Short-term Prediction of Bitcoin Price based on Generative Adversarial Network

Moosakhani, M.; Jahangard-Rafsanjani, A.; Zarifzadeh, S.

doi:10.22061/jecei.2024.10760.734

Document Type : Original Research Paper

Authors

Department of Computer Engineering, Faculty of Computer Engineering, Yazd University, Yazd, Iran.

https://doi.org/10.22061/jecei.2024.10760.734

Abstract

Background and Objectives: Investment has become a paramount concern for various individuals, particularly investors, in today's financial landscape. Cryptocurrencies, encompassing various types, hold a unique position among investors, with Bitcoin being the most prominent. Additionally, Bitcoin serves as the foundation for some other cryptocurrencies. Given the critical nature of investment decisions, diverse methods have been employed, ranging from traditional statistical approaches to machine learning and deep learning techniques. However, among these methods, the Generative Adversarial Network (GAN) model has not been utilized in the cryptocurrency market. This article aims to explore the applicability of the GAN model for predicting short-term Bitcoin prices.
Methods: In this article, we employ the GAN model to predict short-term Bitcoin prices. Moreover, Data for this study has been collected from a diverse set of sources, including technical data, fundamental data, technical indicators, as well as additional data such as the number of tweets and Google Trends. In this research, we also evaluate the model's accuracy using the RMSE, MAE and MAPE metrics.
Results: The results obtained from the experiments indicate that the GAN model can be effectively utilized in the cryptocurrency market for short-term price prediction.
Conclusion: In conclusion, the results of this study suggest that the GAN model exhibits promise in predicting short-term prices in the cryptocurrency market, affirming its potential utility within this domain. These insights can provide investors and analysts with enhanced knowledge for making more informed investment decisions, while also paving the way for comparative analyses against alternative models operating in this dynamic field.

Keywords

Main Subjects

Machine Learning

Open Access

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Journal of Electrical and Computer Engineering Innovations (JECEI)

Short-term Prediction of Bitcoin Price based on Generative Adversarial Network

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Volume 12, Issue 2
July 2024
Pages 485-496

Short-term Prediction of Bitcoin Price based on Generative Adversarial Network

References

References

Send comment about this article

Volume 12, Issue 2July 2024Pages 485-496

Volume 12, Issue 2
July 2024
Pages 485-496