Furthermore, regarding the difference in share price impact when an analyst changes their target price/investment recommendation, the study noted a significant difference depending on the industry in which the analyst is involved. By comparing the results of stock price impact and analyst forecast accuracy in the earlier part of this research, the study found that the industry where the analyst had lower forecast accuracy showed less impact on the analyst's stock price.
Introduction
At the end of this research, based on the results obtained, the correlation between the influence of each analyst and stocks with high forecast accuracy will be discussed. Most of the previously published research tends to focus on the accuracy and benefit of forecasting performance according to the characteristics of each analyst.
Literature Reviews
In a similar vein, Kim and Eum (2009) conduct an empirical analysis of the difference between forecast accuracy and analysts' stock price impact according to the location of a firm's head office under analysis. In other words, an empirical analysis will be conducted by comparing the differences in the impact on the stock price and the accuracy of the analysts' forecasts as well as to investigate the causes of the results.
DATA
On the other hand, regarding the management of an investment fund, Coval and Moskowits (2001) showed that fund managers invest more in the companies that are geographically closer by analyzing the roles of an investment company's geographical proximity to describe the negative correlation between information gathering cost and geographic proximity. In this particular research, it will focus on the differences in the trends of prediction projected by analysts according to the characteristics of a company under audit.
Classification of Industries
As for financial businesses, it excessively includes companies involved in the securities industry, the banking industry and the insurance industry, which would defeat the main purpose of the study. Consequently, in this research, the processing industry and the financial industry will be excluded from the 22 industry categories, so only 20 industries will be included as subjects for analysis.
Sample Population
To select the analysis report for the accounting year t, the reports published in the period between April of the year t and March of the year t+1.4 are selected. However, for financial businesses and some other companies that settled accounts in March tend to present the performance of year t around June of year t+1, therefore, this research has selected the accounting income forecast published from July i of the year t until June of the year t+1 as a research subject according to standard (5).
Hypotheses and Methodology
In addition, the absolute value of the previously used value of prediction error is used for the accuracy of prediction. If there is a significant difference between the accuracy of forecasts and the tendency to forecast of each industry, then there must be a difference in the level of reliance of market participants on the information provided by analysts. In the end, such a difference will be interpreted in relation to the trend of a forecast made by analysts.
Before anything else, this particular hypothesis will examine the impact on the stock price of analysts for each industry using CAR for 20 days before and after the date on which the target price or investment recommendation of an analyst changes as for the event study. It showed that when the target price was rising, market participants took a different position than the movements in the market. Furthermore, it was confirmed that the analyst's changes in target price or investment recommendation in certain industries could become the factor to provide distorted information.
To summarize the results of the analysis, firstly, depending on the company's activities, differences were found in the tendency to overpredict and the accuracy of the forecast. Finally, the comparison between the analyst's forecast trends and the CAR results based on the changes in the target price or investment recommendation, which were the two aforementioned factors for the analysis, showed that the sectors that analysts tend to overestimate showed more in comparison with other sectors. which was the opposite of the investment recommendation. It is speculated that in these industries, the analyst's changes in price target or investment recommendation are recognized by investors as distorted information.
To generalize the trend of overforecasting and the forecasting error among industries, there is an empirical analysis of the market with more diversity as in the case of the United States. Given that the studies on analyst forecasting trends previously focused mainly on analyst characteristics, this research could be thought of as the experimental approach.
Result of analysis
Results of analysis on the difference in forecast error and the
In the transportation and storage sector, sales are often very volatile depending on economic conditions, such as in the airline or passenger sector. Therefore, it is possible that the prediction error could be very large. On the other hand, it was found that the largest forecast error regarding operating profit was observed in the chemical, paper and wood, and transportation storage industries. Therefore, Hypothesis 2-1, which states that in case of changes in the target price or investment recommendation, a significant difference would be observed in the impact on stock prices between the sectors, is partially supported.
The findings, as shown in
