Optimism and Accuracy in Forecasts of Financial Analysts
| Author | : Susan Marie Young |
| Publisher | : |
| Total Pages | : 214 |
| Release | : 2000 |
| Genre | : |
| ISBN | : |
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Financial Analysts' Forecasts and Stock Recommendations
| Author | : Sundaresh Ramnath |
| Publisher | : Now Publishers Inc |
| Total Pages | : 125 |
| Release | : 2008 |
| Genre | : Business & Economics |
| ISBN | : 1601981627 |
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Financial Analysts' Forecasts and Stock Recommendations reviews research related to the role of financial analysts in the allocation of resources in capital markets. The authors provide an organized look at the literature, with particular attention to important questions that remain open for further research. They focus research related to analysts' decision processes and the usefulness of their forecasts and stock recommendations. Some of the major surveys were published in the early 1990's and since then no less than 250 papers related to financial analysts have appeared in the nine major research journals that we used to launch our review of the literature. The research has evolved from descriptions of the statistical properties of analysts' forecasts to investigations of the incentives and decision processes that give rise to those properties. However, in spite of this broader focus, much of analysts' decision processes and the market's mechanism of drawing a useful consensus from the combination of individual analysts' decisions remain hidden in a black box. What do we know about the relevant valuation metrics and the mechanism by which analysts and investors translate forecasts into present equity values? What do we know about the heuristics relied upon by analysts and the market and the appropriateness of their use? Financial Analysts' Forecasts and Stock Recommendations examines these and other questions and concludes by highlighting area for future research.
The Effect of Earnings Quality on Analyst Forecast Accuracy, Dispersion, and Optimism and Implications for CEO Compensation
| Author | : David F. Salerno |
| Publisher | : |
| Total Pages | : 153 |
| Release | : 2013 |
| Genre | : Chief executive officers |
| ISBN | : |
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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.
Systematic Optimism in Financial Analysts' Earnings Forecasts
| Author | : Dmitri Yu Kantsyrev |
| Publisher | : |
| Total Pages | : |
| Release | : 2007 |
| Genre | : |
| ISBN | : |
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This study examines forecast errors in financial analysts' annual earnings forecasts and finds that analysts exhibit systematic optimism for a specific subset of companies. The magnitude of the analysts' optimistic forecast bias increases with the difficulty of the forecasting task, which is represented by statistical characteristics of a firm's earnings as well as the overall economic activity. We find that both the mean and median forecast errors are largest for companies with the most volatile earnings that move against or independently of the market earnings. We also develop a model of the analysts' forecasting behavior and provide evidence that the analysts' optimistic forecast error increases in periods of economic downturns, and somewhat slowly decreases throughout the forecast horizon. In contrast to most of the existing literature, which deals with samples, we analyze all available consensus as well as timely constructed forecasts for the 1987-2004 period.
An Empirical Study of Financial Analysts Earnings Forecast Accuracy
| Author | : Andrew Stotz |
| Publisher | : |
| Total Pages | : 122 |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
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Over the past 12 years, financial analysts across the world have been optimistically wrong with their 12-month earnings forecasts by 25.3%. This study may be the first of its kind to assess analyst earnings forecast accuracy at all listed companies across the globe, covering 70 countries. A review of prior research shows little uniformity in the preparation of the data set, yet differences in how outliers are treated, for example, can create substantially different results. This research lays out six specific steps to prepare the data set before any analysis is done.Three main conclusions come from this research: First, analyst earnings forecasts globally were 25.3% optimistically wrong, meaning on average, analysts started each year forecasting company profits of US$125, but 12 months later that company reported profits of US$100. Second, analysts had a harder time forecasting earnings for companies in emerging markets, where they were 35% optimistically wrong. Third, that analyst optimism mainly occurred when the companies they forecasted experienced very low levels of actual earnings growth, analysts did not make an equal, but opposite error for fast growth companies.
Earnings Predictability and Bias in Analysts? Earnings Forecasts
| Author | : Somnath Das |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2008 |
| Genre | : |
| ISBN | : |
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This paper examines cross-sectional differences in the optimistic behavior of financial analysts. Specifically, we investigate whether the predictive accuracy of past information (e.g., time-series of earnings, past returns, etc.) is associated with the magnitude of the bias in analysts' earnings forecasts. We posit that there is higher demand for non-public information for firms whose earnings are difficult to accurately predict than for firms whose earnings can be accurately forecasted using public information. Assuming that optimism facilitates access to management's non-public information, we hypothesize that analysts will issue more optimistic forecasts for low predictability firms than for high predictability firms. Our results support this hypothesis.
The Incremental Predictive Ability of Individual Financial Analysts
| Author | : Marc Andrew Giullian |
| Publisher | : |
| Total Pages | : |
| Release | : 1996 |
| Genre | : |
| ISBN | : |
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Financial analysts are among the most influential group of users of financial accounting information. Because the FASB has advocated usefulness as the "overriding criterion" (FASB, 1980, p.26) to judge accounting choices, accountants have a stake in understanding this important group of financial statement users. The majority of existing accounting research concerning financial analysts focuses on aggregated analysts' earnings forecasts rather than individual analysts' forecasts. Studies in accounting have documented the superiority of aggregated analysts' earnings forecasts relative to models. This is in contrast to the robust result from years of judgment/decision making (JDM) research that human predictions are inferior to statistical model predictions. Prior accounting studies have also documented that analysts exhibit optimism when forecasting earnings. Humans can make a significant contribution to accurate forecasting in spite of cognitive limitations. Some skills people bring to bear are cue identification, rapid adaptability to environmental changes and the evaluation of qualitative factors. Although statistical models are not well-equipped to utilize qualitative factors and be adaptable, they do offer consistency and significant computational power. Thus, the strengths of humans and statistical models in forecasting are complementary. This research documents the incremental predictive ability of both individual financial analysts and statistical models in forecasting earnings. It also provides evidence that both individual financial analysts' and statistical models' incremental predictive ability varies between industries. In addition, tests show a pessimistic bias for individual analysts, contrary to prior studies. Additional evidence is presented regarding forecast accuracy for four different forecast generation methods.
Proceedings of the 7th International Conference on Economic Management and Green Development
| Author | : Xiaolong Li |
| Publisher | : Springer Nature |
| Total Pages | : 2095 |
| Release | : |
| Genre | : |
| ISBN | : 9819705231 |
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Firm-specific Information Environment and Analyst Forecast
| Author | : Wei Hsu (Ph.D.) |
| Publisher | : |
| Total Pages | : 84 |
| Release | : 2019 |
| Genre | : Business forecasting |
| ISBN | : |
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I examine how firm-specific private and public information affect analyst forecast revisions. I find that when managers easily beat (struggle to meet) the consensus forecasts in the previous quarter, financial analysts revise their earnings forecasts upward (downward). The revision magnitudes are higher when there is more private information. Similarly, I find that when managers provide upward (downward) earnings guidance, analysts revise their forecasts upward (downward) more when there is more private information. In contrast, the revision magnitudes are lower when there is more public information. Additionally, I find that the magnitudes of analysts' downward revisions increase with private information prior to the stock option grant dates. I attribute these results to the analysts' dependence on managers in gleaning relevant private information. The effect of private information is smaller for firms covered by star analysts, consistent with star analysts acting as sophisticated skeptics and being more confident in their forecasts than other analysts. Further, for well-governed firms, upward revisions for positive earnings surprises are smaller when there is more private information. This is consistent with stronger governance attenuating analysts' concerns about firms' earnings quality, which in turn increases their reliance on public earnings numbers and reduces their need to accommodate managers for private information. Finally, I find that private information is negatively associated with target price forecast accuracy, and positively associated with target price forecast optimism. These results suggest that greater information asymmetry adversely affects forecast accuracy and creates incentives for analysts to appease managers to access private information.
On the Properties of Financial Analyst Earnings Forecasts: Some New Evidence
| Author | : |
| Publisher | : |
| Total Pages | : |
| Release | : |
| Genre | : |
| ISBN | : |
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The importance of information in the formation process of security prices has a long history. The dissemination of information can take on different forms depending on the legal constraints. However, in all developed financial markets, financial analysts play a prominent role in collecting, analysing and diffusing information. Financial analysts typically supply future earnings estimates and stock picking advices in the form of recommendations. Earnings estimates are the essential part of security valuation by analysts and investors. They have even become an integral part of financial reporting in the financial press. Early research has accumulated evidence that these estimates are optimistically biased. More recently, empirical studies have found that analysts' optimistic bias is lessening, that its extent differs across analysts, firm characteristics and countries. Broadly speaking, this dissertation investigates the determinants of financial analyst forecasts bias. In the first essay, I examine the relative accuracy of European financial analysts' earnings forecasts and its determinants. I show that the results obtained for US analysts can not be generalised to European analysts who face a seemingly different job market as well as several different institutional and economic environments. In the second essay, I investigate the influence of financial analysts' location on their performance. More precisely, I examine the relative performance of local versus foreign analysts on Latin American stock markets. I find foreign analysts to be more timely and more accurate than their local counterparts. In addition, I document stronger price reactions after foreign analysts' forecast revisions than after those of local analysts. The third essay is related to the declining pattern of financial analyst forecast bias. In particular, I investigate whether US CEOs compensation arrangements give CEOs incentives to manipulate analysts' expectations downward in order to release ea.
