ICTACT Journal on Soft Computing

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Automated Cryptocurrencies Prices Prediction Using Machine Learning


Affiliations
1 Division of Computer Engineering, Netaji Subhas Institute of Technology, India
2 Division of Computer Engineering, Netaji Subhas Institute of Technology
     

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Currently, Cryptocurrency is one of the trending areas of research among researchers. Many researchers may analyze the cryptocurrency features in several ways such as market price prediction, the impact of cryptocurrency in real life and so on. In this paper, we focus on market price prediction of the number of cryptocurrencies based on their historical trend. For our study, we tried to understand and identify the daily trends in the cryptocurrency market which analyzing the features related to the price of cryptocurrency. Our dataset consists of over nine features relating to the cryptocurrency price recorded daily over the period of 6 months. We applied some machine-learning algorithms to predict the daily price change of cryptocurrencies.

Keywords

Cryptocurrency, Bitcoin, Decentralization, Network, Price Prediction.
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Abstract Views: 330

PDF Views: 2




  • Automated Cryptocurrencies Prices Prediction Using Machine Learning

Abstract Views: 330  |  PDF Views: 2

Authors

Ruchi Mittal
Division of Computer Engineering, Netaji Subhas Institute of Technology, India
Shefali Arora
Division of Computer Engineering, Netaji Subhas Institute of Technology, India
M. P. S Bhatia
Division of Computer Engineering, Netaji Subhas Institute of Technology

Abstract


Currently, Cryptocurrency is one of the trending areas of research among researchers. Many researchers may analyze the cryptocurrency features in several ways such as market price prediction, the impact of cryptocurrency in real life and so on. In this paper, we focus on market price prediction of the number of cryptocurrencies based on their historical trend. For our study, we tried to understand and identify the daily trends in the cryptocurrency market which analyzing the features related to the price of cryptocurrency. Our dataset consists of over nine features relating to the cryptocurrency price recorded daily over the period of 6 months. We applied some machine-learning algorithms to predict the daily price change of cryptocurrencies.

Keywords


Cryptocurrency, Bitcoin, Decentralization, Network, Price Prediction.

References