Earnings Expectations Research Articles

Ultimate Price: The Value We Place on Life

Ultimate Price: The Value We Place on Life

기업의 ESG 활동과 주가동조성

In this study, the effect of the level of ESG activity of companies, which is receiving worldwide attention, on stock price informativeness, is to be confirmed through empirical analysis. Specifically, in this study, the effect of ESG activity on stock price informativeness was empirically analyzed through stock price synchronicity to determine how the ESG activity performance of an individual company had an effect on the volatility of market returns and industrial returns. If investors judge a company’s ESG activities and performance as useful accounting information for forecasting future prospects, they will make investment decisions with more weight on the company’s ESG information when forming future earnings expectations. In this case, the level of stock price movement will be low due to the high explanation of the company’s ESG information. On the other hand, ESG activities and performance will facilitate the use of future vision and information for investors, which will improve the flow of information to the market, and increase information efficiency, which will improve stock price information. The research sample was December settlement companies in the KOSPI market and KOSDAQ market from 2018 to 2021, targeting non-financial listed corporations, and ESG, the main independent variable, was subjected to empirical analysis targeting KOSPI 200 ESG constituents. As a result of empirical analysis, a company’s ESG activity showed a significant positive(＋) correlation with stock price movement. This shows that ESG-active companies have high information efficiency because the unique information of individual companies is sufficiently reflected in the stock price. In other words, it can be judged that companies that actively engage in ESG activities have a high level of information environment and that sufficient information is reflected in their stock prices. The implication of this study is that it will be helpful for creditors and investors to make investment decisions by considering ESG management activities and performance information of companies as ethical management and transparency based on the results of this study. And it is expected that it will be able to induce ESG management activities of companies.

The Stock Market and the Space Age

Having emerged from World War II as a permanent feature of American political and economic life, the “glamour” of research and development (R&D) would soon take hold of Wall Street. By the 1960s, shares of high-tech electronics and aerospace firms became irresistible to the flood of young men entering the securities business with the hopes of getting rich quick off capital gains. For this generation, R&D spending today came to mean earnings growth tomorrow, and in periods of financial hardship, executives under pressure to meet earnings expectations changed R&D accounting policies to boost their bottom lines. With this change, firms experiencing significant losses could maintain the appearance of profitability while reinforcing public perceptions of R&D as a magic bullet for growth. Contrary to the mythology of the “space age,” however, those intimately involved in R&D and tracking its costs insisted that expenditures so incurred failed in practice to qualify as assets. Drawing from arguments made by industrial researchers and cost accountants, this article problematizes the “R&D underinvestment” consensus that emerged in the wake of the space age and suggests dropping the R&D asset view wherever it circulates, including in academic scholarship.

Hard to arbitrage, hard for analysts to forecast

This paper examines whether limits to arbitrage (LA) affect analysts' earnings forecast accuracy. Using the LA index, which is constructed from unique trading constraints in the Chinese stock market and other commonly used measures, we find that forecast accuracy is much lower for stocks with high LA. Moreover, our results are more suited to explanations of cognitive bias that turn to investor sentiment or limited attention and cannot be fully explained by more objective factors, including analyst ability, broker size, broker experience, and commission pressure. We also find that LA amplifies analyst forecast dispersion. Such results indicate that LA distorts analysts’ earnings expectations and provides new insight into how LA affects anomaly returns.

Does the market reward meeting or beating analyst earnings forecasts? Empirical evidence from China

PurposeUsing 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).Design/methodology/approachThe authors use an event study methodology to capture market reactions to MBE.FindingsThe 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.Research limitations/implicationsThe 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.Practical implicationsThe 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.Originality/valueThe 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.

Do independent directors and big-4 audit firms limit classification shifting: evidence from Indian firms

PurposeThis study investigates the moderating role of Big-4 audit firms on the association between board independence and classification shifting (CS) in Indian firms.Design/methodology/approachThis study has employed a fixed-effect panel data regression model to analyze the sample data. Board independence is measured by taking the proportion of independent directors on a firm’s board. CS is measured from the core earnings expectation model (McVay, 2006). Principal Score Matching is applied to validate the results.FindingsBased on 6,016 firm-year observations of Indian firms listed on the Bombay Stock Exchange, results show that firms with a higher proportion of independent directors on board are effective in limiting expense CS. Further, firms that Big-4 audit firms audit play a significant role in curbing expense CS. Overall, results also exhibit that Big-4 audit firms significantly influence the association between board independence and CS.Originality/valueThis study is one of its kind to examine the moderating role of Big-4 audit firms between board independence and CS.

LINKAGE AND SPILLOVER EFFECTS OF CHINA'S CARBON MARKET AND STOCK MARKET UNDER THE BACKGROUND OF CARBON NEUTRALITY: AN ANALYSIS BASED ON INVESTOR SENTIMENT REGULATION

LINKAGE AND SPILLOVER EFFECTS OF CHINA'S CARBON MARKET AND STOCK MARKET UNDER THE BACKGROUND OF CARBON NEUTRALITY: AN ANALYSIS BASED ON INVESTOR SENTIMENT REGULATION

A re‐examination of analysts versus time‐series extrapolation of quarterly earnings: Superiority in accuracy and earning expectation proxy

AbstractWe document findings that earning extrapolation based on seasonal random trend (SRT) model is not inferior to analysts’ quarterly earnings forecasts, which contradicts the belief that analysts are superior to time‐series models. Our findings suggest that while the frequency of analysts beating SRT extrapolations is greater than 50%, the marginal accuracy improvement is weak. Analysts’ forecasts contain larger absolute forecast error and significant pessimistic bias than SRT extrapolation. Prior studies attribute the superiority of analysts’ forecasts in proxying for earnings expectation to its higher accuracy. Given that the SRT extrapolations have lower average forecast error, we explore whether market participants use them to develop earnings expectations. Our findings indicate that the market anchors to analysts’ forecasts and treats SRT extrapolations as supplemental.

Taxes in Non-GAAP Reporting: Evidence of Strategic Behavior in Selecting Tax Rates Applied to Exclusions

When reporting after-tax non–generally accepted accounting principles (GAAP) earnings, firms are required to adjust for the tax effects of exclusions. Since 2010, the Securities and Exchange Commission (SEC) has issued and updated compliance and disclosure interpretations (C&DIs), which specifically require firms to disclose the tax effects of exclusions. We assemble a detailed, hand-collected data set of S&P 1500 firms’ disclosures to provide the first large-sample evidence on the reporting of the tax effects of non-GAAP exclusions. We find three key results. First, echoing the SEC’s concern, a significant proportion of non-GAAP reporting firms do not follow the C&DI guidelines (i.e., they do not disclose the tax effects of exclusions). Second, among firms that disclose the tax effects of exclusions, we find that managers strategically select the tax rates applied to exclusions to achieve after-tax earnings targets. Third, manager-reported non-GAAP earnings are less persistent for future operating earnings and cash flows relative to non-GAAP earnings calculated by applying various benchmark tax rates to exclusions. This evidence suggests that managers’ strategic behavior in selecting the tax rates applied to exclusions pollutes reported non-GAAP earnings and reduces their usefulness for predicting future performance. Overall, our results shed light on a specific channel through which firms use non-GAAP reporting to meet or beat earnings expectations. This paper was accepted by Brian Bushee, accounting. Funding: N. (X.) Chen appreciates financial support from the University of Houston. T. Shevlin acknowledges financial support from the Paul Merage School of Business at the University of California–Irvine. P.-C. Chiu acknowledges the financial support received from the Hong Kong Research Grant Council [Grant RGC14522716]. Supplemental Material: Data files and the online appendix are available at https://doi.org/10.1287/mnsc.2022.4433 .

The reliability of students’ earnings expectations

The elicitation of subjective expectations in surveys has gained significant interest in economics. Students’ earnings expectations have been widely used to model school and occupational choices, but quantification of the reliability of this variable has not yet been done. To what extent are earnings expectations affected by random measurement error? To assess this issue, in this paper we use different waves of a survey carried out in a Spanish university eliciting the earnings expectations of economics students. A test-retest method is applied with different time spans between the first wave and subsequent repetitions of the survey: two weeks and two and a half months later. A significant number of students declared large differences in earnings expectations, even in the case where the time span between surveys was short. Apart from the reliability, we also provide an estimate of the measurement error variance. With this information we show how a sensitivity analysis can be performed in external earnings expectations data research.

Social media discussion and the market reaction to earnings announcements: evidence from China

ABSTRACT This study investigates the influence of earnings-related social media discussion on stock returns surrounding the earnings announcement. By using deep learning approach to develop a new measure of market-wide earnings expectations based on Chinese Sina Weibo, we find that the constructed Weibo optimism index is positively related to the upcoming earnings announcement returns within a short window. This positive effect is more pronounced for firms with lower-quality earnings and firms with no traditional media coverage. Additionally, we also find that an increase in our Weibo optimism index indicates stronger post-announcement return reversals over a longer window. These results imply that earnings-related social media discussion is largely driven by sentiments, leading investors to overreact to earnings announcements. Our evidence supports the view that social media impedes stock price efficiency in financial markets.

Information Provision and Postgraduate Studies

This is the first paper to examine experimentally effects of information provision on beliefs about pecuniary and non‐pecuniary returns of postgraduate education, enrolment intentions and realized enrolment. We find that our treatment causally affects beliefs measured six months after treatment. The effects on beliefs differ by gender and academic background, and we find that stated enrolment intentions change accordingly; in particular, males adjust significantly downwards their beliefs and intentions to undertake postgraduate studies. This is driven by males upward adjusting earnings expectations with a first degree only. We follow the students further and provide evidence on actual enrolment one and two years after treatment. Taken together, this study highlights the relevance of information provision on pecuniary and non‐pecuniary labour market returns for postgraduate study decisions.

Caught in an Expectations Trap: Risks of Giving Securities Analysts What They Expect

Although recent research shows that there is mounting pressure on firms to achieve earnings expectations of securities analysts, firms are far from being passive conformers; many firms proactively manage such pressure, particularly with earnings management tools. Yet why does the pressure to meet analyst expectations persist despite firms’ efforts to reduce it? To address the question, we develop an intertemporal model of the mutually reinforcing relationships between analyst expectations and firms’ strategic response, combining the behavioral theory of the firm and the concept of expectations trap. We argue that firms’ efforts to meet analyst expectations strengthen their salience as a predominant performance benchmark and, in doing so, ironically put them under greater pressure from analysts in three sequentially related steps—escalating future earnings expectations, imposing more severe penalties for failure to meet heightened expectations, and generating compensatory action for missed expectations. Our analysis, using data on more than 700 of the largest listed U.S. firms between 1986 and 2015, supports our arguments. Our study expands the scope of the behavioral theory of the firm, by demonstrating the increasing importance of performance feedback based on analyst expectations. Our study also contributes to the research on earnings pressure, by illuminating why the pressure persists despite firms’ efforts to reduce or evade it, and finally to the literature on strategic management of external expectations, by elaborating its unintended, long-term consequences. Supplemental Material: The e-companion is available at https://doi.org/10.1287/orsc.2021.1569 .

Exploiting Earnings Persistence to Better Measure Market Expectations in Detecting Post-Earnings Announcement Drift

ABSTRACT We construct an alternate proxy for earnings expectations that does not depend on analyst following and exploits differential earnings persistence across earnings levels. We examine the usefulness of our proxy in the context of post-earnings announcement drift (PEAD) where the random walk model is still widely used in the literature. We show that a refined trading strategy using our alternative proxy results in statistically significant and economically large increases in PEAD relative to the random walk model. Furthermore, using a subsample where analysts' forecasts are available, we show that the PEAD associated with our alternate proxy is incremental to the PEAD associated with analyst forecast errors. Our earnings expectation proxy can be used in other settings where extreme earnings or earnings surprise portfolios are the focus of the analysis and researchers want to include firms without analyst following.

Critical review of models of earnings mean reversion

The hypothesis that earnings are mean reverting was suggested 90 years ago and has been extensively tested since then. Expectations of earnings’ mean reversion (hereinafter “EMR”) significantly influence pricing of shares or earnings forecasts. Despite proposals and testing of numerous models of EMR, there has been very little inquiry into the meaning of those models in corporate and valuation terms in the academic literature. Therefore, we see such an inquiry as highly desirable. The aim of this paper is to critically review the models of transitory earnings (vice versa EMR), their methodology, practical applicability of their results, and their limitations stemming from the characteristics of earnings data. We find that most of the recent models of transitory earnings (EMR) are misspecified in terms of target earnings or reasons of EMR. We also find that EMR is partly caused by cycles in relevant industry or economy, and partly by company-specific processes and accruals. Also, elimination of survivorship bias and use of margins or lower-level profitability like ROI and ROC instead of ROE is worth testing in EMR models.

The Origins of Gender Differences in Competitiveness and Earnings Expectations: Causal Evidence from a Mentoring Intervention

The Origins of Gender Differences in Competitiveness and Earnings Expectations: Causal Evidence from a Mentoring Intervention

Consumption Choices and Earnings Expectations: Empirical Evidence and Structural Estimation

Consumption Choices and Earnings Expectations: Empirical Evidence and Structural Estimation

The Origins of Gender Differences in Competitiveness and Earnings Expectations: Causal Evidence from a Mentoring Intervention

The Origins of Gender Differences in Competitiveness and Earnings Expectations: Causal Evidence from a Mentoring Intervention

Information Coordination: Does Preannouncement Media Coverage Improve Earnings Expectations?

Information Coordination: Does Preannouncement Media Coverage Improve Earnings Expectations?

The Rise in the Cross-Sectoral Dispersion of Earnings Expectations During COVID-19

The Rise in the Cross-Sectoral Dispersion of Earnings Expectations During COVID-19