The Research on the Prediction of Cryptocurrency Based on Linear Regression and LSTM

DOI

10.2991/978-94-6463-102-9_154How to use a DOI?

Keywords

Cryptocurrency; Linear Regression; RNN; LSTM

Abstract

As the growing interest of investment on Cryptocurrencies and the huge volatility of their price, a need for scientific model to predict the future price is growing. In this context, the paper uses linear regression and LSTM model to predict the price of Bitcoin and Ethereum. The result shows that the prediction made by Linear Regression shows less errors but greater lag compared with the prediction made by LSTM method. The lag problem is considered to generate from lack of peripheral information other than previous prices. The prediction implies that the prices of Cryptocurrencies are theoretically predictable, and shows a direction of further research, such as the use of mixed-LSTM model. The methods provided in this paper can be used in development of better models and further investments.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Feng Ding
PY  - 2022
DA  - 2022/12/29
TI  - The Research on the Prediction of Cryptocurrency Based on Linear Regression and LSTM
BT  - Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)
PB  - Atlantis Press
SP  - 1472
EP  - 1481
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-102-9_154
DO  - 10.2991/978-94-6463-102-9_154
ID  - Ding2022
ER  -