Earnings Forecast Errors Research Articles

Earnings optimism in green stocks

ABSTRACT In this study, we systematically examine earnings expectations, proxied by consensus analyst earnings forecast errors (EFEs), about stocks in green energy and clean technology sectors. We find that the EFEs of green stocks are generally positive from 1992 to 2016, indicating a predominance of earnings optimism. However, the earnings optimism of green stocks is significantly less strong than that of the market portfolio. In addition, we observe a segment-varying earnings optimism pattern in green stocks. Moreover, it is observed that investors become more and more optimistic when forecasting earnings of green stocks. In the period from 2008 to 2016, while investors exhibit slightly less optimistic expectations about market-level earnings performance after experiencing the 2008 Global Financial Crisis, they tend to be clearly more confident about the earnings prospects of green stocks in the same period as the first and second commitment periods of the Kyoto Protocol take effect.

Predicting Analysts’ S and P 500 Earnings Forecast Errors and Stock Market Returns using Macroeconomic Data and Nowcasts

This study scrutinizes the quality of “bottom-up” forecasts of near-term S and P 500 Composite earnings, derived by aggregating analysts’ forecasts for individual firm-level earnings. We examine whether forecasts are broadly consistent with current macroeconomic conditions reflected in economists’ near-term outlook and other available data. To the contrary, we find that a simple macroeconomic model of aggregate S and P 500 earnings, coupled with GDP forecasts from the Blue Chip Survey and recent dollar exchange rate movements, can predict large and statistically significant errors in equity analysts’ bottom-up forecasts for S and P 500 earnings in the current quarter and the quarter ahead. This finding is robust to the requirement that our econometric model is calibrated using only data available at the time of forecast. Moreover, the discrepancy between the macro-model-based earnings forecasts and analysts’ forecasts has predictive power for 3-month-ahead stock returns

A comparison of analysts’ and investors’ information efficiency of corporate social responsibility activities

Purpose This paper aims to examine the extent to which sell-side analysts efficiently incorporate firms’ corporate social responsibility (CSR) activities into their earnings forecasts. In addition, this paper also investigate the CSR information efficiency of analysts vis-à-vis that of investors. Design/methodology/approach This paper measures CSR activities by using CSR strength and CSR concern scores from the Morgan Stanley Capital International Environmental, Social and Governance database. This paper uses analysts’ earnings forecast errors and dispersion as proxies for their information efficiency. To compare the CSR information efficiency of analysts to that of investors, this paper uses the Vt/Pt ratio, which is the equity value estimates inferred from analysts’ earnings forecasts (a proxy for analysts’ CSR information efficiency) to the stock price of the focal company (a proxy for investors’ CSR information efficiency). Findings The regression analysis indicates that analysts’ earnings forecasts are optimistically biased and more dispersed for firms with positive CSR activities. The paper also finds that analysts’ forecasts are more optimistically biased than investors in interpreting CSR activities. Practical implications The lack of standardized protocols in CSR reporting and activities has raised the risk of mispricing by analysts, threatening the stability of sustainable investments. This paper suggests that regulators and standard-setters should establish a uniform framework governing firms’ CSR activities, along with their reporting and measurement, to ensure more consistent and reliable evaluations of CSR practices. Social implications Analysts’ mispricing of CSR activities may distort sustainable investing, as it can overly focus on the positive impacts of stakeholder theory, overlooking agency theory’s warnings about managerial self-interest. Investors need to assess CSR efforts with a dual perspective, acknowledging their societal value but also examining their alignment with shareholder interests. Originality/value To the best of the authors’ knowledge, this research is the first to assess the efficiency of analysts versus investors in processing CSR information amidst growing sustainable investment interests. Furthermore, building on Dhaliwal et al. (2012), which found that voluntary CSR disclosures correlate with more accurate analyst forecasts, this research provides fresh perspectives on the evolving nature of how analysts assimilate CSR information over time.

Can a machine learn from behavioral biases? Evidence from stock return predictability of deep learning models

We examine how the return predictability of deep learning models varies with stocks’ vulnerability to investors’ behavioral biases. Using an extensive list of anomaly variables, we find that the long-short strategy of buying (shorting) stocks with high (low) deep learning signals generates greater returns for stocks more vulnerable to behavioral biases, i.e., small, young, unprofitable, volatile, non-dividend-paying, close-to-default, and lottery-like stocks. This performance of deep learning models for speculative stocks becomes pronounced when investor sentiment is high, and when new information is delivered through earnings announcements. Moreover, our nonlinear deep learning signals are negatively associated with analysts’ earnings forecast error especially for speculative stocks, implying that analysts’ forecasts are too low for speculative stocks with high deep learning signals. These results suggest that deep learning models with nonlinear structures are useful for capturing mispricing induced by behavioral biases.

Relationship of the rating of the companies with the forecast error of market analysts

This study sought to assess the existence of a relationship between the rating and the earnings forecast error of market analysts. The sample relates to 44 companies for the period from 2010 to 2018, which was selected from the data collected onthe Thomson Reuters® platform, in the I/B/E/S database. The methodology chosen was panel data analysis. The results showed that the rating impacts the level of analysts’ forecast error, so companies with better credit risk rating have lowererror in their earnings forecasts. The study contributes to the literature on capital market, specifically that of analysts’ forecasts, focusing on the rating variable as an important factor to be considered by market analysts and contributes to the literature on the predictive quality of accounting information.

Implications of mergers and acquisitions for information disclosures in earnings calls

We examine the linkages between firms' M&A activity and the information exchange between executives and analysts during quarterly earnings calls. Prior M&A research has mostly focused on the considerations presented by information asymmetry between buyers and sellers themselves in M&A. However, these concerns also exist between the buying firm's executives and capital markets. We examine whether firms' M&A activity results in an information exchange between executives and analysts that highlights corporate strategy as a discussion topic. Thus, we test whether there is consistency between firms' corporate growth agendas and the information released to the public by these firms. This question is relevant, as disclosure is central to firms' ability to raise capital and compete. We also investigate the degree to which these information exchanges affect analysts' earnings forecast errors.

Auditors’ legal liability and client firms’ comparability: evidence from China

PurposeThis paper aims to investigate the relation between audit firms’ switch to limited liability partnership (LLP) from limited liability company (LLC) and client firms’ earnings comparability. If LLP auditors, who have a higher liability exposure than LLC auditors, are more consistent in implementing generally accepted accounting principles and executing firm-wide audit methodologies, client firms’ earnings comparability will increase.Design/methodology/approachUsing data from China, the authors examine whether client firm-pairs of LLP auditors have higher earnings comparability than client firm-pairs of LLC auditors. The authors also perform cross-sectional tests to shed light on the mechanisms through which auditors’ litigation exposure affects client firms’ comparability.FindingsThe authors find that firm-pairs in which both firms are audited by LLP auditors exhibit higher earnings comparability than other firm-pairs. This result is stronger when client firms are audited by the same auditor, when client firms are audited by the top 10 auditors and when the auditors are less dependent on the client firms. The authors also document that firm-pairs in which both firms are audited by LLP auditors have lower average analyst earnings forecast error and forecast dispersion.Originality/valueTo the best of the author’s knowledge, this study is the first to examine the relation between auditor’s litigation exposure and client firms’ earnings comparability. It also extends the literature on audit firm organizational form and audit quality.

Analysis of strategic deviance decisions considering investors’ risk aversion and the industrial earnings forecast errors

Analysis of strategic deviance decisions considering investors’ risk aversion and the industrial earnings forecast errors

Impact of Integrated Reporting on Information Asymmetry: Evidence from Sri Lanka

Considering the dearth of empirical evidence on the impact of integrated reporting (IR) on information asymmetry in developing countries, this paper investigates the impact of IR on information asymmetry in Sri Lanka. A paired sample t-test and a panel regression analysis are employed to draw empirical evidence. Information asymmetry is proxied by earnings forecast error, earnings forecast dispersion, and cost of equity capital, whereas firms' IR level is measured using the IR framework. Findings indicate a significant reduction in information asymmetry upon adopting IR. Further, they reveal that the level of IR has a feeble but statistically significant negative impact on the cost of equity capital. Earnings forecast error and forecast dispersion do not indicate significant associations with IR levels. Given the substantial cross-country differences, this paper offers a better understanding of the impact of IR on information asymmetry from a developing country setting where the adoption of IR is voluntary.

Shaping the Information Environment: International Evidence on Financial Reporting Frequency and Analysts’ Earnings Forecast Errors

This article investigates the role of mandatory interim financial reporting in financial analysts’ annual earnings forecast errors. We provide large-scale evidence from 49 countries that a mandatory quarterly (as compared to semi-annual) reporting regime is associated with lower analysts’ annual earnings forecast errors. This conjecture is further supported when we exploit an exogeneous change in the mandatory frequency regime from a semi-annual to a quarterly reporting mandate in Japan. Consistent with an improvement in the information environment, our findings are more pronounced for firms and analysts subject to higher information acquisition costs and in countries where the institutional setting is less able to meet analysts’ information needs. We corroborate this conjecture by documenting that more frequent mandatory reporting decreases analysts’ forecast dispersion and improves the profitability of their stock recommendations. Overall, our findings extend the research on the role of the institutional setting in analysts’ output, suggesting that the mandate of more frequent reporting improves analysts’ forecasting process.

Analysts’ foreign ancestral origins and firms’ information environment

PurposeThe purpose of this study is to examine whether and how analysts’ foreign ancestral origins would have an effect on analysts’ earning forecasts in particular and ultimately on firms’ information environment in general.Design/methodology/approachBy inferring analysts’ ancestral countries based on their surnames, this study empirically examines whether analysts’ ancestral countries affect their earnings forecast errors.FindingsUsing novel data on analysts’ foreign ancestral origins from more than 110 countries, this study finds that relative to analysts with common American surnames, analysts with common foreign surnames tend to have higher earnings forecast errors. The positive relation between analyst foreign surnames and earnings forecast errors is more likely to be observed for African-American analysts and analysts whose ancestry countries are geographically apart from the USA. In contrast, this study finds that when analysts’ foreign countries of ancestry are aligned with that of the CEOs, analysts exhibit lower earnings forecast errors relative to analysts with common American surnames. More importantly, the results show that firms followed by more analysts with foreign surnames tend to exhibit higher earnings forecast errors.Originality/valueTaken together, findings of this study are consistent with the conjecture that geographical, social and ethnical proximity between managers and analysts affect firms’ information environment. Therefore, this study contributes to the determinants of analysts’ earnings forecast errors and adds to the literature on firms’ information environment.

Environmental and social transparency and investment efficiency: The mediating effect of analysts’ monitoring

We evaluate how financial analysts' information environment mediates the influence of a firm's environmental and social transparency on its investment efficiency. We argue that via their information intermediary and monitoring capabilities, analysts both react to and act upon transparency in such a way as to affect a firm's investment efficiency. Consistent with prior research, investment efficiency represents a firm's increase in net tangible assets relative to its sales growth. Transparency is based upon comprehensive ratings constructed by Bloomberg. Analysts' information environment is proxied by earnings forecast errors and dispersion. Our sample comprises S&P 500 index firms over 2012–2018. Results show that environmental and social transparencies each positively relate to investment efficiency, with analysts' information environment partially mediating this relationship. Moreover, environmental and social transparencies each relate to smaller forecast errors as well as less forecast dispersion. Furthermore, enhanced analyst forecasts imply less firm-level investment inefficiency. These results suggest that greater environmental and social transparency enhances financial analysts' information environment and, thus, their information intermediary and monitoring capabilities. Consequently, firms are more likely to attain investment efficiency.

The impact of disclosure quality on analyst forecasts in China

ABSTRACT Since the establishment of the Shenzhen Stock Exchange (SZSE) Disclosure Ranking System in 2001, the disclosure quality of listed companies has increased in China. As a result, analysts can access more timely, valuable, and reliable information to understand companies’ overall operating status, financial reports, and accrual components of earnings. As analysts can save time and costs when they have access to high-quality information provided by firms, their earnings forecast error and optimism bias are reduced, and analysts’ divergence of opinion on firm prospects decreases. Using a sample of 419 A-share firms listed on the Main Board of the SZSE over the 2001–2018 period, we investigate whether disclosure quality affects analysts’ forecasting behaviour in China’s securities market using SZSE disclosure ranking data, and find that high disclosure quality improves analyst forecast accuracy and reduces forecast optimism and forecast dispersion. We also find that disclosure quality is associated with an increase in a firm’s stock price synchronicity with the market and a decrease in industry-wide and firm-specific information, and that a good disclosure ranking can enhance the credibility of firm-specific information and therefore its usefulness to financial analysts in the emerging market of China.

Doing good in periods of high uncertainty: Economic policy uncertainty, corporate social responsibility, and analyst forecast error

We investigate the behavior of analyst earnings forecast error in response to policy uncertainty. We find that the accuracy of analyst forecasts is compromised at times of increased economic policy uncertainty, when market volatility and information opacity are high. This negative association between policy uncertainty and earnings forecast accuracy is alleviated in firms where good CSR practices are in place. The disclosure of CSR-related nonfinancial information reportedly improves forecast accuracy; in the context of policy uncertainty, we document that CSR plays a stabilizing role by moderating analyst forecast error. Additionally, we report that the moderating effect of CSR is more pronounced in domestic rather than multinational firms, where, for the former, analysts are able to better assess the quality of information. Finally, we observe that analysts attach more value to the external legitimacy aspect of CSR rather than internal sustainability in guaranteeing earnings resilience in the face of high policy uncertainty. Our results remain valid in various robustness settings.

Voluntary intellectual capital disclosure and earnings forecast in Indonesia–Malaysia–Thailand growth triangle's pharmaceuticals sector

PurposeThis study examines the role of intellectual capital disclosure (ICD) on earnings forecasting by analysts in the pharmaceutical industry in emerging countries, particularly in Indonesia, Malaysia and Thailand. This study specifically examines the role of each component of the ICD on analysts' forecasts, which consists of errors of forecasted earnings, the standard deviation of forecasted earnings and analyst recommendations.Design/methodology/approachPanel data analysis is conducted using a sample of 17 companies from pharmaceuticals industries in Indonesia, Malaysia, Thailand – Growth Triangle (IMT-GT), which are listed in the Indonesia Stock Exchange (IDX), Malaysia Stock Exchange (MYX) and Stock Exchange of Thailand (SET) from 2010 to 2017. Secondary data is obtained from Bloomberg and Annual report, where they are being analyzed to measure the ICD and gather the control variables.FindingsThe results indicate that the three components of ICD, namely human capital disclosure (HCD), structural capital disclosure (SCD) and relational capital disclosure (RCD), insignificantly influence average analysts' consensus recommendation and analysts' earnings forecast dispersion. However, the findings show a significant negative influence of relational capital disclosure (RCD) on analysts' earnings forecast error. In contrast, HCD and SCD have an insignificant impact.Practical implicationsTransparency in disclosing activities related to external parties is essential for the pharmaceutical industry. It is found that relational capital disclosure is the only ICD indicator that can strengthen analysts' profit predictions. Transparency about company activities in maintaining customer satisfaction and activities related to strategic alliances with other organizations are two critical things that can accommodate the accuracy of earnings forecasting from analysts in pharmaceutical companies.Originality/valueThis study contributes to ICD-related research by discussing the financial analyst's response to this voluntary disclosure in the pharmaceutical industry, particularly in Indonesia, Malaysia and Thailand. The selected observation period is seven years, starting one year after the global financial crisis. The results showed that the disclosure of IC is not an exciting thing for financial analysts. In forecasting current earnings, financial analysts are more interested in errors than the previous year's estimates.

Private Communication between Managers and Financial Analysts: Evidence from Taxi Ride Patterns in New York City

This study constructs a novel measure that aims to capture face-to-face private communications between firm managers and sell-side analysts by mapping detailed, large-volume taxi trip records from New York City to the GPS coordinates of companies and brokerages. Consistent with earnings releases prompting needs for private communications, we observe that daily taxi ride volumes between companies and brokerages increase significantly around earnings announcement dates (EAD) and reach their peak on EAD. After controlling for an extensive set of fixed effects (firm, analyst, and year) and other potential confounding factors, we find that increases in ride volumes around EAD are negatively associated with analysts’ earnings forecast errors in periods after EAD and positively associated with the profitability of recommendations issued after EAD (but these effects dissipate over longer horizons). Taken together, our results suggest that analysts may obtain a private source of information orthogonal to their pre-existing information from these in-person meetings, which may help them better understand the implications of current earnings signals for future earnings.

Earnings Forecast Error and Long-Run Underperformance: Evidence from Bangladesh

Earnings Forecast Error and Long-Run Underperformance: Evidence from Bangladesh

Forecasting Shares Outstanding

Despite the importance of EPS forecasts as benchmarks, little is known about their denominator: shares outstanding forecasts. Because investing clients have limited demand for accurate share forecasts, we predict that analysts develop share forecasts strategically to facilitate EPS incentives. We divide earnings forecasts by EPS forecasts to infer analysts’ share forecasts and evaluate their properties. Analysts’ forecasts of shares outstanding are significantly less accurate than simple time-series models; however, these same forecasts actually improve EPS forecast accuracy. Additional analysis explains why: analysts use share forecasts to herd EPS toward the consensus. That is, share forecast errors often have the same sign as street earnings forecast errors, moving EPS closer to the consensus and to actual EPS, and significantly reducing EPS dispersion. Analysts also appear to use share forecasts to cater to management. Specifically, bias in share forecasts facilitates firms’ ability to meet or beat (“MB”) EPS benchmarks and is consistent with manager preferences (i.e., deflating EPS forecasts at short horizons and inflating at longer horizons). Much of the MB effect arises because analysts fail to incorporate predictable variation in shares outstanding, such as past repurchases. Interviews with sell-side analysts confirm that clients have limited demand for share forecasts, consistent with the inattention and strategic use of forecasts documented in our study.

Asymmetric Cost Behavior and Its Impact on Improving Earnings Prediction Models

The purpose of the study is to exhibit the terms, characteristics, and drivers of asymmetric cost behavior and to highlight the main factors that cause error in analysts' earnings forecasts. As well as, showing the impact of the asymmetric cost behavior on analysts' earnings forecasts in the Egyptian market. The study uses multiple regression analysis to examine the impact of the behavior of total costs (TC), selling, general, and administrative costs (SG&A) and costs of goods sold (COGS), each, on earnings forecast error for the Egyptian-listed firms. Using a sample of most effective Egyptian firms listed in the EGX100 index, the results of the study indicated that the asymmetric cost behavior has a significant impact on analysts' earnings forecast in both total costs and costs of goods sold with lower significance of selling, general, and administrative costs. The study suggests analysts to adopt models that consider the asymmetric cost behavior.

The effect of integrated reporting quality on market liquidity and analyst forecast error

Purpose The purpose of this study is to examine the effect of integrated reporting (IR) quality on both market liquidity and analyst forecast accuracy in South Africa as the only country in the world having IR as a listing requirement. This study uses the Sustainability Disclosure Transparency Index (SDTI) as a proxy for IR disclosure quality. The analysis of this study is based on the period after the publication of the international framework and its adoption by the International Reporting Committee of South Africa in 2014. Design/methodology/approach The companies sampled in this study are those listed on the Johannesburg Stock Exchange (JSE) from 2013 to 2015. The major factor driving the selection of this particular period was to not only analyse the existing IR practice but also investigate IR two years after King III came into force. The SDTI developed by Integrated Reporting and Assurance Services (IRAS) was used to analyse IR quality. Ordinary least squares regressions were analysed. The models include year and industry fixed effects. The variance inflation factor and its tolerance were used to test the severity of multi-collinearity. Also, alternative measures of IR quality and alternate model specifications were analysed to check the robustness of the results. Findings The authors find that quality of IR is associated with lower earnings forecast error. The evidence indicates that earnings forecast error is lower for firms in the materials sector of the South African economy. Consistent with prior research, the results also suggest that forecast errors are higher for companies with volatile returns and lower for larger firms. Additional analysis indicates that IR quality is positively associated with market liquidity. Overall, these findings support the virtues of IR, thus providing useful information to capital markets. Research limitations/implications The results obtained cannot be generalised to other jurisdictions. While the South African economy is the best setting to investigate IRs, new economies are also working actively on IR disclosures, so future research is likely to extend the literature in this field. Secondly, the availability of data constrained the sample size; however, this only mediates against finding any statistically significant result. While the IRAS database offers information about 324 JSE companies, Datastream covers only the 170 largest South African firms. In spite of the sample reduction, robust and consistent results are found in the market liquidity and analyst forecast accuracy proxies. Practical implications The sample period of this study (2013-2015) allows to understand disclosure behaviour after the international IR framework was published and endorsed by the JSE. The release of the IIRF gave clear guidance to firms regarding the nature and purpose of IR. Overall, the results obtained in this paper are consistent with IR expectations, thus providing useful information for investors and financial analysts. It is expected that the results might have practical implications for other nations about the cost and benefits of implementing integrated management reporting. Originality/value This paper contributes incrementally to the existing debate about whether disclosure information through IR has real benefits or is a passing fad. It examines the economic consequences of IR in a mandatory setting using an in-house ranking system, adapted to South Africa, designed by IRAS to determine IR quality. IRAS provides an SDTI that assesses the accuracy, consistency, completeness and reliability of quantitative data for 84 indicators based on IR and global reporting initiative aspects and subdivided into seven categories.