EVALUATING THE PERFORMANCE OF BITCOIN PRICE FORECASTING USING MACHINE LEARNING TECHNIQUES ON HISTORICAL DATA

Since entering the market in 2009, Bitcoin has had a price that is extremely erratic. Its price is influenced by factors such as adoption rates, regulatory changes, geopolitical occurrences, and macroeconomic developments. Experts believe that Bitcoin's price will rise in the long run due to limited supply and rising demand. Therefore, the aim of this study is to propose an ensemble feature selection and machine learning-based approach to predict bitcoin price. For this research purpose, the cryptocurrency-based dataset has been used, visualized, and preprocessed. Five different feature selection approaches (Pearson, RFE, Embedded Random Forest, Tree-based and Light GBM) are followed by ensemble methodology, with the maximum voting approach to extract the most significant features and generate a dataset with reduced…