The Construction Of News-Driven Monetary Policy Volatility Spillover Statistical Indicators

With the development of the times,data information has become a strategic resource,and it is very important for investors to identify the effective information in the massive information in the correct way.This study constructs a news-driven statistical indicator of monetary policy volatility spillovers,conducts social network analysis of the indicator,and further explores the impact of monetary policy volatility spillovers on fixed asset investment.Firstly,this study crawled news text data about monetary policy from news information websites,calculated the effective information index of monetary policy in each region,and constructed a news-driven monetary policy volatility spillover network.The characteristics of the network;Next,the difference method is used to construct the fixed asset investment matrix,and the QAP method is used to explore the relationship between the matrices.Finally,the following conclusions are drawn:Firstly,the news-driven effective information of monetary policy has a volatility spillover effect between different regions.The network has good accessibility,and the spatial characteristics of the network will also change with time;second,geographic location will have an impact on the similarity between fixed asset investments in different regions.The smaller the difference in fixed asset investment between the two,and the stronger the similarity in space;third,the volatility spillover of news-driven monetary policy effective information will have an impact on the difference in fixed asset investment,such as in the first During the period,when there is a volatility spillover effect of effective monetary policy information between the two places,the difference in fixed asset investment between the two places will be smaller,and there will be stronger similarity in space.Through the method of machine learning,this paper extracts the monetary policy effective information index from the complicated monetary policy news text information,which provides a new idea for local governments to effectively use computer science and technology methods to study policy news information.