We reassess whether and to what degree the hiring, development, and promotion decisions of S P 500® companies have led to misrepresentation of and bias against their minority executives. Instead of the US population benchmark that has conventionally been used to measure misrepresentation, and from such misrepresentation attribute the presence and magnitude of racial bias and discrimination, we measure misrepresentation in US executives using the benchmark of the racial/ethnic densities (RAEDs) of their college cohort peers. Our key result is that the differences between US executive RAEDs and the RAEDs of their college peers are far smaller than those found using the US population, typically by an order of magnitude or more. Whereas under the US population benchmark, Black and Hispanic S P 500® US executives are reliably greatly under-represented by − 9.1

Consultants, business leaders, and activists often promote the view that a strong and settled business case exists behind the normative view that firms should increase the racial/ethnic diversity of their employees.3 A highly influential piece of evidence in support of this view comes from McKinsey & Co., which in a series of studies(4) in 2015 ("Diversity Matters"), 2018 ("Delivering through Diversity"), 2020 ("Diversity Wins: How Inclusion Matters"), and 2023 ("Diversity Matters Even More: The Case for Holistic Impact") reports finding statistically significant positive relations between the industry-adjusted earnings before interest and taxes as a percentage of revenues (EBIT margin) of global McKinsey-chosen sets of large public firms and the racial/ethnic diversity of their executives. Exhibit 7 from McKinsey's 2020 study (p. 20), reproduced in our Figure 1, summarizes their 2015, 2018, and 2020 studies' results. Dame Vivian Hunt, McKinsey's managing partner in the UK and Ireland at the time and a coauthor on all four of McKinsey's studies, crystalizes McKinsey's view that greater racial/ethnic diversity in a firm's executive team drives better firm financial performance: "What our data shows is that companies that have more diverse leadership teams are more successful. And so the leading companies in our datasets are pursuing diversity because it's a business imperative and driving real business results" (link).

In contrast to the equivocal findings in academic research, “the business case for diversity” is the dominant rhetorical paradigm for how US corporations debate actions and policies around racial/ethnic diversity. In this paper, we conduct an empirical test of the paradigm by gathering data on the race/ethnicity of the individuals shown on the leadership pages of S&P 500 firms’ websites as of mid-2011, 2014, 2017, 2020, and 2021, and then determining if any of nine measures of the racial/ethnic diversity of these executives reliably predict cross-sectional variation in any of six measures of their firms’ financial performance over the next fiscal year. We do not find reliable evidence that they do. As such, our results do not support the “business case for diversity” when the claim is assessed using 1-year-ahead financial performance metrics and multiple measures of the race/ethnicity of S&P 500 executives over the last decade.

We investigate the stock market reactions to the announcements of Black CEO and top management team (TMT) appointments in light of two conflicting studies that advance competing and opposite theories. In 2021, Gligor and colleagues theorized that reactions will be negative due to racial stereotyping, and found negative mean stock price reactions for both Black CEOs and TMTs. Conversely, in 2023, Jeong and colleagues theorized that the stock market will respond positively to the appointment of Black CEOs, because these CEOs have to meet a “higher bar” to be appointed. They reported a positive mean reaction to such appointments. In our quasi-replication of these two prior studies, we find a reliably positive mean reaction for Black CEOs but an immaterial median reaction, and no marginal stock price impact to the announcement of the appointment of a Black CEO and TMT executives after controlling for explanatory factors that go outside the racial bias and higher bar theories. In light of the fragility and lack of robustness in these results, we recommend that future research in the area of Black top executives and the stock market be cautious when presenting and interpreting results.

We measure and calibrate the racial and ethnic densities (RAEDs) of executives in US public companies. We find that calibrating executive RAEDs against an economic benchmark that captures the historical demand for and supply of top BA/BS qualified proto-executive talent yields different inferences about executive racial/ethnic under- and overrepresentation 58% of the time as compared to calibrating against the US population. For example, Blacks and Hispanics are overrepresented and Whites underrepresented in S&P 500® executives when calibrated against the historical RAEDS of top BA/BS qualified proto-executive talent matched to executive age. We also find that the magnitudes of the underrepresentations for Blacks and Hispanics and the overrepresentation for Whites are 10X+ smaller using our economic benchmark. This suggests that 90+% of the underrepresentation of Black and Hispanic executives comes from factors that are in play before companies hire their proto-executive talent versus 10% or less coming from actions that companies take at or after they hire their proto-executive talent.

Since 2001, the number of financial statement line items forecasted by analysts and managers that I/B/E/S and FactSet capture in their data feeds has soared. Using this new data, we find that 13 item surprises—11 income statement-based and 2 cash flow statement-based analyst and management guidance surprises—reliably explain firms’ signed earnings announcement returns. No balance sheet or expense surprises are significant. The most important surprises are (i) one-quarter-ahead sales guidance surprise, (ii) analyst sales surprise, (iii) annual Street earnings guidance surprise, and (iv) analyst Street earnings surprise. We also find that the adjusted R2s of our multivariate regressions are three times higher than the adjusted R2s of univariate Street earnings surprise regressions, and that the four most important surprises account for approximately half of this increase in explanatory power.

In a series of influential studies, McKinsey (2015, 2018, 2020) report a statistically significant positive relation between the industry-adjusted EBIT margin of global samples of large public firms and the racial/ethnic diversity of their executives. However, when we revisit McKinsey’s tests using recent data for US S&P 500® firms, we find statistically insignificant relations between McKinsey’s inverse normalized Herfindahl-Hirschman measures of executive racial/ethnic diversity and not only industry-adjusted EBIT margin, but also industry-adjusted sales growth, gross margin, ROA, ROE, and TSR. Our results suggest that despite the imprimatur often given to McKinsey’s (2015, 2018, 2020) studies, caution is warranted in relying on their findings to support the view that US publicly traded firms can deliver improved financial performance if they increase the racial/ethnic diversity of their executives.

Correction to this paper has been published: https://doi.org/10.1007/s11142-021-09616-6

We measure and calibrate the racial and ethnic densities (RAEDs) of executives in US public companies. We find that calibrating executive RAEDs against an economic benchmark that captures the historical demand for and supply of top BA/BS qualified proto-executive talent yields different inferences about executive racial/ethnic under- and overrepresentation 58% of the time as compared to calibrating against the US population. For example, Blacks and Hispanics are overrepresented and Whites underrepresented in S&P 500® executives when calibrated against the historical RAEDS of top BA/BS qualified proto-executive talent matched to executive age. We also find that the magnitudes of the underrepresentations for Blacks and Hispanics and the overrepresentation for Whites are 10X+ smaller using our economic benchmark. This suggests that 90+% of the underrepresentation of Black and Hispanic executives comes from factors that are in play before companies hire their proto-executive talent versus 10% or less coming from actions that companies take at or after they hire their proto-executive talent.

We separate the forecasted one-year-ahead stock return implied by an analyst’s target price into two parts: the expected compensation for bearing risk, and analyst-claimed mispricing. We use the cost of equity disclosed by analysts in their reports for the former, and the difference between the implied return and the cost of equity for the latter. When we regress realized one-year-ahead stock returns on the two components in an issuer, year and firm fixed effects design, we find that the coefficient on the cost of equity is close to one for US and international firms, but the coefficient on mispricing is reliably positive and far less than one. We also find that in a manner consistent with the asymmetric valuation incentives faced by analysts and firm managers, analysts do not on average identify overvaluation but do identify undervaluation alpha at the rate of 25 cents per analyst-claimed mispriced dollar.

Since 2001, the number of financial statement line items forecasted by analysts and managers that I/B/E/S and FactSet capture in their data feeds has soared. Using this new data, we find that 13 item surprises—11 income statement-based and 2 cash flow statement-based analyst and management guidance surprises—reliably explain firms’ signed earnings announcement returns. No balance sheet or expense surprises are significant. The most important surprises are (i) one-quarter-ahead sales guidance surprise, (ii) analyst sales surprise, (iii) annual Street earnings guidance surprise, and (iv) analyst Street earnings surprise. We also find that the adjusted R2s of our multivariate regressions are three times higher than the adjusted R2s of univariate Street earnings surprise regressions, and that the four most important surprises account for approximately half of this increase in explanatory power.

Since 2001, the number of financial statement line items forecasted by analysts and managers that I/B/E/S and FactSet capture in their data feeds has soared. Using this new data, we find that 13 item surprises—11 income statement-based and 2 cash flow statement-based analyst and management guidance surprises—reliably explain firms’ signed earnings announcement returns. No balance sheet or expense surprises are significant. The most important surprises are (i) one-quarter-ahead sales guidance surprise, (ii) analyst sales surprise, (iii) annual Street earnings guidance surprise, and (iv) analyst Street earnings surprise. We also find that the adjusted R2s of our multivariate regressions are three times higher than the adjusted R2s of univariate Street earnings surprise regressions, and that the four most important surprises account for approximately half of this increase in explanatory power.

Using a dataset of 3,234 letters sent by 434 hedge funds to their investors during 1995-2011, we study what motivates hedge fund managers to make voluntary disclosures. Contrary to the hedge fund industry’s reputation for opacity, we observe that managers provide their investors with an array of quantitative and qualitative information about fund returns, risk exposures, holdings, benchmarks, performance attribution, and future prospects. We find that the tensions between the agency costs faced by investors and the proprietary costs faced by managers affect fund disclosures. Consistent with managers reducing proprietary costs, better performing funds disclose less quantitative data about performance and holdings, and consistent with the presence of agency costs, riskier funds disclose less quantitative information about performance and assets under management.

We take up Cochrane’s (2011) challenge to identify the firm characteristics that provide independent information about average U.S. monthly stock returns by simultaneously including 94 characteristics in Fama-MacBeth regressions that avoid overweighting microcaps and adjust for data snooping bias. We find that while 12 characteristics are reliably independent determinants in non-microcap stocks during 1980-2014 as a whole, return predictability fell sharply in 2003 such that just two characteristics have been independent determinants since then. Outside of microcaps, the hedge returns to exploiting characteristics-based predictability have also been insignificantly different from zero since 2003.

ABSTRACT We investigate the use and performance of residual income (RI) valuation methods by U.S. sell-side equity analysts in a small-sample manner wherein we extract the rich details of analysts' RI valuations from their PDF reports over the period 1998–2013. We observe that RI valuations are much rarer than discounted cash flow (DCF) valuations, and that different RI and DCF valuations are sometimes provided by the same analyst for the same firm in the same report. We find that while some analysts build RI models around net operating income (RNOA-RI) and others around net income (ROE-RI), RNOA-RI valuations are optimistic to the same degree as DCF valuations and contain RNOAs that increase to an economically unlikely terminal year median of 27 percent. In contrast, analysts' ROE-RI valuations are unbiased when done in tandem with a DCF valuation, as are the DCFs that accompany them, and contain ROEs that decline over the forecast horizon to a more plausible terminal year median of 17 percent. We conclude that analysts' use of ROE-RI methods can lead to more sophisticated forecasts of economic fundamentals and equity valuations, especially when used in tandem with DCF. JEL Classifications: G12; G17; G32.

We evaluate sell-side equity analysts’ multiyear forecasted income statements, balance sheets and cash flow statements, and the profitability, efficiency and leverage ratios that they imply. Using both small- sample data extracted manually from Investext PDFs, and large-sample data taken from the I/B/E/S non-EPS archival detail history file, we find that analysts’ long-horizon financial statements contain many biases, many but not all of which are optimistic. Analysts make highly optimistic forecasts of long-horizon EPS, ROE, ROA, ROS and asset turnover, driven by overly bullish projections about revenues and all common-sized expenses except income tax, which they forecast pessimistically. Analysts are optimistic about both long-horizon operating cash flows and operating accruals, and while they are unbiased in their forecasts of long-horizon total assets, they underestimate long-horizon debt and overestimate long-horizon equity. Our regressions support the view that analysts strategically inflate their long-horizon forecasts of EPS the more intangible and hard-to-verify are the firm’s assets.

We investigate the number of and reasons for errors and questionable judgments that sell-side equity analysts make in constructing and executing discounted cash flow (DCF) equity valuation models. For a sample of 120 DCF models detailed in reports issued by U.S. brokers in 2012 and 2013, we estimate that analysts make a median of three theory-related and/or execution errors and four questionable economic judgments per DCF. Recalculating analysts’ DCFs after correcting for major errors changes analysts’ mean valuations and target prices by between −2% and 14% per error. Based on face-to-face interviews with analysts and those who oversee them, we conclude that analysts’ DCF modeling behavior is semi-sophisticated in the sense that analysts genuinely make mistakes regarding certain aspects of correctly valuing equity but also respond rationally to the incentives they face, particularly the reality that they are not directly compensated for being textbook DCF correct.

We study the use of residual income (RI) valuation methods by U.S. sell-side equity analysts, particularly as compared to DCF. We document that RI valuations are rare — just 1/16th as common as DCF — and that different RI and DCF valuations are not infrequently provided by the same analyst for the same firm in the same report. We find that while analysts build their RI models around both net operating income (RNOA-RI) and net income (ROE-RI), analysts’ RNOA-RI valuations are as optimistic as their DCF valuations and contain RNOAs that increase to an economically implausible terminal year median of 27%. In contrast, analysts’ ROE-RI valuations contain ROEs that decline over the forecast horizon to a more plausible terminal year median of 17%. While optimistic when done on their own, analysts’ ROE-RI valuations are unbiased when done in tandem with DCF, as are the DCFs that accompany them.

Contemporary Accounting ResearchVolume 32, Issue 3 p. 1050-1052 Original Article Discussion of “Customer Franchise—A Hidden, Yet Crucial, Asset”† John R. M. Hand, John R. M. Hand University of North Carolina – Chapel HillSearch for more papers by this author John R. M. Hand, John R. M. Hand University of North Carolina – Chapel HillSearch for more papers by this author First published: 07 April 2015 https://doi.org/10.1111/1911-3846.12132Citations: 2 †Accepted by Patricia C. O'Brien. I am grateful for the opportunity to discuss Bonacchi, Kolev, and Lev 2014 (BKL). My preferred way of doing so is to take a deliberately supraview in place of a detailed analysis. With apologies to Bonacchi and Kolev for appearing to sideline them, to me the BKL paper is classically “Baruch.” It is simultaneously uncomfortable, jarring, interesting, and worthwhile. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat References Bernard, V. L., and J. K. Thomas. 1989. Post–earnings announcement drift: Delayed price response or risk premium? Journal of Accounting Research 27 (Supplement): 1–36. Bernard, V. L., and J. K. Thomas. 1990. Evidence that stock prices do not fully reflect the implications of current earnings for future earnings. Journal of Accounting and Economics 13(4): 305–40. Bonacchi, M., K. Kolev, and B. Lev. Customer franchise—A hidden, yet crucial, asset. Contemporary Accounting Research (this issue). Cochrane, J. H. 2011. Presidential address: Discount rates. Journal of Finance 66 (4): 1047–108. Green, J., J. R. M. Hand, and X. F. Zhang. 2013. The supraview of return predictive signals. Review of Accounting Studies 18 (3): 692–730. Green, J., J. R. M. Hand, and X. F. Zhang. 2014a. The remarkable multidimensionality in the cross-section of expected US stock returns. Working paper, UNC–Chapel Hill. Green, J., J. R. M. Hand, and X. F. Zhang. 2014b. A new perspective on analyst sophistication: Errors and questionable judgments in analysts' DCF valuation models. Working paper, UNC–Chapel Hill. Lyle, M. R., J. L. Callen, and R. J. Elliott. 2013. Dynamic risk, accounting-based valuation, and firm fundamentals. Review of Accounting Studies 18 (4): 899–929. Penman, S. H., F. Reggiani, S. A. Richardson, and A. I. Tuna. 2013. An accounting-based characteristic model for asset pricing. Working paper, Columbia University. Sloan, R. 1996. Do stock prices fully reflect information in accruals and cash flows about future earnings? The Accounting Review 71 (3): 289–315. Citing Literature Volume32, Issue3Fall 2015Pages 1050-1052 ReferencesRelatedInformation

Using a large database of news stories from newswires, national press, internet-based news outlets, news aggregators and local news channels, we study differences in the coverage of business news across types of press sources. We document that bad news business stories receive more coverage than good news stories in newswires, the national press and local news channels, while the opposite occurs in internet-based news outlets and news aggregators. We observe that the gap between good and bad news coverage is smaller for stories that are based on firm fundamentals and larger for bigger firms. We also report results that we propose help distinguish between the different roles that prior research has hypothesized are played by the business press. In particular, our evidence most supports the hypothesis that press coverage enhances firm visibility, leading to higher demand for the firm’s shares. We conclude that while coverage of stories in the business press does provide value-relevant information to investors, the main role of the business press is to make firms more visible to a broad set of market participants.