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

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

• Korea Trade Review
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• v.46 no.2
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• pp.245-262
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• 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 Asian Finance, Economics and Business
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• v.8 no.8
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• pp.647-658
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• 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.

• Journal of the Korea Convergence Society
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• v.9 no.2
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• pp.207-215
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• 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 Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.45-54
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• 2019

This study examines whether auditors restrain the analysts' opportunistic behavior as reviewing the companies' interim reports. Analysts' forecasts show a walkdown pattern in which their optimism has decreased as the earnings announcement date has approached. At the beginning of the year, there is a lack of high-quality benchmark information that enables information users to judge the accuracy of analyst's earnings forecasts. Thus, early in the year, analysts are highly inspired to disseminate optimistic forecasts in order to gain manager's favor. In this study, we examine adequate benchmarks prevent analysts from disclosing optimistically biased forecasts. We conjecture that auditors' efforts might mitigate analysts' walkdown pattern. To test this hypothesis, we use data from Korea, where it is mandatory to disclose auditor's review hours. We find that the analyst forecast's walkdown decreases with the ratio as well as the number of audit hours. It implies that an auditor's effort in reviewing interim financial information has a monitoring function that reduces analysts' opportunistic optimism at the beginning of the year. We conjecture that the tendency will be more pronounced when BIG4 auditors review the interim reports. Consistent with the prediction, BIG4 auditors' interim review effort is more effective in suppressing the analysts' walkdown.

• The Journal of Industrial Distribution & Business
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• v.11 no.1
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• pp.39-47
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• 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
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• v.10 no.9
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• pp.199-207
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• 2019

This study aims to analyze the profitability of Robo-Advisors portfolio combined with the analysts' forecasts on the Korean stock prices. Sample stocks are 8 blue-chips and sample period is from 2003 to 2019. Robo-Advisor portfolio was suggested using the Black-Litterman model combined with the analysts' forecasts and its profitability was analyzed. Empirical result showed the suggested Robo-Advisor algorithm produced 1% annual excess return more than that of the benchmark. The study documented that the analysts' forecasts had an economic value when applied in the Robo-Advisor portfolio despite the prevalent blames from investors. The profitability on small or medium-sized stocks will need to be analyzed in the Robo-Advisor context because their information is relatively less known to investors and as such is expected to be strongly influenced by the analysts' forecasts.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.81-90
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• 2020

We examine the effects of the complexity of tax-related information on the issuance of analyst's pre-tax income forecast and its value relevance. If analysts respond adequately to the needs of investors, they are more likely to provide a pre-tax income forecast. The provision of a pre-tax income forecast may indicate analysts' confidence in assessing the quality of earnings. Thus, investors, in turn, would be more confident in the analysts' pre-tax income forecasts if analysts provide both pre-tax and earnings forecasts than only the latter. Using a sample of Korean listed companies for 2005-2014, we find that analysts are likely to provide an implicit tax forecast when the volatility of the effective tax rate is low and the book-tax differences are small. We also find that when analysts provide pre-tax and after tax income forecasts, the value relevance for unexpected earnings increases. These results indicate that analysts are likely to be interested in corporate tax information and the complexity of tax-related information affects the availability of implicit tax forecasts. Furthermore, this study provides empirical evidence that when analysts provide both pre-tax and after tax income forecasts, investors have more confidence in analysts' earnings forecasts, which results in greater investors' responses.

• Journal of Distribution Science
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• v.17 no.10
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• pp.41-48
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• 2019

Purpose - This study investigates whether financial analysts consider the intangible investment implicit in selling, general, and administrative (SG&A) expenditures to forecast firms' future earnings. Research design, data, and methodology - Using 52,609 U.S. firm-year observations spanning 1984-2016, this study examines the association between the Intangible investment implicit in SG&A expenditures and properties of analysts' earnings forecasts. To estimate the Intangible investment of SG&A, I decompose SG&A excluding R&D and advertising expenditures into maintenance and investment components following Enache and Srivastava (2017). Results - The main results show that analysts' earnings forecast errors and dispersion in analysts' forecasts increase with the intangible investment derived from SG&A because the investment component of SG&A affects future earnings and the uncertainty of those earnings. However, these results are weakened in the wholesale and retail industries where firms have a higher level of investment component of SG&A. I attribute the weaker results to low R&D expenditures in those industries. Conclusion - This study indicates that financial analysts incorporate the intangible investment of SG&A into their earnings forecasts differently across firms and industries. Furthermore, this study supports the argument for the separate reporting of the investment nature of SG&A from other operating expenses such as maintenance nature of SG&A.