CEO Compensation Mix and Analysts' Forecast Accuracy and Bias PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download CEO Compensation Mix and Analysts' Forecast Accuracy and Bias PDF full book. Access full book title CEO Compensation Mix and Analysts' Forecast Accuracy and Bias by Kiridaran (Giri) Kanagaretnam. Download full books in PDF and EPUB format.
Author: Kiridaran (Giri) Kanagaretnam Publisher: ISBN: Category : Languages : en Pages : 40
Book Description
We investigate the relation between the proportion of total compensation received by CEOs from stock options and the accuracy and bias of analysts' earnings forecasts. We hypothesize that forecast accuracy decreases as the proportion of stock option pay increases. Higher proportions of stock options induce managers to undertake riskier projects, to change and/or reallocate their effort, to manipulate accounting earnings, and to make opportunistic voluntary disclosures, resulting in an increase in the complexity of forecasting. We also examine the relation between forecast bias and the proportion of stock option pay. Analysts' optimistic forecast bias increases as the proportion of stock option pay increases. Because forecast complexity increases with stock option pay, analysts, needing greater access to management's information to produce accurate forecasts, have incentives to increase the optimistic bias in their forecasts. Our empirical evidence indicates that analysts' earnings forecast accuracy decreases and forecast optimism increases as the proportion of CEO compensation from stock options increases, even after controlling for previously identified determinants of forecasting difficulty.
Author: Kiridaran (Giri) Kanagaretnam Publisher: ISBN: Category : Languages : en Pages : 40
Book Description
We investigate the relation between the proportion of total compensation received by CEOs from stock options and the accuracy and bias of analysts' earnings forecasts. We hypothesize that forecast accuracy decreases as the proportion of stock option pay increases. Higher proportions of stock options induce managers to undertake riskier projects, to change and/or reallocate their effort, to manipulate accounting earnings, and to make opportunistic voluntary disclosures, resulting in an increase in the complexity of forecasting. We also examine the relation between forecast bias and the proportion of stock option pay. Analysts' optimistic forecast bias increases as the proportion of stock option pay increases. Because forecast complexity increases with stock option pay, analysts, needing greater access to management's information to produce accurate forecasts, have incentives to increase the optimistic bias in their forecasts. Our empirical evidence indicates that analysts' earnings forecast accuracy decreases and forecast optimism increases as the proportion of CEO compensation from stock options increases, even after controlling for previously identified determinants of forecasting difficulty.
Author: David F. Salerno Publisher: ISBN: Category : Chief executive officers Languages : en Pages : 153
Book Description
Extant research indicates that earnings attributes are important considerations to corporate decision makers and users of accounting information (e.g., Francis et al., 2004). One such attribute is earnings quality; often measured as the magnitude of accruals that do not convert to cash in a timely manner, where a poor match of cash flows and accruals indicates low earnings quality (e.g., Dechow and Dichev, 2002). Such accruals could be used to manage earnings, a practice that aims to achieve a pre-determined level of earnings by using accounting techniques rather than actual firm performance. This study consists of two essays and examines the effect of earnings quality on two groups of financial statement users; specifically financial analysts and CEO compensation setters. The first essay investigates the impact of earnings quality on earnings forecast accuracy, forecast dispersion, and forecast optimism of individual financial analysts. The primary model employed for analyst forecast accuracy is consistent with Barniv et al. (2005), Clement (1999), and Jacob et al. (1999). Further reduced model of forecast accuracy based on variables used by Bae et al. (2008) is also used. The forecast dispersion model is based on that of Behn (2008), and forecast optimism is measured following Cowen et al. (2006). The findings show that when earnings quality is higher, analyst forecasts exhibit greater accuracy and lower optimism. Higher earnings quality has some impact on forecast dispersion; however the affect largely disappears when correcting for correlation within firm clusters. The second essay examines whether earnings quality plays a role in CEO compensation when corporate earnings satisfy (or fail to satisfy) the market's expectations. Specifically, Essay II examines CEO bonus as the measure of compensation used to reward the CEO for performance. Because such rewards are often accomplished with cash compensation, and because salary is usually set before the start of the year, the bonus portion of the CEO's total pay package is likely to be affected by earnings quality (Matsunaga and Park (2001). The results provide evidence that lower earnings quality is associated with higher CEO bonus compensation for firms that have satisfied market earnings expectations.
Author: Dan Bernhardt Publisher: ISBN: Category : Languages : en Pages : 27
Book Description
In a recent paper, Bernhardt et al. (2004) developed a non-parametric test for bias in forecasts by professional financial analysts that is robust to correlated information amongst analysts and information arrival over the forecasting cycle. The tests show that analysts anti-herd: Analysts systematically issue biased contrarian forecasts that overshoot the publicly-available consensus forecast in the direction of their private information. In this campanion paper, we show that for those analysts that report later in the forecast-horizon, a reward scheme that is convex in relative performance may shed some light on this strategic behavior. The pattern and magnitude of the forecast bias in the last forecast are identical to the results in Bernhardt et al., and slightly higher in some sub-samples. An analysis of daily returns around the date of earnings announcement reveals that investors do not fully unravel the bias in late forecasts.
Author: Guido Bolliger Publisher: ISBN: Category : Languages : en Pages : 60
Book Description
During the last decade, a surprisingly high percentage of U.S. companies has fulfilled or beaten analysts' earnings per share forecasts. One of the most frequently cited reasons for this growing tendency is a change in the nature of U.S. executive compensation structure. As stock options have become an increasingly important part of executive compensation, the preservation or enhancement of short term stock value around the earnings announcement has become a priority for managers. Besides earnings management, a widespread way to meet analyst expectations is to inject pessimism into their forecasts by providing analysts with negative clues, or so-called downward guidance. This paper is the first to investigate the relationship between the practice of analyst guidance and executive compensation packages. We document a strong link between expectations management and the relevant options component of CEO compensation, bonus plans, and the percentage of the company's shares owned by the CEO who manages it. In a second set of tests, we show that firms which meet or beat analyst forecasts at the earnings announcement generate positive abnormal returns, which are significantly lower for firms suspected of managing expectations.
Author: Murugappa (Murgie) Krishnan Publisher: ISBN: Category : Languages : en Pages :
Book Description
In this paper, we provide an equilibrium explanation for the observed optimism in analysts' earnings forecasts. Our analysis provides theoretical support to the widely held notion that analysts engage in earnings optimism to gain access to management's private information. We show that a strategic analyst, who is motivated by improving the combined accuracy of his forecasts, issues a biased initial forecast to extract information from management, but issues unbiased forecasts subsequently. The management, on the other hand, provides more access because this optimistic bias reduces the proprietary costs associated with disclosure at the margin. An important element of our model is the assumption that analysts also have private information relevant to assessing firm value. Despite rational expectations about analyst bias, analysts' private information cannot be fully unravelled by other agents due to the noise introduced by the diversity in analysts' incentives.
Author: John T. Mentzer Publisher: SAGE ISBN: 1452238391 Category : Business & Economics Languages : en Pages : 369
Book Description
Incorporating 25 years of sales forecasting management research with more than 400 companies, Sales Forecasting Management, Second Edition is the first text to truly integrate the theory and practice of sales forecasting management. This research includes the personal experiences of John T. Mentzer and Mark A. Moon in advising companies how to improve their sales forecasting management practices. Their program of research includes two major surveys of companies′ sales forecasting practices, a two-year, in-depth study of sales forecasting management practices of 20 major companies, and an ongoing study of how to apply the findings from the two-year study to conducting sales forecasting audits of additional companies. The book provides comprehensive coverage of the techniques and applications of sales forecasting analysis, combined with a managerial focus to give managers and users of the sales forecasting function a clear understanding of the forecasting needs of all business functions. New to This Edition: The author′s well-regarded Multicaster software system demo, previously available on cassette, has been updated and is now available for download from the authors′ Web site New insights on the critical area of qualitative forecasting are presented The results of additional surveys done since the publication of the first edition have been added The discussion of the four dimensions of forecasting management has been significantly enhanced Significant reorganization and updating has been done to strengthen and improve the material for the second edition. Sales Forecasting Management is an ideal text for graduate courses in sales forecasting management. Practitioners in marketing, sales, finance/accounting, production/purchasing, and logistics will also find this easy-to-understand volume essential.
Author: Michael Gilliland Publisher: John Wiley & Sons ISBN: 1119782473 Category : Business & Economics Languages : en Pages : 435
Book Description
Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field In Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo deliver relevant and timely insights from some of the most important and influential authors in the field of forecasting. You'll learn about the role played by machine learning and AI in the forecasting process and discover brand-new research, case studies, and thoughtful discussions covering an array of practical topics. The book offers multiple perspectives on issues like monitoring forecast performance, forecasting process, communication and accountability for forecasts, and the use of big data in forecasting. You will find: Discussions on deep learning in forecasting, including current trends and challenges Explorations of neural network-based forecasting strategies A treatment of the future of artificial intelligence in business forecasting Analyses of forecasting methods, including modeling, selection, and monitoring In addition to the Foreword by renowned researchers Spyros Makridakis and Fotios Petropoulos, the book also includes 16 "opinion/editorial" Afterwords by a diverse range of top academics, consultants, vendors, and industry practitioners, each providing their own unique vision of the issues, current state, and future direction of business forecasting. Perfect for financial controllers, chief financial officers, business analysts, forecast analysts, and demand planners, Business Forecasting will also earn a place in the libraries of other executives and managers who seek a one-stop resource to help them critically assess and improve their own organization's forecasting efforts.
Author: Kiridaran (Giri) Kanagaretnam
Author: Kiridaran (Giri) Kanagaretnam
Author: David F. Salerno
Author: Dan Bernhardt
Author: American Accounting Association
Author: Hakan Saraoglu
Author: Guido Bolliger
Author: Murugappa (Murgie) Krishnan
Author: Anachit Bagntasarian
Author: John T. Mentzer
Author: Michael Gilliland