Abstract
Cryptocurrencies are becoming a major moneymaker because of their high availability and abundance of easy investment platforms. In this paper, we have attempted to predict bitcoin value by taking into consideration various features that may affect its price. The amount of cryptocurrency in circulation, the volume of cryptocurrency exchanged in a day and the demand for cryptocurrency are a few of the factors that influence its cost. The forecasting is done using different time series analysis techniques like moving average, ARIMA and machine learning algorithms including SVM, linear regression, LSTM and GRU. Our goal is to compare all these models based on their observed accuracy. The dataset has been recorded daily over the course of three years.
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Gupta, A., Nain, H. (2021). Bitcoin Price Prediction Using Time Series Analysis and Machine Learning Techniques. In: Joshi, A., Khosravy, M., Gupta, N. (eds) Machine Learning for Predictive Analysis. Lecture Notes in Networks and Systems, vol 141. Springer, Singapore. https://doi.org/10.1007/978-981-15-7106-0_54
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DOI: https://doi.org/10.1007/978-981-15-7106-0_54
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