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The purpose of this paper is to assess whether there is an association between CEO age and analysts forecast properties (particularly forecast accuracy and bias/optimism). CEOs, having the central role in managing firms, can significantly influence the financial and non-financial decisions in an organisation. Furthermore, having been identified as key culprits in past major accounting scandals, it is also important to identify the CEO characteristics that affect financial reporting decisions.

This study adopts the upper echelon theory on the relationship between CEO age and analysts forecast properties. The authors use a sample of 2,730 Australian firm-year observations for the period 2004–2013 drawn from IBES, Connect 4 and SIRCA databases.

The authors find that analyst forecast accuracy increases and bias (optimism) reduces with the CEO age. The authors conclude that earnings and related information provided to analysts improves with the CEO age, which increases the forecast accuracy and reduces bias (optimism). Additional results suggest that the positive (negative) effect of CEO age on forecast accuracy (bias) remains until the CEOs reach the age of their retirement age (65 years). The results remain consistent with a number of sensitivity tests and provide implication for stakeholders such as firms, analysts, auditors, financial statements users and regulators.

The authors demonstrate that the relationship between CEO age and analyst forecast properties is not linear but is, in fact, curvilinear substantiating concerns that CEOs that are much younger or much older do not help increase the quality of the information environment. Consequently, firms hiring CEOs in the right age bracket also benefit by having higher-quality information environment leading possibly to reduce costs such as those relating to debt and/or equity ultimately increasing firm value.

Empirical studies on the association between CEO age and analysts earnings properties in Australia are scarce and this paper contributes to the determinants of the analysts forecast accuracy and bias (optimism) and the CEO age literature.

This paper aims to examine the impact of disclosure regulation on the levels of bias and accuracy in management earnings forecasts disclosed in the prospectuses of Malaysian initial public offering (IPO). Specifically, the authors investigated the two environments of regulation (mandatory versus voluntary) to draw some conclusions regarding the benefits of regulating disclosure of management earnings forecasts.

A sample of 111 Malaysian IPOs listing on the Main Market of Bursa Malaysia from January 1, 2004 to February 29, 2012 was used. The paper uses both univariate and multivariate statistical analyses on this sample of IPOs.

The empirical results of these multivariate regressions indicated that disclosure regulation has positive and significant impact on the bias and accuracy of management earnings forecasts disclosed in IPO prospectus. In general, the study results suggest that using disclosure regulation to improve the quality of IPO earnings forecasts can be, to some extent, an effective strategy.

The findings of this study have important implications for regulators and investors. The findings can provide them some relevant insights on the improvements to the earnings forecasts accuracy and trends of the forecast (optimistic or pessimistic) after the change from mandatory to voluntary disclosure. Thus, the authorities may learn whether this change is an effective policy or whether the regime of mandatory disclosure was better for IPO companies and should be reversed.

This study is regarded as the first attempt to investigate the impact of reforms in disclosure regulation on the quality of management earnings forecasts of IPO prospectuses in a developing nation such as Malaysia. In spite of this, the paper focuses on a single country, and it contributes significant insights to the debate about the credibility of IPO management earnings forecasts.

Underpricing is one of the most important anomalies associated with initial public offerings (IPOs). The purpose of this paper is twofold; first, it examines the impact of underwriter’s market share and spread on the underpricing of IPOs; and second, it investigates the effect of management earnings forecasts bias and accuracy on the underpricing of IPOs.

A sample of 190 Malaysian IPOs listing on the main market of Bursa Malaysia from January 1, 2002 to February 29, 2012 was used and collected data were analyzed through univariate analysis and pooled ordinary least squares regression.

The empirical evidence shows that IPOs underwritten by underwriters as having high market share and charging low underwriting spread experience higher level of underpricing. The paper also finds that IPOs issued more biased earnings forecasts are related with severe underpricing. Finally, this paper reveals that the more accurate the earnings forecasts are, the more minimized will be the asymmetric information and hence, the less will be IPO underpricing.

The paper has some implications for policy makers, investors and underwriters. First, this study offers some insights for policy makers who are responsible for Malaysian financial markets current reforms. Further, knowing the importance of the economic outcomes of the earnings forecasts on underpricing for policy makers, they may adopt the findings in their discussion of costs of litigation and potential modifications in the requirements of issuing earnings forecasts. For the investors, findings may improve their understanding of equity valuation and for the underwriters, it would assist them in identifying underwriting cost.

This paper is considered the first study to extend IPO literature by investigating the relationships between underwriter’s market share, underwriter’s spread, earnings forecasts bias, earnings forecasts accuracy and IPO underpricing in an emerging country, such as Malaysia.

The purpose of this paper is to investigate the impact of audit quality and ownership structure on the degrees of accuracy and bias in earnings forecasts issued in initial public offering (IPO) prospectuses in a frontier market, Bangladesh.

The paper uses both univariate and multivariate tests on the sample of 75 IPOs. The paper employs the tests to see the association between the degree of forecast bias and three corporate governance variables.

The results reveal that the magnitude of earnings forecast bias is significantly explained by issuer, auditor reputation, proportions of capital raised from domestic as well as foreign investors, and whether the IPO firm is a start-up venture. Underwriter prestige, length of the issuing firms' operating history, leverage, whether the firm went public during a stock market boom, and forecast horizon do not appear to be statistically significant in explaining the degree of forecast bias.

Although auditor reputation and the proportion of equity retained by pre-IPO owners have been investigated in several studies on IPO forecast accuracy and/or bias, no study has attributed them to corporate governance as a whole by combining auditor reputation, and ownership categories held by small private investors and foreign portfolio investors.

This study examines the accuracy and bias of profit forecasts disclosed in prospectuses by New Zealand companies for initial public offerings during the period 1987 to 1994. The results show that profit forecasts in this period are, on average, more accurate titan those disclosed prior to 1987, which were examined in prior studies. However, the results reject the null hypothesis that profit forecasts are accurate. In examining forecast bias, the evidence shows that the forecasts are, on average, somewhat pessimistic, but not sufficiently to reject the hypothesis that profit forecasts are unbiased. Tests of the determinants of error show that larger companies make more accurate forecasts, and forecasts made in the year 1987 are less accurate than in other years. Tests of the determinants of bias show that forecasts made in 1987 are also more optimistic, and that companies with longer trading histories and pessimistic forecasts make less biased forecasts. Forecast period and industry type are not significantly related to error or bias.

This study aims to evaluate the earnings forecasting models of Hou et al. (J Account Econ, 53:504–526, 2012) and Li and Mohanram (Rev Account Stud, 19:1152–1185, 2014) in terms of bias and accuracy and validity of the implied cost of capital (ICC) estimates for a sample of initial public offerings (IPOs).

The authors use a sample of 1,657 NYSE, Amex and Nasdaq IPOs from 1972 to 2013.

The models of Hou et al. and Li and Mohanram produce relatively inaccurate and biased earnings forecasts, leading to unreliable ICC estimates, particularly for small and loss-making IPOs that constitute the bulk of new listings. As a remedy, the authors propose a new earnings forecasting model, a combination of Hou et al.’s and Li and Mohanram’s earnings persistence models, and show that it produces more accurate and less biased earnings forecasts and more valid ICC estimates.

The study contributes novel results to the literature on the validity of cross-sectional earnings models in forecasting IPO firm earnings and estimating the ICC. The findings are directly relevant for practitioners, who can improve their earnings forecasting accuracy for IPO firms and related ICC estimates. The insights can be extended to other settings where investors have limited access to financial information, such as acquisitions of private targets.

This paper examines the effect of managerial insider trading on analyst forecast accuracy, dispersion and bias. Specifically, the authors test whether insider-trading information is positively associated with the precision of earnings forecasts. In addition, this relationship between Regulation Fair Disclosure (FD) and the Galleon insider trading case is examined.

Pooled ordinary least squares (Pooled OLS) rregressions with year-fixed effects, firm-fixed effects, and firm-level clustered standard errors are used. Our proxies for forecast precision are regressed on alternative measures of insider trading activities and a vector of control variables.

Insider-trading information is positively associated with the precision of earnings forecasts. Analysts provide better forecast accuracy, less forecast dispersion and lower forecast bias among firms with insider trading in the six months leading to the forecast issues. In addition, bullish (bearish) insider trades are associated with increased (decreased) forecast bias. Insider trading information complements analysts' independent opinion and increases the precision of their forecast.

Regulators may pursue rules that promote the rapid disclosure of managerial insider trades, particularly given the increasing availability of Internet tools. Securities regulators may attempt to increase transparency and enhance the reporting procedures of corporate insiders, for example, using Internet sources with direct release to the public to ensure more timely information dissemination.

The authors document a positive association between earnings forecast precision and managerial insider trading up to six months prior to the forecast issue. This relationship is stronger after the Securities and Exchange Commission (SEC) prohibited the selective disclosure of material nonpublic information through Regulation FD. In addition, the association between insider trading and forecast accuracy has weakened after the Galleon insider trading case.

The purpose of this paper is to examine how family firms affect analyst forecast dispersion, accuracy and optimism and how earnings smoothness as the moderating factor, affects these relationships in an emerging market context.

This paper uses the population sample of firms listed on the Taiwan Stock Exchange from 2009 to 2010 as the research sample, which includes 963 firm-year observations.

The findings show that analysts following family firms are more likely to have more dispersed, less accurate and more optimism biased forecasts than those following nonfamily firms. Earning smoothness is mainly used by nonfamily firms as a signaling strategy to improve analyst forecast quality. In contrast, earnings smoothness is mainly used by families as a garbling strategy, stimulating forecast optimism. Only earnings smoothness in family firms with a high level of family ownership concentration is likely to be signaling-oriented to improve analyst forecast accuracy and mitigate analyst optimism biases.

Emerging markets are not only featured by prevailing principal-principal conflicts but also have multiple levels of agency conflicts among large shareholders, minority shareholders and professionally hired managers. This research reveals the multiple governance roles of family owners in affecting analyst forecast quality, including their entrenchment role in extracting private benefits of control through opaque environments and market discipline distortion role in aligning interests between managers and families without prioritizing meeting or beating analyst forecasts, both at the cost of minority shareholders. This research further disentangles the intertwined signaling oriented and garbiling oriented incentives associated with earnings smoothness under family governance.

The purpose of our study is to examine the influence of three external corporate governance mechanisms (continuous disclosure regulatory reform, analyst following and ownership concentration) and one internal corporate governance mechanism (board structure) on the likelihood, frequency, horizon, precision and accuracy of management earnings forecasts in the low private litigation environment of New Zealand.

The authors use a sample of 1,082 management earnings forecasts issued by 125 firms listed on the New Zealand Exchange during the 1998-2007 financial reporting periods. The authors effectively control the self-selection bias problem inherent in management earnings forecasts.

The findings provide strong evidence that corporate governance significantly influences management earnings forecast behaviour. Firms with effective corporate governance tend to forecast earnings and provide these earnings forecasts more frequently and precisely. Earnings forecasts issued by firms with more non-executive directors on the board are less optimistically biased. A possible interpretation of the findings is that effective corporate governance mechanisms are able to substitute for a private enforcement alternative.

The findings have value in informing governance choices in the absence of external disciplinary mechanisms such as private litigation.

The purpose of this paper is to identify herding behaviour on financial markets and measure the herding behaviour impact on the accuracy of analysts' earnings forecasts.

Two alternative measures of herding behaviour, on analysts' earnings forecasts are proposed. The first measure identifies herding as the tendency of analysts to forecast near the consensus. The second measure identifies herding as the tendency of analysts to follow the most accurate forecaster. This paper employs the method of The Generalised Method of Moments in order to relax any possible biases.

In both measures employed, a positive and significant relation is found between the accuracy of analysts' earnings forecasts and herding behaviour. According to the first measure analysts exhibit herding behaviour by forecasting close to the consensus estimates. According the second herding measure, it is found that analysts tend to herd towards the best forecaster at the time. Finally, it is concluded that the accuracy of analysts' forecasts increases as herding increases.

The present study triggers concerns for further research in the modelling of analysts' forecasting behaviour.

This paper proposes that a measure based on human biases is the best way to estimate and predict the analysts' earnings forecast future accuracy.