The effect of consistency in book-tax differences on analysts’ earnings forecasts: Evidence from forecast accuracy and informativeness

This study examines the relationship between the consistency of book-tax differences and the quality of analysts’ earnings forecasts. We find that the consistency of book-tax differences is associated with more accurate and informative forecasts. This suggests that the information embedded in the consistency of book-tax differences plays an important role in elevating the quality of analysts’ forecasts. Furthermore, the effect of consistency in book-tax differences on analyst forecast quality is greater for firms with noisier information environment. Finally, we find that the relation between consistency in book-tax differences and improvements in forecast accuracy and informativeness is stronger after the implementation of Regulation Fair Disclosure, which increased the role of public information in analysts’ forecasts.     

Causal language intensity in performance commentary and financial analyst behaviour

We use automated techniques to measure causal reasoning on earnings‐related financial outcomes of a large sample of MD&A sections of US firms and examine the intensity of causal language in that context against extent of analyst following and against properties of analysts’ earnings forecasts. We find a positive and significant association between a firm's causal reasoning intensity and analyst following and analyst earnings forecast accuracy respectively. Correspondingly, analysts’ earnings forecast dispersion is negatively and significantly associated with causal reasoning intensity. These results suggest that causal reasoning intensity provides incremental information about the relationship between financial performance outcomes and its causes, thereby reducing financial analysts’ information processing and interpreting costs and lowering overall analyst information uncertainty. Additionally, we find that decreases in analyst following are followed by more causal reasoning on performance disclosure. We also find that firms with a considerable increase of causal disclosure especially attract new analysts who already cover many firms. Overall, our evidence of the relationship between causal reasoning intensity and properties of analyst behaviour is consistent with the proposition that causal reasoning is a generic narrative disclosure quality characteristic, able to provide incremental information to analysts and guide analysts' behaviour.     

Do analysts who understand accounting conservatism exhibit better forecasting performance?

This study investigates the performance of analysts when they match the asymmetric timeliness of their earnings forecast revisions (i.e., asymmetric forecast timeliness) with the asymmetric timeliness of firms’ reported earnings (i.e., asymmetric earnings timeliness). We find that better timeliness‐matching analysts produce more accurate earnings forecasts and elicit stronger market reactions to their forecast revisions. Further, better timeliness‐matching analysts issue less biased earnings forecasts, more profitable stock recommendations and have more favorable career outcomes. Overall, our results indicate that analysts’ ability to incorporate conditional conservatism into their earnings forecasts is an important reflection of analyst expertise and professional success.     

Value relevance of analyst earnings forecasts in emerging markets

Even though research in accounting and finance has extensively examined the role of financial analysts in developed economies, this issue has not been thoroughly examined in an emerging market setting. In this paper, I examine whether, following a market opening, analyst forecast accuracy and the market's reliance on analyst forecasts increase with time. Accuracy is expected to increase over time as analysts exert more effort and gain valuable forecasting experience. Results indicate that time is positively related to analyst forecast accuracy after controlling for a number of other firm and country characteristics. Second, I posit that time should also be related to the market's propensity to use analyst forecasts to form earnings expectations. As markets open and investors become more sophisticated, the reliance on analyst forecasts should also increase. Results are consistent with this expectation. In particular, I find that in the first sub-period earnings expectations based on random walk exhibit greater relative information content than earnings expectations based on analyst forecasts. This pattern is reversed in the third sub-period where analyst forecast errors better explain returns. Incremental information content tests produce similar results. Future research should further investigate the relation between financial analysts and other important market characteristics in emerging economies.     

High-Technology Intangibles and Analysts' Forecasts

This study examines the association between firms' intangible assets and properties of the information contained in analysts' earnings forecasts. We hypothesize that analysts will supplement firms' financial information by placing greater relative emphasis on their own private (or idiosyncratic) information when deriving their earnings forecasts for firms with significant intangible assets. Our evidence is consistent with this hypothesis. We find that the consensus in analysts' forecasts, measured as the correlation in analysts' forecast errors, is negatively associated with a firm's level of intangible assets. This result is robust to controlling for analyst uncertainty about a firm's future earnings, which we also find to be higher for firms with high levels of internally generated (and expensed) intangibles. Given that analyst uncertainty increases and analyst consensus decreases with the level of a firm's intangible assets, we also expect and find that the degree to which the mean forecast aggregates private information and is more accurate than an individual analyst's forecast increases with a firm's intangible assets. Finally, additional analysis reveals that lower levels of analyst consensus are associated with high-technology manufacturing companies, and that this association is explained by the relatively high R&D expenditures made by these firms. Overall, our results are consistent with financial analysts augmenting the financial reporting systems of firms with higher levels of intangible assets (in terms of contributing to more accurate earnings expectations), particularly R&D-driven high-tech manufacturers.     

Can security analyst forecasts predict gold returns?

This paper examines whether security analyst earnings forecasts for firms primarily operating in the gold market can be utilised to predict returns on the price of gold. We first demonstrate that analysts are at least in part basing their earnings forecasts for gold firms on the return expectations of the gold commodity market. We show this by providing evidence that analyst coverage impounds not only market-wide and industry information, but also gold price information for these firms — as measured via its impact on stock return synchronicity. We then examine if the difference between forecast and observed earnings for these firms has predictive value for changes in the price of gold whilst controlling for a number of macroeconomic factors. We find that this difference does hold predictive power, but also has some limitations. However, there is potential for it to be used as an additional variable within gold forecasting frameworks.     

Stock index adjustments and analysts’ forecast optimism: A quasi-natural experiment on the CSI 300 Index

As stock index adjustments comprise a basic system of capital market, their potential influence on analysts’ earnings forecasts is worthy of research. Based on a research sample of 23 adjustments to the CSI 300 Index from June 2007 to June 2018 and the backup stocks announced during the same period, this study examines the impact of additions to stock index on analysts’ forecast optimism using a staggered difference-in-differences model. The research results show that after stocks are added to the stock index, analysts’ earnings forecast optimism about these stocks increases significantly. Cross-sectional analysis indicates that this increase is more significant when the market is bullish, institutional ownership is low, the ratio of listed brokerage firms is low, star analyst coverage is low, firms show seasoned equity offering activity, the ratio of analysts from the top five brokerage firms ranked by commission income is high, and the analysts’ brokerage firms are shareholders. However, analyst-level tests find that analysts’ ability helps to reduce the impact of additions to stock index on earnings forecast optimism. Furthermore, additions to stock index significantly increase analyst coverage and forecast divergence. Economic consequences tests find additions to stock index significantly increases stock price synchronization, which is partly mediated by analysts’ earnings forecast optimism. This study enriches the literature on the impact of basic capital market systems and analyst behavior. The findings suggest that investors should rationally evaluate analysts’ earnings forecasts for stocks added to the stock index and obtain further information from various channels to improve asset allocation efficiency.     

Do voluntary disclosures of product and business expansion plans impact analyst coverage and forecasts?

We investigate whether voluntary disclosures of product and business expansion plans affect analyst coverage and forecasts. We find that the level of analyst coverage is positively associated with the incidence of disclosures of product and business expansion plans. We also find that product and business expansion disclosures increase the informativeness of analyst earnings forecasts. We find no evidence that product and business expansion disclosures increase analyst forecast errors. Overall, our study contributes to understanding the role of product and business expansion disclosures in analyst forecast behaviour.     

Do Managers Use Meeting Analyst Forecasts to Signal Private Information? Evidence from Patent Citations

This study examines whether firms manage earnings to meet analyst forecasts to signal superior future performance. Prior research finds that firms use earnings management to just meet analyst forecasts and that these firms have a positive association with future performance (Bartov et al., 2002). There are two potential explanations for the positive association – signaling and attaining benefits that allow for better future performance (i.e., the real benefits explanation). Prior studies cannot provide evidence of signaling because they do not control for the real benefits explanation. Our research design enables us to control for the real benefits explanation because we can identify potential signaling firms within the sample of firms that just meet analyst forecasts. We use a unique database from the National Bureau of Economic Research to construct a proxy for the manager's belief about future firm value due to patents. We find that firms with more patent citations are more likely to just meet the analyst forecast and manage earnings to achieve this goal. We also find firms that just meet analyst forecasts with more patent citations have significantly better performance than firms with fewer patent citations, which is consistent with signaling and not the real benefits explanation.     

The supply of analysts and earnings forecasts

Using a unique set of hand-collected data, this study examines whether a larger supply of prospective analysts leads to existing financial analysts' higher earnings forecast accuracy. We analyze the effect of the analyst supply proxied by the number of universities and the number of finance and economics universities located in the same city as the headquarters of brokerage firms. Our findings suggest that brokerage firms located closer to a larger supply of potential analyst candidates are associated with higher analyst forecast accuracy, as observed by a lower forecast error. We further find that the degree of employed analysts' effort acts as a mediator between the supply of prospective analysts and the accuracy of their earnings forecasts.     

A new approach to predicting analyst forecast errors: Do investors overweight analyst forecasts?

I provide evidence that investors overweight analyst forecasts by demonstrating that prices do not fully reflect predictable components of analyst errors, which conflicts with conclusions in prior research. I highlight estimation bias in traditional approaches and develop a new approach that reduces this bias. I estimate characteristic forecasts that map current firm characteristics into forecasts of future earnings. Contrasting characteristic and analyst forecasts predicts analyst forecast errors and revisions. I find abnormal returns to strategies that sort firms by predicted forecast errors, consistent with investors overweighting analyst forecasts and predictable biases in analyst forecasts influencing the information content of prices.     

“Big Bang” Accounting Reforms in Japan: Financial Analyst Earnings Forecast Accuracy Declines as the Japanese Government Mandates Japanese Corporations to Adopt International Accounting Standards

The mandated adoption of International Accounting Standards (IAS) for Japanese corporations did not result in improved earnings that forecast predictability. These findings contradict the research findings of Ashbaugh and Pincus (2001). Herrmann, Inoue, and Thomas’ (2003) research findings support the need for mandating the adoption of IAS. They found that Japanese managers were “manipulating” reported earnings by managing the sale of fixed assets and marketable securities. Adoption of IAS decreases the availability of this practice and it was and is expected to increase disclosure and transparency. Increased disclosure and transparency are expected to decrease financial analyst forecast errors, which did not decrease for 139 firms examined in this study for the timeframe of 1999–2002. This research finding does not support the idea that adoption of IAS improves financial information used in decision making relative to forecasting earnings. Assuming that increased predictability indicates higher quality reported earnings and enhanced usefulness of financial information, the mandated adoption of IAS did not result in these. Assuming that adoption of IAS in Japan increased the level of transparency and disclosure by Japanese firms, which made it harder for Japanese firms to manage their earnings in order to meet the managerial earnings forecasts that these firms must make. Thus, after the adoption of IAS in Japan, forecast errors for managerial forecasts of earnings increased. This evidence is new to the literature.     

Analyst Specialization and Conglomerate Stock Breakups

This paper examines whether firms emerging from conglomerate stock breakups are able to affect the types of financial analysts that cover their firms as well as the quality of information generated about their performance. Our sample comprises 103 focus-increasing spin-offs, equity carve-outs, and targeted stock offerings between 1990 and 1995. We find that, after these transactions, sample firms experience a significant increase in coverage by analysts that specialize in subsidiary firms' industries, and a 30–50% increase in analyst forecast accuracy for parent and subsidiary firms. The improvement in forecast accuracy is partially attributable to expanded disclosure. However, forecast improvements for specialists exceed those for non-specialists, leading us to conclude that corporate focus can facilitate improved capital market intermediation by financial analysts with industry expertise.     

Making Sense of Cents: An Examination of Firms That Marginally Miss or Beat Analyst Forecasts

This paper examines the performance consequences of cutting discretionary expenditures and managing accruals to exceed analyst forecasts. We show that firms that just beat analyst forecasts with low quality earnings exhibit a short-term stock price benefit relative to firms that miss forecasts with high quality earnings. This trend, however, reverses over a 3-year horizon. Additionally, firms reducing discretionary expenditures to beat forecasts have significantly greater equity issuances and insider selling in the following year, consistent with managers understanding the myopic nature of their actions. Our results confirm survey evidence suggesting managers engage in myopic behavior to beat benchmarks.     

To beat or not to beat? The importance of analysts’ cash flow forecasts

We investigate the implications of firms’ benchmark-beating patterns with respect to analysts’ quarterly cash flow forecasts for firms’ current capital market valuation and their future performance. We hypothesize that nonnegative earnings surprises are more likely to be supported by real operating performance and signal higher earnings quality if they are achieved via higher than expected cash flows or lower than expected accruals. We show that firms beating analyst earnings forecasts have larger positive capital market reactions and larger earnings response coefficients if they beat analyst cash flow forecasts or report lower than expected accruals. We also demonstrate that these firms’ superior future performance may provide an economic justification for their more favorable market response. Our findings suggest that firms’ ability to beat analyst cash flow forecasts is informative regarding the quality of their earnings surprises.     

The effect of repeat restructuring charges on analysts’ forecast revisions and accuracy

The primary objective of this study is to examine the effect of prior restructuring charges on analyst forecast revisions and accuracy. We find evidence that analysts respond differently to first-time restructuring firms than to repeat restructuring firms. Analysts revise their forecasts of both one-year-ahead earnings and five-year long-term growth in earnings more negatively for first-time restructuring firms than for firms with prior charges. When we examine forecast errors in the year subsequent to the restructuring, we find that current charges complicate analysts’ earnings forecast task. We further find that the decline in analyst forecast accuracy is mitigated by prior charges within past two years.     

Learning and incentive: A study on analyst response to pension underfunding

There is a long-standing debate on whether sell-side analysts learn from their experience to improve earnings forecast skills. This study shows that incentive is an important factor for understanding the “learning by doing” effect by analysts. We examine analysts’ response to a complex type of information – corporate pension underfunding. Pension underfunding negatively impacts future earnings and analysts on average underreact to such information in their earnings forecasts. More importantly, when there is a strong incentive for analysts to deliver accurate forecasts, analyst learning effectively reduces their underreaction to pension underfunding information. On the other hand, when such an incentive is absent, the analyst learning effect is not discernible in the data. Further evidence suggests that analyst learning and incentive jointly reduce stock market mispricing associated with corporate pension underfunding.     

Economic policy uncertainty and analysts’ forecast characteristics

We examine the influence of economic policy uncertainty (EPU) on the characteristics of analysts’ earnings forecasts over a thirty-year period, spanning a wide variety of political and economic conditions. Motivated by both theory and empirical evidence that suggest a decline in the quality of the information environment for firms as EPU increases, we establish that analysts’ forecast errors increase with EPU, as does the degree of forecast dispersion. Increased error and dispersion persist after controlling for several competing sources of economy-wide uncertainty. Cross sectional analysis exploring heterogeneity in forecast quality across both analyst and firm characteristics establishes that forecast error and dispersion increase with EPU across a broad spectrum of firms and levels of analyst expertise. We control for analysts’ experience overall and the years spent covering a particular industry and firm. Five alternative methods for classifying firms as policy sensitive versus policy neutral provide consistent evidence that analyst forecast errors and dispersion increase with EPU, even for firms not deemed to be particularly sensitive to policy.     

Do corporations manage earnings to meet/exceed analyst forecasts? Evidence from pension plan assumption changes

A significantly larger number of firms increase the expected rate of return on pension plan assets (ERR) to make their reported earnings meet/exceed analyst forecasts than would be expected by chance. In the short run, the stock market reacts positively to these firms’ earnings announcements, suggesting that investors fail to recognize that earnings benchmarks are achieved through ERR manipulation. In the long run, however, firms that employ this earnings management strategy significantly underperform control firms in both stock returns and operating performance.     

Market implied future earnings and analysts’ forecasts

This study provides evidence on market implied future earnings based on the residual income valuation (RIV) framework and compares these earnings with analyst earnings forecasts for accuracy (absolute forecast error) and bias (signed forecast error). Prior research shows that current stock price reflects future earnings and that analyst forecasts are biased. Thus, how price-based imputed forecasts compare with analyst forecasts is interesting. Using different cost of capital estimates, we use the price-earnings relation and impute firms’ future annual earnings from three residual income (RI) models for up to 5 years. Relative to I/B/E/S analyst forecasts, imputed forecasts from the RI models are less or no more biased when cost of capital is low (equal to a risk-free rate or slightly higher). Analysts slightly outperform these RI models in terms of accuracy for immediate future (1 or 2) years in the forecast horizon but the opposite is true for more distant future years when cost of capital is low. A regression analysis shows that, in explaining future earnings changes, analyst forecasts relative to imputed forecasts do not impound a significant amount of earnings information embedded in current price. In additional tests, we impute future long-term earnings growth rates and find that they are more accurate and less biased than I/B/E/S analyst long-term earnings growth forecasts. Together, the results suggest that the RIV framework can be used to impute a firm’s future earnings that are high in accuracy and low in bias, especially for distant future years.