• 유통과학연구
• /
• 제20권12호
• /
• 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.

• The Journal of Asian Finance, Economics and Business
• /
• 제1권3호
• /
• 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.

• 무역학회지
• /
• 제46권2호
• /
• 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 Asian Finance, Economics and Business
• /
• 제8권8호
• /
• 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.

• 한국융합학회논문지
• /
• 제9권2호
• /
• pp.207-215
• /
• 2018

본 연구는 유가증권 및 코스닥상장기업을 대상으로 기업의 비정상 투자가 재무분석가의 이익예측과 어떠한 관계가 있는지 실증적으로 분석하였다. 본 연구의 분석기간은 관심변수를 기준으로 2003년부터 2015년까지(종속변수는 2004년부터 2016년까지)이며 재무분석가가 주당이익예측치를 발표한 기업 중 연구조건을 만족하는 최종표본 4,917개 기업/년 자료를 분석대상으로 선정하여 연구를 진행하였다. 실증분석결과는 다음과 같다. 첫째, 비정상 총투자, 비정상 R&D, 비정상 CAPEX 투자가 많을수록 재무분석가의 이익예측정확성은 유의하게 향상되었다. 둘째, 비정상 총투자, 비정상 R&D, 비정상 CAPEX 투자가 많을수록 재무분석가의 이익예측은 비관적인 성향을 갖는 것으로 나타났다. 추가분석을 통해 이러한 결과는 과소투자 집단보다는 주로 과잉투자 집단에 의해 발생되는 결과임이 입증되었다. 본 연구결과는 재무분석가의 이익예측 결정요인으로 비정상투자가 고려된다는 점에서 기존 연구에 추가적인 공헌점이 있을 것으로 기대된다.

• The Journal of Asian Finance, Economics and Business
• /
• 제6권2호
• /
• pp.45-54
• /
• 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.

• 산경연구논집
• /
• 제11권1호
• /
• 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.

• 한국융합학회논문지
• /
• 제10권9호
• /
• pp.199-207
• /
• 2019

우리나라 주식시장에서 애널리스트들이 발표하는 주가 전망 자료를 입력변수로 활용한 로보어드바이저 포트폴리오의 수익성이 있는지를 분석하고자 하였다. 포트폴리오 구성을 위한 표본 주식은 업종을 대표하는 8개의 우량주이며, 분석 기간은 2003년부터 2019년까지의 17년 자료이다. 표본 주식에 대한 주가와 애널리스트 주가 전망 자료를 결합하는 블랙리터만모형을 통해 로보어드바이저 포트폴리오를 추천하고 벤치마크 대비 수익성을 비교하였다. 실증 분석 결과, 애널리스트들의 주가 전망 자료를 결합한 로보어드바이저 알고리즘의 수익성은 벤치마크 포트폴리오보다 연평균 1% 이상의 초과 수익을 시현하였다. 투자자들의 비판적 시각에도 불구하고 개별 종목에 대한 투자가 아닌 상대적 투자 비중을 구하는 로보어드바이저 관점에서는 애널리스트들의 주가 전망 자료가 경제적 가치를 보유하고 있음을 밝혔다. 향후 연구에서는 애널리스트들의 주가 전망 영향력이 대형주보다 더 클 것으로 예측되는 중 소형주를 포함한 로보어드바이저 포트폴리오의 수익성을 분석할 필요가 있다.

• The Journal of Asian Finance, Economics and Business
• /
• 제7권1호
• /
• pp.81-90
• /
• 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.

• 유통과학연구
• /
• 제17권10호
• /
• pp.41-48
• /
• 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.