Managerial Earnings Forecasts Bias and Managers' Decision to Issue Earnings Guidence PDF Download
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Author: Yoel Beniluz
Publisher:
ISBN:
Category : Business forecasting
Languages : en
Pages : 248
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Book Description
Author: Yoel Beniluz
Publisher:
ISBN:
Category : Business forecasting
Languages : en
Pages : 248
Get Book Here
Book Description
Author: Yoel Beniluz
Publisher:
ISBN:
Category :
Languages : en
Pages : 55
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Book Description
This paper examines the hypothesis that when disappointing information regarding a firm's performance is released, the firm's management faces particularly strong incentives to counter the disappointing news with overly optimistic forward-looking statements. To address this issue, the paper investigates the properties of management earnings forecasts released simultaneously with earnings announcements. The paper predicts and finds that the more disappointing the earnings announcement news, the higher the optimistic bias in the simultaneously released management long-horizon forecasts of annual earnings. Since managers may use short-horizon forecasts of quarterly earnings to avoid disappointing earnings announcements, the paper also examines the interplay between management short-horizon forecasts of quarterly earnings and long-horizon forecasts of annual earnings that are released simultaneously. The paper documents a significantly negative association between the news contained in the short-horizon forecasts of quarterly earnings and the optimistic bias in the accompanying long-horizon forecast of annual earnings. The paper also investigates the link between management's decision to issue earnings guidance and the contemporaneous earnings announcement news, finding that, in general, more extreme earnings announcement news results in more earnings guidance. Finally, using market reaction tests, the paper documents that market participants are aware, at least to some extent, of management's tendency to counter disappointing earnings news with overly optimistic forecasts.
Author: Amy P. Hutton
Publisher:
ISBN:
Category :
Languages : en
Pages : 53
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Book Description
Prior to Regulation Fair Disclosure (Reg FD) some management spent considerable time and effort guiding analyst earnings estimates, often through detailed reviews of analysts' earnings models. In this paper I use proprietary survey data from the National Investor Relations Institute to identify firms that reviewed analysts' earnings models prior to Reg FD and those that did not. Under the maintained assumption that firms conducting reviews implicitly or explicitly guided analysts' earnings forecasts, I document firm characteristics associated with the decision to provide private managerial earnings guidance. Then, I document the characteristics of 'guided' versus 'unguided' analyst earnings forecasts. Findings demonstrate an association between several firm characteristics and guidance practices: managers are more likely to review analyst earnings models when the firm's stock is highly followed by analysts and largely held by institutions, when the firm's market-to-book ratio is high, and its earnings are important to valuation (high Industry-ERC R2), but hard to predict because its business is complex (high # of Segments). A comparison of guided and unguided quarterly forecasts indicates that guided analyst estimates are more accurate, but also more frequently pessimistic. An examination of analysts' annual earnings forecasts over the fiscal year does not distinguish between guidance and no guidance firms; both experience a quot;walk downquot; in annual estimates. To distinguishing between guidance and no guidance firms, one must examine quarterly earnings news: unguided analysts walk down their annual estimates when the majority of the quarterly earnings news is negative, guided analysts walk down their annual estimates even though the majority of the quarterly earnings news is positive.
Author: Amy P. Hutton
Publisher:
ISBN:
Category :
Languages : en
Pages : 46
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Book Description
Abstract: Prior to Regulation Fair Disclosure some management spent considerable time and effort guiding analyst earnings estimates; other management did not. In this paper I examine the determinants and consequences of management's decision to work with analysts in the development of their earnings estimates using proprietary survey data from the National Investor Relations Institute. Findings suggest that when earnings are important to valuation but hard to forecast because businesses and financial transactions are complex, management is more likely to provide assistance to analysts presumably to avoid inaccurate analyst forecasts and negative earnings surprises. A comparison of guided and unguided analyst forecasts indicates that guided quarterly earnings forecasts are more accurate but also more frequently pessimistic, consistent with analysts rationally trading offbias for accuracy to retain access to management's earnings guidance. Cross-sample comparisons of analysts' stock recommendations and long-term growth forecasts provide additional support for the hypothesis that analyst objectivity and independence is affected by management's decision to provide earnings guidance. Finally, evidence from stock price reactions to deviations from the consensus forecast (the traditional measure of earnings surprises) indicates that investors distinguish between guided and unguided analyst forecasts when forming their earnings expectations. This study furthers our understanding of what factors affect management's disclosure choices and how managers' disclosure choices influence the objectivity and independence of sell-side analysts.
Author: Cheng Few Lee
Publisher: World Scientific
ISBN: 9811202400
Category : Business & Economics
Languages : en
Pages : 5053
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Book Description
This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.
Author: Andrew A. Anabila
Publisher:
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
The safe harbor provisions have increased over the years, following the Private Securities Litigation Reform Act (PSLRA) of 1996 and the Securities Litigation Uniform Standards Act (SLUSA) of 1998. The objective is to encourage more earnings guidance by managers. However, a number of firms like Coca Cola and Gillette moved to abandon quantitative earnings forecasts, due to concerns over the markets' response when they miss their forecasts. This study examines the determinants of management earnings forecasts bias and inaccuracy. The evidence suggests that forecast bias and inaccuracy are not systematically associated with diversification however, are associated with the fraction of nonoperating assets. Also, capital structure, audit quality and institutional holdings are systematic determinants of forecast bias and inaccuracy. Finally, industry attributes of munificence, dynamism and concentration are indicators of inherent imperfections of management forecasts, but are exogenous to management's control. The reasons for, and implications of these findings are discussed.
Author: Mark Bagnoli
Publisher:
ISBN:
Category :
Languages : en
Pages : 58
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Book Description
We ask whether the history of interactions between a firm and its analysts affects management's quarterly earnings forecast decision and analysts' subsequent earnings estimate revisions. We show that the history of their interactions not only reflects their individual incentives but is also used to form expectations about current decisions. Specifically, guidance is more likely to be pessimistically biased if management has a history of offering pessimistic forecasts and if analysts have tended to respond passively (i.e., by mimicking guidance or revising in the direction indicated by management). Individual analysts are more likely to respond passively to management's current forecast if they have historically responded in such a manner or if management has tended to offer unbiased or accurate guidance. Analysts with superior earnings forecasting track records are less likely to respond passively to guidance that is pessimistically biased. Collectively, our results indicate that downward bias in quarterly guidance and information production by analysts depend on what management and analysts have learned about each other over time as reflected in their forecasting histories.
Author: Richard A. Cazier
Publisher:
ISBN:
Category :
Languages : en
Pages : 47
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Book Description
In this study we examine whether managers' voluntary forecasts of future earnings are consistent with the implicit forecasts of future earnings that underlie a specific mandatory accrual, the valuation allowance. This accrual relies heavily on managerial estimation and is also based, in part, on managers' private, forward-looking information. Thus, it provides an ideal setting to investigate the interplay between voluntary and mandatory financial disclosures. By examining the consistency between the voluntary and mandatory forecasts, we are also able to provide insight into whether the predictable accrual-related bias in voluntary earnings forecasts carries over into the mandatory forecast embedded in the valuation allowance. We then investigate whether the biased voluntary earnings guidance helps analysts and investors more accurately interpret the information in valuation allowance changes about future earnings expectations. To increase the power of our tests we utilize a sample of loss firms, which frequently record valuation allowances to fully or partially offset deferred tax assets.We first document that more than 62 percent of our sample of loss firms report valuation allowance changes and management earnings guidance that convey the same basic information about future earnings (i.e., either both forecast profit or both forecast loss). Thus, these voluntary and mandatory forecasts are largely consistent with each other. We then provide evidence that managers provide overly pessimistic forecasts for observations whose valuation allowance changes signal bad news about future earnings, but overly optimistic forecasts for observations whose valuation allowance changes signal strong good news about future earnings. Finally, our results suggest that managers' biased earnings forecasts actually help analysts and investors more accurately interpret the information about future earnings in valuation allowance changes. Our findings provide new insights into actions managers can take to improve investor and analyst processing of financial statement-based tax information.
Author: Lawrence D. Brown
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Managerial behavior differs considerably when managers report quarterly profits versus losses. When they report profits, managers seek to just meet or slightly beat analyst estimates. When they report losses, managers do not attempt to meet or slightly beat analyst estimates. Instead, managers often do not forewarn analysts of impending losses, and the analyst's signed error is likely to be negative and extreme (i.e., a measured optimistic bias). Brown (1997 Financial Analysts Journal) shows that the optimistic bias in analyst earnings forecasts has been mitigated over time, and that it is less pronounced for larger firms and firms followed by many analysts. In the present study, I offer three explanations for these temporal and cross-sectional phenomena. First, the frequency of profits versus losses may differ temporally and/or cross-sectionally. Since an optimistic bias in analyst forecasts is less likely to occur when firms report profits, an optimistic bias is less likely to be observed in samples possessing a relatively greater frequency of profits. Second, the tendency to report profits that just meet or slightly beat analyst estimates may differ temporally and/or cross-sectionally. A greater tendency to 'manage profits' (and analyst estimates) in this manner reduces the measured optimistic bias in analyst forecasts. Third, the tendency to forewarn analysts of impending losses may differ temporally and/or cross-sectionally. A greater tendency to 'manage losses' in this manner also reduces the measured optimistic bias in analyst forecasts. I provide the following temporal evidence. The optimistic bias in analyst forecasts pertains to both the entire sample and the losses sub-sample. In contrast, a pessimistic bias exists for the 85.3% of the sample that consists of reported profits. The temporal decrease in the optimistic bias documented by Brown (1997) pertains to both losses and profits. Analysts have gotten better at predicting the sign of a loss (i.e., they are much more likely to predict that a loss will occur than they used to), and they have reduced the number of extreme negative errors they make by two-thirds. Managers are much more likely to report profits that exactly meet or slightly beat analyst estimates than they used to. In contrast, they are less likely to report profits that fall a little short of analyst estimates than they used to. I conclude that the temporal reduction in optimistic bias is attributable to an increased tendency to manage both profits and losses. I find no evidence that there exists a temporal change in the profits-losses mix (using the I/B/E/S definition of reported quarterly profits and losses). I document the following cross-sectional evidence. The principle reason that larger firms have relatively less optimistic bias is that they are far less likely to report losses. A secondary reason that larger firms have relatively less optimistic bias is that their managers are relatively more likely to report profits that slightly beat analyst estimates. The principle reason that firms followed by more analysts have relatively less optimistic bias is that they are far less likely to report losses. A secondary reason that firms followed by more analysts have relatively less optimistic bias is that their managers are relatively more likely to report profits that exactly meet analyst estimates or beat them by one penny. I find no evidence that managers of larger firms or firms followed by more analysts are relatively more likely to forewarn analysts of impending losses. I conclude that cross-sectional differences in bias arise primarily from differential 'loss frequencies,' and secondarily from differential 'profits management.' The paper discusses implications of the results for studies of analysts forecast bias, earnings management, and capital markets. It concludes with caveats and directions for future research.
Author: Jong-Hag Choi
Publisher:
ISBN:
Category :
Languages : en
Pages : 286
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Book Description
