Forecasting Stock Market with Social Media Sentiment Based on Adaptive Network Fuzzy Inference System

The Adaptive Neuro Fuzzy Inference System (ANFIS), based on fuzzy inference system, describes the process of human logical reasoning by establishing a number of fuzzy rules. It has a good ability to deal with uncertain and imprecise systems and is suitable for application in stock market forecasting. In this paper, the model inputs are chosen based on multiple feature combinations with multiple experiments, and social media is added as part of the features. Gaussian membership function was selected as the main constraint and triangle function was the result optimizer. The experiments using data from both social media and stock markets—the Sina Weibo and the Shanghai Stock Market—to train and evaluate the change in trend for the next trading day, with the ‘‘buy and hold” strategy and several other timing trading strategies. The empirical results show that our proposed method outperforms the ANFIS with only technical index as input.