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ZUO, Meng (2020) An Empirical Study on the Influencing Factors of Accuracy of Chinese Securities Analysts’ Earnings Forecasts. [Dissertation (University of Nottingham only)]

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Abstract

Based on the external environment and personal characteristics of financial analysts, this research explores the influence of analysts’ own factors on the accuracy of earnings and provides theoretical basis and empirical evidence for how to improve the accuracy of analysts’ earnings forecasts. This paper takes the earnings forecast deviation as the research content and reviews the relevant research on earnings forecast. The review found that researchers all found that the earnings forecast report of securities analysts was valuable and tried to explain this finding through the characteristics of listed companies and the motivation of analysts' own interests. This study defines the concept of securities analysts and their earnings forecasts, using the 2016-2019 earnings per share forecast data of A-share listed companies by Chinese securities analysts as samples to study the accuracy of Chinese securities analysts’ earnings forecasts. Starting from the analyst's own factors, using the empirical research method of multiple regression to study the factors affecting the accuracy of the securities analyst's earnings forecast. The research results show that there are certain errors in the earnings forecasts of Chinese securities analysts, and there is a clear tendency to optimistic estimates. In addition, analyst optimism, securities company size, analyst reputation, and forecast days are significantly negatively correlated with analysts’ earnings forecast accuracy. The forecasting experience of analysts is significantly positively correlated with the accuracy of analysts’ earnings forecasts, while factors such as analyst gender and the number of analysts’ forecasts have insignificant correlations with forecast accuracy.

Key words: Securities analyst Earnings forecast Accuracy

Item Type:	Dissertation (University of Nottingham only)
Depositing User:	ZUO, MENG
Date Deposited:	13 Dec 2022 15:45
Last Modified:	13 Dec 2022 15:45
URI:	https://eprints.nottingham.ac.uk/id/eprint/61567

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