Forecasting Bitcoin Price Movements Using Neural Networks: A Time Series Approach
The extreme volatility and pronounced non-stationarity of cryptocurrency prices challenge traditional time-series models and motivate the use of deep learning. This thesis addresses three focused research questions: (i) Do gated recurrent neural networks (GRNNs) produce more accurate one-day-ahead Bitcoin return predictions than feedforward neural networks and linear benchmarks? (ii) Can a GRNN ba
