Cryptocurrencies such as bitcoin have garnered a lot of attention in recent months due to their meteoric rise. In this paper, we propose a new method for predicting the direction of bitcoin price using linear discriminant analysis (LDA) together with sentiment analysis. Concretely, we train an LDA-based classifier that uses the current bitcoin price information and Twitter headline news in order to forecast the next-day direction of bitcoin price. The proposed model achieves highly accurate results beating several benchmark targets. In particular, the proposed approach produces forecast accuracy of 0.828 and AUC of 0.840 on the test data.

The proposed method using linear discriminant analysis and sentiment analysis effectively predicts bitcoin price direction, with a forecast accuracy of 0.828 and AUC of 0.840 on test data.

Paper

Bitcoin Price Forecasting: Linear Discriminant Analysis with Sentiment Evaluation

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