The Impact of Fund Characteristics on the Use of Analyst Forecasts

2013 ◽  
Author(s):  
Alexander Franck ◽  
Alexander Gabriel Kerl
Keyword(s):  
2017 ◽  
Vol 93 (4) ◽  
pp. 309-333 ◽  
Author(s):  
Kin Lo ◽  
Serena Shuo Wu

ABSTRACT We examine the impact of Seasonal Affective Disorder (SAD) on financial analysts. We hypothesize and find that analysts are more pessimistic, less precise, and more asymmetric in their boldness in the fall, as indicated by their forecasts of quarterly earnings. The effects are apparent in all forecast horizons analyzed and robust across multiple specifications. Importantly, pessimism in fall forecast revisions shows analyst-specific persistence, providing a strong indication that the effect is a result of SAD rather than other coincident factors. We also find evidence of a reversal in pessimism in the spring. Additional analyses show that analyst forecasts exhibit less seasonality than equity returns, and that the presence of analyst forecasts in the fall is associated with attenuation in the seasonal pattern in stock returns. Overall, the evidence suggests that SAD affects both financial analysts and equity investors, but the effect on the latter is stronger. JEL Classifications: G11; G12; G14; G41; M41. Data Availability: Data are available from public sources cited in the text.


The authors examine the impact that the monthly Employment Situation Report issued by the Bureau of Labor Statistics (BLS) and the analyst forecasts of that report have on the U.S. Treasury securities market. Surprise increases in total non-farm payroll employment lead to increases in interest rates (especially one- to five-year rates), and surprise decreases lead to smaller declines in interest rates. This interest rate reaction is conditioned on the level of analyst uncertainty about the coming report. Interest rates also react to subsequent revisions of the payroll employment figures. Analyst forecasts as compiled by Bloomberg are unbiased forecasts of the BLS numbers and correctly anticipate most employment level changes. Moreover, there is evidence that the markets react to these forecasts prior to the BLS release. The authors also find that the release of the employment report lowers market uncertainty about future interest rates.


2014 ◽  
Vol 15 (2) ◽  
pp. 92-109 ◽  
Author(s):  
Alexander Franck ◽  
Alexander Kerl
Keyword(s):  

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Wessel M. Badenhorst

Analysts’ earnings and book value forecasts play an important role in price discovery in equity markets. As the role of fair value measurements in accounting increases, the impact on analysts’ ability to accurately forecast earnings and book values is unclear. This article develops a method to calculate the degree of fair value measurement in financial statements and investigates the impact thereof on the accuracy of analysts’ book value and earnings forecasts, using a sample of firms listed in the United States and the United Kingdom from 2010 to 2014. Relying on multivariate regression findings, the article shows that greater fair value intensity decreases the 12-month analyst forecast accuracy for earnings in both countries. Moreover, there is some evidence that higher fair value intensity decreases the accuracy of analysts’ book value forecasts. It therefore appears that increased fair value intensity under a mixed measurement approach limits the ability of analysts to forecast earnings, without a compensating impact on forecasts of book values.


2015 ◽  
Vol 35 (2) ◽  
pp. 167-185 ◽  
Author(s):  
Yi (Ava) Wu ◽  
Mark Wilson

SUMMARY The accuracy and other properties of analyst earnings forecasts represent potentially useful proxies for the impact of audit quality on client financial reports. Extant research in the auditing literature, however, is characterized by diametrically opposite predictions and inconsistent findings regarding the relationship between audit quality and analyst forecast accuracy. We argue that a potential reason for the inconsistency in the literature reflects these studies' focus on end-of-year forecast accuracy, which is subject to competing effects of audit quality. High-quality auditors may simultaneously improve forecast accuracy through their impact on the decision usefulness of clients' prior period reports, and reduce forecast accuracy by constraining client attempts to manage earnings in the direction of the consensus forecast. We argue and present evidence in support of the conjecture that analysts' beginning-of-year forecasts are a superior metric for identifying the impact of audit quality on the properties of analyst forecasts because the decision usefulness effect of audit quality should be dominant with respect to those forecasts. Data Availability: Data are available from sources identified in the article.


Author(s):  
Marc R. Bernard

This study analyzes the impact of CEO turnover on the accuracy of analyst forecasts. Specifically, it examines the level of information that becomes available to analysts covering firms with different levels of internationalization, a proxy for firm complexity, during periods surrounding these events. After controlling for analyst and firm characteristics, along with regulatory period variables, this study finds that the accuracy of analyst forecasts improves in periods immediately following the turnover event. Results further indicate that the accuracy in the post-turnover period is greater for firms with lower levels of internationalization. In general, these findings are consistent with prior research describing the improvement of forecasts surrounding the CEO turnover event, the positive link between forecast accuracy and company disclosures, and finally, the negative link between analyst forecast accuracy and the complexity of the forecasting task.


2019 ◽  
Vol 27 (1) ◽  
pp. 151-188
Author(s):  
Sherwood Lane Lambert ◽  
Kevin Krieger ◽  
Nathan Mauck

Purpose To the authors’ knowledge, this paper is the first to use Detail I/B/E/S to study directly the timeliness of security analysts’ next-year earnings-per-share (EPS) estimates relative to the SEC filings of annual (10-K) and quarterly (10-Q) financial statements. Although the authors do not prove a causal relationship, they provide evidence that the average time from firms’ filings of 10-Ks and 10-Qs to the release of analysts’ annual EPS forecasts during short timeframes (for example, 15-day timeframe from a 10-K’s SEC file date) subsequent to the 10-K and 10-Q filing dates significantly shortened with XBRL implementation and then remained relatively constant following implementation. Design/methodology/approach Using filing dates hand-collected from the SEC website for 10-Ks during 2009-2011 and filing dates for 10-Ks and 10-Qs during 2003-2014 input from Compustat along with analysts’ estimated values for next year EPS, actual estimated next year EPS realized and estimate announcement dates in Detail I/B/E/S, the authors study the days from 10-K and 10-Q file dates to announcement dates and the per cent errors for individual estimates during per- and post-XBRL eras. Findings The authors find that analysts are announcing next-year EPS forecasts significantly more frequently and in significantly shorter time in zero to 15 days immediately following 10-K and 10-Q file dates post-XBRL as compared to pre-XBRL. However, the authors do not find a significant change in forecast accuracy post-XBRL as compared to pre-XBRL. Research limitations/implications Because this study uses short timeframes immediately following the events (filings of 10-Ks and 10-Qs), the relationship between 10-Ks and 10-Qs with and without XBRL and improved forecast timeliness is strengthened. However, even this strengthened difference-in-difference methodology does not establish causality. Future research may determine whether XBRL or other factors cause the improved forecast timeliness the authors’ evidence. Practical implications This improved efficiency may become critical if financial statement reporting expands as a result of new innovations such as Big Data and continuous reporting. In the future, users may be able to electronically connect to financial statement data that firms are maintaining on a perpetual basis on the SEC website and continuously monitor and analyze the financial statement data dynamically in real time. If so, then unquestionably, XBRL will have played a critical role in bringing about this future innovation. Originality/value Whereas previous studies have utilized Summary IBES data to assess the impact of XBRL on analyst forecasts, the authors use Detail IBES to study the effects of XBRL adoption directly by measuring days from 10-K and 10-Q file dates in Compustat to each estimate’s announcement date recorded in IBES and by computing the per cent error using each estimate’s VALUE and ACTUAL recorded in Detail IBES. The authors are the first to evidence a significant shortening in average days and an increase in per cent of 30-day counts in the zero- to 15-day timeframe immediately following the fillings of 10-K s and 10-Qs.


2021 ◽  
pp. 1-24
Author(s):  
Shaorou Hu ◽  
Ming Liu ◽  
Byungcherl Charlie Sohn ◽  
Desmond C. Y. Yuen

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