Research On Stock Market Liquidity Prediction Based On Option Market Informatio

Liquidity reflects the quality of the market.When the market lacks liquidity,it often causes problems such as investors’ trading difficulties and stock price fluctuations.At this time,if investors can obtain future stock liquidity information,it will help them make timely decisions and avoid systemic risks.As a risk management tool,option has attracted investors with more information to trade because of its flexible design,and its information content is often forwardlooking.Therefore,it is important for investors to study stock liquidity from the perspective of option market information to prevent liquidity risk.This paper takes the earliest listed stock index option in China as an example——SSE 50 ETF option.It comprehensively uses complex network model and regression model,and starts with the transaction information easily obtained in the market and the implicit information extracted through the model,respectively,to explore the information content of the stock liquidity contained in the option market.This is helpful to better understand the transmission,linkage and prediction of cross-market information between the stock market and the option market in the context of China’s financial market.The specific empirical thinking is as follows: First,examine the information content of trading information in the option market.Using complex network technology to construct a network of options trading volume,positions,and stock liquidity,we verify whether there is a close correlation between trading volume,positions,and stock liquidity changes by studying the similarity of network topology characteristics;On this basis,a regression model is further used to empirically test the ability of options trading volume and positions to predict stock market liquidity.The results show that for the component stocks of the 50 ETF option target,the option trading information contains information about the future liquidity of the target stock,and has significantly positive predictive power.Among them,the trading volume indicator is superior to the position indicator,while both the call and put options have predictive power,but the predictive power varies.The trading volume and position of the put option are superior to the call option.After further subdividing the degree of value and maturity of options,it is found that the prediction ability of the trading indicators of virtual options is higher than that of real and flat values,while the prediction ability of long-term options is better than that of short-term and medium-term options.After verifying the liquidity information of the entire A-share market,it was found that the option trading information did not reflect the prediction ability.Further,unlike trading information obtained directly from the option market,implicit information extracted from the market through models and formulas is not easily recognized by public investors,and therefore contains more abundant information.Therefore,this article uses regression analysis to examine the predictive ability of option prices to A-share market liquidity by extracting implicit information,including implied volatility,implied skewness,implied volatility spread,and variance risk premium.The research finds that the implied volatility difference has the strongest prediction ability for stock market liquidity,and the implied volatility and skewness also contain information about the future short-term liquidity of the stock market;In addition,the Dstat function is introduced to examine the accuracy of option implicit information on the trend of liquidity fluctuations outside the sample,and the results show that the prediction effect is good;The empirical results show that implied volatility,implied skewness,and implied volatility difference are good indicators for predicting stock market liquidity.Relevant research conclusions have verified the role of option market information in predicting the liquidity of the stock market,and compared with the intuitive trading information,the extracted option implicit information is more abundant in information content.So investors should learn more option knowledge and tap the potential information content in the option market can make the investment behavior more scientific.