Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7376588 | Physica A: Statistical Mechanics and its Applications | 2018 | 11 Pages |
Abstract
Forecasting financial market volatility is an important issue in the area of econophysics, and revealing the determinants of the market volatility has drawn much attentions of the academics. In order to better predict market volatilities, we use news-based implied volatility (NVIX) to measure uncertainty, and examine the predictive power of NVIX on the stock market volatility in both long and short-term among Asia-Pacific markets via GARCH-MIDAS model. We find that NVIX does not well explain long-term volatility variants in the full sample period, and it is positively associated with market volatility through a subsample analysis starting from the Financial Crisis. We also find that NVIX is more efficient in determining short-term volatility than the long-term volatility, indicating that the impact of NVIX is short-lived and information that investors concern could be quickly reflected in the stock market volatilities.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Zhi Su, Tong Fang, Libo Yin,