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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
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    References listed on IDEAS

    as
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    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. Larissa M. Batrancea & Mehmet Ali Balcı & Ömer Akgüller & Anca Nichita, 2024. "The impact of social media discourse on financial performance of e-commerce companies listed on Borsa Istanbul," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-20, December.
    3. Shang, Dawei & Guo, Ziyu & Wang, Hui, 2024. "Enhancing digital cryptocurrency trading price prediction with an attention-based convolutional and recurrent neural network approach: The case of Ethereum," Finance Research Letters, Elsevier, vol. 67(PB).
    4. 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.
    5. Sharif, Taimur & Ghouli, Jihene & Bouteska, Ahmed & Abedin, Mohammad Zoynul, 2024. "The impact of COVID-19 uncertainties on energy market volatility: Evidence from the US markets," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 25-41.

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