Wan & Baojun Ma & Yu Pan, 2018. "Opinion evolution of online consumer reviews in the e-commerce environment," Electronic Commerce Research, Springer, vol. 18(2), pages 291-311, June.
    7. K. Sznajd-Weron & R. Weron, 2002. "A Simple Model Of Price Formation," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 115-123.
    8. Kaizoji, Taisei, 2000. "Speculative bubbles and crashes in stock markets: an interacting-agent model of speculative activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 493-506.
    9. M. E. J. Newman & D. J. Watts, 1999. "Renormalization Group Analysis of the Small-World Network Model," Working Papers 99-04-029, Santa Fe Institute.
    10. Lei Feng & Mark Seasholes, 2005. "Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets?," Review of Finance, Springer, vol. 9(3), pages 305-351, September.
    11. Francesco Cordoni & Luca Di Persio, 2014. "Backward Stochastic Differential Equations Approach to Hedging, Option Pricing, and Insurance Problems," International Journal of Stochastic Analysis, Hindawi, vol. 2014, pages 1-11, September.
    12. Kaizoji, Taisei, 2006. "An interacting-agent model of financial markets from the viewpoint of nonextensive statistical mechanics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 109-113.
    13. Krzysztof Kułakowski & Maria Nawojczyk, 2008. "The Galam Model Of Minority Opinion Spreading And The Marriage Gap," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 19(04), pages 611-615.
    14. Vincenzo Crescimanna & Luca Di Persio, 2016. "Herd Behavior and Financial Crashes: An Interacting Particle System Approach," Journal of Mathematics, Hindawi, vol. 2016, pages 1-7, February.
    15. Mitchell, Mark L & Mulherin, J Harold, 1994. "The Impact of Public Information on the Stock Market," Journal of Finance, American Finance Association, vol. 49(3), pages 923-950, July.
    16. Sznajd-Weron, K. & Weron, R., 2003. "How effective is advertising in duopoly markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 437-444.
    17. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    18. Sornette, Didier & Zhou, Wei-Xing, 2006. "Importance of positive feedbacks and overconfidence in a self-fulfilling Ising model of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(2), pages 704-726.
    19. Lei Feng & Mark S. Seasholes, 2005. "Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets?," Review of Finance, European Finance Association, vol. 9(3), pages 305-351.
    20. Galam, Serge & Jacobs, Frans, 2007. "The role of inflexible minorities in the breaking of democratic opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 366-376.
    21. Takeshi Inagaki, 2004. "Critical Ising Model and Financial Market," Papers cond-mat/0402511, arXiv.org, revised Feb 2004.
    22. Rainer Hegselmann & Ulrich Krause, 2002. "Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-2.
    23. Lima, L.S., 2017. "Modeling of the financial market using the two-dimensional anisotropic Ising model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 544-551.
    24. Horvath, Philip A. & Roos, Kelly R. & Sinha, Amit, 2016. "An Ising spin state explanation for financial asset allocation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 112-116.
    25. Fang, Wen & Ke, Jinchuan & Wang, Jun & Feng, Ling, 2016. "Linking market interaction intensity of 3D Ising type financial model with market volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 531-542.
    26. Bonggyun Ko & Jae Wook Song & Woojin Chang, 2016. "Simulation of financial market via nonlinear Ising model," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 27(04), pages 1-15, April.
    27. Bernardo J. Zubillaga & Andr'e L. M. Vilela & Chao Wang & Kenric P. Nelson & H. Eugene Stanley, 2019. "A Three-state Opinion Formation Model for Financial Markets," Papers 1905.04370, arXiv.org.
    28. Kaizoji, Taisei & Bornholdt, Stefan & Fujiwara, Yoshi, 2002. "Dynamics of price and trading volume in a spin model of stock markets with heterogeneous agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 441-452.
    29. Zhaogang Ding & Yucheng Dong & Haiming Liang & Francisco Chiclana, 2017. "Asynchronous Opinion Dynamics with Online and Offline Interactions in Bounded Confidence Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(4), pages 1-6.
    30. Kostas Bimpikis & Asuman Ozdaglar & Ercan Yildiz, 2016. "Competitive Targeted Advertising Over Networks," Operations Research, INFORMS, vol. 64(3), pages 705-720, June.
    31. M Günther & C Stummer & L M Wakolbinger & M Wildpaner, 2011. "An agent-based simulation approach for the new product diffusion of a novel biomass fuel," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 12-20, January.
    32. Krawiecki, A. & Hołyst, J.A., 2003. "Stochastic resonance as a model for financial market crashes and bubbles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 317(3), pages 597-608.
    33. Wang, Jun, 2009. "The estimates of correlations in two-dimensional Ising model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(5), pages 565-573.
    34. Bornholdt, Stefan & Wagner, Friedrich, 2002. "Stability of money: phase transitions in an Ising economy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 453-468.
    35. W.-X. Zhou & D. Sornette, 2007. "Self-organizing Ising model of financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 55(2), pages 175-181, January.
    36. Zhang, Bo & Wang, Guochao & Wang, Yiduan & Zhang, Wei & Wang, Jun, 2019. "Multiscale statistical behaviors for Ising financial dynamics with continuum percolation jump," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1012-1025.
    37. Andrzej Krawiecki, 2009. "Microscopic spin model for the stock market with attractor bubbling on scale-free networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 4(2), pages 213-220, November.
    38. Bak, P. & Paczuski, M. & Shubik, M., 1997. "Price variations in a stock market with many agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 430-453.
    39. Kewei Hou & Tobias J. Moskowitz, 2005. "Market Frictions, Price Delay, and the Cross-Section of Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 981-1020.
    40. Thomas Lux & Michele Marchesi, 2000. "Volatility Clustering In Financial Markets: A Microsimulation Of Interacting Agents," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 675-702.
    41. Katarzyna Sznajd-Weron & Józef Sznajd, 2000. "Opinion Evolution In Closed Community," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1157-1165.
    42. Tetsuya Takaishi, 2016. "Dynamical cross-correlation of multiple time series Ising model," Evolutionary and Institutional Economics Review, Springer, vol. 13(2), pages 455-468, December.
    43. Martins, André C.R. & Pereira, Carlos de B. & Vicente, Renato, 2009. "An opinion dynamics model for the diffusion of innovations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(15), pages 3225-3232.
    44. Anders Johansen & Olivier Ledoit & Didier Sornette, 2000. "Crashes As Critical Points," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 219-255.
    45. Galam, Serge, 2004. "Contrarian deterministic effects on opinion dynamics: “the hung elections scenario”," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 453-460.
    46. Eckrot, A. & Jurczyk, J. & Morgenstern, I., 2016. "Ising model of financial markets with many assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 250-254.
    47. Fang, Wen & Wang, Jun, 2013. "Fluctuation behaviors of financial time series by a stochastic Ising system on a Sierpinski carpet lattice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4055-4063.
    48. Wang, Guochao & Zheng, Shenzhou & Wang, Jun, 2019. "Complex and composite entropy fluctuation behaviors of statistical physics interacting financial model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 97-113.
    49. Stefan Bornholdt, 2001. "Expectation Bubbles In A Spin Model Of Markets: Intermittency From Frustration Across Scales," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 12(05), pages 667-674.
    50. Situngkir, Hokky, 2006. "Advertising in Duopoly Market," MPRA Paper 885, University Library of Munich, Germany.
    51. Guillaume Deffuant & David Neau & Frederic Amblard & Gérard Weisbuch, 2000. "Mixing beliefs among interacting agents," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 3(01n04), pages 87-98.
    52. Katarzyna Sznajd-Weron, 2005. "Sznajd model and its applications," HSC Research Reports HSC/05/04, Hugo Steinhaus Center, Wroclaw University of Technology.
    53. Easley, David & O’Hara, Maureen & Yang, Liyan, 2016. "Differential Access to Price Information in Financial Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(4), pages 1071-1110, August.
    54. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    55. A. Krawiecki, 2005. "Microscopic Spin Model For The Stock Market With Attractor Bubbling And Heterogeneous Agents," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 549-559.
    56. Maldarella, Dario & Pareschi, Lorenzo, 2012. "Kinetic models for socio-economic dynamics of speculative markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 715-730.
    57. Galam, Serge, 1999. "Application of statistical physics to politics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 274(1), pages 132-139.
    58. Sebastian M. Krause & Stefan Bornholdt, 2012. "Opinion formation model for markets with a social temperature and fear," Papers 1212.4751, arXiv.org.
    59. Sabatelli, Lorenzo & Richmond, Peter, 2004. "A consensus-based dynamics for market volumes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 62-66.
    60. da Silva, L.R & Stauffer, D, 2001. "Ising-correlated clusters in the Cont-Bouchaud stock market model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 294(1), pages 235-238.
    61. Christian Schulze, 2003. "Advertising In The Sznajd Marketing Model," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 95-98.
    62. Haiming Liang & Yucheng Dong & Congcong Li, 2016. "Dynamics of Uncertain Opinion Formation: An Agent-Based Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(4), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    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. Ditian Zhang & Yangyang Zhuang & Pan Tang & Hongjuan Peng & Qingying Han, 2023. "Financial price dynamics and phase transitions in the stock markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(3), pages 1-21, March.
    2. Catherine A. Glass & David H. Glass, 2021. "Social Influence of Competing Groups and Leaders in Opinion Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 799-823, October.
    3. Kristoufek, Ladislav & Vošvrda, Miloslav S., 2016. "Herding, minority game, market clearing and efficient markets in a simple spin model framework," FinMaP-Working Papers 68, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    4. Fan, Kangqi & Pedrycz, Witold, 2016. "Opinion evolution influenced by informed agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 431-441.
    5. Bornholdt, Stefan, 2022. "A q-spin Potts model of markets: Gain–loss asymmetry in stock indices as an emergent phenomenon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    6. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    7. Yue Chen & Xiaojian Niu & Yan Zhang, 2019. "Exploring Contrarian Degree in the Trading Behavior of China's Stock Market," Complexity, Hindawi, vol. 2019, pages 1-12, April.
    8. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
    9. Tiwari, Mukesh & Yang, Xiguang & Sen, Surajit, 2021. "Modeling the nonlinear effects of opinion kinematics in elections: A simple Ising model with random field based study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    10. Simon Cramer & Torsten Trimborn, 2019. "Stylized Facts and Agent-Based Modeling," Papers 1912.02684, arXiv.org.
    11. Torsten Trimborn & Philipp Otte & Simon Cramer & Max Beikirch & Emma Pabich & Martin Frank, 2018. "SABCEMM-A Simulator for Agent-Based Computational Economic Market Models," Papers 1801.01811, arXiv.org, revised Oct 2018.
    12. Kei Katahira & Yu Chen & Gaku Hashimoto & Hiroshi Okuda, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Papers 1902.02040, arXiv.org.
    13. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2020. "Robust Mathematical Formulation And Probabilistic Description Of Agent-Based Computational Economic Market Models," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 23(06), pages 1-41, September.
    14. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    15. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2019. "Robust Mathematical Formulation and Probabilistic Description of Agent-Based Computational Economic Market Models," Papers 1904.04951, arXiv.org, revised Mar 2021.
    16. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
    17. Galam, Serge, 2011. "Collective beliefs versus individual inflexibility: The unavoidable biases of a public debate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(17), pages 3036-3054.
    18. Stefan Bornholdt, 2021. "A q-spin Potts model of markets: Gain-loss asymmetry in stock indices as an emergent phenomenon," Papers 2112.06290, arXiv.org.
    19. Katahira, Kei & Chen, Yu & Hashimoto, Gaku & Okuda, Hiroshi, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 503-518.
    20. Ko, Bonggyun & Kim, Kyungwon, 2017. "Simulation of sovereign CDS market based on interaction between market participant," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 324-340.

    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:fininn:v:6:y:2020:i:1:d:10.1186_s40854-020-00211-3. 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.