The Journal of Asian Finance, Economics and Business
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v.6
no.4
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pp.91-98
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2019
Dividend policy is an important business decision and is considered a channel to communicate a firm's performance to shareholders. Given the empirical findings that earnings quality significantly affects financial analysts' forecasting activities, it is predicted that higher earnings quality would positively influence forecast accuracy. Specifically, it is expected that financial analysts would forecast dividends more accurately for firms with higher earning quality. Unlike the research on financial analysts' earnings forecasts was heavily conducted, there is little study about financial analysts' dividend forecasts. This paper examines the effect of earnings quality on financial analysts' dividend forecast accuracy. We use a sample of South Korean firms for the period of 2011-2015 for multivariate regression. Earnings quality is measured by accruals quality and performance-adjusted discretionary accruals followed by prior studies. We first compare the accuracy between dividend forecasts and earnings forecasts using t-test and Wilcoxon singed-rank test. It is confirmed that financial analysts' dividend forecasts are more accurate than earnings forecasts in Korea. We find that financial analysts' dividend forecasts are more accurate for firms with higher earnings quality. We also find that the result is still valid after controlling for the accuracy of financial analysts' earnings forecasts. This confirms that earnings quality positively affects financial analysts' dividend forecasts.
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.
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.
This paper analyzes empirically how analysts' forecasts affected by ownership structure. This study examine a sample of 1,037~1,629 the analysts' forecasts of firms registered in Korean Stock Exchange in the period from 2000 to 2006. The empirical results are summarized as follows. First, from the analysis, companies which have higher major shareholder's holdings tend to increase earnings forecast errors and earnings forecast accuracy. Meanwhile, companies which have higher institution shareholder's holdings tend to decrease earnings forecast errors and earnings forecast accuracy. This result is in line with the view of previous works that companies with higher major shareholder's holdings look towards more of analysts' optimistic forecasts in order to maintain friendly relations with major shareholders. Because of analysts' private information use from major shareholders, earnings forecast accuracy is higher in high major shareholder's holdings firm than in high institution shareholder's holdings it. Second, this analysis is whether the minimal required selection condition of outside directors, audit committee adoption and audit quality affect the relation between ownership structure and analysts' forecasts. This result is that variables related corporate governance do not affect statically the relation between ownership structure and analysts' forecasts. The meanings of this paper is to suggest the positive relations between ownership structure and analysts' forecasts. After this, if analysts will notice forecasts of more many firms, capital market will be more efficient and this field works are plentiful. Also it will need monitoring systems not to distort market efficiency by analysts' dishonest forecasts.
This study examines the effects of managerial ability on information asymmetry. We use analyst forecast errors as a proxy for information asymmetry, because analysts are referred to as efficient users using firm-level data. The sample consists of 2,246 non-banking firm-years listed in Korea Stock Exchange(KOSPI) during the period 2000 to 2013. We measure managerial ability using DEA(Data Envelopment Analysis) following Demerjian et al.(2012). Using those measures, we examines the effects of managerial ability on analysts' earnings forecast errors and analysts' earnings forecast bias. The results of this study are as follows. First, we find that managerial ability are positively associated with analysts' earnings forecast accuracy. Second, we show that the firms with higher managerial ability tend to have lower the optimistic errors in analysts' earnings forecasts. This study could be useful for outside stakeholders to understand the importance of managerial ability.
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.
This study investigates the effect of revenue recognition by percentage of completion method on financial analysts' earnings forecasting information in order industry. Specifically, we examines how the analysts' earnings forecast errors and biases differ according to whether or not to report the unbilled revenue account balance and the level of unbilled revenue account balance. The sample consists of 453 firm-years listed in Korea Stock Exchange during the period from 2010 to 2014 since the information on unbilled revenue accounts can be obtained after the adoption of K-IFRS. The results are as follows. First, we find that the firms with unbilled revenue account balances have lower analysts' earnings forecast accuracy than the firms who do not report unbilled revue account balances. In addition, we find that the accuracy of analysts' earnings forecasts decreases as the amount of unbilled revenue increases. Unbilled revenue account balances occur when the revenue recognition of the contractor is faster than the client. There is a possibility that managerial discretionary judgment and estimation may intervene when the contractor calculates the progress rate. The difference between the actual progress of the construction and the progress recognized by the company lowers the predictive value of financial statements. Our results suggest that the analysts' earnings forecasts may be more difficult for the firms that report unbilled revenue balances as applying the revenue recognition method based on the progress criteria. Second, we find that the firms reporting unbilled revenue account balances tend to have higher the optimistic biases in analysts' earnings forecast than the firms who do not report unbilled revenue account balances. And we find that the analysts' earnings forecast biases are increases as the amount of unbilled revenue increases. This study suggests an effort to reduce the arbitrary adjustment and estimation in the measurement of the progress as well as the introduction of the progress measurement method which can reflect the actual progress. Investors are encouraged to invest and analyze the characteristics of the order-based industry accounting standards. In addition, the results of this study empower the accounting transparency enhancement plan for order industry proposed by the policy authorities.
The paper investigates the possible relationship between earnings prediction by security analysts and special ownership ties that link security companies those analysts belong to and firms under analysis. "Security analysts" are known best for their role as information producers in stock markets where imperfect information is prevalent and transaction costs are high. In such a market, changes in the fundamental value of a company are not spontaneously reflected in the stock price, and the security analysts actively produce and distribute the relevant information crucial for the price mechanism to operate efficiently. Therefore, securing the fairness and accuracy of information they provide is very important for efficiencyof resource allocation as well as protection of investors who are excluded from the special relationship. Evidence of systematic distortion of information by the special tie naturally calls for regulatory intervention, if found. However, one cannot presuppose the existence of distorted information based on the common ownership between the appraiser and the appraisee. Reputation effect is especially cherished by security firms and among analysts as indispensable intangible asset in the industry, and the incentive to maintain good reputation by providing accurate earnings prediction may overweigh the incentive to offer favorable rating or stock recommendation for the firms that are affiliated by common ownership. This study shares the theme of existing literature concerning the effect of conflict of interests on the accuracy of analyst's predictions. This study, however, focuses on the potential conflict of interest situation that may originate from the Korea-specific ownership structure of large conglomerates. Utilizing an extensive database of analysts' reports provided by WiseFn(R) in Korea, we perform empirical analysis of potential relationship between earnings prediction and common ownership. We first analyzed the prediction bias index which tells how optimistic or friendly the analyst's prediction is compared to the realized earnings. It is shown that there exists no statistically significant relationship between the prediction bias and common ownership. This is a rather surprising result since it is observed that the frequency of positive prediction bias is higher with such ownership tie. Next, we analyzed the prediction accuracy index which shows how accurate the analyst's prediction is compared to the realized earnings regardless of its sign. It is also concluded that there is no significant association between the accuracy ofearnings prediction and special relationship. We interpret the results implying that market discipline based on reputation effect is working in Korean stock market in the sense that security companies do not seem to be influenced by an incentive to offer distorted information on affiliated firms. While many of the existing studies confirm the relationship between the ability of the analystand the accuracy of the analyst's prediction, these factors cannot be controlled in the above analysis due to the lack of relevant data. As an indirect way to examine the possibility that such relationship might have distorted the result, we perform an additional but identical analysis based on a sub-sample consisting only of reports by best analysts. The result also confirms the earlier conclusion that the common ownership structure does not affect the accuracy and bias of earnings prediction by the analyst.
As advertising and promotions are categorized as operating expenses, managers tend to reduce marketing budget to improve their short term profitability. Gauging the value and accountability of marketing spending is therefore considered as a major research priority in marketing. To respond this call, recent studies have documented that financial market reacts positively to a firm's marketing activity or marketing related outcomes such as brand equity and customer satisfaction. However, prior studies focus on the relation of marketing variable and financial market variables. This study suggests a channel about how marketing activity increases firm valuation. Specifically, we propose that a firm's marketing activity increases the level of the firm's product market information and thereby the dispersion in financial analysts' earnings forecasts decreases. With less uncertainty about the firm's future prospect, the firm's managers and shareholders have less information asymmetry, which reduces the firm's cost of capital and thereby increases the valuation of the firm. To our knowledge, this is the first paper to examine how informational benefits can mediate the effect of marketing activity on firm value. To test whether marketing activity contributes to increase in firm value by mitigating information asymmetry, this study employs a longitudinal data which contains 12,824 firm-year observations with 2,337 distinct firms from 1981 to 2006. Firm value is measured by Tobin's Q and one-year-ahead buy-and-hold abnormal return (BHAR). Following prior literature, dispersion in analysts' earnings forecasts is used as a proxy for the information gap between management and shareholders. For model specification, to identify mediating effect, the three-step regression approach is adopted. All models are estimated using Markov chain Monte Carlo (MCMC) methods to test the statistical significance of the mediating effect. The analysis shows that marketing intensity has a significant negative relationship with dispersion in analysts' earnings forecasts. After including the mediator variable about analyst dispersion, the effect of marketing intensity on firm value drops from 1.199 (p < .01) to 1.130 (p < .01) in Tobin's Q model and the same effect drops from .192 (p < .01) to .188 (p < .01) in BHAR model. The results suggest that analysts' forecast dispersion partially accounts for the positive effect of marketing on firm valuation. Additionally, the same analysis was conducted with an alternative dependent variable (forecast accuracy) and a marketing metric (advertising intensity). The analysis supports the robustness of the main results. In sum, the results provide empirical evidence that marketing activity can increase shareholder value by mitigating problem of information asymmetry in the capital market. The findings have important implications for managers. First, managers should be cognizant of the role of marketing activity in providing information to the financial market as well as to the consumer market. Thus, managers should take into account investors' reaction when they design marketing communication messages for reducing the cost of capital. Second, this study shows a channel on how marketing creates shareholder value and highlights the accountability of marketing. In addition to the direct impact of marketing on firm value, an indirect channel by reducing information asymmetry should be considered. Potentially, marketing managers can justify their spending from the perspective of increasing long-term shareholder value.
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.
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