공정공시제도 도입 이후 경영자예측정보의 정확성

권수영 ( Soo Young Kwon ),이동헌 ( Dong Heun Lee ),황문호 ( Mun Ho Hwang ) 한국회계학회 2009 회계학연구 Vol.34 No.1

본 연구는 공정공시를 통해 보고된 경영자 예측정보의 정확성을 재무분석가의 예측정보와 비교하고, 경영자 예측정보의 정확성을 결정짓는 기업특성요인 및 예측정보의 제 특성을 분석한다. 공정공시제도가 도입된 2002년 11월 이후 2007년 말까지 영업실적에 대한 전망을 보고한 상장기업을 대상으로 분석한 결과, 경영자 예측정보는 재무분석가 예측정보에 비해 이익항목에서 높은 예측정확성이 나타났다. 또한 예측기간(forecast horizon)이 짧을수록, 재무분석가 예측정보에 비해 비관적인 성향을 가질수록 정확성이 높은 것으로 나타났다. 이는 경영자가 가진 내부정보의 우위가 매출예측보다는 이익예측에, 장기예측보다는 단기예측에 효과적임을 의미하며, 시장 기대치에 비해 보수적인 예측치를 보고할수록 예측정확성이 제고됨을 의미한다. 한편 경영자 예측정보의 정확성 결정요인을 분석한 결과에서는, 기업규모가 크고 부채비율이 낮을수록, 수익성과 이익성장성이 높을수록, 매출의 변동성은 낮을수록 예측정보의 정확성이 높아지며, 공시정보의 예측기간이 짧고 공시되는 예측항목 수가 많을수록, 언론이나 자사 홈페이지를 통한 정보보다는 기업설명회나 컨퍼런스 콜을 통한 정보일수록, 재무분석가 예측정보와의 예측차이가 작을수록 예측정보의 정확성이 높아지는 것으로 나타났다. 본 논문은 국내에서 비교적 활발치 않은 경영자 예측정보에 대하여 연구를 수행하였다는 점에서 그 의의가 있다. 더욱이 관련 선행연구와 비교하여 공정공시 이후로 분석대상을 확대한 점과 정보의 원천 및 재무분석가의 예측정보와의 관련성을 고려하였다는 점에서 본 연구의 공헌점이 있는 것으로 판단된다. This study examines the accuracy of management earnings forecasts after Regulation Fair Disclosure is adopted in 2002. We make comparisons of accuracy between management forecasts and analyst forecasts, and investigate what determines the accuracy of management forecasts for the firms listed on Korean Stock Exchange for the period of 2002 November to 2007. For the comparison of the accuracy of management forecasts with analysts forecasts, we first find that management forecasts tend to be optimistically biased given that 68% of management forecasts turn out to be greater than actual earnings. Second, management earnings forecasts is more accurate than analyst earnings forecast in general, while management sales forecast is no more accurate than analyst sales forecast. This suggests that managers have inside information such as cost structure, capital budgeting and execution of strategies so that they can better predict earnings than outside financial analysts. Third, management forecasts with short forecast horizon are more accurate than those with long forecast horizon. This implies that the shorter forecast horizon, the more information advantage managers have as they get to know the realized operating performance in detail. This also indicates that in the early period of year, the operating environment is so uncertain that managers are not better than financial analysts in forecasting sales and earnings. Fourth, management forecast errors are larger (smaller) than analyst forecast errors when management forecasts are greater (less) than analyst forecasts. That is, management forecasts are less (more) accurate than analyst forecasts when managers are optimistic (pessimistic) about the future prospect. This is consistent with the explanation that managers are inherently optimistic so that they tend to look at the bright side and release pessimistic forecasts only if they are very likely. This results in the asymmetric accuracy of forecasts depending on whether management forecasts are optimistic or not. For the analysis of determinants of management forecast accuracy, we employ firm size, leverage, profitability, earnings growth, variability, volume of information, source of information, the discrepancy between management forecasts and analyst forecasts. The results show that the larger firm size is, the more accurate management forecasts are, while the accuracy of management forecasts decrease when firms are more leveraged, less profitable or have higher earnings variability. Related to the characteristics of forecast disclosures, the accuracy of management forecasts improves when forecast horizon is shorter, the number of forecast disclosures is larger, and/or management forecasts are less optimistic. In addition, the smaller discrepancy between management forecasts and analyst forecasts, the more accurate management forecasts are. Prior studies investigated the relative accuracy of management and analyst forecasts in Korea. Despite this effort, no consistent conclusions emerge because the studies were limited due to the small sample size. Attempting to resolve this conflicting evidence on the relative accuracy of management and analyst forecasts, we use a large set of management forecasts since Regulation Fair Disclosure was adopted and find the evidence on the relative accuracy of management forecasts to analyst forecasts. We also examined the determinants of accuracy in management forecasts. This provides insight into the question of why managers issue earnings forecasts, what factors investors take into account in understanding management forecasts.

경영자 예측정보의 연속적 공시행태에 관한 연구 -전기 예측정확성 및 재무분석가의 영향을 중심으로

김경혜 ( Kyung Hye Kim ),최경수 ( Kyong Soo Choi ),황문호 ( Mun Ho Hwang ) 한국회계학회 2013 회계학연구 Vol.38 No.3

본 연구는 경영자 예측정보의 연속적 공시행태를 분석한다. 구체적으로, 전기에 공시된 경영자 예측정보의 사후적 정확성 및 재무분석가와의 상호작용이 당기의 예측정보 공시에 미치는 영향을 분석한다. 선행연구에 따르면, 경영자의 자발적인 예측정보 공시에는 다양한 경제적 유인이 수반되는 것으로 보고된다. 따라서 예측정보 공시에 따른 기대효익이 크게 예상되면 경영자는 적극적인 공시정책을 취할 것이며, 그렇지 않은 경우라면 소극적인 모습이 나타날 수 있다. 본 연구는 이러한 영향관계에 기초하여 과거에 발표한 경영자 예측정보의 신뢰성이 떨어질수록 당기의 예측정보 공시가능성이 낮아질 것으로 예상한다. 아울러 이러한 경영자의 연속적 공시행태에 있어 재무분석가들이 완충적인 역할을 수행할 것으로 예상한다. 경영자와 재무분석가는 예측정보를 생산하는 주요 주체로서 서로의 예측정보를 긴밀하게 모니터링한다. 따라서 경영자가 재무분석가의 예측정보를 통해서 자신의 예측정확성을 보완할 수 있다고 판단한다면 이를 적극 참조하여 공시에 반영할 것으로 기대되기 때문이다. 본 연구는 2002년부터 2008년까지 공정공시를 통해 발표된 경영자 영업이익 예측치를 대상으로 분석을 수행하였으며, 주요 결과는 다음과 같다. 첫째, 경영자의 전기 예측정확성이 낮을수록 당기 예측정보의 공시가능성이 감소하는 것으로 나타났다. 이는 과거 예측정보의 신뢰성이 떨어질수록 당기의 공시에 따른 기대효과가 크지 않을 것으로 예상하여 소극적인 공시활동이 이루어지고 있음을 시사한다. 둘째, 재무분석가의 전기 예측정확성이 경영자보다 우수할수록, 경영자의 전기 예측정확성과 당기 예측정보 공시 간에 나타나는 양(+)의 관계는 유의하게 감소하였으며, 경영자의 예측정확성은 유의하게 개선되는 것으로 나타났다. 이는 경영자의 예측정보 공시 의사결정에 재무분석가 예측정보가 참조되고 있음을 나타내는 한편 재무분석가를 통해 경영자 예측정보의 신뢰성이 향상될 수 있음을 시사하는 결과이다. 본 연구는 경영자의 전기 예측정확성과 당기의 예측정보 공시간에 체계적인 관련성이 있음을 보여줌으로써 경영자의 자발적 공시유인 연구를 확장하고 있다. 아울러 경영자의 예측정보 공시에 재무분석가 예측정보가 유의하게 활용되고 있음을 보여줌으로써 경영자와 재무분석가간의 상호작용을 실증적으로 검증하였다는 점에서 차별적 공헌점이 있는 것으로 판단된다. We examine the manager`s consecutive reporting behavior about the voluntarily disclosed earnings forecast. Specifically, the primary objective of our study is to explore the effect of prior management earnings forecast accuracy and financial analysts on the current management earnings forecasts disclosure probability. First, we examine how the accuracy of prior management earnings forecast influences the disclosure probability of current management earnings forecast. In addition, we investigate how the number of analysts following and analysts` relative earnings forecast accuracy of prior year impact on the relation between prior management earnings forecast accuracy and current management earnings forecasts disclosure probability. In order to perform the empirical analysis, we hand collect management earnings forecasts for fiscal years 2002-2008 from Financial Supervisory Service`s Data Analysis, Retrieval and Transfer System (DART). Our specific results are given as follows. First, this research finds that as the accuracy of prior management earnings forecasts decreases the disclosure probability of current management earnings forecasts also decreases. Extant literatures demonstrate that various economic incentives have an effect on the disclosure policy of voluntarily disclosed earnings forecast. Therefore, if managers expect higher expected benefits of disclosing earnings forecast, he would be inclined to make an earnings forecast. On the other hand, when managers expect lower expected benefits of disclosing earnings forecast, he would not be inclined to make an earnings forecast. In this paper, based on the number of prior researches, we maintain that a relatively large errors of prior management earnings forecasts diminishes the expected benefits of current management earnings forecasts disclosure, which in turn generates a diminution of managers` incentives to provide current management earnings forecasts to the market participants. Therefore, the systematic positive (+) association between prior management earnings forecasts accuracy and current management earnings forecasts disclosure probability is consistent with our expectations. Second, when the analysts` prior relative earnings forecast accuracy are relatively high, the significant positive (+) association between prior management earnings forecasts accuracy and disclosure probability of current management earnings forecasts becomes small. On the contrary, the number of analysts` following of prior year does not affect the systematic positive (+) association between prior management earnings forecasts accuracy and disclosure probability of current management earnings forecasts. These findings indicate that since the manager`s specific ability to forecast a firm`s prospect increases in a relatively short period as the analysts` prior relative earnings forecast accuracy becomes higher, the manager`s incentives to stop management earnings forecast in the current period which is due to prior management earnings forecasts errors decreases. However, since the number of analysts` following of prior year is limited in improving manager`s specific ability to forecast a firm`s prospect, it does not influence the manager`s incentives to stop management earnings forecast in the current period which is due to prior management earnings forecasts errors. This paper, by demonstrating the systematic positive (+) association between prior management earnings forecasts accuracy and current management earnings forecasts disclosure probability, provides a new insight about the manager`s consecutive earnings forecasts disclosure policy. In particular, prior literatures which deal with management earnings forecasts concentrate mainly on the temporary forecasting behavior of managers. On the other hand, our research is discriminated by focusing on the sequential management earnings forecast strategies. As a result, our research might expand the scope of prior literatures which have dealt with manager`s voluntary disclosure policy Also, establishing the fact that the significant positive (+) association between prior management earnings forecasts accuracy and current management earnings forecasts disclosure probability decreases as the analysts` prior relative earnings forecast accuracy increases, this study documents the crucial impact of the analysts` on the manager`s consecutive earings forecasts behavior.

재무분석가의 특성이 이익예측정확성에 미치는 영향

안윤영 ( Yoon Young Ahn ),유영태 ( Young Tae Yoo ),조영준 ( Young Jun Cho ),신현한 ( Hyun Han Shin ),장진호 ( Jin Ho Chang ) 한국회계학회 2006 會計學硏究 Vol.31 No.4

본 연구는 IBES Detail Tape에 포함된 1999년부터 2003년까지의 재무분석가 이익예측자료를 사용하여, 재무분석가의 개인특성 변수를 중심으로 재무분석가의 이익예측정확성 결정요인에 대하여 살펴보았다. 분석결과 첫째, 많은 기업에 대한 분석을 담당하는 재무분석가일수록 이익예측오차는 높음을 발견하였다. 이는 재무분석가의 분석기업 수가 늘어날수록 분석업무의 복잡성이 증가하여 이익예측에 어려움을 겪고 있음을 의미한다. 둘째, 많은 분석보고서를 발행하는 재무분석가일수록 이익예측오차는 낮음을 발견하였다. 이는 특정기업에 대한 예측정보를 빈번하게 제공하여 활발한 분석활동을 수행하는 재무분석가일수록 이익예측능력이 높음을 의미한다. 셋째, 특정산업에 대한 분석을 실시하는 재무분석가일수록 이익예측오차가 낮음을 발견하였다. 이는 특정산업에 특화된 재무분석가일수록 분석업무의 복잡성이 감소하여 이익예측이 용이하였음을 의미한다. 마지막으로 기업특성 요인이 이익예측정확성에 미치는 영향을 분석한 결과 예측기간, 주가수익률 변동성, 표준화된 ROA, 부채비율 등이 높은 기업에서 이익예측오차가 높았으며, 재벌계열사에 소속된 기업에서 이익예측오차가 낮음을 발견하였다. Prior study finds that analysts` forecast activities(accuracy, coverage, the number of analysts following a firm, herding behavior, etc.) are related to several analysts characteristics(reputation, past accuracy, forecast frequency, firm-specific and general experience, and the number of firms and industries following) and environmental factors(employed brokerage size, and various characteristics of individual firms). Most of the empirical research on analysts` forecast accuracy in the current Korea security market focuses on environmental variables (individual company characteristics other than analyst characteristics. Therefore, our research has been conducted to extend the extant literatures` results on determinants of forecast accuracy using a sample of Korean firms included in the IBES database for a five year period from 1999 to 2003. We focus on the effect of analysts` characteristics on forecast accuracy. Since prior research provides mixed effects and results of analysts` characteristics on forecast accuracy, the direction of the effect of analysts` characteristics on forecast accuracy is unclear. We therefore established the non-directional hypothesis stated in the null form. To test whether each (analyst characteristics) variable has explanatory power incremental to the other, analyst characteristics variables are separately included in regression models respectively, and all variables are included as well. While the main focus of this study is to examine the effect of analyst characteristics on forecast accuracy, we have also considered the contribution of environmental variables (characteristics of individual firms) on forecast accuracy. The dependent variable of the basic research regression model is the forecast accuracy. Here forecast accuracy is defined as the logarithm of absolute forecast error and measured forecast error as the deviation of the actual EPS from the forecasted EPS which is deflated by the stock price to facilitate comparisons across firms. Thus more accurate forecasts are represented by lower forecast error values, i.e. there is an inverse relationship between forecast accuracy and forecast error. The three analyst characteristics (number of firms followed, forecast frequency and industry specialization) are key independent variables. In addition, we control for five variables of characteristics of firms (forecast horizon, stock price return volatility, standardized ROA, debt ratio and Chaebul dummy variable that prior research has shown to be related. First, we find that forecast accuracy decreases with the number of firms followed. The estimated coefficients of the number of firms followed are positively related to analysts` forecast error at the 1% significance level in all models represented by table 5 and table 6. This result indicates that the number of firms followed can be interpreted as a proxy for analysts` task (forecast) difficulty (portfolio complexity). If analysts follow a larger set of firms then it is difficult to devote more attention to each firm and to produce accurate forecasts. Second, forecast accuracy increases with the number of forecasts reports issued. The coefficients on the number of reports issued are negatively related to forecast error at the 5% or 1% significance level respectively presented by table5 and table 6. This result suggests that forecast error is significantly lower for analysts with more frequent reports. The number of forecasts reports issued can be considered as a proxy for analysts` skillful performance outputs and forecast ability. Third, forecast precision increases with the analyst industry specialization. This finding means that forecast error is significantly lower for analysts with a higher percentage of the companies followed by analysts that are in the same industry classification. Because industry specialization is expected to result in more accurate forecasts, the coefficients of analyst industry specialization are negatively associated with forecast error to a 1% or 5% significance level respectively presented by table 5 and table 6. Our overall conclusion is that forecast accuracy is associated with analyst-specific characteristics. We also examined the firm-specific characteristics effect on forecast accuracy. Regarding firm-specific characteristics variables, the coefficients on the forecast horizon, stock price return volatility, standardized ROA, leverage and Chaebul dummy are significantly related to forecast error. Consistent with prior studies, we find that environmental factors do influence analysts` forecast accuracy. Taken as a whole, analyst forecast accuracy is influenced by analyst-related properties as well as by environmental factors. This study makes several contributions. First, we contribute to the growing literature on analysts` forecast accuracy of the emerging market. Second, we suggest that analysts` characteristics may be helpful for predicting forecast accuracy. Future research might focus on investigating whether capital market participants should consider analyst-related properties in forming earnings expectations and evaluating analyst performance.

감사품질이 경영자 예측정보의 편의성 및 정확성에 미치는 영향: 감사능력 대 감사노력

권수영 ( Soo Young Kwon ),기은선 ( Eun Sun Ki ) 한국회계학회 2011 회계학연구 Vol.36 No.1

본 연구는 감사품질이 경영자 예측정보의 편의성 및 정확성에 미치는 영향에 대하여 살펴본다. 감사품질이 높을수록 예측치에 실적치를 맞추려는 경영자의 재량권을 제한함으로써 경영자가 보다 정확한 예측정보를 공시하도록 유도할 것으로 예상된다. 본 연구에서 감사품질은 감사능력을 나타내는 감사인의 규모(BIG4 여부)와 산업전문성 이외에도 감사노력을 반영하는 비정상 감사시간으로 측정한다. 경영자 예측정보의 편의성(bias)은 경영자의 예측치와 실적치 간의 차이를 당기 매출로 나눈 값으로, 예측정보의 정확성(accuracy)은 예측편의에 절대값을 취해 측정한다. 본 연구는 유가증권시장상장기업 중 2002년부터 2008년까지의 기간에 경영자 예측정보를 공시한 638개의 기업-연 자료를 분석에 이용하였다. 본 연구의 실증분석 결과 대형회계법인에게 감사를 받거나 감사인이 추가적인 노력을 기울일수록(즉, 비정상 감사시간이 많을수록) 경영자 예측정보의 정확성은 높아지는 것으로 나타났다. 이러한 결과는 감사품질이 높을수록 경영자의 재량권이 제약되기 때문에 경영자는 되도록 실제치와 예측치의 차이를 줄여 부정확한 예측으로 인한 손실을 최소화하고자 한다는 것을 의미한다. 특히, 대형회계법인이 아니더라도 또는 산업전문성이 없는 감사인이라도 추가적인 노력을 기울이면 경영자 예측정보의 편의성은 줄어들고 정확성은 높아진다는 결과는 감사인의 추가적인 감사노력이 감사인의 평판이나 산업전문성을 보완하는 중재적 역할을 한다는 것을 보여준다. 추가분석 결과 특정 고객에 대한 경제적 의존도가 높아 감사인의 독립성이 저해될 수 있는 상황이라 할지라도 비정상 감사시간이 많으면 경영자 예측정보의 편의성은 줄어들고 정확성은 높아지는 것으로 나타났다. This study examines the effect of audit quality on the bias and accuracy of management forecasts. Management forecasts are voluntary in nature, and thus may not be reliable since managers may exercise discretion over the content and timing of management forecasts disclosures. However, high audit quality may restrict managers to exercise their discretion in the financial statements. This forces managers to forecast their sales and earnings as accurate as possible given that the discrepancy of forecasts from the actual numbers may cause managers to be legally liable. Audit quality is known as an elusive concept due to the difficulty to observe and measure. DeAngelo (1981) suggested that audit quality is jointly determined by auditor independence and auditor competence. Setting auditor independence aside, prior studies used audit firms size (BIG affiliation) and auditors` industry specialization as proxies for audit competence to address audit quality. However, one thing the audit quality literature did not consider is audit effort. The more audit hours an auditor makes, the higher audit quality is likely to be. An auditor can professionally respond to a particular audit contract by determining how much audit effort he/ she needs to make, while auditor reputation and industry expertise is beyond the scope of an individual auditor`s decision. This study examines whether Big 4 auditors or auditors with industry expertise induce managers to forecast with higher accuracy than non-Big 4 auditors or those with no industry expertise. In addition, the forecast accuracy is also higher when auditors make additional audit effort controlling for audit complexity and risk. We employ two proxies- forecast bias and forecast accuracy. This study uses the 638 firm-year management forecasts released by firms listed on the Korea Stock Exchange for the period of 2002 to 2008. Empirical results show that firms audited by Big 4 tend to have more accurate management forecasts, but no significant difference in forecast bias. When an auditor has industry expertise, no significant difference in management forecast bias and accuracy is observed. In addition the more additional effort an auditor makes (i.e., abnormal audit hours are positive), the more accurate management forecast is. In summary, it appears that there is a positive relation between audit quality and management forecast accuracy. This result is consistent with the explanation that high audit quality restricts managers to exercise their discretion in the financial statements and thus forces them to forecast as accurate as possible in order to reduce the cost associated with the inaccurate forecast (e.g., litigation risk and/or stock price plunge). One notable empirical result is the effect of audit effort on the relation of audit quality proxied by Big 4 affiliation and auditor industry specialization with management forecast accuracy. That is, the accuracy of management forecasts improves even for firms audited by non-Big 4 or industry non-specialist auditors if they make additional effort by spending audit hours more than the expected level of hours given audit complexity and audit risk. This result is interesting because it shows that audit quality is determined by not only audit competence but also audit effort. Note that audit firm-level audit competence can not be changed overnight. On the other hand, contract-level audit effort can be adjusted based on the risk assessment. This evidence illustrates the importance of professional responses to the audit risk to assure a certain level of audit quality, which has not been considered in the audit quality literature. Prior studies show that the joint provision of non-audit services to audit clients increases audit risk due to the greater economic dependence on the clients. The empirical test provides the evidence that auditors` additional effort can improve the accuracy of management forecasts even for the highly economic dependent clients. It appears that the concern about auditor independence in the presence of non-audit service provision to audit clients may be mitigated by providing additional audit effort. Overall, the results of this study suggest that market participants should use the audit hour information disclosed in the business report as well as the auditor reputation and expertise in judging the accuracy and credibility of management forecasts.

역세권 특성에 따른 수요예측의 정확도 분석 - 서울시 지하철을 중심으로 -

김동준,김덕녕,양재환,성현곤,이성모 한국교통연구원 2010 交通硏究 Vol.17 No.1

Recently, there have been constant criticisms over the low accuracy of the rail demand forecast. The accurate demand forecast is important as the rail project requires copious budget and time. However, the study on the accuracy of the rail demand forecast has not attracted researchers, whereas it is necessary to understand the factors which affect the accuracy. Especially, different station tends to show different accuracy in the same rail project, it is also necessary to study on this characteristic. The aim of this study is to analyze the effect on the microscopic characteristics of the station impact area to the accuracy of demand forecast. 142 subway stations in Seoul are analyzed to draw 10 characteristic indexes - density, land use mix, number of companies, number of labors, purpose of land use, number of bus lines, number of short-range bus lines, average number of bus lines of bus stop, w or w/o transfer - with categorizing the station impact area to the land use and the public transit. In addition, estimated demand is also analyzed. The accuracy of demand forecast in each station is used to estimate the ratio of risk. As a result, firstly, in terms of the land use, the demand forecast is more accurate with the higher density, land use mix, number of companies and labors which decreases the overestimation. At the same time, the station in the residential area with steady demand shows the higher accuracy. Secondly, in terms with the transit system, the demand forecast is more accurate when there are more bus lines connected to the subway station, on the other hand, the larger demand leads to the lower accuracy. Besides, the transit station shows lower accuracy than the non-transit station, which is supposed to be due to the limitation of the data. With the results above, it is discovered that the accuracy of rail demand forecast shows great differences between stations, which seems to be related with the characteristics of each station. Particularly, similar to the anticipated effect of TOD, an area with high density, mixed land use and feeder transit will improve the accuracy of rail demand forecast. 막대한 재원과 오랜 기간이 소요되는 철도사업의 수요예측 정확도가 낮아 비효율성을 초래한다는 지적이 지속적으로 제기되고 있다. 그러나 이와 관련된 연구는 많지 않은 실정으로, 수요예측의 정확도에 영향을 미치는 다양한 요인을 파악하고 분석하는 것이 필요하다. 특히 하나의 노선이라 할지라도 각 역별로 수요예측 정확도는 큰 차이가 발생하게 되는데, 역별 수요예측의 정확도를 높여 전체 노선의 정확도를 향상시키는 것이 중요하다. 본 연구에서는 서울시에 위치한 142개 지하철역을 대상으로 미시적 역세권 특성이 수요예측의 정확도에 미치는 영향을 파악하였다. 이를 위해 먼저 역세권 특성을 개발밀도, 토지이용의 다양성, 사업체수, 종사자수, 토지이용 목적 등의 토지이용 특성과 버스노선수, 환승/비환승역의 유무 등의 대중교통 특성으로 구분하고 GIS 등의 자료를 활용하여 파악하였다. 또한 지역별 수요예측의 정확도를 위험도라는 지표를 활용하여 산정하였다. 그 결과 개발밀도가 높을수록, 토지이용의 다양성이 높을수록, 사업체수 및 종사자수가 많을수록 수요예측의 정확도가 높아 과다 예측된 경우가 적은 것으로 나타났다. 고정적으로 통행이 발생하는 주거중심의 역이 상대적으로 정확도가 높은 것으로 나타났다. 또한 지하철과 연계되는 버스노선수가 많을수록, 연계성을 갖는 단거리 버스노선수가 많을수록 예측이 정확했으며, 환승역의 경우 비환승역에 비해 오히려 정확도가 낮게 나타났는데, 이는 자료의 한계로 인한 결과라 판단된다. 더불어 예측수요가 많을수록 정확도는 오히려 감소하는 것으로 나타났다. 본 연구결과를 통해 철도사업 수요예측의 정확도는 역별로 큰 차이를 보이며, 이는 역세권의 특성과 관련이 있음을 보여주고 있으며, 향후 철도사업 수요예측 정확도 향상을 위한 기초자료로 활용될 수 있을 것이다. 특히 TOD의 기대효과와 유사하게 개발밀도를 높이고 토지이용을 다양화하며, 연계교통수단의 서비스수준을 향상시킴으로써 수요예측의 정확도를 높일 수 있음을 보여주는 결과라 할 수 있다.

증권회사의 산업 전문성이 이익예측 정확성에 미치는 영향

최정운 한국회계정책학회 2012 회계와 정책연구 Vol.17 No.1

The purpose of this study is to examine whether brokerage houses' industry expertise exists and how the expertise affects analyst’s forecast accuracy. In order to fulfill its purpose, this paper investigates the effect of brokerage houses' industry expertise on forecast accuracy. Specifically, three criteria, such as the number of firms in analysts' coverage, the percentage of market share, and the portfolio of sales in industry, are used for the analysis of analysts’ forecast properties in this paper. Prior research(Clement, 1999; Jacob et al. 1999) focused on how individual analysts' characteristics affected on forecast accuracy. For example, individual analysts' ability, complexity of work, and size of brokerage house were taken into account for the determinants on forecasts properties. Especially, size of house brokerage, as a proxy for information resource for analysts, has affected the analyst’s forecast accuracy, which implies and assumes that the level of brokerage house character may affect the forecast accuracy. Despite this effort, no consistent and specific conclusion about the effect of brokerage houses' industry expertise on analyst forecast properties has ever been suggested empirically. This paper extends the area of analysts research by taking the characteristics of brokerage houses' expertise. Our findings are as follows. The higher house’s industry expertise is, the forecast accuracy increases. In detail, the bigger the number of firms that are covered by analysts is, the forecast accuracy increases on the basis of market share. Also, the bigger the sales of firms that are dealt with by analysts are, the forecast accuracy increases on the basis of portfolio. Overall, the results of this paper are consistent with the notion that forecast properties are affected by brokerage house’s characteristics, specifically industry expertise. Recently, the Financial Investment Services and Capital Markets Act, officially known as Consolidated Capital Market Act went into effect on February 4. 2009. The purpose of this act is to stimulate the competition of analysts in capital market. In this regard, the results of this paper suggest the insight of analyst forecast properties. This paper is very significant in that it has shown that house brokerage expertise determines the accuracy of analyst forecasts empirically. First of all, this paper provides the usefulness of information about analysts’ house brokerage for the potential investors. Analyst forecasts are used as a proxy for market expectation, which implies that information user for analysts forecast should take industry expertise of brokerage house into account. Secondly, this paper extends the research area linked to analysts by suggesting the level of brokerage house characteristics incrementally, which affects analysts forecasts properties, compared to previous study that focus on individual analyst characteristics. 본 연구는 증권회사의 산업 전문성이 소속된 재무분석가의 이익예측 정확성에 미치는 영향을 검증하였다. 구체적으로 해당 산업 내 기업의 수, 매출액과 총자산 합계를 기준으로 하는 산업 내 점유율과 해당 증권회사가 분석하는 기업의 수, 매출액과 총자산 합계를 기준으로 하는 포트폴리오를 이용하였다. 재무분석가의 이익예측 정확성과 관련된 선행연구에서는 개별 재무분석가의 특성에 초점을 맞추어 이익예측 정확성과의 관계를 분석하였다(Clement, 1999). 또한 증권회사 단위에서도 소속된 재무분석가 인원 수에 초점을 맞추어 이익예측 정확성과의 관계를 분석하였다(Jacob 외, 1999). 이는 증권회사의 규모에 기반한 분석으로 증권회사가 보유하는 산업 전문성을 직접 나타내지 못한다는 한계가 있을 수 있다. 따라서 본 연구에서는 증권회사의 분석기업 시장 점유율과 분석기업 포트폴리오를 이용하여 선행연구에서 직접 보여주지 못한 증권회사 단위의 산업 전문성과 이익예측 정확성의 관계를 분석하고자 하였다. 실증분석 결과 증권회사의 산업 전문성이 높을수록 이익예측이 정확한 것으로 나타났다. 특히 시장 점유율 기준에서는 특정 산업 내 분석기업 수가 많을수록, 포트폴리오 기준에서는 증권회사 내 전체 분석 기업에서 특정 산업에 속한 기업들의 매출액과 총자산 비중이 높을수록 이익예측 정확성이 높은 것으로 나타났다. 이는 특정 산업 내에서 규모가 큰 소수의 기업을 분석하는 것보다 다양한 상황의 다수 기업을 분석하는 것이 해당 산업을 보다 잘 이해하는 산업 전문성이 높아지는 것을 의미하며, 동시에 증권회사가 특정 산업에 주력하는 것이 산업 전문성을 높여 이익예측을 상대적으로 정확하게 하는 것으로 해석할 수 있다. 이러한 결과는 자본 통합법 시행으로 인하여 무한경쟁에 노출된 증권회사에 많은 시사점을 제시한다. 증권회사에서 제공하는 투자정보를 참조하는 투자자 입장에서 해당 증권회사의 산업 전문성이 해당 정보의 정확성에 영향을 미치고 있으므로, 투자의사결정시 사용정보의 정확성 판단에 증권회사의 산업 전문성을 고려해야 할 것이다. 따라서 증권회사에서는 투자자가 사전적으로 인지할 산업 전문성을 높이기 위하여 역량을 투입해야 할 것이다. 이는 경쟁을 통한 증권회사 단위의 질적 성장을 가져올 것이므로 자원배분의 효율성을 달성할 수 있을 것이라 판단된다.

IFRS 의무도입 후 이익 정보력이 재무분석가의 이익예측의 정확성에 미치는 영향

박종일 한국세무학회 2018 세무와 회계저널 Vol.19 No.3

This study empirically examines whether the effect of mandatory IFRS adoption, suggesting a association between the financial impact on earnings of the changes to IFRS from GAAP and financial analysts’ earnings forecast accuracy. In other words, this paper predict that the predictability of earnings in the post-IFRS periods are more informative than those of earnings in the pre-IFRS periods are associated with lower forecast errors and dispersion in analyst forecasts. Because I expect that the accuracy of analyst forecasts is related to the accuracy of financial statement-based forecasts and, therefore, that the improvement in analysts’ forecast accuracy around mandatory IFRS adoption is associated with the improvement in the accuracy of earnings on financial reports with firm-level. This relation reflects a fundamental mechanism that could explain the general change in analysts’ earnings forecast around mandatory IFRS adoption. As the relationship, this study also examines whether the adoption effect likely varies with firm-level incentives for auditor effort, foreign investor ownership, and accruals quality. Furthermore, this study partition the sample into market type and test whether the relationship earlier is different for KOSPI versus KOSDAQ listed firms. On the other hand, prior research examine the effects of mandatory IFRS adoption on the accuracy of analysts’ earnings forecasts (e.g., Nam 2015;Houqe et al. 2014;Miralles and Sanabria 2014;Horton et al. 2013;Cotter et al. 2012;Byard et al. 2011;Tan et al. 2011 etc.) Unlike previous studies, this paper differs in that I focus on the informational power of earnings related to analysts’ earnings forecasts errors between the pre-IFRS and post-IFRS periods. For instance, financial analysts are among the major and most intensive users of firms’ financial reports, as they are required to predict a firm’s fundamental value. Furthermore, analysts use firms’ previous financial reports, particularly earnings information, to predict future earnings. Therefore, intuitively, the accuracy of analysts’ forecasts is directly correlated to the quality of financial reports and the information environment(Horton et al. 2013;Houqe et al. 2014). Therefore, I test that the effects of changes in the informational power of earnings on the accuracy of analysts’ earnings forecasts after the mandatory IFRS adoption. Thus, this paper extend prior studies about properties of analyst forecasts in both the national GAAP and IFRS setting in the period before and after mandatory IFRS adoption. To test the effect of mandatory IFRS adoption, test variable in model to estimate the incremental effect of the informational power of earnings in the post-IFRS period is an interaction of IFRS and earnings (i.e., earnings per share deflated by the price, hereafter EL), where IFRS is an indicator variable that equals one for the post-IFRS period (2011-2015) and zero for the pre-IFRS period (2006-2010). The dependent variable is analysts’ earnings forecast accuracy, in particular, this study capture the properties of analysts’ earnings forecast accuracy using absolute forecast errors, forecast errors (i.e., optimistic or pessimistic bias), and forecast dispersion, where smaller absolute forecast errors, smaller optimistic bias, and smaller forecast dispersion generally indicates a richer information environment. The sample covers KOSPI and KOSDAQ listed firms with available data in non-financial industries with fiscal year-end based on the dependent variable (test variable) from 2007 to 2016 (from 2006 to 2015). The final samples includes 7,116 firm-year observations with available data for analyst’ earnings forecast. The empirical findings of this study are following. First, after controlling for several factors that affect analyst’ forecast errors, I find that the coefficient on interaction term between IFRS and EL (IFRS*EL) is signi... 본 연구는 IFRS 의무도입 이후에 산출된 보고이익 정보력이 이전의 경우보다 재무분석가 측면에서 이익예측의 정확성을 더 향상시키는지를 규명하는데 있다. 또한 앞서의 관계가 감사인의 감사노력, 외부지배구조 및 재무보고의 질의 영향에 따라 차별적인지와 시장유형에 따라 다른지도 살펴보았다. 이를 위해 본 연구는 이익 수준과 IFRS 도입 전후기간의 교차항을 변수로 이용하여 재무분석가의 이익예측의 정확성, 편의 및 분산과의 관계를 알아보았다. 분석기간은 IFRS 의무도입전후의 각 5년간(2006년부터 2015년까지)이고, 표본은 유가증권 및 코스닥기업을 대상으로 7,116 개 기업/연 자료가 이용되었다. 실증결과는 첫째, IFRS 도입 이후에 산출된 보고이익을 이용한 재무분석가의 이익예측치의 정확성이 도입 이전과 비교할 때 더 증가되었고, 낙관적인 편의의 성향은 낮아졌으며, 이익예측의 분산은 줄어든 것으로 나타났다. 둘째, 감사인의 감사노력(비정상 감사시간), 외부지배구조(외국인투자지분율) 및 재무보고의 질(발생액의 질) 수준에 따라 표본을 나누어 분석하더라도 모두 IFRS 도입이후가 이전보다 보고이익을 이용한 재무분석가들의 이익예측의 정확성이 더 높고, 낙관적인 편의의 성향은 낮아졌다. 마지막으로, 시장유형별로 표본을 나누어 분석하면 앞서의 결과들은 주로 코스닥기업보다는 유가증권기업일 때 더 뚜렷한 결과를 보였다. 이상을 종합하면, 본 연구는 IFRS 의무도입 이후가 이전과 비교해 재무분석가의 정보환경을 개선시켜 이익 정보력을 통한 재무분석가의 이익예측의 정확성이 증가되었음을 보여주었다는데 의미가 있다. 따라서 본 연구는 IFRS의 도입 효과를 분석한 관련연구에 새로운 증거를 제공하며, 또한IFRS 도입의 효과성에 관심이 있는 실무계, 회계기준제정기관, 규제당국 및 정책입안자에게 시사점을 제공한다. 아울러 재무분석가의 이익예측 정보는 자본시장의 투자자의 의사결정에도 적지 않은 영향을 미친다는 점을 감안할 때 본 연구는 투자자들에게도 유용한 정보를 제공한다.

발생액의 질과 재무분석가의 정보 환경이 이익예측 정확도에 미치는 영향

김지홍 ( Jee Hong Kim ),백혜원 ( Hye Won Paik ),고재민 ( Jai Min Goh ) 한국회계학회 2010 회계학연구 Vol.35 No.3

재무분석가들은 공적(public) 혹은 사적(private) 경로를 통하여 기업 분석을 위한 정보를 획득한다. 그리고 이러한 정보를 해석하는 과정에서 재무분석가들의 정보는 공통 정보(common information)와 고유 정보(idiosyncratic information)로 구분된다. 즉 재무분석가들이 공적 정보인 회계정보를 동일하게 해석하는 경우 공통 정보로 구분되지만, 재무분석가별로 서로 달리 해석하는 경우 고유 정보로 구분된다. Barron et al.(1998)은 재무분석가들이 이익예측시에 사용 가능한 모든 정보를 재무분석가의 정보환경이라 정의하고, 개별 재무분석가들이 공통 정보와 고유 정보에 각각 어느 정도의 비중을 두는지를 측정하기 위해, 공통 정보 활용도(BKLS consensus) 측정치를 제안하였다. 본 연구는 이들이 제안한 측정치를 이용하여, 발생액의 질에 따라 개별 재무분석가의 공통 정보 활용도에 차이가 있는지를 살펴보고, 개별 재무분석가들의 이러한 정보 활용 행태가 재무분석가의 이익예측 정확도에 미치는 영향을 분석하였다. 본 연구 결과 첫째, 우리나라 재무분석가들은 발생액의 질이 높을수록 공통 정보의 활용 비중을 낮추는 경향을 보였다. 이는 투자자들은 양질의 정보를 제공받을 경우 재무분석가에게 이와 차별화되는 정보를 요구한다는 Indjeijikian(1991)와 같이, 재무분석가들은 투자자들의 요구에 부응하고자 고유 정보의 활용 비중을 높이는 것으로 보인다. 둘째, 재무분석가들이 공통 정보 활용 비중을 높일수록 재무분석가의 이익예측 정확도는 낮아졌다. 이는 재무분석가들이 상당한 시간과 비용을 들여 고유 정보를 수집할 때 이익예측정확도가 평균적으로 높아진다는 사실을 의미한다. 셋째, 발생액의 질이 높은 기업의 경우, 재무분석가들이 공통 정보의 활용 비중을 높일수록 이익예측 정확도는 증가하였다. 이는 회계이익의 질이 높은 기업의 경우, 수집과 해석에 시간과 비용이 소모되지 않는 공통 정보를 활용하더라도 이익예측 정확도를 향상시킬 수 있다는 사실을 의미한다. 본 연구의 결과는 발생액의 질이 높을수록 재무분석가들은 공통 정보 대신 고유 정보를 더 많이 활용하고 있지만, 이와 같은 행태가 이익예측 정확도를 높이는 데에는 도움이 되지 않음을 알 수 있다. 따라서 재무분석가들은 발생액의 질이 높은 경우 공통 정보의 활용 비중을 높이는 것이 이익예측 정확도를 높이는 효율적인 방법이 될 수 있음을 제안한다. This study examines how accruals quality and individual analysts` information environments affect on the accuracy of analysts` earnings forecasts. Barron et al.(1998) reveal about the properties of analysts` information environments, developing BKLS consensus, which is the measure of information commonality individual analysts possess at the time they announce earnings forecasts. BKLS consensus assumes analysts` information can be represented as either common to all analysts or idiosyncratic to some individual analysts. Thus, by using BKLS consensus, we can measure the degree to which analysts base their forecasts on common information relative to idiosyncratic information. Francis et al.(2005) suggest that accruals quality is a proxy for the information risk associated with earnings because this measure tells investors about the mapping of accrual-based accounting earnings into cash flows. Relatively poor accruals quality weakens this mapping and, therefore, increases information risk. First, we investigate whether accruals quality is associated with BKLS consensus, the ratio of common-to-total information in the average analysts` forecasts. Second, we examine whether analysts` behavior to change the degree of information commonality depending on accruals quality contributes to improve the accuracy of earnings forecasts. We find that higher accruals quality decreases BKLS consensus, which shows lower information risk decreases investors` demands on common information which is publicly available to all investors. Accordingly, such investors` demands enable analysts to generate more idiosyncratic information rather than common information. Our results are consistent with Indjeijikian(1991), which find that higher level of disclosures afford analysts more opportunity to develop and convey more uniquely private information in their individual forecasts. Further, we provide evidence that the accuracy of analysts` earnings forecasts decreases as BKLS consensus increases, which suggests that high ratio of common-to-total information in the average analysts` forecasts decreases analysts` earnings forecast accuracy. However, the increased reliance on common information as for firms with high accruals quality contributes to increase analysts` earnings forecast accuracy. Therefore, these findings suggest that, as for firms with high accruals quality, analysts do not have to spend their time and economic resources to acquire or develop idiosyncratic information because using common information is helpful to increase earings forecast accuracy. In sum, while analysts tend to place more reliance on idiosyncratic information rather than common information as for firms with high accruals quality, we find that their efforts on generating idiosyncratic information do not contribute to increase the accuracy of earnings forecasts. Our study suggests that it is cost effective for analysts to evaluate firms` accruals quality before they work harder to exploit more idiosyncratic information to increase the accuracy of earnings forecasts. Our results are consistent with Lobo et al.(2006) which find that low accruals quality are followed by a great number of analysts in response to greater demand on analyst services and more effort by analysts when firms have high information risk. Prior studies find that corporate disclosures are important source for analysts in forming their earnings forecasts. Byard and Shaw(2002) find that analysts rely more heavily on publicly available financial data rather than privileged communication with management. Evidence on how analysts use accounting information is still one of the main issues among those interested in understanding analysts` role as information intermediaries. Our study contributes to better understand how analysts react to market participants by analyzing that earnings forecast accuracy differs according to not only information environments but also its interaction effect with the quality of accounting information.

감사인의 국제회계기준 도입 자문서비스와 재무분석가의 예측정확성 및 수요: K-IFRS 연결재무제표를 중심으로

이우재 ( Woo Jae Lee ),정석우 ( Seok Woo Jeong ),최승욱 ( Seung Uk Choi ) 한국회계학회 2014 회계학연구 Vol.39 No.3

본 연구는 감사인의 한국채택국제회계기준(K-IFRS) 도입관련 자문서비스의 제공 여부가 재무분석가의 해당 기업에 대한 이익예측특성과 관련이 있는지 연결재무제표를 중심으로 분석한다. 이를 통해 K-IFRS의 도입으로 증가한 재무분석가 예측환경의 복잡성이 감사인의 KIFRS자문서비스 제공에 따라 감소하는지 검증하며, 재무분석가 예측특성으로는 정확성의 대용치인 이익예측정확성과 예측이익표준편차, 예측수요를 나타내는 재무분석가 수를 이용한다. K-IFRS 도입관련 자문서비스가 감사서비스와 함께 제공될 경우, 감사인은 K-IFRS가 피감사기업의 재무제표 전반에 미치는 영향을 사전적으로 검토하는 기회를 가지게 된다. 따라서 피감사기업에 최적화된 K-IFRS 관련 이해를 바탕으로 감사인의 전문성이 제고됨에 따라 회계정보이용자들은 보다 높은 품질의 회계정보를 이용할 수 있을 것이다. 이에 본 연구는 감사인의 자문서비스로 인한 재무보고품질의 향상이 재무분석가의 이익예측능력에 어떠한 영향을 미치는지 살펴보고자 한다. 실증분석 결과는 다음과 같다. 우선, K-IFRS 도입관련 자문서비스를 받은 기업들에 대한 재무분석가 예측정확성이 증가하였으며, 예측이익표준편차가 감소하고 재무분석가의 수가 증가하였다. 또한 감사인의 K-IFRS 자문서비스 제공 여부 외에 해당 서비스를 받은 기업들이 감사인에게 지급한 K-IFRS 관련 서비스 비용의 누적 값을 이용하여 재무분석가의 이익예측정확성 및 예측수요와의 관련성을 살펴보았다. 그 결과 자문용역에 대한 누적 보수가 증가할수록 해당 기업에 대한 이익예측치를 제공하는 재무분석가 수가 증가하며, 예측정확성이 높아지고 재무분석가 의견불일치 정도가 줄어드는 것으로 나타났다. 이는 감사인이 피감사기업에 K-IFRS 자문서비스를 제공하는 경우, 해당 기업에 대한 재무분석가의 예측환경에 긍정적인 영향을 주어 이익의 예측가능성을 높이는 데 도움을 주는 것으로 해석할 수 있다. This paper investigates whether the auditor-provided K-IFRS advisory service has an effect on the accuracy and demand of analysts` forecasts for consolidated financial statements. Auditor`s IFRS advisory service is expected to improve analysts` information environment because incumbent auditors` enhanced understanding about firms` accounting system alleviates the complexity and uncertainty in analysts` forecasting caused by K-IFRS adoption. To prepare for the mandatory IFRS adoption in 2011, many listed firms in Korea purchased K-IFRS advisory services from incumbent auditors as a non-audit service after the K-IFRS adoption plan was announced in 2007. Because the K-IFRS adoption requires technical knowledge and experience, many listed firms purchased K-IFRS adoption advisory services from their auditors rather than preparing on their own. When incumbent auditors provide advisory services to firms for the preparation of K-IFRS adoption, they are more likely to better understand about firms` accounting issues firms face in preparing financial statements based on K-IFRS. Also, the more money auditors receive from firms for the service, the more effort auditors are likely to put on the service which will lead to better understanding of the firms` situation for issues in adopting K-IFRS. Financial analysts are likely to consider the effect of provision of K-IFRS adoption advisory services by incumbent auditors when they forecast earnings under K-IFRS. In this paper, we use two measures to capture the impact of K-IFRS advisory services: the dummy variable which indicates whether the firm purchased K-IFRS advisory services or not, and the amount of expenditure for the service. To test the effect of auditor-provided K-IFRS advisory service on analyst forecast accuracy and demand, we use following three measures: absolute forecast error and forecast dispersion as proxies for forecast accuracy, and the number of analysts following as a proxy for forecast demand. We focus on analysts` forecasts for consolidated financial statements rather than separate financial statements because primary financial statements under K-IFRS are consolidated financial statements. We believe that by purchasing K-IFRS advisory services from incumbent auditors, auditors may improve the information quality of consolidated financial statement by controlling firms` opportunistic behavior and/or clearing uncertainties in accounting treatment, which eventually affects analyst forecast accuracy and demand for consolidated financial statement earnings. We use individual forecasts for listed in the Korean Stock market rather than consensus because we allow the difference among analysts forecast ability and their accuracy. By analyzing 7,332 firm-year-analyst forecast data of listed firms for consolidated financial statements in 2011, we find that analysts` absolute forecast errors and forecast dispersion decreased and the number of analyst following increased for firms which purchased K-IFRS consulting services from their auditors. Furthermore, we document the accuracy and dispersion of analysts` forecasts have been improved more, when firms spend more money for the advisory services for the K-IFRS adoption. These results imply that the provision of K-IFRS adoption advisory service helps incumbent auditors to better understand firms and leads to provide higher quality audits, thereby improve information environment analysts face after K-IFRS adoption. To check the robustness of our results we also perform several sensitivity tests. First, we run two-stage and change variable regressions to control potential sample selection bias problems. Second, we exclude early K-IFRS adopters from our main samples and re-run regressions. Third, 59% of firms purchase K-IFRS advisory service from their incumbent auditors in our sample, so we re-estimate regressions by using subsample of only purchasers of advisory service from their auditors. Forth, we retest the results by using matching sample firms. We select matching firms based on firm size and industry. Fifth, we check whether our results change depending on the timing of advisory service purchasing year because early purchasers may have larger benefits from K-IFRS adoption. Most results from our robustness tests are qualitatively similar to our results of main tests. Our paper makes several contributions to the existing literature. First, our results show the important roles of auditor-provided advisory service when accounting standards are mandatorily adopted. Investors are concerned whether auditors compromise their independence when they provide both audit and non-audit services to their client. Our results suggest that advisory services for K-IFRS adoption by incumbent auditors turn out to be useful for investors. Second, the results of our paper shed light on the growing body of literature of the effects of K-IFRS on accounting information quality. By providing evidence that analysts` forecasts for firms that purchase advisory services early for K-IFRS adoption are more accurate, our paper suggests that firms may have bigger benefits if they prepare early for the adoption when new accounting standards are mandatorily introduced across all firms by regulation. However, we should be cautious in interpreting the results of this study because sample periods covered in this study is the mandatory adoption year and this study focus on consolidated financial statements prepared under K-IFRS only. Further, even though we try to reduce endogeneity caused by sample selection bias, there still is a concern about the issue. In addition our study does not consider and test whether other K-IFRS related non-audit services may improve the analysts` forecast accuracy and demand.

은퇴시점 재무분석가의 이익예측특성

최정운 한국회계정책학회 2015 회계와 정책연구 Vol.20 No.3

본 연구는 은퇴시점 재무분석가의 이익예측특성을 조사한다. 재무분석가의 유인을 분석대상기업과의 관계유지와 거래량 증대를 통한 소속 증권회사의 수수료 수입 증가에 근거한 낙관적 이익예측 유인과 시장의 평판 형성 및 유지에 근거한 정확한(또는 덜 낙관적인) 이익예측 유인으로 구분할 수 있다. 따라서 본 연구는 재무분석가의 은퇴시점에 초점을 맞추어, 상대적으로 시장의 평판으로부터 자유로울 수 있는 시점에 제시하는 이익예측이 보다 더 낙관적인지를 조사한다. 이는 역으로 은퇴시점이 아닌 재무분석가가 시장의 평판을 고려하고 있음을 간접적으로 조사할 수 있다는 점과, 시장의 평판이 유효하게 작동될 수 있는 시기를 구분함으로서 시장의 평판을 직접 측정하는데 따르는 오차를 회피할 수 있는 점에서 장점이 있다. 실증결과, 은퇴시점 재무분석가의 이익예측치가 상대적으로 낙관성이 높게 나타났다. 또한 시장최초진입, 증권사 이동 재무분석가에 비해 은퇴시점 재무분석가의 이익예측치가 상대적으로 높은 낙관성을 보이고, 은퇴 재무분석가로 한정한 분석에서도 은퇴 이전 시기에 비해 은퇴시점의 이익예측치가 상대적으로 낙관적 수준이 높게 나타났다. 이는 은퇴시점 재무분석가의 이익예측 과정에서 시장의 평판이 유효하게 고려되지 않는다고 해석할 수 있다. 이러한 결과는 역으로 은퇴시점이 아닌 재무분석가는 시장의 평판을 상대적으로 중요하게 고려하고 있음을 추측할 수 있다. 따라서 재무분석가의 이익예측치가 전반적으로 낙관적인 특성을 가진다는 우려에도 불구하고 여전히 시장의 평판은 유효하게 작동하고 있으며, 과도한 낙관적 편향의 문제점을 보완하기 위하여 시장 평판에 대한 유인을 강화할 필요가 있다는 정책적 시사점을 제공한다. This study investigates the relation between analyst retirement and forecast properties. The favorable relations with firms and brokerage’s commissions affect analysts’ forecast optimism. In contrast, market reputations affect analysts’ forecast accuracy(or conservative forecast). But there is no longer a need for considering market reputation at the time they retire. So this study focuses on the effect of market reputation on analysts at the time they retire. The results are following. Analysts’ forecasts are more optimistic at the time they retire. And analysts’ forecasts are more optimistic, compared with rookie or changing brokerage analysts. These results indicate that market reputation cannot be considered by analysts at the time they retire. In contrast, these results indicate that incumbent analysts still consider market reputation for forecast accuracy. These findings show that market reputation for forecast accuracy(or conservative forecast) is effective though forecasts are generally optimistic. This study contributes to the growing literature on the effect of analysts’ reputation on forecast accuracy. And as focusing on the analysts’ retirement time, this study can avoid measurement errors to capture market reputation for forecast accuracy.