The cryptocurrency market is experiencing rapid growth, making it a potentially more lucrative alternative to conventional financial markets. However, this expansion goes hand in hand with significant volatility, thus presenting a crucial challenge. In the context of this master's thesis, time series prediction models for the closing price of Bitcoin were developed using deep learning algorithms such as LSTM and GRU. In addition, a comparison was carried out with traditional models such as ARIMA, with the purpose of analyzing and evaluating their performance.
