Research On The Impact Of Listed Companies' Own Factors On The Accuracy Of Securities Analysts' Earnings Forecasts

As a bridge between listing Corporations and investors, securities analysts play an important role in the capital markets, They use professional knowledge and skills to analyze the financial and non-financial information they collected from listing Corporations, and then issue earnings forecasts and investment advice to investors, help investors to make sound investment decisions. Securities analysts' earnings forecast information is an important accounting information, It meets the needs of investors in the interpretation of information, to a certain extent, it also alleviates the problem of information asymmetry in capital market, Improve the efficiency of resource allocation. Therefore, it has very important practical significance to study the accuracy of the securities analysts' earnings forecast.Many factors affect the accuracy of securities analysts' earnings forecasts, experts and scholars at home and abroad divide these factors into the listing Corporation's own factors, securities analysts' personal factors and external environmental factors, One of the most important is the listing Corporation's own factors. In this paper, author only studies in the impact of the listing Corporation's own factors on the accuracy of the securities analysts' earnings forecast.On the basis of summarizing the research status quo at home and abroad, this paper divide the listing Corporation's own factors into three dimensions, they are Corporate features, information disclosure and corporate governance, each dimension is selected a few variables. Choosing the Shenzhen Stock Exchange A-share board listing companies'data from 2011 to 2014 as the sample, using multiple linear regression model to test whether the various variables have a significant impact on the accuracy of the securities analysts' earnings forecasts.First of all, this paper has the sample firstly round's test to verify which variables have significant impacts on the earnings forecast accuracy, Then remove the variables which has multi collinearity, build the optimized regression model. Next, having the samples packet inspection to compare the impact of each variables on Securities analyst earnings forecast at different forecast tendencies, different industries, besides, figure out the variation tendency on the prediction accuracy in the long period time. Finally, according to the conclusions of this paper, the author put forward relevant proposals in order to change securities analysts' attitudes and behavior, Improve the accuracy of securities analysts' earnings forecast, reduce investors' investment risk, improve capital market efficiency.