Empirical Study on the Difference in Analyst’ Tendency for earning forecast and Impact on Stock Price by Industry Types

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Empirical Study on the Difference in Analyst’ Tendency for earning forecast and Impact on Stock Price by Industry Types
Choi, Jae Hyung
Kim, Kwanho
Issue Date
Graduate School of UNIST
When analysts forecast the future earnings of a firm, the method used in analyzing and forecasting such a firm differs according to the industry that it participates in due to the various characteristics each industry possesses. This study is motivated by this point. Firstly this study investigates whether the overestimating tendency and forecast accuracy of an analyst are different among industries, as well as running a cross-sectional regression using dummy variables to test the effect of the industry to forecast errors. In addition, this study examines whether there exists difference in stock price impact of analysts according to industry types using CAR for 20 days before and after changing the recommendations. It turned out that there exists a significant difference in the tendency for over-forecast and the accuracy of forecasts of analysts according to each industry. In addition, a tendency for the under-prediction has been identified especially for the Bank Industry. Interestingly even in the same industry, analysts are more likely to overestimate earnings about net income compared to sales and operating profit. Furthermore, in regards to the difference in the influence on the stock price in cases where an analyst changes its target price/investment recommendation, the study has observed a significant difference depending on the industry that an analyst is participating in. At the end of the study, by comparing the results of the influence on stock prices and the accuracy of forecasts of an analyst in the earlier section of this research, it has identified that the industry where an analyst had lower forecasting accuracy showed a lower influence towards the stock price of an analyst. It seems that investors tend not to trust analysts’ who have already presented a relatively less accurate forecast.
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