Due to the volatility of cryptocurrency speculation, investors will often try to incorporate sentiment from social media and news articles to help guide their trading strategies. One such indicator is the Crypto Fear and Greed Index (FNG) which attempts to use a variety of data sources to produce a daily FNG value for cryptocurrency. The Python Notebooks lstm_stock_predictor_closing.ipynb and lstm_stock_predictor_fng contains the deep learning models using both the FNG values and simple closing prices to determine if the FNG indicator provides a better signal for cryptocurrencies than the normal closing price data.
In the notebooks, I used deep learning recurrent neural networks to model bitcoin closing prices. One model used the FNG indicators to predict the closing price while the second model used a window of closing prices to predict the nth closing price.