Share Forecasts Research Articles

Do analysts provide information about other comprehensive income in book value forecasts for financial firms?

Analysts' earnings forecasts exclude other comprehensive income (OCI). However, OCI affects firm value on a dollar-for-dollar basis and can enhance investors' assessments of the riskiness of firms' equity capital. Focusing on financial firms and using analysts' book value per share (BVPS) forecasts as a proxy for forward-looking information about OCI, we examine whether analysts provide information about future OCI via BVPS forecasts, whether investors respond to BVPS innovations (which should include OCI innovations), and whether such innovations are more useful to investors in financial firms with difficult-to-value financial assets. We find evidence consistent with: 1) Analysts' BVPS forecasts generally conveying at least some information about future OCI; and, 2) The market responding to whether firms miss analysts' consensus BVPS expectations (which should include OCI expectations), with stronger evidence for firms with larger holdings of difficult-to-value financial assets. The evidence supports the intuition that analysts provide at least some information about future OCI in their BVPS forecasts.

Explaining Returns Through Valuation

This article develops an analytically coherent yet parsimonious framework which explains market returns in terms of contemporaneous information. It anchors on the idea that valuation (static perspective) can be connected to the dynamics that explain returns, and vice versa. The framework requires two components. First, an explicit function that maps information to an estimate of value—a valuation heuristic. Second, the framework assumes that the difference between a firm’s actual value and value-per-heuristic follows an autoregressive stochastic process with a contraction parameter and no intercept. The contraction parameter can be estimated efficiently and nonparametrically. This modeling suffices to derive implied returns. Using scaled Earnings Per Share (``EPS'') forecasts as valuation heuristics, we empirically evaluate the framework’s validity and robustness. Its explanatory power compares favorably to that of traditional ordinary least squares (``OLS'') regressions, despite only requiring a single parameter. In a setting with pooled annual data, the implied and realized returns correlations range between 64% and 73%.

Profit Forecast Accuracy of Time Series Model - A Case Study of Associated British Foods

Accurate earnings per share (EPS) forecasting is crucial for financial decision-making. This study explores the potential of improving EPS forecasting accuracy by integrating economic lead indicators into time-series models. By incorporating macroeconomic factors like GDP growth and interest rates, the models capture the influence of the broader economic environment on a company’s financial performance. Results demonstrate that including economic lead indicators significantly enhances EPS predictability beyond traditional time-series models. This integration offers a forward-looking perspective, comprehensive analysis, and context to the forecasting process, enabling stakeholders to make more informed investment decisions and develop better strategies. Further research can investigate additional lead indicators, assess their impact in different industries, and develop hybrid forecasting models for refined EPS predictions.

Analysts’ Earnings per Share Forecasts: The Effects of Forecast Uncertainty and Forecast Precision on Investor Judgements

This study uses controlled experiments to investigate the joint effects of forecast uncertainty and forecast precision on investor judgements. It finds that forecast precision moderates the effects of forecast uncertainty on investors’ forecast reliability judgements such that the effects of forecast uncertainty on investors’ judgements of forecast reliability are more negative when an analyst's point earnings per share (EPS) forecast is rounded than when it is precise. In addition, the relationship between forecast precision and investors’ judgements of forecast reliability is mediated by investors’ perceptions of forecast attributes. The evidence also suggests that while forecast uncertainty exerts a negative effect on investment judgements, forecast precision does not play a role in mitigating these negative effects. Using a supplementary within‐participants experiment, the study further finds that investors may not be consciously aware of how forecast precision influences their judgements of forecast reliability.

Budget Impact Analysis of Expanding Gliflozin Coverage in the CKD Population: A French Perspective.

Gliflozins have historically been indicated for type 2 diabetes in France. However, their efficacy has recently been demonstrated in heart failure and chronic kidney disease (CKD), with positive recommendations by Haute Autorité de Santé for gliflozin therapies in these indications. The study objective was to investigate the 5-year budget impact associated with the introduction of gliflozins in addition to standard therapy in people with CKD and elevated albuminuria, regardless of diabetes status, from the perspective of the French healthcare system. A budget impact model was developed to estimate the 5-year implications of incorporating gliflozins in the treatment of patients withCKD in France, using efficacy data from the Dapagliflozin and Prevention of Adverse Outcomes in Chronic Kidney Disease (DAPA-CKD) trial. Direct medical costs associated with drug acquisition and management, treatment-related adverse events, dialysis and kidney transplantation, and adverse clinical outcomes were considered. Market share forecasts were estimated from historical data and expert opinions. Event rates were derived from trial data, while cost data were sourced from published estimates. The introduction of gliflozins was estimated to be cost saving compared to the no gliflozins scenario, with an expected cumulative 5-year budget impact of -€650 million, driven by slowed disease progression in patients treated with gliflozins, with fewer patients cumulatively progressing to end-stage kidney disease (84,526 vs. 92,062). This, in addition to fewer hospitalisations for heart failure and deaths from any cause, led to substantial medical care cost offsets (kidney-related: -€894 million; hospitalisation for heart failure: -€14.3 million; end-of-life care: -€17.3 million) to the additional drug acquisition (€273 million) and treatment-related adverse events costs (€2.98 million). In concert with early diagnosis and proactive management of CKD, the expansion of the gliflozin indications into the French CKD population presents the opportunity to reduce the substantial burden associated with cardio-renal complications which outweighs the additional cost of the new treatment. INFOGRAPHIC.

Do Analysts’ EPS Forecasts Obey Benford’s Law? An Empirical Analysis

Benford’s law gives the expected frequencies of digits in tabulated data. In this study, I investigate the extent to which a sample of analysts’ earnings per share (EPS) forecasts obey Benford’s law. I conduct Benford’s law’s second digit and last-two digits tests on a sample of analyst EPS forecasts of S&P 500 firms from 1998 to 2018. Overall, I find that analysts’ EPS forecasts obey Benford’s law’s second digit test but do not obey the last-two digits test. These findings suggest that while analysts do not engage in number invention, they do engage in rounding when making EPS forecasts.

Conteúdo informacional dos principais assuntos de auditoria e a previsão dos analistas financeiros

Abstract The aim of this article was to analyze the relationship between the informational content of the key audit matters (KAMs) reported in the Independent Audit Report (IAR) and financial analysts’ forecasts for the companies listed on the B3 S.A. - Brasil, Bolsa, Balcão (B3). The research that has investigated the relevance of KAMs has not analyzed the incremental information about the audited firm, from the independent auditor’s viewpoint, that can affect financial analysts’ forecasts. The findings of this research reveal that the KAMs reported present relevant informational content about the audited firm for financial analysts, thus improving the quality of their forecasts. In addition, it was observed in the quantile analysis that the KAMs contribute to the fine tuning of analysts’ forecasts. The debate on the auditor-analyst relationship is also widened, specifically regarding the utility of KAMs for financial analysts, in terms of them considering using this information in their projections for the analyzed companies, thus reinforcing the search for their improvement by the regulator. The analysis was conducted based on generalized least squares (GLS) and quantile regressions covering 137 non-financial companies, using data from (quarterly and annual) analysts’ forecasts available from Thomson Reuters Eikon® and financial information from Economatica®. In general, the quantity and content of the items reported as KAMs were revealed to be significant in relation to the analysts’ earnings per share forecasts and to their forecasting error, revealing a reduction in asymmetry. Thus, the higher the informational value of the KAMs, the better the quality of that information is, contributing to forming an earnings forecast consensus and minimizing the error in the financial analysts’ estimates. In addition, it was observed that the disclosure of KAMs has no immediate reflection in the earnings forecast in the quarter following their disclosure, with their informational content being diluted over the following financial period, impacting the annual earnings forecast.

Meet, beat, and pollute

We investigate two related questions about the trade-off between the short-term pressures on managers to meet earnings targets and the long-term environmental benefits of reduced pollution. Do firms release more toxins by cutting back on pollution abatement costs to boost earnings in years they meet earnings benchmarks? If so, is that relation weaker for firms with higher environmental ratings? Using Environmental Protection Agency (EPA) data on toxic emissions, we find that U.S. firms pollute more when they meet or just beat consensus earnings per share (EPS) forecasts, suggesting that meeting expectations is a more important goal than reducing pollution. We find this relation is stronger, not weaker, for firms with higher environmental ratings: they increase pollution even more when meeting earnings benchmarks than firms with lower ratings. This suggests that highly rated firms build regulatory and reputational slack over time and use it when needed to soften the negative impact of increased pollution. We contribute to the real earnings management and environmental economics literatures by documenting a negative externality of financial reporting incentives on the environment and society. We also contribute to the corporate sustainability literature by showing that an environmental, social, and governance (ESG) focus does not curb managerial short-termism.

Do Analysts’ Cross‐year Revisions Contain Information about Audit Adjustment? Evidence from the Chinese Capital Market*

AbstractThis study tests the information content of changes in analysts’ earnings forecasts. Using audit adjustment data from China, this study investigates whether changes in analysts’ cross‐year forecast revisions reflect audit information. The results show that the cross‐year revision of analysts’ earnings per share forecasts is positively related to the magnitude of audit adjustment, which may be mainly due to analysts’ communication with management. Furthermore, analysts who display higher forecast frequency, who issue their last forecast closer to the day the annual report is announced, or who show better forecast performance reflect a greater amount of audit information in their cross‐year forecast revisions.

PND16 Socioeconomic Value of Ocrelizumab in the Treatment of Patients with Primary Progressive Multiple Sclerosis

Ocrelizumab is the first and only disease-modifying therapy (DMT) approved by Health Canada for patients with primary progressive multiple sclerosis (PPMS). In this study, we assess the socioeconomic benefits derived from using ocrelizumab in PPMS compared with best supportive care (BSC) in Canada. A Markov-state model based on one-point spaced Expanded Disability Status Scale (EDSS) states (0–9) was used to estimate costs associated with disease progression. EDSS at baseline and transition probabilities were derived from the ORATORIO trial and MSBase natural history study, respectively. Treatment effect on delaying disability progression was modeled through the hazard ratio for time to 24-week confirmed disability progression, which was derived from a counterfactual analysis of the ORATORIO double-blind and open-label extension phases. Societal benefits included savings in direct healthcare and non-healthcare costs, and indirect costs (including informal care and productivity loss, among others). Drug costs were excluded to focus on treatment benefits. Resource use and cost inputs at 2019 prices were derived from published studies in the multiple sclerosis space or from national statistics databases. Data on PPMS prevalence and proportion of patients receiving BSC in Canada were obtained by triangulating Canadian epidemiologic data, Roche PPMS market share forecast, and real world data from the Ocrevus patient support program. The socioeconomic value of ocrelizumab compared with BSC in Canada is estimated to be CAD$61.3 million over 5 years. These cost savings are driven by reduction in the utilization of healthcare resources and community services ($33.1 million), productivity loss ($13.8 million), and informal care ($10.8 million). Ocrelizumab for PPMS offers substantial socioeconomic benefits compared with BSC in Canada.

Analysts’ EPS Forecasts: The Effects of Forecast Uncertainty and Forecast Precision on Investors’ Judgments of Forecast Reliability

I use controlled experiments to investigate the joint effects of forecast precision and forecast uncertainty on investor judgments. I find that forecast precision moderates the effects of forecast uncertainty on investors’ forecast reliability judgments such that the effects of forecast uncertainty on investors’ judgments of forecast reliability are more negative when an analyst’s point earnings per share (EPS) forecast is round than when it is precise. In addition, the relationship between forecast precision and investors’ judgments of forecast reliability is mediated by investors’ perceptions of analysts’ personal characteristics related to their forecasting ability. My evidence also suggests that while forecast uncertainty continues to exert a negative effect on investors’ investment judgments, forecast precision does not play a role in mitigating these negative effects. Using a supplementary within-participants experiment, I further find that investors may not be consciously aware of how forecast precision influences their judgments of forecast reliability. My findings are informative to analysts and investors because they provide insights into how investors perceive and react to rounding in analysts’ point EPS forecasts under differing levels of forecast uncertainty.

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.

Mandatory Repurchase Disclosure, Opportunistic Repurchases, and Their Real Effects

In 2003, the SEC amended Rule 10b-18, significantly increasing the disclosure requirements for and transparency of share repurchases with the intention to curb false signaling by management. Bonaime (2015) finds that the 2003 SEC amendment reduced firms’ open market repurchase announcements and increased repurchase announcement completion rates, resulting in a decline in false signaling. In this paper, we examine the effect of the 2003 SEC amendment on firms’ opportunistic use of stock repurchases to meet or beat analyst earnings per share (EPS) forecasts and the resultant negative real effects. We find that the 2003 SEC amendment curtails opportunistic repurchases, enables the market to recognize and discount opportunistic repurchases, and eliminates the employment and investment reductions following opportunistic repurchases. Our evidence suggests that the increased transparency of share repurchases mandated by the 2003 SEC amendment has significantly altered both the corporate use of repurchases as an earnings management device and the negative real consequences of opportunistic repurchases.

Examining the phenomenon of rounding in analysts' EPS forecasts: evidence from Singapore

PurposePrior studies have documented the phenomenon of rounding of analysts' earnings per share (EPS) forecasts in the USA. From the outset, it is unclear if analysts following Singapore firms also similarly engage in the rounding of their EPS forecasts. This study aims to investigate the extent to which analysts engage in rounding of EPS forecasts of firms listed on the Singapore Exchange.Design/methodology/approachThe author conducted his analysis on a sample of analyst EPS forecasts of companies listed on the Singapore Stock Exchange, downloaded from the International Brokers Estimate System (I/B/E/S). This sample consists of 24,219 annual EPS forecasts announced from June 2011 to September 2019. These forecasts were made for 285 unique firms by 48 unique analysts.FindingsThe author finds that there is substantial rounding of EPS forecasts, with 9.59% of EPS forecasts examined ending in five- or ten-cent intervals. In supplementary analysis, the author further finds that the level of rounding was comparable across two periods under examination, from 2011 to 2015 and from 2016 to 2019. The author also finds that there was substantial rounding even for forecasts of relatively large magnitudes (i.e. US$1.00 and above).Originality/valueThis study is the first to examine the rounding of analysts' EPS forecasts of Singapore firms. It extends the literature on analyst EPS forecasts and highlights how the phenomenon of rounding of analyst EPS forecasts of US firms extends to Singapore.

The Information Content of Analysts' Book Value Per Share Forecasts

We investigate the information content of analysts’ book value per share (BVPS) forecasts. We test whether analysts’ BVPS forecasts are informative about future realizations of other comprehensive income (OCI) and special items controlling for analysts’ EPS forecasts. Our results suggest that analysts’ BVPS forecasts generally incorporate upcoming realizations of OCI and special items, especially for financial firms. We also find evidence that BVPS forecasts provide expectations of non-EPS income, and that the market responds to BVPS innovations, especially BVPS forecasts misses. Finally, we find evidence that analysts provide more BVPS forecasts for financial firms that 1) have greater absolute levels of accumulated other comprehensive income (AOCI) from securities and derivatives, 2) report higher levels of OCI from securities, and 3) hold more opaque financial assets, and for non-financial firms with high absolute levels of pension-related AOCI.

Sustainability disclosure and financial analysts' accuracy: The European case

AbstractThis study aims to analyze whether the adoption of Directive 2014/95/EU on sustainability disclosure has contributed to more truthful reporting to financial analysts in terms of risks and firms' performance. Financial analysts, as requesters of sustainability reports, are expected to have produced more accurate forecasts as a result of this legal reform. To investigate this, we have examined analysts' earnings per share (EPS) forecasts for 434 companies, 241 of which are classified as low sustainability companies, from 2008 to 2017. To detect a possible increase in EPS forecast accuracy after the enforcement of the directive, we perform an analysis based on panel regression specifications. The results show that EPS forecast accuracy has increased due to the higher levels of both sustainability disclosure and reporting quality after the enforcement of Directive 2014/95/EU.

Do intangible assets matter to financial analysts in the Brazilian stock market?

Purpose – This paper aims to investigate how and to what extent intangible assets influence the evaluations of financial analysts covering companies listed on the Brazilian Stock Exchange ( Brazil, Bolsa, Balcao – B3) from 2010 to 2016. Design/methodology/approach – The analysis was divided into two stages. In the first stage, we examined intangible asset taxonomies (i.e., structural, relational, and human capital) through content analysis by counting repeated key terms related to each category of intangible assets cited in the financial analysts’ reports. In the second stage, we analyzed the influence of intangible asset proxy variables on coverage, forecasting errors, and accuracy of earnings per share forecasts by financial analysts. Findings – In the first stage, the results suggested that analysts cited more terms related to the structural capital category, particularly the terms “strategy” and “mission.” In the second stage, the results pointed to the absence of statistically significant relationships between the studied variables. Therefore, it is possible to infer that although financial analysts covering firms in the Brazilian Stock Exchange cite terms related to intangible assets in their reports – which, in turn, points to the relevance of these assets during the company valuation process – the difficulty of conducting evaluations grounded on reliable bases, the scarcity of quality information about their development, and incentive problems may challenge or even prevent quantitative assessments targeted at capital market participants. Originality/value – By adopting an innovative methodological approach in the Brazilian context, this study highlights the fact that intangible assets influence financial analysts to a certain extent and they, in turn, manage to incorporate them into their analyses, although the statistical relationships have not been explicitly demonstrated.

Measuring public opinion via digital footprints

Do digital traces accurately reflect individual preferences? Can signals from social media be used to measure public opinion? This paper provides evidence in favour of these hypotheses. We test a regression and post-stratification strategy that combines samples of digital traces with a stratification frame containing individual-level socio-economic data, in order to generate area forecasts of the outcome social phenomena of interest. In our example, we forecast the two-party vote of Democrats and Republicans in the 2018 Texas congressional district and Senate election. Our implementation assumes we can observe, and sample, individuals signaling their preference by favoring one virtual location over another; in our case, visiting Democrat versus Republican Facebook pages during the election campaign. Over the course of seven weeks preceding the mid-term elections we generate vote share forecasts which do not use any traditional survey data as input. Our results indicate that individuals leave digital traces that reflect their preferences.

Air Transportation Direct Share Analysis and Forecast

Air transportation direct share is the ratio of direct passengers to total passengers on a directional origin and destination (O&D) pair. Direct share is an essential factor of passenger flow distribution and shows passengers’ general preference for direct flight services on a certain O&D. A better understanding and a more accurate forecast of direct share can benefit air transportation planners, airlines, and airports in multiple ways. In most of the previous research and applications, it is commonly assumed that direct share is a fixed ratio, which contradicts the air transportation practice. In the Federal Aviation Administration (FAA) Terminal Area Forecast (TAF), the O&D direct share is forecasted as a constant based on the latest observation of direct share on the O&D. To find factors which have significant impacts on O&D direct share and to build an accurate model for O&D direct share forecasting, both parametric and nonparametric machine learning models are investigated in this research. We propose a novel category-based learning method which can provide better forecasting performance compared to employing the single modeling method for O&D direct share forecasting. Based on the comparison, the developed category-based learning model is a promising replacement for the model used for O&D direct share forecasting by the FAA TAF.

Why do stock repurchases change over time?

AbstractRecent studies have shown the time trends of firm stock repurchase behavior. We examine these time changes for stock repurchase through the lens of real activities earnings management. Managers appear more likely to manipulate earnings through stock repurchases since the passage of the Sarbanes–Oxley Act (SOX) in 2002. Furthermore, suspect firms that just missed analyst earnings per share forecasts have higher incentives to manipulate earnings through stock repurchases. The results are not driven by changes in corporate governance associated with the passage of SOX. Overall, our results suggest earnings management can be a significant determinant of the dynamics of stock repurchases.