IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i21p3964-d952632.html
   My bibliography  Save this article

Network-Induced Soft Sets and Stock Market Applications

Author

Listed:
  • Mehmet Ali Balcı

    (Department of Mathematics, Muğla Sıtkı Koçman University, Muğla 48000, Turkey)

  • Larissa M. Batrancea

    (Department of Business, Babeş-Bolyai University, 7 Horea Street, 400174 Cluj-Napoca, Romania)

  • Ömer Akgüller

    (Department of Mathematics, Muğla Sıtkı Koçman University, Muğla 48000, Turkey)

Abstract

The intricacy of the financial systems reflected in bilateral ties has piqued the interest of many specialists. In this research, we introduce network-induced soft sets, a novel mathematical model for studying the dynamics of a financial stock market with several orders of interaction. To achieve its intelligent parameterization, this model relies on the bilateral connections between economic actors, who are agents in a financial network, rather than relying on any other single feature of the network itself. Our study also introduces recently developed statistical measures for network-induced soft sets and provides an analysis of their application to the study of financial markets. Findings validate the efficacy of this novel method in assessing the effects of various economic stress periods registered in Borsa Istanbul.

Suggested Citation

  • Mehmet Ali Balcı & Larissa M. Batrancea & Ömer Akgüller, 2022. "Network-Induced Soft Sets and Stock Market Applications," Mathematics, MDPI, vol. 10(21), pages 1-24, October.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:21:p:3964-:d:952632
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/21/3964/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/21/3964/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, vol. 6(3), pages 1-19, September.
    2. Areejit Samal & Hirdesh K. Pharasi & Sarath Jyotsna Ramaia & Harish Kannan & Emil Saucan & Jurgen Jost & Anirban Chakraborti, 2020. "Network geometry and market instability," Papers 2009.12335, arXiv.org, revised Jan 2021.
    3. Yongxu Liu & Zhi Zhang & Yan Liu & Yao Zhu, 2022. "GATSMOTE: Improving Imbalanced Node Classification on Graphs via Attention and Homophily," Mathematics, MDPI, vol. 10(11), pages 1-18, May.
    4. Ghous Ali & Musavarah Sarwar, 2021. "Novel Technique for Group Decision-Making under Fuzzy Parameterized - Rung Orthopair Fuzzy Soft Expert Framework," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-22, October.
    5. Mehmet Ali Balcı & Larissa M. Batrancea & Ömer Akgüller & Anca Nichita, 2022. "Coarse Graining on Financial Correlation Networks," Mathematics, MDPI, vol. 10(12), pages 1-16, June.
    6. Gang-Jin Wang & Chi Xie & H. Eugene Stanley, 2018. "Correlation Structure and Evolution of World Stock Markets: Evidence from Pearson and Partial Correlation-Based Networks," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 607-635, March.
    7. Frank Werner, 2020. "Graph-Theoretic Problems and Their New Applications," Mathematics, MDPI, vol. 8(3), pages 1-4, March.
    8. Nicolás Magner & Jaime F. Lavín & Mauricio A. Valle, 2022. "Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach," Mathematics, MDPI, vol. 10(19), pages 1-30, October.
    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. Iraklis Kollias & John Leventides & Vassilios G. Papavassiliou, 2024. "On the solution of games with arbitrary payoffs: An application to an over‐the‐counter financial market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1877-1895, April.
    2. Ömer Akgüller & Mehmet Ali Balcı & Larissa M. Batrancea & Lucian Gaban, 2023. "Path-Based Visibility Graph Kernel and Application for the Borsa Istanbul Stock Network," Mathematics, MDPI, vol. 11(6), pages 1-25, March.

    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. Laleh Tafakori & Armin Pourkhanali & Riccardo Rastelli, 2022. "Measuring systemic risk and contagion in the European financial network," Empirical Economics, Springer, vol. 63(1), pages 345-389, July.
    2. Peng Yue & Qing Cai & Wanfeng Yan & Wei-Xing Zhou, 2020. "Information flow networks of Chinese stock market sectors," Papers 2004.08759, arXiv.org.
    3. Zhu, Xuzhen & Wang, Ruijie & Wang, Zexun & Chen, Xiaolong & Wang, Wei & Cai, Shimin, 2019. "Double-edged sword effect of edge overlap on asymmetrically interacting spreading dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 617-624.
    4. Artur F. Tomeczek & Tomasz M. Napiórkowski, 2024. "PageRank and Regression as a Two-Step Approach to Analysing a Network of Nasdaq Firms During a Recession: Insights from Minimum Spanning Tree Topology," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 56-69.
    5. Baumöhl, Eduard & Shahzad, Syed Jawad Hussain, 2019. "Quantile coherency networks of international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 119-129.
    6. Yudistira Permana & Saiqa Akbar & Anisa Nurpita, 2022. "Systemic risk and the financial network system: an experimental investigation," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 631-651, December.
    7. Lu, Shan & Zhao, Jichang & Wang, Huiwen & Ren, Ruoen, 2018. "Herding boosts too-connected-to-fail risk in stock market of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 945-964.
    8. Zhang, Weiping & Zhuang, Xintian & Wang, Jian & Lu, Yang, 2020. "Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    9. Xue Guo & Hu Zhang & Tianhai Tian, 2019. "Multi-Likelihood Methods for Developing Stock Relationship Networks Using Financial Big Data," Papers 1906.08088, arXiv.org.
    10. Alexander Koch & Toan Luu Duc Huynh & Mei Wang, 2024. "News sentiment and international equity markets during BREXIT period: A textual and connectedness analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 5-34, January.
    11. Duc Thi Luu, 2022. "Portfolio Correlations in the Bank-Firm Credit Market of Japan," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 529-569, August.
    12. Nicoló Andrea Caserini & Paolo Pagnottoni, 2022. "Effective transfer entropy to measure information flows in credit markets," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 729-757, October.
    13. Kiran Sharma & Anindya S. Chakrabarti & Anirban Chakraborti, 2018. "Multi-layered Network Structure: Relationship Between Financial and Macroeconomic Dynamics," Papers 1805.06829, arXiv.org, revised Mar 2019.
    14. Ling, Yu-Xiu & Xie, Chi & Wang, Gang-Jin, 2022. "Interconnectedness between convertible bonds and underlying stocks in the Chinese capital market: A multilayer network perspective," Emerging Markets Review, Elsevier, vol. 52(C).
    15. Erick Treviño Aguilar, 2020. "The interdependency structure in the Mexican stock exchange: A network approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-31, October.
    16. Rigana, Katerina & Wit, Ernst-Jan Camiel & Cook, Samantha, 2023. "A new way of measuring effects of financial crisis on contagion in currency markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    17. Sayantan Banerjee & Kousik Guhathakurta, 2019. "Change-point Analysis in Financial Networks," Papers 1911.05952, arXiv.org.
    18. Katerina Rigana & Ernst-Jan Camiel Wit & Samantha Cook, 2021. "Using Network-based Causal Inference to Detect the Sources of Contagion in the Currency Market," Papers 2112.13127, arXiv.org.
    19. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    20. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, vol. 7(1), pages 1-25, January.

    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:gam:jmathe:v:10:y:2022:i:21:p:3964-:d:952632. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.