We collected cryptocurrencies (BTC,BCN,DASH,ETH,LTC,XEM,XMR,XRP, etc) data including daily open,close,volume.
We also collected related data which may affect the movement of cryptocurrencies prices. These data include S&P 500 index, Nikkei 225 index, volatility index, US treasury rates, gold and silver price, etc.
We also scraped news from bitcoin.com and bitcoinist.com.
We use classical time series analysis like ARIMA, VARMAX to analysis the time series.
We use NLP to analysis the news.
Finally, we try to combine these numeric features and text features together to build a model based on recurrent neural network, with the aim to predict price movement.
Presentation Material
https://docs.google.com/presentation/d/1MwCHqh3XQdDtTh2ynAH59yQLo1vpJ6_e6ROO1BYBpMA/edit?usp=sharing