Developed an algorithmic trading model and strategy for the BTC/USDT cryptocurrency market. To create the strategy, historical data from January 1, 2018, to January 31, 2022 was processed with Open, Close, High, Low, Volume at 5 minute intervals to create financial indicators. Then a long short-term memory network (LSTM) model was used to predict prices, and then the predicted prices were utilized in the mean reversion mathematical strategy.
It was observed that the returns generated by the strategy generated 114 percent profits, which outperformed the returns of a simple buy and hold strategy.