Design And Application Of Stock Volatility Index Based On Big-Data Strategy

This paper mainly focus on the quantification of investor emotion and social mood using Big-Data-Strategy with internet data and information from social network, while the base of the quantification lies on the former research from in and abroad. Big Data Volatility Index(BDVI) was built to forecast the fluctuation tendency of Shanghai Composite Index, Shanghai Exchange volume, iVix and other financial indicator through Granger test and coefficiency test in order to avoid heavy losses especially in the slump. Since BDVI established three essential indicators— Investor Emotion Big Data Search indicator, Social-Network Emotion Sector, Emotion indicator of Social-Network Search from mass internet data to composite the BDVI,it is of importance in making attempt to quantify the investor emotion without collecting the information from the active shares options exchange market as well as its speed and volume. BDVI is mainly built to help forecast the fluctuation tendency in the near future, and is recommended use with other indicators such as Shanghai Composite Index and Shanghai Exchange volume, and it could be of great use in predicting the fall shape in comparison to the rise shape, and the research in this domain of quantifying market and investor emotion for forecasting future risk in financial market and has been proved of great predictive ability of financial market indicators. As is proved in this paper, BDVI based on the investor emotion extracted from the social network greatly predict the fluctration of stock market, especially the declining movement. While the predict comes 1 or 2 days before the downward of the market, thus has great use in the predicting of market votility and have considerable potential application possibility for risk aversion in the future.