Affiliation:
1. School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Abstract
Liquidity reflects the quality of the market. When the market is short of liquidity, it often causes investors’ trading difficulties and stock price volatility, expanding the investment risk. As a risk management tool, options attract more informed investors to trade because of their flexible design. To explore whether the implied information based on the formation of option price can predict the liquidity of stock market, we take SSE 50ETF options from February 9, 2015, to December 31, 2020, as the research sample. Based on the idea of data-driven approach, we extract the implied information contained in option price, including implied volatility, implied volatility spread, and variance risk premium. Through the regression analysis method, we examine the ability to predict the liquidity of the stock market. The results show that implied volatility spread has the strongest ability to predict the liquidity of the stock market, and it is more significant within 270 days. Implied volatility contains the information about the short-term (120 days) liquidity of the stock market in the future. It shows that implied volatility and implied volatility spread are good indicators to predict stock market liquidity. In contrast, variance risk premium cannot predict the liquidity of stock market. The research conclusion verifies the role of option-implied information in predicting the stock market’s liquidity. By extracting the information of options price, investors and financial regulators can scientifically participate in the financial market under data guidance.
Funder
National Natural Science Foundation of China-Henan Joint Fund