Multiple Regression Model Of Open-end Fund And Stock Market Volatility

With the development of global financial markets, the open-end fund has occupied anirreplaceable dominant position in the financial markets. Fund industry is a “sunriseindustry” in China, which has a huge space for development and is the main force in thesecondary market. It can effectively guide the direction of market investment and thusplays a very important demonstration effect for other investors. However, in recent years,with the reform of China’s financial system and the deepening of capital markets, manyproblems are appeared, which has enlarged the volatility of Chinese stock market.Therefore, for the sake of financial investors, how to reduce the risk and maximize thebenefit is the most concerned issue. This makes it important to analyze the impact ofopen-end fund on the stock market volatility.Firstly, this thesis outlines the background, the definition, the development status, therecent research as well as the impact of open-end fund on the stock market volatility andsome research achievement at home and abroad. Secondly, the thesis introduces a multipleregression model and a multiple stepwise regression which eliminates multicollinearityproblem during the modeling. Finally, by combining all the factors based on unilateral ones,selecting the data from2004to2011in Shanghai Composite Index and ShenzhenComposite Index and using EViews5.0software to do multiple stepwise regressionanalysis, a multiple regression model of volatility factors on Shanghai stock market andShenzhen stock market is achieved.The model results and the empirical analysis show that the positive influence of theopen-end fund’s herd behavior, the inner capital flow rate and the net redemption rate onthe stock market volatility is striking, whilst the influence of the lag period of volatility ismilder and the concentration on stocks is the least.