Predicting the Price of Bitcoin, Dogecoin and Ethereum by Machine Learning

Authors

  • Siyi Liao

DOI:

https://doi.org/10.54691/bcpbm.v38i.4312

Keywords:

Cryptocurrency; machine learning; prediction of price.

Abstract

Contemporarily, blockchains and cryptocurrencies have gained their popularity among investors and hedge funder, where both have bright prospects. On this basis, cryptocurrencies have been used in trading more and more with the development of website and computer. In this case, their prices fluctuations do have great significance to the public. This paper chooses three machine learning model (i.e., XGBoost, LightGBM and Linear Model) to predict the price of three cryptocurrencies (i.e., Bitcoin, Dogecoin and Ethereum). To be specific, this study uses the data from 2020-01-01 to 2022-12-07, including close price, open price, high price, low price, and the volume of trading coins. According to the analysis, Linear Model can predict the price best, with well-fitted trend prediction and accurate price prediction. In addition, other models can also have good predictions but they are not better than Linear model. These results can help others to predict the price of cryptocurrencies and have a deep understanding of cryptocurrency and machine learning.

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References

Diffie W, Hellman M. New directions in cryptography. IEEE Transactions on Information Theory, 1976, 22(6):644-654

Lamport L. The part-time parliament. ACM Transactions on Computer Systems, 1998, 16(2):133-169.

Cao M, Celik B. Valuation of bitcoin options. Journal of Futures Markets,2021, 41(7): 1007-1026.

Hal F. Reusable Proofs of Work. 2004, Retrieved from https://nakamotoinstitute.org/finney/rpow/.

Vitalik B. A next-generation smart contract and decentralized application platform. 2013 Retrieved from: https://github.com/Ethereum/wiki/wiki/White-Paper, 2013.

Haber S, Stornetta W S. How to Time-Stamp a Digital Document. Journal of Cryptology, 1991, 3(2).

Madan S S, Zhao A. Automated Bitcoin trading via machine learning algorithms. Dept. Comput. Sci., Stanford Univ., Stanford, CA, USA, Tech. Rep., 2015.

Fischer T, Krauss C. Deep learning with long short-term memory networks for financial market predictions. European Journal of Operational Research, 2017.

Valencia F, Gómez-Espinosa A, Valdés-Aguirre B. Price Movement Prediction of Cryptocurrencies Using Sentiment Analysis and Machine Learning. Entropy, 2019, 21(6): 589.

Utami S D, Saleh A A, Nuning K, et al. Forecasting Historical Data of Bitcoin using ARIMA and α-Sutte Indicator. Journal of Physics: Conference Series, 2018, 1028:012194.

Jang H, Lee J. An Empirical Study on Modeling and Prediction of Bitcoin Prices With Bayesian Neural Networks Based on Blockchain Information. IEEE Access, 2018, 6: 5427-5437.

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Published

2023-03-02

How to Cite

Liao, S. (2023). Predicting the Price of Bitcoin, Dogecoin and Ethereum by Machine Learning. BCP Business & Management, 38, 3389-3395. https://doi.org/10.54691/bcpbm.v38i.4312