Underwriting Relationships and Analyst Independence in Europe

This paper examines the accuracy of security analysts’ earnings forecasts and stock recommendations for firms in 13 European countries. We document at least three key findings. First, we find strong evidence that lead and co‐lead underwriter analysts’ earnings estimates and stock recommendations are significantly more optimistic than those provided by unaffiliated analysts. Second, we find that lead and co‐lead underwriter analysts’ earnings forecast and stock recommendations are significantly more optimistic for underwriter stocks than for those they provide for other stocks. Third, we also find evidence that these biases found within earnings forecasts and stock recommendations are not driven by one particular country. In short, these findings suggest that affiliated analysts are more optimistic perhaps to maintain investment banking relations.     

ABNORMAL RETURNS AND ANALYSTS' EARNINGS FORECAST REVISIONS ASSOCIATED WITH THE PUBLICATION OF “STOCK HIGHLIGHTS” BY VALUE LINE INVESTMENT SURVEY

We examine the reaction of stocks and the response of financial analysts' earnings forecasts to securities recommended as “Stock Highlights” by Value Line Investment Survey. Significant abnormal returns appear around the publication of stock highlights. Stock price responses are relatively efficient and permanent. Using earnings expectation data provided by the Institutional Brokers Estimate System, we find analysts raise their forecasts significantly following Value Line recommendations. Near-term forecast revisions are significantly related to stock returns at the time of the recommendations. Thus, an explanation for Value Line's security recommendation success is its ability to generate firm-specific earnings information.     

Conflicts of Interest and Research Quality of Affiliated Analysts in the German Universal Banking System: Evidence from IPO Underwriting

The quality of equity research by financial analysts is a prerequisite for an efficient capital market. This study investigates the quality of earnings forecasts and stock recommendations for initial public offerings (IPOs) in Germany. The empirical study includes 12,605 earnings forecasts and 6,209 stock recommendations of individual analysts for the time period from 1997 to 2004. The focus of this study is on analysing the potential conflicts of interest that arise when the analyst is affiliated with the underwriter of an IPO. In a universal banking system these conflicts of interest are usually more pronounced and therefore interesting to investigate. The empirical findings for the German financial market suggest that earnings forecasts and stock recommendations of the analysts belonging to the lead-underwriter are on average inaccurate and biased, indicating some conflicts of interest. Moreover, the stock recommendations of the analysts that are affiliated with the lead-underwriter are often too optimistic resulting in a significant long-run underperformance for the investor. In contrast, unaffiliated analysts provide better earnings forecasts and stock recommendations that result in a superior performance for the investor.     

THE EFFECT OF SELF-TENDER OFFERS ON EARNINGS EXPECTATIONS

We examine financial analysts' earnings revisions after self-tender offers. Consistent with the assertions of earlier studies that self-tender offers signal future performance, financial analysts significantly increase their forecasts of earnings for firms that announce self-tender offers. However, the revisions differ based on the method chosen to repurchase shares. For Dutch auction offers, analysts significantly revise their estimates of short-term earnings only. For fixed-price tender offers, analysts increase both short-term and long-term earnings estimates. Also, long-term earnings revisions are significantly related to announcement-period abnormal returns for fixed-price tender offers, which suggests that fixed-price self-tender offers convey more positive information about future earnings than do Dutch auction offers.     

Does revenue-expense matching play a differential role in analysts’ earnings and revenue forecasts?

This paper investigates whether matching has differential implications for the accuracy of analysts' earnings and revenue forecasts. We construct a novel measure of firm-level matching and document that matching improves analysts' earnings forecasts to a greater extent than their revenue forecasts. We also document matching's differential impact on analysts' earnings and sales forecasts by proposing a new count metric capturing a wedge in the accuracy of earnings and revenue forecasts. In additional tests, we report that the differential impact of matching is less (more) pronounced in a situation where the balance sheet (income statement) orientation likely dominates. We also report that matching's differential role is weaker (stronger) when firms have high intangible intensity (analysts have appropriate resources or expertise). In short window tests, matching's role in analysts' forecast revisions is more pronounced for earnings than sales forecasts. Overall, these results show how analysts benefit from better revenue-expense matching.     

Analyst Impartiality and Investment Banking Relationships

This study examines whether investment banking ties influence the speed with which analysts convey unfavorable news. We hypothesize that affiliated analysts have incentives to respond promptly to good news but prefer not to issue bad news about client companies. Using duration models of the time between an equity issue and the first downgrade, we find affiliated analysts are slower to downgrade from Buy and Hold recommendations and significantly faster to upgrade from Hold recommendations, in both within‐analyst and within‐issuer tests. We also find affiliated analysts issue recommendations sooner and more frequently after an offering than unaffiliated analysts, and that unaffiliated analysts are more likely than affiliated analysts to drop coverage of sample firms. Our findings indicate that banking ties increase analysts' reluctance to reveal negative news, and that reform efforts must carefully consider the incentives of affiliated and unaffiliated analysts to initiate coverage and convey the results of their research.     

Natural disasters and analysts' earnings forecasts

The effects of natural disasters on capital markets have been investigated by limited evidence even though these calamities bring considerable damages or loss of life. To fill this gap, we investigate the impacts of natural disasters, particularly earthquakes, on security analysts' earnings forecasts for affected firms in China. We obtain three key findings. First, analysts' optimism significantly decreases for firms located in neighborhood areas. Second, earthquakes do not significantly affect firm earnings and stock returns, thereby indicating that post-earthquake analyst pessimism is not based on rational judgment. Third, media attention promotes irrational pessimism among analysts, and post-earthquake pessimism is a result of heuristics bias attributable to psychological shocks. However, analysts correct the bias after initial irrational forecasts. Taken together, our findings contribute to the broader psychology and economics literature on the effects of natural disasters on analyst forecasts.     

RATIONAL EXPECTATIONS AND THE DYNAMIC ADJUSTMENT OF SECURITY ANALYSTS' FORECASTS TO NEW INFORMATION

We report the results of unbiasedness tests of security analysts' earnings forecasts. By examining how analysts incorporate new information into their updated earnings forecasts we can analyze directly the effect of new information on analysts' forecast revisions and evaluate whether these revised forecasts converge to rational expectations forecasts. The forecasts made by security analysts participating in the Institutional Brokers Estimate System (IBES) database are analyzed. Using standard statistical tests, we reject the simple form of the rational expectations hypothesis. However, by extending the standard tests used in previous studies, we obtain results that suggest that analysts' earnings forecasts conform to a dynamic form of rationality. The tendency of revised forecasts to converge stochastically toward the rational expectations forecast cautions against the rejection of more complicated forms of rationality.     

Expectations and the Cross-Section of Stock Returns

Previous research has shown that stocks with low prices relative to book value, cash flow, earnings, or dividends (that is, value stocks) earn high returns. Value stocks may earn high returns because they are more risky. Alternatively, systematic errors in expectations may explain the high returns earned by value stocks. I test for the existence of systematic errors using survey data on forecasts by stock market analysts. I show that investment strategies that seek to exploit errors in analysts' forecasts earn superior returns because expectations about future growth in earnings are too extreme.     

A comparison of buy‐side and sell‐side analysts

There is very little research on the topic of buy-side analyst performance, and that which does exist yields mixed results. We use a large sample from both the buy-side and the sell-side and report several new results. First, while the contemporaneous returns to portfolios based on sell-side recommendations are positive, the returns for buy-side analysts, proxied by changes in institutional holdings, are negative. Second, the buy-side analysts' underperformance is accentuated when they trade against sell-side analysts' recommendations. Third, abnormal returns positively relate to both the portfolio size and the portfolio turnover of buy-side analysts' institutions, suggesting that large institutions employ superior analysts and that superior analysts frequently change their recommendations. Abnormal returns are also positively related to buy-side portfolios with stocks that have higher analyst coverage, greater institutional holding, and lower earnings forecast dispersion. Fourth, there is substantial persistence in buy-side performance, but even the top decile performs poorly. These findings suggest that sell-side analysts still outperform buy-side analysts despite the severe conflicts of interest documented in the literature.     

Sell-side analyst heterogeneity and insider trading

This study explores insider trading patterns under different earnings surprises. After controlling for stock market liquidity and earnings announcements returns, we show that insiders sell more aggressively depending on the heterogeneity of analysts whose EPS forecasts are met or beaten to camouflage their trades. Specifically, insiders sell more shares of their company sooner after the publication of earnings when top analysts' forecasts are met or beaten. Consistent with the informed trading literature, insiders strategically select these moments because the stock price impact is low and the legal scrutiny of their trades is minimal. To support this result, we employ an exogenous drop in firms' analyst coverage due to the closure or merger of brokerage houses. Furthermore, in line with the camouflage incentives, by selling after top analysts' forecasts are met or beaten, stock prices adjust slowly to insider trades. Finally, we show that the incentives of insiders to hide their trades are concentrated in opportunistic insiders and members of the top management team, who are more likely to bear the costs of selling shares after positive news.     

Earnings Forecasts and the Information Contained in Spinoff Announcements

This study examines spinoff announcements in conjunction with financial analysts’ forecasts of earnings. The analysis shows that spinoff announcement abnormal returns are significantly related to the firm's information environment as proxieci by financial analysts’ earnings prediction errors. The findings also indicate that analysts significantly increase their short-term earnings forecasts in response to spinoffs, but do not significantly revise their long-term earnings forecasts. However, the earnings revisions are not significantly different across prediction error groups, which confirms that spinoff-related abnormal returns cannot be attributed solely to expected performance gains.     

The effects of social bias against female analysts on markets

I provide evidence for the effects of social bias on markets by studying female analysts. I find that the market reaction to female analysts' forecasts is weaker and slower than that to male analysts' forecasts. I also find that female analysts' forecasts are more accurate and timely than those of male analysts. Taken together, these findings imply that female analysts are underestimated even if they have better forecasting ability than male analysts. This effect decreases when female analysts are attractive, increases when the covered firm's CEO is male and is mediated by analysts' self-confidence. These results emphasize three sources of social bias against female analysts: incompetence bias, immorality bias, and credit bias. I also employ two exogenous shocks to rule out alternative explanations and conduct robustness tests to further support my results. My findings thus highlight that social bias against females remains an issue that significantly affects the capital market.     

Comparing the Post–Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts

Post–earnings announcement drift is the tendency for a stock's cumulative abnormal returns to drift in the direction of an earnings surprise for several weeks following an earnings announcement. We show that the drift is significantly larger when defining the earnings surprise using analysts' forecasts and actual earnings from I/B/E/S than when using a time series model based on Compustat earnings data. Neither Compustat's policy of restating earnings nor the inclusion of “special items” in reported earnings contribute significantly to the disparity in drift magnitudes. Rather, our results suggest that this disparity is attributable to differences between analyst forecasts and those of time‐series models—or at least to factors correlated with these differences. Further, we document that analyst forecasts lead to return patterns around future earnings announcements that differ from those observed when using time‐series models, suggesting that the two types of surprises may capture somewhat different forms of mispricing.     

Accurate forecasts attract clients; Biased forecasts keep them happy

We examine whether business relationships between mutual funds and sell-side analysts influence earnings forecasts using Chinese data from 2007 to 2019. Consistent with prior studies, our results support the commission pressure hypothesis. Analysts' forecasts are overly optimistic for the holdings of existing fund clients. Significantly, we propose the potential client hypothesis and show that analysts' forecasts are more accurate for the holdings of funds that are not clients than for holdings of clients or for stocks not held by any fund. Our results suggest that commission pressure from existing fund clients increases analysts' optimistic bias, while potential clients pressure inhibits analysts' optimistic bias to some extent. Finally, our evidence supports the conflicts of interest hypothesis. Commission pressure is reduced as economic uncertainty grows.     

Lead indicator models and UK analysts' earnings forecasts

This study examines the predictive ability of models which adjust random walk forecasts of corporate earnings, to incorporate past changes in economic lead indicators. The results suggest that changes in the broad money supply measure M4 contain predictive ability, beyond equivalent changes in other lead indicators or an individual firm's earnings. When forecasts from the broad-money model are compared with forecasts generated by financial analysts a size effect is evident: the superiority of analysts' forecasts is apparent much earlier for large firms than for small firms. This result is consistent with studies suggesting a size-related differential in the collection and dissemination of information by market participants.     

Information misweighting and the cross-section of stock recommendations

This paper provides evidence that analysts whose earnings forecast revisions showed signs of greater exaggeration in the past make recommendation changes that lead to lower abnormal returns than their peers. Interpreting stock recommendations as a forecast of future abnormal returns, I show that this evidence is consistent with the hypothesis that analysts who typically exaggerate or overstate the weight of their private information when issuing forecasts also do so when making recommendations. The paper also shows that past earnings forecasts provide incremental information about analysts' recommending behavior beyond that contained in past recommendations.     

CEO happiness and forecasting

We utilize the IBM Watson Tone Analyzer to measure chief executive officers' (CEOs') levels of joy (happiness) in year-end conference calls, and empirically test how CEOs' happiness affects the properties of their own and analysts' forecasts. We find that joyful CEOs are more likely to issue forecasts, less likely to miss their forecast targets, and exhibit lower optimistic bias in their forecasts. When joyful CEOs issue earnings forecasts, analysts revise their forecasts upwards and produce forecasts that are less dispersed and more accurate. Our results demonstrate that inherent CEO happiness significantly impacts the forecast properties of both managers and analysts, thus supporting upper echelons theory.     

主承销商的买入推荐可信吗?——来自中国的证据和启示

以2004-2009年的A股IPO公司为样本,我们探讨主承销商分析师买入推荐的可信性问题。我们的研究表明,在市场表现较差时,主承销商分析师倾向于给出买入推荐。此外,相对于主承销商,市场更相信其他券商分析师给出的买入推荐。我们还发现,其他券商分析师也能够识别主承销商买入推荐所包含的乐观性偏差。我们的这一结论为主承销商分析师所面临的利益冲突问题提供了直接证据,不仅有助于投资者更好地进行投资决策,也有利于监管当局对证券分析师行业对症下药,从而更好地保护投资者利益。     

Real earnings management and the properties of analysts' forecasts

Prior literature generally finds analysts are able to identify and process complex financial information. However, research suggests that in certain settings, analysts struggle to fully incorporate into their forecasts all available information. We examine analysts' forecast properties in the face of a specific type of complex financial information: real earnings management (REM). First, we investigate the relation between measures of REM and analysts' forecast properties. We find REM measures are associated with greater forecast error and dispersion in the following year. However, REM measures, by definition, capture abnormal operating results, and thus include both firms engaging in manipulative REM as well as firms experiencing firm-specific economic shocks. Thus, we conduct cross-sectional tests of analysts' forecasts for firms with and without incentives to manipulate earnings. We find that firms with low incentives to engage in earnings management (i.e., firms most likely experiencing firm-specific economic shocks) generate the strongest positive relation between REM measures and the following year's analysts' forecast properties, suggesting analysts more fully incorporate the earnings implications of firms with high incentives (i.e., firms most likely engaging in manipulative REM). Our results are consistent across numerous REM proxies and indicators of earnings management incentives.