The influence of stock market indexes (S&P500 and Dow Jones) on cryptocurrencies prices

Abstract

In this paper we analyze openly available time series data for the prices of 18 cryptocurrencies and 2 stock market indexes (S&P500 and Dow Jones). First, we calculate the correlation values between the cryptocurrencies and indexes datasets. Then, we use a state of the art time series prediction library (XGBoost) in order to make prediction models for the daily prices of all the cryptocurrencies, using the stock market index datasets as input features in the training model. We calculate metrics for the difference between the actual prices and the prices predicted using our models. Finally, we show the feature importance score that our model attributed to each prediction model, and compare the score between the three input features (S&P500 dataset, Dow Jones dataset, and the actual cryptocurrency dataset).