| This paper mainly studies the relationship between the open-ended equity fund yield rate and eight fund variables. These variables include rate, net asset value, the fund family scale, the fund age, net fund flow, the fund’s holdings concentration, fund turnover rate and the fund’s past performance. This article utilizes two modules to analysis the fund yield rate. In the model I conclude that the turnover is significantly negative under the significance level of 1%.The frequent trade not only have no corresponding benefits, it do harm to yield growth. Rate is significantly negative under 1% significance level, this conclusion is different from previous Chinese scholars’research results.It confirmed there have be problems in the Chinese fund rate setting.High yield rate not only donnot give the corresponding incentive, but brought the negative growth rate. Lag earning is positive under 5% significance level. It means that funds has certain continuity feature. It also shows that China’s stock market is not effective. Fund age is positive at 1% significance level, that means that old funds can use their own brand or human’s ability than new funds. Net inflows is negative in the 5% significance level, that is to say, the net inflow does not bring high profits.It may be that the Chinese fund managers donnot have good ability in the selection of the stock When face large capital inflows,they donnot seize the opportunity to invest.Jaffe and Mandelker (1974) proposed calendar time regression methods to analysis the fund yield rate.However, this method is only suitable for studying two cross-sectional data. It lose effect when the variables are multivariate. Dahlquist (2000) invented the two-stage regression model to improve the former’s deficiencies. The model is divided into two steps.In the first step analysis the relationship between fundyields rate and Fama and French three-factor model factors or the factor model factor in the time series regression.In the second step,analysis the relationship between the alpha and the fund variables. Finally, I in the panel data model analyze the correlation between yields rate and the fund variables. Driscoll and Kraay (2000) pointed out that when there is a cross-sectional correlation, the above model will lead to the results are not convincing because of ignoring information. Therefore, this article uses the module that Hoechle (2012) proposed.It is called generalized calendar time regression model (I referred to as GCT model).It is used to analysis the fund yields rate and Fama and French three-factor model factors or the factor model factor and fund variables. GCT model solves the problem of the above model, and it use the DK standard error.The innovation of this paper is that it provides a comprehensive method to study the correlation between funds yields and the funds variables in the panel data model. In the past it mainly judged the effects through a significant t value of statistical results, and most of the empirical analysis is based on simple linear regression and a basic white standard error. But it is necessary to analyze the methodology based on different criteria because the error cannot reflect the real situation when the residual is related to the time factors or the cross-section factors. White standard errors are no longer reliable results.DK standard error can guarantee the result is convincing when there is cross-sectional correlation, heteroscedasticity or the serial correlation.I hope to provide a reference to help investors in investment.This paper is divided into five parts:The first part introduces the research background, methods and meaning for the open-ended equity fund yields rate and discuss the main innovation of this article.The second part I analyze and summarize the domestic and foreign scholars on the research on the open-end funds yield rate.I provide a general framework for the development about the research.The third part describes the data sources and the methods of the two models.I also explain some special variables.The fourth part is the main part of this paper.I introduce the two classic models to study the Chinese open-end fund yield rate. Then I analysis the differences for the two modules. I can conclude some results by comparing the different significantly difference.In the fifth part of this paper I summarize the main viewpoints and analyze the shortcomings of the paper. I hope to provide a reference to help investors in investment. |
