A Quantitative Analysis of S&P 500 VIX Futures Return and Volatility Based on Public News Sentiment

The relationship between return and information flow as well as the relationship between return volatility and information flow are currently of growing interest to investors and academics. This study offers fresh evidence through sentiment analysis of the S&P 500 VIX futures index in the United States. The main objective of the research is to use news sentiment as a proxy for information flow with the help of natural language processing (NLP). The data are drawn from 9194 pieces of VIX-relevant news collected from 283 public news websites. The study uses a nonlinear framework for the threshold regression and GJR-GARCH (1,1) to analyze the empirical process. The evidence obtained indicates the following: First, VIX futures are aligned with the efficient market hypothesis (EMH), so information flow does not affect the long-term return. Second, the short-term impact of information flow on VIX futures returns is inefficient, and COVID-19 leads to abnormal returns. Third, negative news negatively influences return volatility on the contemporaneous trading day, which is consistent with MDH. Positive news has a one to three trading-day lag on positive return volatility, which is compatible with SIAH