A Comprehensive Survey of Cryptocurrency Forecasting: Methods, Trends, and Challenges

  1. Mahmood Yousaf
  2. Muhammad Tariq
  3. Abdul Jabbar
  4. Syed Qaisar Jalil

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Abstract

This comprehensive review paper explores the diverse landscape of cryptocurrency forecasting, tracing its evolution from an alternative to traditional monetary systems to its significant growth in the global financial arena. It consolidates existing research by categorizing and analyzing 234 scholarly articles, organizing them into machine learning, deep learning, deep reinforcement learning, and statistical methodologies, and evaluating the related metrics. The case study titled “Examining the performance differences between backtesting and forward testing” highlights the challenges investors face, as strategies that appear effective in backtesting often fail in practical use. Another case study, “Social Data Exploration in Cryptocurrency Trends,” examines how social media data can provide insights into market movements and investor sentiment, revealing the impact of social trends on cryptocurrency prices. The findings section provides a detailed view, illuminating trends such as yearly publication rates, methodological distributions, input features, training/testing splits, the total number of data samples considered, and forecasting time horizons. This survey paper serves as a valuable resource, providing researchers and investors with a solid foundation for understanding and navigating the dynamic field of cryptocurrency forecasting.

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  1. PREreview

    This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/17379656.

    Does the introduction explain the objective of the research presented in the preprint? Yes
    Are the methods well-suited for this research? Highly appropriate
    Are the conclusions supported by the data? Highly supported
    Are the data presentations, including visualizations, well-suited to represent the data? Highly appropriate and clear
    How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Very clearly
    Is the preprint likely to advance academic knowledge? Highly likely
    Would it benefit from language editing? No
    Would you recommend this preprint to others? Yes, it's of high quality
    Is it ready for attention from an editor, publisher or broader audience? Yes, as it is

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they did not use generative AI to come up with new ideas for their review.

  2. Version published to 10.20944/preprints202411.2330.v2
  3. Version published to 10.20944/preprints202411.2330.v1