What do analysts do? Discussion of “Information interpretation or information discovery: which role of analysts do investors value more?”

Three decades of accounting and finance research has extensively studied the outputs from financial analysts. However, there is sparse systematic evidence on what analysts do to generate their outputs in the form of forecasts, recommendations, and research reports. Livnat and Zhang (Rev Account Stud, 2012) provide interesting new evidence regarding the relative amount of value added that analysts produce by examining investors?? reaction to analysts?? forecast revisions issued promptly after firms?? public disclosures compared with those issued at other times. Their analysis shows that prompt revisions are associated with larger returns, which the authors interpret as evidence that analysts?? ability to interpret public disclosures is more valuable to investors. Three issues bear consideration in the interpretation of these findings.     

Information content of repurchase signals: Tangible or intangible information?

The outperformance of repurchasing firms with a high book-to-market (B/M) ratio is usually explained by investors’ undervaluation of the firm’s past performance. However, several studies suggest that the underestimation of future intangible value may explain the high return associated with the share repurchase. To better understand the actual information content of repurchases, I decompose the B/M ratio into past tangible information and future intangible information and find that repurchase signals an undervaluation of the intangible return. In addition, I investigate several potential proxies for intangible information—R&D expenses, intangible assets, and future operating performance. My results show that intangible information signals the undervaluation of future operating performance.     

How value–glamour investors use financial information: UK evidence of investors’ confirmation bias

This paper investigates how investors in value and glamour stocks use financial information. The empirical evidence presented is in line with a model of investors’ asymmetric reaction to good and bad news due to confirmation bias. Pessimistic value investors typically under-react to good financial information, while they process bad information rationally or over-confidently. On the contrary, glamour investors are often too optimistic to timely update prices following bad financial information, while they are likely to fairly price or even over-react when receiving good information.     

Do star analysts know more firm-specific information? Evidence from China

Using a unique database in China, we extend the literature to further distinguish the information production role of star vs. non-star analysts. We confirm the general conclusion of a positive association between analyst coverage and stock return synchronicity measured by a firm’s R² in China. The findings from star analysts, however, show that star analyst coverage actually decreases stock return synchronicity. We contend that the firm-specific human capital in star analysts helps the analysts overcome the challenges of information production in an emerging market. The superior firm-specific human capital argument of star analysts is further supported by the negative association of star analysts’ firm-specific experiences and stock return synchronicity. Our conclusions are robust to different specifications of star analyst presence and different definitions of analysts’ firm-specific experiences. We also find that star analysts exhibit a more accurate earnings forecast than non-star analysts.     

With which countries do tax havens share information?

In recent years tax havens and offshore financial centres have come under increasing political pressure to cooperate with other countries in matters of taxation and efforts to crowd back tax evasion and avoidance. As a result many tax havens have signed tax information exchange agreements (TIEAs). In order to comply with OECD standards tax havens are obliged to sign at least 12 TIEAs with other countries. This paper investigates how tax havens have chosen their partner countries. We ask whether they have signed TIEAs with countries to which they have strong economic links or whether they have systematically avoided doing this, so that information exchange remains ineffective. We analyse 565 TIEAs signed by tax havens in the years 2008–2011 and find that on average tax havens have signed more TIEAs with countries to which they have stronger economic links. Our analysis thus suggests that tax havens do not systematically undermine tax information exchange by signing TIEAs with irrelevant countries. However, this does not mean that they exchange information with all important partner countries.     

Measuring investors’ assessment of earnings persistence: do investors see through smoothed earnings?

Prior studies document that investors value persistent earnings more than transitory earnings. This argument offers incentives to managers to smooth their reported earnings and make them look more persistent. This study examines whether investors are misled by management’s income-smoothing behavior and whether they can correctly assess the persistence of smoothed earnings. Using a simple theoretical model, this paper shows that investors’ assessment of earnings persistence can be derived from their reactions to reported earnings, which is the ratio of the coefficient on earnings change relative to the coefficient on earnings level in the return–earnings relation. Empirical results show that investors’ assessment of earnings persistence is negatively associated with the level of income smoothing after controlling for time-series persistence of earnings and hence suggest that investors understand that the high persistence of smoothed earnings is not real and they discount the persistence of smoothed earnings when they react to such earnings news.     

Foreign versus local investors: Who knows more? Who makes more?

This paper examines the nature of information asymmetry between foreign and local investors on the Helsinki stock exchange (HEX) for the period 1999–2004. We take into account the differences in informational characteristics by partitioning stocks into single-listed, cross-listed and internationally well-known stock categories, after which we compare foreign and local investors’ performance and trading advantages. Local investors have trading advantages in the short term in all stock categories. However, such local advantages diminish for Nokia, the only internationally well-known stock on HEX.     

Do independent research analysts issue more or less informative recommendation revisions?

This paper studies whether independent research analysts issue more informative stock recommendation revisions than investment bank analysts. I find independent analyst recommendation upgrades and downgrades significantly less informative. I also investigate whether the identified differences in informativeness are the result of systematic cross-sectional variation in analyst ability, portfolio complexity, and brokerage firm resources. Including these variables reduces the disparity in information content between groups. However, independent revisions continue to have lower informativeness. I follow prior research and compute daily buy-and-hold abnormal returns to portfolios formed based on analyst firm type. I find that investment bank analyst portfolios generally outperform those of independent research analysts. Lastly, I examine market reactions before and after the Global Settlement Agreement that was enacted to limit the perceived conflicts in the industry. Lastly, investment bank analyst upgrades generate an 18.7% greater reaction in the post-regulation period, suggesting the Global Settlement helped mitigate biased research. Independent analysts continue to issue less informative recommendations.     

Detailed management earnings forecasts: do analysts listen?

We provide archival evidence on how a particular type of supplementary information affects the credibility of management earnings forecasts. Managers often provide detailed forecasts of specific income statement line items to shed light on how they plan to achieve their bottom-line earnings targets. We assess the effect of this forecast disaggregation on the credibility of management earnings forecasts. Based on a relatively large hand-collected sample of 900 management earnings forecasts, we find that disaggregation increases analysts’ sensitivity to the news in managers’ earnings guidance, suggesting that analysts find the guidance more credible. More importantly, we identify several factors that influence this relation. First, disaggregation plays a more important role when earnings are otherwise more difficult to forecast. Second, disaggregation is more important after Regulation Fair Disclosure prohibited selective disclosure, especially for firms that were more affected because they had previously provided more private guidance. Finally, in contrast to common assertions in the prior literature, we find that, in more recent years, disaggregation matters more for guidance that conveys bad news. Managers as well as researchers should be interested in evidence suggesting that financial analysts find disaggregation especially helpful in contexts where managers’ credibility is particularly important.     

Option trading: Information or differences of opinion?

This paper investigates the motive of option trading. We show that option trading is mostly driven by differences of opinion, a finding different from the current literature that attempts to attribute option trading to information asymmetry. Our conclusion is based on three pieces of empirical evidence. First, option trading around earnings announcements is speculative in nature and mostly dominated by small, retail investors. Second, around earnings announcements, the pre-announcement abnormal turnovers of options seem to predict the post-announcement abnormal stock returns. However, once we control for the pre-announcement stock returns, the predictability completely disappears, implying that option traders simply take cues from the stock market and turn around to speculate in the options market. Third, cross-section and time-series regressions reveal that option trading is also significantly explained by differences of opinion. While informed trading is present in stocks, it is not detected in options.     

Do higher value firms voluntarily disclose more information? Evidence from China

This paper examines the effect of guanxi on the relation between firm value and voluntary disclosure of information about new investment projects in China's institutional setting. We find a negative relation between firm value and voluntary disclosure for firms that rely heavily on guanxi in their value creation (e.g. non-high-tech firms, and firms located in regions with underdeveloped institutions). By contrast, for firms that rely less heavily on guanxi and more on other sources of core competencies (e.g. high-tech firms, and firms in high-marketisation regions), we find a positive relation between firm value and voluntary disclosure. The moderating role of guanxi on the relation between firm value and voluntary disclosure is explained by firms conscientiously balancing the costs and benefits of voluntary disclosure relative to guanxi. Specifically, high guanxi-dependence firms refrain from detailed voluntary disclosures for fear of revealing sensitive information that may harm their guanxi. In contrast, low guanxi-dependence firms rely more heavily on voluntary disclosures to reduce information asymmetry and financing cost, with such incentives being particularly strong for high value firms. Our evidence has implications for research on motives for disclosure and regulation of financial reporting.     

Does disaggregation of fair value information increase the value relevance of the fair value hierarchy?

In response to pressures from Congress, the SEC and investors, the FASB issued ASU 2010-06, Improving Disclosures about Fair Value Measurement. ASU 2010-06 mandates that firms provide disaggregated fair value information by class of financial instruments under each level of the fair value hierarchy. Using financial statements of publicly traded banks for the first quarters of 2009 and 2010, this study examines whether providing class-level information increases the value relevance of the fair value hierarchy. In support of our hypothesis, we find that fair value relevance increases under ASU 2010-06.     

Does IFRS make analysts more efficient in using fundamental information included in financial statements?

This paper investigates the efficiency with which analysts use fundamental signals when forecasting one-year-ahead change in earnings per share (EPS) in Australian and European contexts and the impact of International Financial Reporting Standards (IFRS) on this efficiency. Results reveal that adoption of IFRS seems to increase analysts’ awareness of fundamental signals useful for predicting future changes in EPS. However, overall, analysts remain only as efficient as they were pre-IFRS in using these fundamental signals. While their efficiency in using the earnings signal decreased, it increased for non-earnings signals in the post-compared to pre-IFRS period. Furthermore, analysts substantially underutilise the earnings signal in common compared to code law countries. These findings are likely to be of interest to analysts and market participants when making forecasts and investment decisions, and to standard setters and regulators in evaluating the impact of accounting standards.     

Red chips or H shares: which China-backed securities process information the fastest?

This study examines the information flow between China-backed securities, namely H shares, red chips, Shanghai and Shenzhen listed common shares. We document several findings. We find that an exponential generalized autoregressive conditional heteroscedasticity in mean (EGARCH-M) model appears to describe adequately the return process of the China-backed securities. Our empirical findings show that both H shares and red chips (which are listed in Hong Kong) are more sensitive to ‘good’ news than ‘bad’ news, while stocks listed in the China market are more sensitive to ‘bad’ news than ‘good’ news. Using a multivariate EGARCH-M model, we have found significant return and volatility spillover effects among the China-backed securities. Our study indicates that the red chips appear to spread information to other China-backed markets ‘directly’ or ‘indirectly’. The results imply that the red chip market processes information faster than the other markets.     

The role of “other information” in analysts’ forecasts in understanding stock return volatility

This study identifies “other information” in analysts’ forecasts as a legitimate proxy for future cash flows and examines its incremental role in explaining stock return volatility. We suggest that “other information” contains information about fundamentals beyond that reflected in current financial statements and reflects firms’ fundamentals on a more timely basis than dividends or earnings. Using standardized regressions, we find volatility increases when current “other information” is more uncertain and increases more in response to unfavorable news compared to favorable news. Variance decomposition analysis shows that the variance contribution of “other information” dominates that of expected-return news. The incremental role of “other information” is at least half of the effect of earnings in explaining future volatility. The results are more pronounced for firms with poor information environments. Overall, our results highlight the importance of including “other information” as an additional cash-flow proxy in future studies of stock prices and volatility.     

The role of the carbon market in relation to the cryptocurrency market: Only diversification or more?

The role of the carbon market in relation to the cryptocurrency market is still unclear. Given the carbon-intensive nature of the cryptocurrency industry, whether the carbon market is able to capture the carbon footprint of the cryptocurrency market (i.e., diversification) or act as a safe haven or a hedge against it remain unexplored issues. To address this issue, this paper employs the generalized autoregressive score-dynamic conditional score-Copula (GAS–DCS–Copula) model, incorporating the asymmetric tail distribution. We identify the asymmetric tail properties of both the carbon and cryptocurrency markets with significant otherness. Further, to account the importance of China in mining the cryptocurrencies, we incorporate Chinese carbon market in our analysis to investigate the difference with the European carbon market. Finally, we provide evidence that the European carbon market provides a safe haven and a hedge against the cryptocurrency market while Chinese carbon market is not. Our findings have implications for both investors and policymakers.     

Do analysts and investors fully understand the persistence of the items excluded from Street earnings?

Previous research has found that the items that are included in GAAP earnings but excluded from Street earnings to allow the firm to meet or beat analyst earnings forecasts (“MBF exclusions”) are more persistent than the other excluded items. In this study, I find that the difference in the levels of persistence between MBF and non-MBF exclusions declined after the introduction of Regulation G, which requires public companies that disclose non-GAAP earnings to also present GAAP earnings and a reconciliation of the two. Analysts underestimate the persistence of non-MBF exclusions, but the degree of this underestimation is lower in the post-regulation period. In contrast, there is little evidence to indicate that analysts underestimate the persistence of MBF exclusions in either time period. I also find strong (weak) evidence that investors underestimate the persistence of Street exclusions in the pre- (post-) regulation period. These results suggest that Regulation G constrains the practice of excluding recurring expenses from Street earnings to meet or beat analyst forecasts and helps analysts and investors to understand the persistence of Street exclusions.     

Discussion of “How well do investors understand loss persistence?”

Li (Rev Acc Stud, 2011) proposes a quarterly earnings prediction model for loss generating firms, shows that it produces better specified future earnings estimates relative to naïve quarterly forecast models, and that it can be used to form a trading strategy that produces economically significant annual hedge returns. I discuss alternative perspectives on Li’s empirical results and suggest directions for future research.     

The fair value of a token: How do markets price cryptocurrencies?

With the rise of cryptocurrency tokens as a new asset class, the question of the fair evaluation of a cryptocurrency token has become a question of increasing importance. We estimate the pricing kernel with which users price factors affecting their token holdings. We investigate how traditional risk factors such as market risk are evaluated, as well as how blockchain specific risk factors are priced in. In order to do so, we introduce an asset pricing model and modify its properties to make it applicable to cryptocurrency markets. We group the risk factors into market related and Bitcoin- and Ethereum blockchain specific risk factors. We find that blockchain specific risk factors are priced in. There is evidence that risk factors have moved from Bitcoin to Ethereum specific risk factors with an increasing importance of market factors, providing evidence for a decoupling of on-chain and off-chain trading activity.