IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v680y2025ics037843712500665x.html

Network transitions in the cryptocurrency market: The impact of regional conflicts

Author

Listed:
  • Zhang, Yuanyuan
  • Chan, Stephen
  • Lord, Nicholas
  • Chu, Jeffrey
  • Yang, Hanfang
  • Chandrashekhar, Durga
  • Liao, Xin
  • Li, Qin

Abstract

This paper analyses the evolution of the cryptocurrency market network structure during two recent military conflicts: the first year of the 2022 Russia–Ukraine war and the first six months of the 2023 Israel–Hamas war, compared with pre-war periods. Analysing data covering the two periods of 1st January 2020 to 31st December 2022 (Russia–Ukraine), and 1st September 2022 to 29th February 2024 (Israel–Hamas), our findings reveal that before both wars officially began, the cryptocurrency network exhibited high interconnectedness, possibly due to investors anticipating conflict and shifting investments into cryptocurrencies. After the conflicts started, the network became significantly disconnected, with the Russia–Ukraine war showing a “small world” effect, where larger cryptocurrencies remained interconnected, while smaller cryptocurrencies became disconnected. In contrast, during the Israel–Hamas conflict, larger cryptocurrencies became more disconnected, driving overall network disconnectivity. Further analysis using the TVP-SV-VAR model showed that macroeconomic variables such as geopolitical risk, the U.S. Dollar Index, oil volatility and gold returns, as well as the Google Trend Index had a significant impact on the network’s structure, with varying effects across conflicts. Geopolitical risk exerted a stronger positive influence on centrality measures during the Israel–Hamas conflict, the Dollar index had a sharp negative effect on centrality following the Russia–Ukraine war, and oil volatility consistently enhanced network centrality and density in both conflicts. Gold returns shifted from having a negative to a positive effect on network connectivity, especially boosting intermediary roles during the Israel Hamas conflict, and the Google Trend Index consistently increased network centrality, highlighting the impact of rising market attention and sentiment. These results are crucial for understanding how military conflicts and economic factors impact cryptocurrency networks, providing valuable insights for academics, investors, policymakers, and legal authorities on market efficiency, risk management, and the potential use of blockchain-based assets in evading sanctions and facilitating cybercrime. As both conflicts are ongoing, future research should focus on analysing extended war periods and the influence of regulatory actions, sanctions, and cryptocurrency-specific events.

Suggested Citation

  • Zhang, Yuanyuan & Chan, Stephen & Lord, Nicholas & Chu, Jeffrey & Yang, Hanfang & Chandrashekhar, Durga & Liao, Xin & Li, Qin, 2025. "Network transitions in the cryptocurrency market: The impact of regional conflicts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 680(C).
    • Handle: RePEc:eee:phsmap:v:680:y:2025:i:c:s037843712500665x
    DOI: 10.1016/j.physa.2025.131013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843712500665X
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2025.131013?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    2. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    3. Cui, Jinxin & Maghyereh, Aktham, 2024. "Unveiling interconnectedness: Exploring higher-order moments among energy, precious metals, industrial metals, and agricultural commodities in the context of geopolitical risks and systemic stress," Journal of Commodity Markets, Elsevier, vol. 33(C).
    4. Castelnuovo, Efrem & Tran, Trung Duc, 2017. "Google It Up! A Google Trends-based Uncertainty index for the United States and Australia," Economics Letters, Elsevier, vol. 161(C), pages 149-153.
    5. Gang-Jin Wang & Chi Xie & Shou Chen, 2017. "Multiscale correlation networks analysis of the US stock market: a wavelet analysis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(3), pages 561-594, October.
    6. Kakinaka, Shinji & Umeno, Ken, 2022. "Cryptocurrency market efficiency in short- and long-term horizons during COVID-19: An asymmetric multifractal analysis approach," Finance Research Letters, Elsevier, vol. 46(PA).
    7. Gambarelli, Luca & Marchi, Gianluca & Muzzioli, Silvia, 2023. "Hedging effectiveness of cryptocurrencies in the European stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    8. Boungou, Whelsy & Yatié, Alhonita, 2022. "The impact of the Ukraine–Russia war on world stock market returns," Economics Letters, Elsevier, vol. 215(C).
    9. Wang, Gang-Jin & Xie, Chi, 2015. "Correlation structure and dynamics of international real estate securities markets: A network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 176-193.
    10. Reza Tajaddini & Hassan F. Gholipour, 2023. "Trade dependence and stock market reaction to the Russia‐Ukraine war," International Review of Finance, International Review of Finance Ltd., vol. 23(3), pages 680-691, September.
    11. Gaio, Luiz Eduardo & Stefanelli, Nelson Oliveira & Pimenta, Tabajara & Bonacim, Carlos Alberto Grespan & Gatsios, Rafael Confetti, 2022. "The impact of the Russia-Ukraine conflict on market efficiency: Evidence for the developed stock market," Finance Research Letters, Elsevier, vol. 50(C).
    12. Umar, Zaghum & Polat, Onur & Choi, Sun-Yong & Teplova, Tamara, 2022. "Dynamic connectedness between non-fungible tokens, decentralized finance, and conventional financial assets in a time-frequency framework," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    13. Yousaf, Imran & Patel, Ritesh & Yarovaya, Larisa, 2022. "The reaction of G20+ stock markets to the Russia–Ukraine conflict “black-swan” event: Evidence from event study approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 35(C).
    14. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    15. Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Herding behaviour in cryptocurrencies," Finance Research Letters, Elsevier, vol. 29(C), pages 216-221.
    16. Aaron Clauset & Cristopher Moore & M. E. J. Newman, 2008. "Hierarchical structure and the prediction of missing links in networks," Nature, Nature, vol. 453(7191), pages 98-101, May.
    17. Raddant, Matthias & Kenett, Dror Y., 2021. "Interconnectedness in the global financial market," Journal of International Money and Finance, Elsevier, vol. 110(C).
    18. 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.
    19. Feng-hai Zhang & Xiao-wei Ma & Wei-hua Yang & Yue-kui Xu, 2013. "An Empirical Study on the Relationships Between Entrepreneur and SMEs’ Vitality," Springer Books, in: Ershi Qi & Jiang Shen & Runliang Dou (ed.), The 19th International Conference on Industrial Engineering and Engineering Management, edition 127, chapter 0, pages 1443-1451, Springer.
    20. Goodell, John W. & Yadav, Miklesh Prasad & Ruan, Junhu & Abedin, Mohammad Zoynul & Malhotra, Nidhi, 2023. "Traditional assets, digital assets and renewable energy: Investigating connectedness during COVID-19 and the Russia-Ukraine war," Finance Research Letters, Elsevier, vol. 58(PA).
    21. Tse, Chi K. & Liu, Jing & Lau, Francis C.M., 2010. "A network perspective of the stock market," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 659-667, September.
    22. Esmaeilpour Moghadam, Hadi & Mohammadi, Teymour & Feghhi Kashani, Mohammad & Shakeri, Abbas, 2019. "Complex networks analysis in Iran stock market: The application of centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    23. Cui, Jinxin & Maghyereh, Aktham, 2024. "Higher-order moment risk spillovers across various financial and commodity markets: Insights from the Israeli–Palestinian conflict," Finance Research Letters, Elsevier, vol. 59(C).
    24. Giuseppe Buccheri & Stefano Marmi & Rosario N. Mantegna, 2013. "Evolution of correlation structure of industrial indices of US equity markets," Papers 1306.4769, arXiv.org.
    25. Yao, Juan & Ma, Chuanchan & He, William Peng, 2014. "Investor herding behaviour of Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 12-29.
    26. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    27. Papana, Angeliki & Kyrtsou, Catherine & Kugiumtzis, Dimitris & Diks, Cees, 2017. "Financial networks based on Granger causality: A case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 65-73.
    28. Nobi, Ashadun & Maeng, Seong Eun & Ha, Gyeong Gyun & Lee, Jae Woo, 2014. "Effects of global financial crisis on network structure in a local stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 135-143.
    29. Khalfaoui, Rabeh & Gozgor, Giray & Goodell, John W., 2023. "Impact of Russia-Ukraine war attention on cryptocurrency: Evidence from quantile dependence analysis," Finance Research Letters, Elsevier, vol. 52(C).
    30. Vidal-Tomás, David, 2021. "Transitions in the cryptocurrency market during the COVID-19 pandemic: A network analysis," Finance Research Letters, Elsevier, vol. 43(C).
    31. Kumar, Sanjeev & Patel, Ritesh & Iqbal, Najaf & Gubareva, Mariya, 2023. "Interconnectivity among cryptocurrencies, NFTs, and DeFi: Evidence from the Russia-Ukraine conflict," The North American Journal of Economics and Finance, Elsevier, vol. 68(C).
    32. Mensi, Walid & El Khoury, Rim & Ali, Syed Riaz Mahmood & Vo, Xuan Vinh & Kang, Sang Hoon, 2023. "Quantile dependencies and connectedness between the gold and cryptocurrency markets: Effects of the COVID-19 crisis," Research in International Business and Finance, Elsevier, vol. 65(C).
    33. Boginski, Vladimir & Butenko, Sergiy & Pardalos, Panos M., 2005. "Statistical analysis of financial networks," Computational Statistics & Data Analysis, Elsevier, vol. 48(2), pages 431-443, February.
    34. Aslanidis, Nektarios & Bariviera, Aurelio F. & López, Óscar G., 2022. "The link between cryptocurrencies and Google Trends attention," Finance Research Letters, Elsevier, vol. 47(PA).
    35. Marco Del Negro & Giorgio E. Primiceri, 2015. "Time Varying Structural Vector Autoregressions and Monetary Policy: A Corrigendum," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1342-1345.
    36. Chortane, Sana Gaied & Pandey, Dharen Kumar, 2022. "Does the Russia-Ukraine war lead to currency asymmetries? A US dollar tale," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    37. Mnif, Emna & Jarboui, Anis & Mouakhar, Khaireddine, 2020. "How the cryptocurrency market has performed during COVID 19? A multifractal analysis," Finance Research Letters, Elsevier, vol. 36(C).
    38. Boufateh, Talel & Saadaoui, Zied, 2021. "The time-varying responses of financial intermediation and inflation to oil supply and demand shocks in the US: Evidence from Bayesian TVP-SVAR-SV approach," Energy Economics, Elsevier, vol. 102(C).
    39. Hu, Guoheng & Liu, Shan & Wu, Guo & Hu, Peng & Li, Ruiqi & Chen, Liujie, 2023. "Economic policy uncertainty, geopolitical risks, and the heterogeneity of commodity price fluctuations in China ——an empirical study based on TVP-SV-VAR model," Resources Policy, Elsevier, vol. 85(PA).
    40. Naeem, Muhammad Abubakr & Bouri, Elie & Peng, Zhe & Shahzad, Syed Jawad Hussain & Vo, Xuan Vinh, 2021. "Asymmetric efficiency of cryptocurrencies during COVID19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    41. Fernandes, Leonardo H.S. & Bouri, Elie & Silva, José W.L. & Bejan, Lucian & de Araujo, Fernando H.A., 2022. "The resilience of cryptocurrency market efficiency to COVID-19 shock," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    42. Parisa Foroutan & Salim Lahmiri, 2024. "Connectedness of cryptocurrency markets to crude oil and gold: an analysis of the effect of COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-23, December.
    43. Yousaf, Imran & Yarovaya, Larisa, 2022. "Herding behavior in conventional cryptocurrency market, non-fungible tokens, and DeFi assets," Finance Research Letters, Elsevier, vol. 50(C).
    44. Yousaf, Imran & Riaz, Yasir & Goodell, John W., 2023. "Energy cryptocurrencies: Assessing connectedness with other asset classes," Finance Research Letters, Elsevier, vol. 52(C).
    45. Thomas R Hurd & James P Gleeson & Sergey Melnik, 2017. "A framework for analyzing contagion in assortative banking networks," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-20, February.
    46. Santorsola, Marco & Caferra, Rocco & Morone, Andrea, 2022. "The financial repercussions of military escalation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    47. Martins, António Miguel, 2024. "Global equity, commodities and bond market response to Israel-Hamas war," Finance Research Letters, Elsevier, vol. 67(PB).
    48. Lin, Zi-Luo & Ouyang, Wen-Pei & Yu, Qing-Rui, 2024. "Risk spillover effects of the Israel–Hamas War on global financial and commodity markets: A time–frequency and network analysis," Finance Research Letters, Elsevier, vol. 66(C).
    49. Koch, Sophia & Dimpfl, Thomas, 2023. "Attention and retail investor herding in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 51(C).
    50. Będowska-Sójka, Barbara & Demir, Ender & Zaremba, Adam, 2022. "Hedging Geopolitical Risks with Different Asset Classes: A Focus on the Russian Invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
    51. Vidal-Tomás, David & Ibáñez, Ana M. & Farinós, José E., 2019. "Herding in the cryptocurrency market: CSSD and CSAD approaches," Finance Research Letters, Elsevier, vol. 30(C), pages 181-186.
    52. Choudhry, Taufiq, 2010. "World War II events and the Dow Jones industrial index," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 1022-1031, May.
    53. Hudson, Robert & Urquhart, Andrew, 2015. "War and stock markets: The effect of World War Two on the British stock market," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 166-177.
    54. Hudson, Robert & Urquhart, Andrew, 2022. "Naval disasters, world war two and the British stock market," Research in International Business and Finance, Elsevier, vol. 59(C).
    55. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2018. "Collective behavior of cryptocurrency price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 499-509.
    56. Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Petropoulou, Athina & Sivaprasad, Sheeja, 2023. "The impact of the Russian-Ukrainian war on global financial markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    57. Gupta, Naveen & Singh, Anurag & Cherifi, Hocine, 2016. "Centrality measures for networks with community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 46-59.
    58. Mark D Humphries & Kevin Gurney, 2008. "Network ‘Small-World-Ness’: A Quantitative Method for Determining Canonical Network Equivalence," PLOS ONE, Public Library of Science, vol. 3(4), pages 1-10, April.
    59. Larissa M. Batrancea & Ömer Akgüller & Mehmet Ali Balcı & Anca Nichita, 2024. "Financial network communities and methodological insights: a case study for Borsa Istanbul Sustainability Index," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-27, December.
    60. Enilov, Martin & Mishra, Tapas, 2023. "Gold and the herd of Cryptos: Saving oil in blurry times," Energy Economics, Elsevier, vol. 122(C).
    61. E. Mnif & A. Jarboui & K. Mouakhar, 2020. "How the Cryptocurrency Market Has Performed during COVID 19? A Multifractal Analysis," Post-Print hal-04457136, HAL.
    62. Foued Hamouda & Imran Yousaf & Muhammad Abubakr Naeem, 2024. "Exploring the Dynamics of Equity and Cryptocurrency Markets: Fresh Evidence from the Russia–Ukraine War," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3555-3576, December.
    63. Ballis, Antonis & Drakos, Konstantinos, 2020. "Testing for herding in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 33(C).
    64. Patel, Ritesh & Kumar, Sanjeev & Bouri, Elie & Iqbal, Najaf, 2023. "Spillovers between green and dirty cryptocurrencies and socially responsible investments around the war in Ukraine," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 143-162.
    65. Thomas A. Lubik & Christian Matthes, 2015. "Time-Varying Parameter Vector Autoregressions: Specification, Estimation, and an Application," Economic Quarterly, Federal Reserve Bank of Richmond, issue 4Q, pages 323-352.
    66. Chen, Yuxuan & Chiu, Junmao & Chung, Huimin & Lien, Donald, 2024. "Bitcoin market connectedness across political uncertainty," International Review of Economics & Finance, Elsevier, vol. 96(PA).
    67. Heiberger, Raphael H., 2014. "Stock network stability in times of crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 376-381.
    68. Caferra, Rocco & Vidal-Tomás, David, 2021. "Who raised from the abyss? A comparison between cryptocurrency and stock market dynamics during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 43(C).
    69. E Brigatti & V Rocha Grecco & A R Hernández & M A Bertella, 2023. "Inferring interactions in multispecies communities: The cryptocurrency market case," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-16, September.
    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. Shroff, Sumita & Agrawal, Nidhi & Paliwal, Udai Lal & Yadav, Miklesh Prasad, 2025. "How do selected asset classes react to sudden shocks? Evidence from Israel-Hamas conflict using Event Study approach," Research in International Business and Finance, Elsevier, vol. 75(C).
    2. Vidal-Tomás, David, 2021. "Transitions in the cryptocurrency market during the COVID-19 pandemic: A network analysis," Finance Research Letters, Elsevier, vol. 43(C).
    3. Abakah, Emmanuel Joel Aikins & Adeabah, David & Tiwari, Aviral Kumar & Abdullah, Mohammad, 2023. "Effect of Russia–Ukraine war sentiment on blockchain and FinTech stocks," International Review of Financial Analysis, Elsevier, vol. 90(C).
    4. Wanidwaranan, Phasin & Wongkantarakorn, Jutamas & Padungsaksawasdi, Chaiyuth, 2025. "Geopolitical risk, herd behavior, and cryptocurrency market," The North American Journal of Economics and Finance, Elsevier, vol. 80(C).
    5. Silva, Thiago Christiano & Wilhelm, Paulo Victor Berri & Tabak, Benjamin Miranda, 2023. "Trade matters except to war neighbors: The international stock market reaction to 2022 Russia’s invasion of Ukraine," Research in International Business and Finance, Elsevier, vol. 65(C).
    6. Chishti, Muhammad Zubair & Khalid, Ali Awais & Sana, Moniba, 2023. "Conflict vs sustainability of global energy, agricultural and metal markets: A lesson from Ukraine-Russia war," Resources Policy, Elsevier, vol. 84(C).
    7. Hosseini, Seyed Soheil & Wormald, Nick & Tian, Tianhai, 2021. "A Weight-based Information Filtration Algorithm for Stock-correlation Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    8. Abakah, Emmanuel Joel Aikins & Abdullah, Mohammad & Tiwari, Aviral Kumar & Wali Ullah, G M, 2024. "Asymmetric dynamics between geopolitical conflict sentiment and cryptomarkets," Research in International Business and Finance, Elsevier, vol. 69(C).
    9. Umar, Zaghum & Bossman, Ahmed & Choi, Sun-Yong & Vo, Xuan Vinh, 2023. "Are short stocks susceptible to geopolitical shocks? Time-Frequency evidence from the Russian-Ukrainian conflict," Finance Research Letters, Elsevier, vol. 52(C).
    10. Mbarek, Marouene & Msolli, Badreddine, 2025. "Tokens and cryptocurrencies: Evidence from asymmetric frequency connectedness approach," Research in International Business and Finance, Elsevier, vol. 77(PA).
    11. Khan, Nasir & Mejri, Sami & Hammoudeh, Shawkat, 2024. "How do global commodities react to increasing geopolitical risks? New insights into the Russia-Ukraine and Palestine-Israel conflicts," Energy Economics, Elsevier, vol. 138(C).
    12. Bijoy Chandra Das & Fakhrul Hasan & Soma Rani Sutradhar & Sujana Shafique, 2023. "Ukraine–Russia Conflict and Stock Markets Reactions in Europe," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(3), pages 395-407, September.
    13. Xiaoyang, Xu & Ali, Shoaib & Naveed, Muhammad, 2024. "Artificial intelligence and big data tokens: Where cognition unites, herding patterns take flight," Research in International Business and Finance, Elsevier, vol. 72(PA).
    14. Mirzat Ullah, 2025. "Risk and return analysis between digital and conventional financial assets in a turbulent geopolitical environment," Digital Finance, Springer, vol. 7(3), pages 479-505, September.
    15. Mbarek, Marouene & Msolli, Badreddine, 2025. "Assessing linkages between supply chain tokens and other assets: Evidence from a time-frequency quantile connectedness approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 46(C).
    16. An Pham Ngoc Nguyen & Martin Crane & Thomas Conlon & Marija Bezbradica, 2025. "Herding unmasked: Insights into cryptocurrencies, stocks and US ETFs," PLOS ONE, Public Library of Science, vol. 20(2), pages 1-49, February.
    17. Seyed Soheil Hosseini & Nick Wormald & Tianhai Tian, 2019. "A Weight-based Information Filtration Algorithm for Stock-Correlation Networks," Papers 1904.06007, arXiv.org.
    18. Huan Qing & Xiaofei Xu, 2025. "Finding Core Balanced Modules in Statistically Validated Stock Networks," Papers 2508.04970, arXiv.org, revised Apr 2026.
    19. Ijaz, Muhammad Shahzad & Ali, Shoaib & Du, Anna Min & Khurram, Mahrukh, 2025. "Analyzing financial market reactions to the Palestine-Israel conflict: An event study perspective," International Review of Economics & Finance, Elsevier, vol. 98(C).
    20. Soliman, Alain & Le Saout, Erwan, 2024. "The impact of the war in Ukraine on the idiosyncratic risk and the market risk," Finance Research Letters, Elsevier, vol. 60(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G40 - Financial Economics - - Behavioral Finance - - - General
    • H56 - Public Economics - - National Government Expenditures and Related Policies - - - National Security and War

    Statistics

    Access and download statistics

    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:eee:phsmap:v:680:y:2025:i:c:s037843712500665x. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.