The price prediction for cryptocurrency based on the state-of-art machine learning approaches

Ying  Guan

doi:10.54691/bcpbm.v23i.1404

Authors

Ying Guan

DOI:

https://doi.org/10.54691/bcpbm.v23i.1404

Keywords:

Cryptocurrency, machine learning, decision tree, light gradient boosting machine, neural network.

Abstract

Cryptocurrency has evolved from a fringe phenomenon to a far more popular method of investing and financing. For investors and traders, predicting the price of bitcoin is critical. Several machine learning algorithms are utilized to anticipate the price of digital money in this research paper. The analysis employed Decision Trees, Light Gradient Boosting Machines, and Neural Networks. The purpose of this study is to look at the predicted accuracy of each machine learning method. According to the analysis, decision tree, lightGBM, and neural networks have a very high accuracy rate when it comes to forecasting cryptocurrencies. These results shed light on guiding further exploration to help investors in building an appropriate digital currency portfolio and reducing risks.

Downloads

Download data is not yet available.

References

Nakamoto S. Bitcoin: A peer-to-peer electronic cash system[J]. Decentralized Business Review, 2008: 21260.

Coleman, Sara. “Buying a Car with Cryptocurrency 2022.” Bankrate, Information on: https://www.bankrate.com/insurance/car/buying-car-with-crypto/.

Jay P, Kalariya V, Parmar P, et al. Stochastic neural networks for cryptocurrency price prediction[J]. Ieee access, 2020, 8: 82804-82818.

Jaquart P, Dann D, Weinhardt C. Short-term bitcoin market prediction via machine learning[J]. The journal of finance and data science, 2021, 7: 45-66.

Mukhopadhyay U, Skjellum A, Hambolu O, et al. A brief survey of cryptocurrency systems[C]. 2016 14th annual conference on privacy, security and trust (PST). IEEE, 2016: 745-752.

“Bitcoin Historical Prices.” Bitcoin Price Chart and Tables | Finance Reference, Information on: https://www.in2013dollars.com/bitcoin-price.

“Ethereum Price Today, ETH to USD Live, Marketcap and Chart.” CoinMarketCap, Information on: https://coinmarketcap.com/currencies/ethereum/.

“Global Cryptocurrency Market Report 2022-2027 - Industry to Cross a Staggering $32.4 Trillion by 2027, Exploding with a CAGR of 58.4%.” Yahoo! Finance, Yahoo!, Information on: https://finance.yahoo.com/news/global-cryptocurrency-market-report-2022-120800380.html.

Quinlan J R. Induction of decision trees[J]. Machine learning, 1986, 1(1): 81-106.

Ke G, Meng Q, Finley T, et al. Lightgbm: A highly efficient gradient boosting decision tree[J]. Advances in neural information processing systems, 2017, 30.

Dhruv P, Naskar S. Image classification using convolutional neural network (CNN) and recurrent neural network (RNN): A review[J]. Machine Learning and Information Processing, 2020: 367-381.

Mounika S, Yadav P A, Yashaswi T, et al. Crypto-Currency Price Prediction using CNN and LSTM Models[J]. Preprint academia.edu, 2021.

U Raghavendra Swamy, D Rupini, G Shravya, V Akhila. Crypto-Currency Price Prediction Using Machine Learning Techniques [J]. JETIR 2021, 8(6): 2349-5162.

Sun X, Liu M, Sima Z. A novel cryptocurrency price trend forecasting model based on LightGBM[J]. Finance Research Letters, 2020, 32: 101084.