Combining two different forms of machine learning is a very exciting concept, especially when it comes to making money. In this case, I combined time series machine learning models with a sentiment analyzer. Two separate forms of machine learning used to create trade signals in the cryptocurrency market. This wasn\u2019t the first time I\u2019ve attempted to do this and it probably won\u2019t be my last.<\/p>\n\n\n\n
In my previous articles, I\u2019ve used Facebook Prophet to forecast Bitcoin prices<\/a> and sentiment analysis on Tweets to predict stock price movement<\/a>. However, I have yet to fuse both of these methods together. But<\/em>, even that statement is not entirely<\/em> true. Recently, I combined Facebook Prophet with sentiment analysis on financial news headlines<\/a>, but not tweets<\/em>. So this time around, I will be experimenting with the slightly altered approach of using tweet sentiment.<\/p>\n\n\n\n Anyways \u2014 let\u2019s dive right in and learn how I backtested a trading strategy using Facebook Prophet and Twitter sentiment analysis! Feel free to code along if you wish, I\u2019ll also provide my code on Github for reference at the end of this article.<\/p>\n\n\n\n