• The Journal of Asian Finance, Economics and Business
• /
• v.1 no.3
• /
• pp.29-36
• /
• 2014

This paper attempts to measure the impact of non-financial factors including analyst practices and broker resources on performance of sell side research. Results reveal that these non-financial factors have a measurable impact on performance of target price forecasts. Number of pages written by an analyst (surrogate for analyst practice) is significantly and directly linked with target price accuracy indicating a more elaborate analyst produces better target price forecasts. Analyst compensation (surrogate for broker resource) is significantly and inversely linked with target price accuracy. Out performance by analysts working with lower paying firms is possibly associated with motivation to migrate to higher paying broking firms. The study finds that employing more number of analysts per research report has no significant impact on target price accuracy -negative coefficient indicates that team work may not result in better target price forecasts. Though insignificant, long term forecast horizon negatively affects target price accuracy while stock volatility improves target price accuracy.

• Korean Journal of Clinical Laboratory Science
• /
• v.53 no.1
• /
• pp.105-121
• /
• 2021

To investigate and accommodate opinions on the revision of the official occupational title of the medical technologist, the Korean Association of Medical Technologists (KAMT) requested 22,638 people registered as its regular members to participate in an online survey and select their two preferred options from the alternative job titles presented. Survey responses were collected from 3,999 people (17.66%). To examine job title preferences among the KAMT members, each respondent was asked to choose two terms from the choice set. As a result, 6,958 responses were obtained, and out of the total responses, 5,555 (79.83%) indicated a choice for a job title that included the word 'analyst' as the preferred alternative. The survey results showed that "Diagnostic Laboratory Analyst" was the most preferred alternative selected by the largest proportion of respondents (2,417 responses, 34.73%), followed by "Clinical Laboratory Analyst" (1,710 responses, 24.57%), "Biomedical Pathology Technologist" (758 responses, 10.89%), "Biomedical Analyst" (730 responses, 10.49%), "Biomedical Laboratory Analyst" (730 responses, 10.03%), and "Clinical Laboratory Scientist" (646 responses, 9.26%). Therefore, based on the responses of the surveyed members, results of consultation and literature review, the Standard Classification of Occupations (SCO), and the current status of the job titles used in major countries, it is suggested that the occupational title of medical technologists should be changed by adopting "Diagnostic Laboratory Analyst", "Biomedical Laboratory Analyst", or "Biomedical Analyst" as their new official job title.

• Journal of Distribution Science
• /
• v.20 no.12
• /
• pp.117-123
• /
• 2022

Purpose: This study investigates the relationship between earnings forecasts estimated from a cross-sectional earnings forecast model and firm characteristics such as firm size, sales volatility, and earnings volatility. Research design, data and methodology: The association between earnings forecasts and the aforementioned firm characteristics is examined using 214 firm-year observations with analyst following and 848 firm-year observations without analyst following for the period of 2011-2019. I estimate future earnings using a cross-sectional earnings forecast model, and then compare these model-based earnings forecasts with analysts' earnings forecasts in terms of forecast bias and forecast accuracy. The earnings forecast bias and accuracy are regressed on firm size, sales volatility, and earnings volatility. Results: For a sample with analyst following, I find that the model-based earnings forecasts are more accurate as the firm size is larger, whereas the analysts' earnings forecasts are less biased and more accurate as the firm size is larger. However, for a sample without analyst following, I find that the model-based earnings forecasts are more pessimistic and less accurate as firms' past earnings are more volatile. Conclusions: Although model-based earnings forecasts are useful for evaluating firms without analyst following, their accuracy depends on the firms' earnings volatility.

• Korea Trade Review
• /
• v.46 no.2
• /
• pp.245-262
• /
• 2021

Despite the numerous advantages that CSR engagement can potentially offer, top managers may not always be willing to invest in CSR as they are expected to meet expectations of external constituents in the short run. Given that financial analysts' expectations are important short-term performance targets that top managers are motivated to meet, this study examines how performance relative to earnings forecasts issued by analysts affect top managers' decisions about CSR engagement. Using a sample of publicly listed U.S. firms from 2000 to 2016, we find that top managers are more likely to reduce discretionary expenditure on CSR activities as performance falls below analyst forecasts to improve financial performance in the following fiscal year. As performance exceeds analyst forecasts, top managers are motivated to reduce CSR investments in order to meet higher expectations of analysts. As financial analysts closely monitor the firms that they follow in order to publish investment advice to market participants, we find that analyst coverage weakens top managers' incentive to reduce CSR engagement. Overall, this research sheds meaningful insight into the contextual background in which the top managers are situated in when they make decisions on CSR engagement.

• The Journal of Industrial Distribution & Business
• /
• v.11 no.1
• /
• pp.39-47
• /
• 2020

Purpose: This study investigated the effects of valuation errors on the capital market through the earnings forecasting errors of financial analysts. As a follow-up to Jensen (2005)'s study, which argued of agency cost of overvaluation, it was intended to analyze the effect of valuation errors on the earnings forecasting behavior of financial analysts. We hypothesized that if the manager tried to explain to the market that their firms are overvalued, the analysts' earnings forecasting errors would decrease. Research design, data and methodology: To this end, the analysis period was set from 2011 to 2018 of KOSPI and KOSDAQ-listed markets. For overvaluation, the study methodology of Rhodes-Kropf, Robinson, and Viswanathan (2005) was measured. The earnings forecasting errors of the financial analyst was measured by the accuracy and bias. Results: Empirical analysis shows that the accuracy and bias of analysts' forecasting errors decrease as overvaluation increase. Second, the negative relationship showed no difference, depending on the size of the auditor. Third, the results have not changed sensitively according to the listed market. Conclusions: Our results indicated that the valuation error lowered the financial analyst earnings forecasting errors. Considering that the greater overvaluation, the higher the compensation and reputation of the manager, it can be interpreted that an active explanation of the market can promote the accuracy of the financial analyst's earnings forecasts. This study has the following contributions when compared to prior research. First, the impact of valuation errors on the capital market was analyzed for the domestic capital market. Second, while there has been no research between valuation error and earnings forecasting by financial analysts, the results of the study suggested that valuation errors reduce financial analyst's earnings forecasting errors. Third, valuation error induced lower the earnings forecasting error of the financial analyst. The greater the valuation error, the greater the management's effort to explain the market more actively. Considering that the greater the error in valuation, the higher the compensation and reputation of the manager, it can be interpreted that an active explanation of the market can promote the accuracy of the financial analyst's earnings forecasts.

• Journal of the Korea Convergence Society
• /
• v.9 no.2
• /
• pp.207-215
• /
• 2018

In this study, targeting KOSPI and KOSDAQ listed companies, the relationship between the abnormal investment of companies and analyst earnings forecasts was empirically analyzed. The analysis period of this study spanned from 2003 to 2015 (with that of dependent variables spanning from 2004 to 2016) based on the variables of interest, and among the companies whose earnings per share forecasts were announced by financial analysts, the final sample of 4,917 companies/year that meets the research condition was selected as the target analysis. The results of the empirical analysis are as follows. First, it turned out that the more total abnormal investment, abnormal R&D and abnormal CAPEX investment, the more accurate were analyst earnings forecasts. Second, the more total abnormal investment, abnormal R&D, abnormal CAPEX investment, the more pessimistic analyst earnings forecasts tended to be. Further analysis has shown that these results came more from over investment groups than under investment groups. The results of this study are expected to make additional contributions to the existing studies in that the abnormal investment is considered as a determinant of analyst earnings forecasts.

• The Korean Journal of Applied Statistics
• /
• v.36 no.5
• /
• pp.489-499
• /
• 2023

As sharing of analyst reports became widely available, reports generated by analysts have become a useful tool to reduce difference in financial information between market participants. The quantitative information of analyst reports has been used in many ways to predict stock returns. However, there are relatively few domestic studies on the prediction power of text information in analyst reports to predict stock returns. We test stock return predictability of text in analyst reports by creating variables representing the TONE from the text. To overcome the limitation of the linear-model-assumption-based approach, we use the random-forest-based F-test.

• Information Systems Review
• /
• v.5 no.1
• /
• pp.49-60
• /
• 2003

The purpose of this study is to empirically and practically verify the applicability of visualization data mining tool in detecting real-word insurance frauds that are now emerged as one of the most serious problems socially and economically. For the verification, Analyst's Notebook by i2, which has been known as the most effective visualization data mining tool, was adopted. With Analyst's Notebook, fraud-probable insurance transactions from a very large insurance claims are selected and then substantiation for insurance frauds are attempted. The results show that Analyst's Notebook not only detects insurance fraud transactions from a vast number of insurance claims, but is also able to pinpoint organized crime group by associating one fraud transaction to another fraud transaction. Therefore, it is safe to conclude that visualization data mining is very effective in detecting false transactions and crime behaviors including insurance fraud.

• International journal of advanced smart convergence
• /
• v.7 no.3
• /
• pp.73-78
• /
• 2018

This study focuses on presenting the IT program module provided by BKLS measure in order to solve the problem of capital cost due to information asymmetry of external investors and corporate executives. Barron at al(1998) set up a BKLS measure to guide the market by intermediate analysts. The BKLS measure was measured by using the changes in the analyst forecast dispersion and analyst mean forecast error squared. This study suggests a model of the algorithm that the BKLS measure can be provided to all investors immediately by IT program in order to deliver the meaningful value in the domestic capital market as measured. This is a method of generating and analyzing real-time or non-real-time prediction models by transferring the predicted estimates delivered to the Big Data Log Analysis System through the statistical DB to the statistical forecasting engine. Because BKLS measure is not carried out in a concrete method, it is practically very difficult to estimate the BKLS measure. It is expected that the BKLS measure of Barron at al(1998) introduced in this study and the model of IT module provided in real time will be the starting point for the follow-up study for the introduction and realization of IT technology in the future.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.8
• /
• pp.647-658
• /
• 2021

Analysts' forecasts are important for providing useful guidance to investors, especially individual or small investors, and therefore it becomes critical to identify the elements which can potentially increase errors in analysts' forecasts. This study investigates potential factors which can lead to errors in forecasting by analysts, specifically in terms of the level and attributes of corporate earnings. Utilizing a sample of firms listed on the Korean stock markets, this study provides evidence that firms with more volatile and unpredictable earnings feature less accurate analyst forecasts. This study fills a void in the literature by conducting empirical tests for earnings attributes in terms of volatility and unpredictability that could potentially undermine the forecast accuracy. The negative association between the quality of earnings and forecast accuracy is more pronounced for firms with negative net income values. Additional analysis demonstrates that forecast accuracy is significantly lower for the fourth quarter than for other fiscal quarters and that fourth quarter earnings tend to be more volatile and unpredictable. This study contributes to the literature by providing new empirical evidence regarding the comprehensive effects of earnings quality and level on analysts' forecasting accuracy and further suggests potential factors contributing to the fourth quarter anomaly in analyst forecasts in terms of earnings attributes.