IDEAS home Printed from https://ideas.repec.org/a/abq/ijist1/v6y2024i7p22-31.html

Volatility Prediction in Cryptocurrency UsingNFTs

Author

Listed:
  • Saeed Arshad

    (FAST-NUCES Lahore campus)

Abstract

The cryptocurrency market has evolved in unprecedented ways over the past decade. However, due to the high price volatility associated with cryptocurrencies, predicting their prices remains an attractive research topic. While many researchers have focused on predicting cryptocurrency prices, there has been relatively little attention given to the latest trend in blockchain applications, specifically non-fungible tokens (NFTs). In this study, we have prepared a dataset comprising NFT sales and transaction data, along with information from other cryptocurrencies. This dataset is utilized to forecast the future price of Bitcoin using several machineslearning models, including Linear Regression, Random Forest, and XGBoost. The results highlight the prediction accuracy of these models. Among the three, the Random Forest regressor demonstrates the highest accuracy, followed closely by the XGBoost regressor and Linear Regression. These findings may assist investors in making informed decisions when investing in cryptocurrencies.

Suggested Citation

  • Saeed Arshad, 2024. "Volatility Prediction in Cryptocurrency UsingNFTs," International Journal of Innovations in Science & Technology, 50sea, vol. 6(7), pages 22-31, October.
    • Handle: RePEc:abq:ijist1:v:6:y:2024:i:7:p:22-31
    as

    Download full text from publisher

    File URL: https://journal.50sea.com/index.php/IJIST/article/view/1079/1630
    Download Restriction: no
    File URL: https://journal.50sea.com/index.php/IJIST/article/view/1079
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Maaz Mahadi & Tarig Ballal & Muhammad Moinuddin & Tareq Y. Al-Naffouri & Ubaid Al-Saggaf, 2022. "Portfolio Optimization Using a Consistent Vector-Based MSE Estimation Approach," Papers 2204.05611, arXiv.org.
    2. Hemendra Gupta & Rashmi Chaudhary, 2022. "An Empirical Study of Volatility in Cryptocurrency Market," JRFM, MDPI, vol. 15(11), pages 1-14, November.
    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. Vladyslav Koltun & Ivan P. Yamshchikov, 2023. "Pump It: Twitter Sentiment Analysis for Cryptocurrency Price Prediction," Risks, MDPI, vol. 11(9), pages 1-14, September.
    2. Mengzhong Ma & Te Bao & Yonggang Wen, 2026. "One Rising Ship Sinks Other Ships: Cross-Chain Negative Spillovers in Crypto Markets," Papers 2602.23762, arXiv.org.
    3. A. Jagdish Mohan Rao & K. G. K. Patnaik & P. Srinivas & M. V. K. Srinivas Rao & A. V. N. Murty, 2026. "Cryptocurrency investments: an empirical analysis of risk and return trends in the contemporary financial landscape," Quality & Quantity: International Journal of Methodology, Springer, vol. 60(1), pages 1923-1949, February.
    4. Kong, Manyu & Zhang, Shunqi, 2026. "Global stock market systemic risk and the asymmetric transmission to Bitcoin’s tail dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 684(C).
    5. Kundan Mukhia & Anish Rai & SR Luwang & Md Nurujjaman & Sushovan Majhi & Chittaranjan Hens, 2024. "Complex network analysis of cryptocurrency market during crashes," Papers 2405.05642, arXiv.org.
    6. Zhang, Shunqi & Xu, Qiuhua & Ding, Xuerou & Han, Kefei, 2025. "Risk spillover between cryptocurrencies and traditional currencies: An analysis based on neural network quantile regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 667(C).
    7. Tomas Peciulis & Asta Vasiliauskaite, 2025. "Advanced GARCH Specifications for Cryptocurrency Volatility Incorporating Asymmetry, Regime-Switching, and Long-Memory Effects," Virtual Economics, The London Academy of Science and Business, vol. 8(2), pages 124-150, July.
    8. Kundan Mukhia & SR Luwang & Md. Nurujjaman & Tanujit Chakraborty & Suman Saha & Chittaranjan Hens, 2025. "Universal Patterns in the Blockchain: Analysis of EOAs and Smart Contracts in ERC20 Token Networks," Papers 2508.04671, arXiv.org.
    9. Mukhia, Kundan & Rai, Anish & Luwang, S.R. & Nurujjaman, Md & Majhi, Sushovan & Hens, Chittaranjan, 2024. "Complex network analysis of cryptocurrency market during crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 653(C).
    10. Hemendra Gupta & Rashmi Chaudhary, 2023. "An Analysis of Volatility and Risk-Adjusted Returns of ESG Indices in Developed and Emerging Economies," Risks, MDPI, vol. 11(10), pages 1-18, October.
    11. Çağlar SÖZEN, 2025. "Volatility dynamics of cryptocurrencies: a comparative analysis using GARCH-family models," Future Business Journal, Springer, vol. 11(1), pages 1-12, December.
    12. Vandana Dangi, 2025. "Cryptocurrency Implied Volatility as a Driver of the Interlinkages Across Cryptocurrencies’ Returns: A Wavelet Analysis," Vikalpa: The Journal for Decision Makers, , vol. 50(4), pages 322-350, December.
    13. Alejandro Rodriguez Dominguez & Muhammad Shahzad & Xia Hong, 2025. "Multi-Hypothesis Prediction for Portfolio Optimization: A Structured Ensemble Learning Approach to Risk Diversification," Papers 2501.03919, arXiv.org, revised May 2025.
    14. Kristína Okasová & Michal Géci & Kristián Košťál, 2026. "Predicting Arbitrage Occurrences With Machine Learning and Improved Decision Threshold Level in Live‐Trading Crypto Environments," International Journal of Network Management, John Wiley & Sons, vol. 36(1), January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:abq:ijist1:v:6:y:2024:i:7:p:22-31. 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: Iqra Nazeer (email available below). General contact details of provider: .

    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.