Abstract
In this research, we survey prior findings of how machine learning is used for financial markets. Even though much research related to artificial intelligence has been published, our focus is on recent studies to financial markets with potential applications to blockchain-based cryptocurrencies. In summary, while various machine learning techniques have different focus their focus converges to obtain profit not only to predict future prices. Our summary shows the benefits of using such modeling to account for various financial market phenomena. We conclude that artificial intelligence technique, mainly machine learnings, for financial markets cannot acquire all the aspects of the given data as general artificial intelligence. Accordingly, it is natural to opt for a desirable approach depending on the structure and hierarchy of the dataset. Additionally, the choice of approach relies on the researcher’s view toward the market.
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Notes
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So, we refer multi layers.
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The authors of this research declare that there is no conflict. They are grateful to the Korea Institute of Science and Technology (Economic and Social Science Research Initiative (ESRI) 2E30443, 2V08460 and 2V08950). All remaining errors are solely of the authors’.
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Cho, H., Lee, KH., Kim, C. (2021). Machine Learning and Cryptocurrency in the Financial Markets. In: Choi, P.M.S., Huang, S.H. (eds) Fintech with Artificial Intelligence, Big Data, and Blockchain. Blockchain Technologies. Springer, Singapore. https://doi.org/10.1007/978-981-33-6137-9_13
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