Bitcoin World Price Forecasting: Time Series Analysis and Machine Learning Approach The ever-growing attention to Cryptocurrencies highlights the demand for higher academic contribution to the subject. Bitcoin is a kind of Cryptocurrencies, which plays a special role in the financial transactions today; hence it is price prediction is of great importance. In recent years, the vast body of research has been devoted to bitcoin # models, but previous research suffers from high prediction errors due to the fluctuations in the price of bitcoin. In this research, we will use SARIMAX, as time series analysis model, XGBOOST, as a gradient method that accelerates model learning by parallelizing decision trees, and Long short-term memory Neural Network Model (LSTM) to predict Bitcoin price between Late 2014 to early 2019. We considered about 20 percent of the data as test data, which LSTM had the best prediction accuracy, R squared of the 98.51 percent for test data
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Bitcoin World Price Forecasting: Time Series Analysis and Machine Learning Approach
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