IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2401.08077.html
   My bibliography  Save this paper

Transformer-based approach for Ethereum Price Prediction Using Crosscurrency correlation and Sentiment Analysis

Author

Listed:
  • Shubham Singh
  • Mayur Bhat

Abstract

The research delves into the capabilities of a transformer-based neural network for Ethereum cryptocurrency price forecasting. The experiment runs around the hypothesis that cryptocurrency prices are strongly correlated with other cryptocurrencies and the sentiments around the cryptocurrency. The model employs a transformer architecture for several setups from single-feature scenarios to complex configurations incorporating volume, sentiment, and correlated cryptocurrency prices. Despite a smaller dataset and less complex architecture, the transformer model surpasses ANN and MLP counterparts on some parameters. The conclusion presents a hypothesis on the illusion of causality in cryptocurrency price movements driven by sentiments.

Suggested Citation

  • Shubham Singh & Mayur Bhat, 2024. "Transformer-based approach for Ethereum Price Prediction Using Crosscurrency correlation and Sentiment Analysis," Papers 2401.08077, arXiv.org.
    • Handle: RePEc:arx:papers:2401.08077
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2401.08077
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dimitrios Koutmos, 2023. "Investor sentiment and bitcoin prices," Review of Quantitative Finance and Accounting, Springer, vol. 60(1), pages 1-29, January.
    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. A. H. Nzokem, 2023. "Bitcoin versus S&P 500 Index: Return and Risk Analysis," Papers 2310.02436, arXiv.org.
    2. Arun Narayanasamy & Humnath Panta & Rohit Agarwal, 2023. "Relations among Bitcoin Futures, Bitcoin Spot, Investor Attention, and Sentiment," JRFM, MDPI, vol. 16(11), pages 1-24, November.
    3. Dimitrios Koutmos & Wang Chun Wei, 2023. "Nowcasting bitcoin’s crash risk with order imbalance," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 125-154, July.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2401.08077. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.