| dc.description.abstract | Over the last couple of years, Bitcoin cryptocurrency and the Blockchain technology that forms the basis of Bitcoin have witnessed a flood of attention. In contrast to fiat currencies used worldwide, the Bitcoin distributed ledger is publicly available by design. This facilitates observing all financial interactions on the network, and analyzing how the network evolves in time. Furthermore, we assess the role of chainlets on Bitcoin price formation and dynamics by forecasting its price. We can exhibit the highest predictive influence on Bitcoin price and investment risk. This thesis is concerned with predicting the price of Bitcoin using machine learning. The goal is to ascertain with what accuracy can the direction of Bitcoin price in USD can be predicted. The price data is sourced from the Bitcoin Price Index . The task is achieved with varying degrees of success through the implementation of a machine learning logistic regression and Long Short Term Memory (LSTM) network. The LSTM achieves the highest classification..... The popular ARIMA model for time series forecasting is implemented as a comparison to the machine learning and deep learning models.
Keywords: ARIMA, machine learning, deep learning, linear regression, long short-term memory. | en_US |
