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The main purpose of this study is to examine the disclosure of earnings forecasts in firms' prospectuses to explain investor demands or, in other words, oversubscription rates of Malaysian initial public offerings (IPOs).

Ordinary least squares and robust methods were used to examine cross-sectional data comprising 466 fixed-price IPOs reported for the period from January 2000 to February 2020 on Bursa Malaysia.

The results showed that IPOs with earnings forecasts obtained higher oversubscription rates than those without earnings forecasts. IPOs with earnings forecasts provide value-relevant signals to prospective investors about the good prospects of firms, resulting in an increase in the demand for IPO shares. For the IPO samples listed during the global financial crisis (GFC) period, IPOs with earnings forecasts had negative impacts on the oversubscription rates. These results were robust to quantile methods and the two-stage least squares method.

The research findings provide fresh information for investors regarding the importance of earnings forecasts as a trustworthy signal of a firm’s quality when making share subscription decisions.

The regulator is advised to encourage issuers to include earnings forecasts in their prospectuses since such forecasts help to increase the demand for IPOs.

This study contributes to the literature by offering empirical evidence regarding the signalling impact of earnings forecast disclosures on investor demands for Malaysian IPOs. Moreover, this study provides evidence demonstrating the impact of earnings forecast disclosures on oversubscription rates of Malaysian IPOs during the GFC period.

Using a sample of 9,898 firm-year observations from 1,821 unique Chinese listed firms over the period from 2004 to 2019, this study aims to investigate whether the market rewards meeting or beating analyst earnings expectations (MBE).

The authors use an event study methodology to capture market reactions to MBE.

The authors document a stock return premium for beating analyst forecasts by a wide margin. However, there is no stock return premium for firms that meet or just beat analyst forecasts, suggesting that the market is skeptical of earnings management by these firms. This market underreaction is more pronounced for firms with weak external monitoring. Further analysis shows that meeting or just beating analyst forecasts is indicative of superior future financial performance. The authors do not find firms using earnings management to meet or just beat analyst forecasts.

The authors provide evidence of market underreaction to meeting or just beating analyst forecasts, with the market's over-skepticism of earnings management being a plausible mechanism for this phenomenon.

The findings of this study are informative to researchers, market participants and regulators concerned about the impact of analysts and earnings management and interested in detecting and constraining managers' earnings management.

The authors provide new insights into how the market reacts to MBE by showing that the market appears to focus on using meeting or just beating analyst forecasts as an indicator of earnings management, while it does not detect managed MBE. Meeting or just beating analyst forecasts is commonly used as a proxy for earnings management in the literature. However, the findings suggest that it is a noisy proxy for earnings management.

The purpose of this paper is to test whether financial analysts’ rationality in making stocks’ earnings forecasts is homogenous or not across different information regimes in stocks’ past returns.

By treating stocks’ past returns as the information variable in this study, the authors employ a threshold regression model to capture and test threshold effects of stocks’ past returns on financial analysts’ rationality in making earnings forecasts in different information regimes.

The results show that three significant structural breaks and four respective information regimes are identified in stocks’ past returns in the threshold regression model. Across the four different information regimes, financial analysts react to stocks’ past returns quite differently when making one-quarter ahead earnings forecasts. Furthermore, the authors find that financial analysts are only rational in a certain information regime of stocks’ past returns depending on a certain return-window such as one-quarter, two-quarter or four-quarter time period.

This study is different from those in the existing literature by arguing that there could exist heterogeneity in financial analysts’ rationality in making earnings forecasts when using stocks’ past returns information. The finding that financial analysts react to stocks’ past returns differently in the different information regimes of past returns adds value to the research on financial analysts’ rationality.

The purpose of this study is to investigate whether audit quality is associated with the speed with which managers revise earnings forecasts to arrive at the actual earnings through the lens of the auditor selection theory. This study examines this relationship in a unique institutional setting, Japan, where nearly all managers disclose earnings forecasts.

The authors pioneer an empirical proxy to capture the speed of management forecast revisions based on well-established principles from the finance and disclosure literatures. This proxy is tested alongside other disclosure proxies (namely, accuracy, frequency and timeliness) to assess the influence of audit quality on managerial forecasting behavior.

This empirical analysis shows that forecast revision speed is higher for firms that select higher-quality auditors. While firms that select higher-quality auditors revise forecasts in a more timely fashion, these firms revise less frequently. Moreover, the authors find that the influence of audit quality on forecast revisions is asymmetric. Specifically, the analysis of downward forecast revisions shows that higher-quality auditors are associated with firms that disclose bad news via forecasts revisions faster, more frequently and in a more timely fashion. However, the analysis of upward forecast revisions shows that higher-quality auditors have no effect on the speed with which firms disclose good news via forecast revisions, even though they are associated with less frequent but more timely forecast revisions. These findings have important implications for prior studies that consistently document an asymmetric response of the stock market to good news and bad news.

The authors provide evidence on the relationship between audit quality and management earnings forecasts using a novel and intuitive measure that captures forecast revision speed. This measure speaks to the growing interest in understanding the notion of speed and timing of voluntary disclosures. This study provides a more robust and comprehensive measure of the speed with which managers revise their earnings forecasts to arrive at the actual earnings. Furthermore, this study is among the first to document an asymmetric effect of audit quality on the type of news disclosed in forecast revisions.

This study examines the relation between the presence of analysts’ long-term growth (LTG) forecasts and the post-earnings-announcement drift (PEAD).

Using a sample of firm-quarters from 1995 to 2013, the author conducts various regression analyses.

The author finds that the magnitude of PEAD is significantly smaller for firms with LTG forecasts. The relationship holds after controlling for a wide range of explanatory variables for PEAD returns or for the presence of LTG forecasts. The author further investigates three nonexclusive hypotheses to explain this relationship. First, LTG forecasts may convey incremental value-relevant information that facilitates investors’ processing of short-term earnings information. Second, the presence of LTG forecasts may indicate superiority in analysts’ short-term forecast ability and identify firms with more efficient short-term forecasts. Third, the presence of LTG forecasts may be associated with cross-sectional differences in the persistence of earnings surprises. The author finds that none of these fully accounts for the negative relationship between the presence of LTG forecasts and PEAD returns. Instead, the relationship may be a result of the presence of LTG forecasts capturing some unobservable firm characteristics beyond those identified in prior studies.

This study contributes to the PEAD literature by identifying a novel analyst-based predictor of the cross-sectional variation in PEAD returns.

As the influence of institutional investors over managerial decision-making grows, so does the importance of understanding the effect of institutional investor ownership (IO) on firm outcomes. The authors take a comprehensive approach to studying the effect of IO on earnings management (EM).

The authors study the relation between IO and EM using a sample of 59,503 listed U.S. firm-year observations from 1981–2019. The authors proxy EM with earnings surprises and with accrual-based and real activity measures. The authors test for nonlinear relations and analyze changes resulting from the passage of the Sarbanes–Oxley Act.

The findings support a positive IO-EM relation overall, but show that the relation is dynamic and heavily context-dependent with evidence of nonlinearity. The authors also find evidence that IO positively affects accrual-based EM and real activities EM negatively.

To the authors’ knowledge, this is the first study of the IO-EM relation to consider evidence of nonlinearity in the U.S. context, measuring changes to the relation over time, and with the use of several measures of EM.

European countries are likely to increasingly adopt integrated reporting (IR) voluntarily, after the 2014/95/EU Directive is revised and other initiatives are implemented. Therefore, the present study provides insights on the relevance of IR in voluntary contexts by exploring analysts' reactions to the release of integrated reports in diverse institutional settings.

Drawing on voluntary disclosure theory, a quantitative empirical research method is used to explore the moderating role of country-level institutional characteristics on the associations between voluntary IR release and analyst forecast accuracy and dispersion.

IR informativeness is not uniform in the voluntary context and institutional settings play a moderating role. IR release is associated with increased consensus among analyst forecasts. However, in countries with weak institutional enforcement, a reverse association is detected, indicating that analysts rely largely on IR where the institutional setting strongly protects investors. Although a strong institutional setting boosts the IR release usefulness in terms of accuracy, it creates noise in analyst consensus.

Academics can appreciate the usefulness of voluntary IR across the institutional enforcement contexts.

Managers can use these findings to understand opportunities offered by IR voluntary release. The study recommends that policymakers, standard setters and regulators strengthen the institutional enforcement of sustainability disclosure.

This study is a unique contribution to recent calls for research on the effects of nonfinancial disclosure regulation and on IR “impacts”. It shows on the international scale that IR usefulness for analysts is moderated by institutional patterns, not country-level institutional characteristics.

Given the limited studies that have started to focus on contexts where integrated reporting (IR) is voluntarily adopted, this paper aims to explore the moderating role of institutional characteristics on the association between voluntary report release and analyst forecast accuracy.

This study uses a quantitative empirical research method grounded on voluntary disclosure theory to provide empirical evidence on an international sample of companies choosing to release integrated reports. Preliminarily, a cluster analysis is used to group countries according to institutional patterns. Multivariate analyses detect the associations between report release choice and analysts’ forecast accuracy across clusters. Multiple econometric approaches are used to address the endogeneity concerns.

IR release is not informative for the market unless considering systematic variations across different institutional settings. Analysts’ forecast is more accurate for IR adopters located in strong institutional enforcement settings than for all the other companies. In the strong institutional setting that is also characterized by a pluralistic society, IR release benefits for the market are conditioned by the fact that the choice to release IR depends on environmental, governance and social disclosure-based managers remuneration and disclosure requirements. In weak institutional settings, IR release is not beneficial for the forecast accuracy.

Academics and practitioners can gain understanding of the usefulness of voluntary IR across different institutional settings.

The study advances the understanding of the IR’s informativeness, overcoming the common dichotomous distinctions between strong and weak institutional settings.

The authors examine the role of analysts’ prior experience of forecasting for firms exposed to epidemics on analysts’ forecast accuracy during the COVID-19 pandemic.

The authors examine the impact of analysts’ prior epidemic experience on forecast accuracy by comparing the changes from the pre-COVID-19 period (calendar year 2019) to the post-COVID period extending up to March 2023 across HRE versus non-HRE analysts. The authors consider a full sample (194,980) and a sub-sample (136,836) approach to distinguish “Recent” forecasts from “All” forecasts (including revisions).

The study's findings reveal that forecast accuracy for HRE analysts is significantly higher than that for non-HRE analysts during COVID-19. Specifically, forecast errors significantly decrease by 0.6% and 0.15% for the “Recent” and “All” forecast samples, respectively. This finding suggests that analysts’ prior epidemic experience leads to an enhanced ability to assess the uncertainty around the epidemic, thereby translating to higher forecast accuracy.

The finding that the expertise developed through an experience of following high-risk firms in the past enhances analysts’ performance during the pandemic sheds light on a key differentiator that partially explains the systematic difference in performance across analysts. The authors also show that industry experience alone is not useful in improving forecast accuracy during a pandemic – prior experience of tracking firms during epidemics adds incremental accuracy to analysts’ forecasts during pandemics such as COVID-19.

The study findings should prompt macroeconomic policymakers at the national level, such as the central banks of countries, to include past epidemic experiences as a key determinant when forecasting the economic outlook and making policy-related decisions. Moreover, practitioners and advisory firms can improve the earning prediction models by placing more weight on pandemic-adjusted forecasts made by analysts with past epidemic experience.

The uncertainty induced by the COVID-19 pandemic increases uncertainty in global financial markets. Under such circumstances, the importance of analysts’ role as information intermediaries gains even more importance. This raises the question of what determines analysts’ forecast accuracy during the COVID-19 pandemic. Building upon prior literature on the role of analyst experience in shaping analysts’ forecasts, the authors examine whether experience in tracking firms exposed to prior epidemics allows analysts to forecast more accurately during COVID-19. The authors find that analysts who have experience in forecasting for firms with high exposure to epidemics (H1N1, Zika, Ebola, and SARS) exhibit higher accuracy than analysts who lack such experience. Further, this effect of experience on forecast accuracy is more pronounced while forecasting for firms with higher exposure to the risk of COVID-19 and for firms with a poor ex-ante informational environment.

The purpose of this paper is to examine the influence of earnings persistence and earnings power on equity valuation.

The purposive sampling method was applied to determine the samples of selected 100 firms. This study employed secondary data obtained from the annual reports and financial statements of consumer goods firms listed on the Indonesian Stock Exchange for the period 2010–2014. The analysis technique used a multiple regression analysis.

The study result shows that, partially, earnings persistence and earnings power affect equity valuation by investors. Earnings persistence has a negative influence, whereas earnings power has a positive influence on equity valuation.

This study throws additional lights on equity valuation specific to consumer goods industries.