The Impact And Its Influencing Factors Of Sino-US Trade War On Chinese Manufacturing Listed Companies

As China's national strength continues to increase and its economic scale grows,China's trade with other countries is increasingly frequent.In particular,Sino-US trade is developing rapidly,and the trade volume between China and the United States is increasing rapidly.However,the trade balance between China and the United States has also increased year by year,and the trade friction between them has become more frequent and intensified.In recent years,the United States has launched a series of trade protection and sanctions measures against China,such as anti-dumping,countervailing,201 investigation,232 investigation and 301 investigation,especially the US President Trump signed the presidential memorandum on March 22,2018 which said that a large-scale tariff will be imposed on goods imported from China,and the tariffs are mainly for "Made in China 2025".This shows that the United States is trying to suppress the development of China's future high-end technology products to curb China's rise.Starting from this incident,Sino-US trade frictions have escalated into a Sino-US trade war.Therefore,from the perspective of micro-enterprises,this paper studies the impact of Sino-US trade war on the stock price of Chinese manufacturing listed companies and analyzes the influencing factors.This paper applies the event study to the study of the impact of Sino-US trade war on Chinese manufacturing listed companies.The event study is now relatively mature,especially when studying short-term effects.By calculating the abnormal rate of return of China's manufacturing listed companies before and after Trump's announcement of the presidential memorandum(from October 12,2017 to April 10,2018),the event can measure the size of the impact and the direction of influence of different companies from the stock data.When exploring the determinants of different impact status to different companies,in order to find out the representative factors as much as possible,this paper adds many variables to the model,so we need to do variable selection.The stepwise regression method and Lasso regression are used to select the variables respectively,and comparing the results of the two regression.This paper uses literature review method and empirical analysis method,by reading a large number of documents related to Sino-US trade war,I understand and organize the work of domestic and foreign scholars in this area,which deepens the understanding of the issues to be studied.I collected detailed information from existing literature and continued to analyze it on this basis.I collected and compiled the stock data of the listed companies in the manufacturing industry from the CSMAR database.Firstly,I conducted an empirical analysis of the event research method,including parameter estimation,normal and abnormal returns,and the measurement of accumulated abnormal returns,and the statistics of accumulated abnormal returns.Then I established a multiple linear regression model to explore the determinants of the different impacts of Sino-US trade wars on different listed companies.First,we selected variable indicators.Then I do data preprocessing,including descriptive statistical analysis,correlation analysis,and data standardization.Finally,stepwise regression method and Lasso regression were used to select variables and compare their results.Through empirical research,it was found that the United States issued a list of proposed tariffs having a large negative effect on the listed companies in China's related manufacturing industries as a whole on the day of the event,but this negative effect didn't last too long.Through out the window period(-10,10),the cumulative average standardized abnormal rate of return is 0.44%,indicating that the listed company maintains positive performance over the entire window period.When studying the influencing factors of the cumulative average standardized ahnormal rate of return of different companies,I consider indicators including company size,business status,financial indicators,equity concentration,market type,and industry to be used as explanatory variables comprehensively.The variables selected by stepwise regression and Lasso regression are the logarithm of asset size,the logarithm of operating income,the logarithm of total equity,the growth rate of operating income,rate of return on assets and industry.The factors have negative relationship with the accumulated standardized abnormal income of each sample company include the logarithm of asset size,the logarithm of operating income,the logarithm of total equity,and rate of return on assets,while the growth rate of operating income and industry are significantly positive with cumulative standardization Abnormal returns.The empirical results show that the larger the company's listed companies in China's manufacturing companies,the better their operating conditions and the stronger their profitability,the smaller the cumulative average standardized abnormal rate of return.The better the development ability,the smaller the negative impact of the US tariff increase.In addition,the type of industry which the sample company is located in also affects the cumulative average standardized abnormal rate of return.Listed companies in the pharmaceutical manufacturing,railway,marine,aerospace and other transportation equipment manufacturing,ferrous metal smelting and rolling processing industries,and paper and paper products industries are relatively least affected.Finally,for the main conclusions drawn from the empirical research,I made some targeted suggestions for the government and enterprises.