IDEAS home Printed from https://ideas.repec.org/a/ibn/ijefaa/v16y2024i11p41.html
   My bibliography  Save this article

Evaluating the Significance of the Total Value Locked to Market Capitalization Ratio

Author

Listed:
  • Konstantinos Pantelidis
  • Ioannis Karakostas

Abstract

This study investigates the impact of the total value locked to market capitalization (T/M) ratio on the returns of four major cryptocurrencies, using daily data spanning from March 2021 to June 2024. Employing a GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model, the analysis reveals a significant negative relationship between the T/M returns and the returns of the corresponding cryptocurrency. In contrast, the T/M ratio differences of peer tokens exhibit a positive relation with the returns of the analyzed cryptocurrency. These findings suggest that the T/M ratio dynamics are crucial in influencing token performance, offering new insights into the interconnected behavior of digital assets within the broader cryptocurrency market.

Suggested Citation

  • Konstantinos Pantelidis & Ioannis Karakostas, 2024. "Evaluating the Significance of the Total Value Locked to Market Capitalization Ratio," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 16(11), pages 1-41, November.
    • Handle: RePEc:ibn:ijefaa:v:16:y:2024:i:11:p:41
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/ijef/article/download/0/0/50786/55044
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/ijef/article/view/0/50786
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Maouchi, Youcef & Charfeddine, Lanouar & El Montasser, Ghassen, 2022. "Understanding digital bubbles amidst the COVID-19 pandemic: Evidence from DeFi and NFTs," Finance Research Letters, Elsevier, vol. 47(PA).
    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. Lei, Heng & Xue, Minggao & Ye, Jing, 2024. "The nexus between ReFi, carbon, fossil energy, and clean energy assets: Quantile time–frequency connectedness and portfolio implications," Energy Economics, Elsevier, vol. 132(C).
    2. Assaf, Ata & Demir, Ender & Ersan, Oguz, 2024. "Detecting and date-stamping bubbles in fan tokens," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 98-113.
    3. Ali, Shoaib & Al-Nassar, Nassar S. & Naveed, Muhammad, 2024. "Bridging the gap: Uncovering static and dynamic relationships between digital assets and BRICS equity markets," Global Finance Journal, Elsevier, vol. 60(C).
    4. Xu, Guiyang & Li, Guanggui & Sun, Peibo & Peng, Dan, 2023. "Inefficient investment and digital transformation: What is the role of financing constraints?," Finance Research Letters, Elsevier, vol. 51(C).
    5. Cevik, Emrah Ismail & Gunay, Samet & Zafar, Muhammad Wasif & Destek, Mehmet Akif & Bugan, Mehmet Fatih & Tuna, Fatih, 2022. "The impact of digital finance on the natural resource market: Evidence from DeFi, oil, and gold," Resources Policy, Elsevier, vol. 79(C).
    6. Dimitriadis, Konstantinos A. & Koursaros, Demetris & Savva, Christos S., 2024. "Evaluating the sophisticated digital assets and cryptocurrencies capacities of substituting international currencies in inflationary eras," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    7. Liu, Jiatong & Zhu, You & Wang, Gang-Jin & Xie, Chi & Wang, Qilin, 2024. "Risk contagion of NFT: A time-frequency risk spillover perspective in the Carbon-NFT-Stock system," Finance Research Letters, Elsevier, vol. 59(C).
    8. Yang, Hui & Ferrer, Román, 2023. "Explosive behavior in the Chinese stock market: A sectoral analysis," Pacific-Basin Finance Journal, Elsevier, vol. 81(C).
    9. Ozge Camalan & Sahika Gokmen & Sibel Atan, 2024. "Using Advanced Machine Learning Techniques to Predict the Sales Volume of Non-Fungible Tokens," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 10(1), pages 17-27, June.
    10. Dominik Metelski & Janusz Sobieraj, 2022. "Decentralized Finance (DeFi) Projects: A Study of Key Performance Indicators in Terms of DeFi Protocols’ Valuations," IJFS, MDPI, vol. 10(4), pages 1-23, November.
    11. Botond Benedek & Bálint Zsolt Nagy, 2025. "Asymmetries in factors influencing non-fungible tokens’ (NFTs) returns," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-20, December.
    12. Eray Gemici & Muslum Polat & Remzi Gök & Muhammad Asif Khan & Mohammed Arshad Khan & Yunus Kilic, 2023. "Do Bubbles in the Bitcoin Market Impact Stock Markets? Evidence From 10 Major Stock Markets," SAGE Open, , vol. 13(2), pages 21582440231, June.
    13. Lennart Ante & Aman Saggu, 2025. "Time-Varying Bidirectional Causal Relationships Between Transaction Fees and Economic Activity of Subsystems Utilizing the Ethereum Blockchain Network," Papers 2501.05299, arXiv.org.
    14. Qiao, Xingzhi & Zhu, Huiming & Tang, Yiding & Peng, Cheng, 2023. "Time-frequency extreme risk spillover network of cryptocurrency coins, DeFi tokens and NFTs," Finance Research Letters, Elsevier, vol. 51(C).
    15. Wu, Zewen, 2024. "Are we in a bubble? Financial vulnerabilities in semiconductor, Web3, and genetic engineering markets," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 32-44.
    16. Wang, Yizhi, 2022. "Volatility spillovers across NFTs news attention and financial markets," International Review of Financial Analysis, Elsevier, vol. 83(C).
    17. Qin, Meng & Mirza, Nawazish & Su, Chi-Wei & Umar, Muhammad, 2023. "Exploring Bubbles in the Digital Economy: The Case of China," Global Finance Journal, Elsevier, vol. 57(C).
    18. Mamidala, Vasanthi & Kumari, Pooja, 2023. "Investigating herding severity in different NFT categories," Finance Research Letters, Elsevier, vol. 58(PB).
    19. Chowdhury, Md Shahedur R. & Damianov, Damian S., 2024. "Uncertainty and bubbles in cryptocurrencies: Evidence from newly developed uncertainty indices," International Review of Financial Analysis, Elsevier, vol. 91(C).
    20. Foglia, Matteo & Maci, Giampiero & Pacelli, Vincenzo, 2024. "FinTech and fan tokens: Understanding the risks spillover of digital asset investment," Research in International Business and Finance, Elsevier, vol. 68(C).

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:ibn:ijefaa:v:16:y:2024:i:11:p:41. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.