We study the use of generative AI for firm-specific financial analysis on the Seeking Alpha platform. After the initial launch of ChatGPT in November 2022, the share of AI-generated articles rose sharply to 13.5% of all articles, then declined in late 2023 after Seeking Alpha equated the use of AI to plagiarism and announced a prohibition on its use. We organize our study around two questions: (1) Does AI use increase author productivity? and (2) does AI use have capital market consequences and ultimately affect the informational landscape? We find that authors who adopt AI become more productive, publishing more articles and covering more new firms than non-adopters. Findings on AI article informativeness are more nuanced. On average, AI articles are less informative than human-written articles, eliciting smaller trading volume and abnormal return responses. However, AI use leads to increased firm coverage and in turn to improved liquidity and faster price discovery. Our findings suggest that, while AI-generated articles are currently perceived as less informative than human-written articles, their comparatively low cost enables increased firm coverage and thereby improves the overall informational landscape.

We examine how brokerage firm initial public offerings (IPOs) influence the research quality of sell-side analysts employed by the brokerage. Our main results focus on earnings forecast bias and absolute forecast errors as proxies for research quality. Using a staggered difference-in-differences analysis, we document significant decreases in forecast bias and absolute forecast error during the two-year period centered on the analysts’ brokerage house IPO. In additional analyses, we explore several potential explanations for the short-term benefits of brokerage house IPOs. We find some evidence that IPOs delay the departure of more talented analysts and that the effects are more concentrated among analysts and brokers that face more scrutiny. This paper was accepted by Brian Bushee, accounting. Supplemental Material: Data are available at https://doi.org/10.1287/mnsc.2022.4610 .

ABSTRACT We examine firm decisions to provide listings of sell-side analyst coverage on corporate investor relations (IR) websites. These listings are related to three major areas of financial research—voluntary disclosure, investor relations, and analysts. Our hand-collected data permit cross-sectional and time-series analyses. Firms are more likely to have such listings when analysts are more important information intermediaries and when firms are directly involved in managing their IR websites. For firms with listings, the probability of an analyst being included on the listing is increasing in firm awareness of and familiarity with the analyst, how active and favorable the analyst is, and the analyst’s reputation. Additional analysis indicates similar results across self-hosting versus third-party hosting IR websites, with a notable exception that self-hosting firms exhibit a stronger preference for analysts who issue more favorable research about the firm. Decisions to add or drop analysts from listings reinforce the main results. Data Availability: Data are available from public sources identified in the text. JEL Classifications: G17; G24; M41.

Both sell-side analysts and the media are information intermediaries in capital markets. This study investigates the association between sell-side analyst research and information in firm-specific news coverage. More frequent recent news coverage is associated with stronger market reactions to analysts' research revisions, and primarily explained by soft information in news coverage. The primary result is robust to using both an instrumental variable and a quasi-natural experimental setting to generate exogenous variation in media coverage, alleviating concerns about endogeneity. In addition, using textual analysis, we document that explicit media references in analyst research reports are significantly associated with more frequent analyst revisions and stronger market reactions to revisions. Our study provides empirical evidence of analysts' assimilation of information from the financial press and their role in the efficiency of capital markets.

ABSTRACT In contrast to the disappearing dividends view prevalent in the literature, we document extensive dividend payments by firms and significant variability within firms and across 16 countries during 2000–2013. We predict that within-firm variability in dividends increases investor demand for forward-looking dividend information, and analysts respond by producing informative dividend forecasts. We find that analyst dividend forecasts are available for most dividend-paying firms and are more prevalent for firms with higher variability of dividends. Analyst dividend forecasts are more accurate than alternative proxies based on extrapolations of past dividends. Finally, dividend forecasts (1) are incrementally useful to investors beyond information in other fundamentals, such as earnings and cash flow forecasts, (2) help investors interpret earnings quality, and (3) are associated with investors' portfolio allocation decisions. Data Availability: Data are available from the public sources cited in the text.

In state owned enterprises (SOEs), taxes are a dividend to the controlling shareholder, the state, but a cost to other shareholders. We examine publicly traded firms in China and find significantly lower tax avoidance by SOEs relative to non-SOEs. The differences are pronounced for locally versus centrally-owned SOEs and during the year of SOE term performance evaluations. We link our results to managerial incentives through promotion tests, finding that higher SOE tax rates are associated with higher promotion frequencies of SOE managers. Our results suggest managerial incentives and tax reporting are conditional on the ownership structure of the firm.

ABSTRACTPrior research demonstrates that a strong institutional infrastructure in a country moderates self‐serving behavior of market participants. Cross‐country economic activities have increased significantly, presenting a research opportunity to examine the relative influence of local versus foreign institutional infrastructure on individual market participants. We utilize variation in analyst‐country location relative to covered firm location to examine institutional determinants of optimism in analyst research. Focusing on target prices, where persistent optimism is well documented, we find that analysts domiciled in countries with stronger institutional infrastructures exhibit significantly attenuated target price optimism and more value‐relevant target prices. Our results demonstrate the importance of domestic country‐level institutional factors in moderating self‐serving behavior of market participants engaged in cross‐country activities.

We use newly available GAAP forecasts to document that traditionally-identified GAAP forecast errors contain 37% measurement error. Correcting for this measurement error, we settle a long-standing debate regarding investor preference for GAAP versus non-GAAP earnings and provide strong evidence of a preference for non-GAAP earnings. We also revisit the use of non-GAAP exclusions to meet analysts’ forecasts when GAAP earnings fall short. Results indicate that 34% of these traditionally-identified meet-or-beat firms are misidentified due to measurement error, and this error masks evidence that firms more frequently exclude transitory rather than recurring expenses for meet-or-beat purposes.

ABSTRACT The within-year walkdown of analysts' earnings forecasts has largely been attributed to analysts' incentives to curry favor with managers. We appeal to cognitive psychology literature on motivated reasoning and propose that forecasting difficulty interacts with such incentives to yield the observed walkdown. Higher forecasting difficulty generates a wider range of outcomes from which analysts can justify optimistically biased forecasts. In regression analyses, we find that the interaction between analysts' incentives for optimism and difficulty exhibits the strongest effect on earnings walkdowns. We also examine revenue forecasts as a benchmark of lower forecasting difficulty and find that revenue walkdowns are relatively diminutive. However, when analysts forecast losses, revenue forecasts are more critical and exhibit markedly steeper walkdowns. Our results suggest that analyst forecast walkdowns are better characterized by an interactive effect between analysts' strategic incentives for optimism and forecasting difficulty. JEL Classifications: G17; M41. Data Availability: Data are available from public sources identified in the text.

Research suggests that earnings announcements reduce information asymmetry and level the playing field among investors. However, some studies find the opposite, with results indicating that the proportion of common information (i.e., consensus) decreases after earnings announcements. We revisit the question of how earnings announcements affect the information environment and provide new evidence that reconciles these seemingly contradictory findings. First, we show that earnings announcements decrease total forecast error by reducing both common forecast error and private forecast error (i.e., forecast dispersion). Therefore, although earnings announcements can decrease consensus, they are beneficial to the information environment because they decrease both common and private error. Second, we highlight the importance of a firm’s pre-existing consensus in understanding how earnings announcements affect the information environment. Specifically, we find that earnings announcements increase, as opposed to decrease, consensus when the pre-existing level of consensus is low. However, with higher levels of pre-existing consensus, this effect becomes attenuated and eventually negative. Third, we find that voluntary disclosures in earnings announcements can also affect consensus, with management forecasts increasing consensus and non-GAAP earnings decreasing consensus. Finally, we decompose earnings into revenues and expenses and find that earnings announcements improve information about revenue more than for expenses. Overall, we reconcile the existing literature by demonstrating that earnings announcements level the informational playing field, even if consensus declines around such announcements, and we provide new evidence about the effects of voluntary disclosures on consensus.

Although risk is forward-looking, accounting is often backwards-looking and relies on historical costs from events realized in the past. This chapter discusses situations in which risk is part of the background inputs in the preparation of financial statement information. Second, The chapter also highlights examples of how accounting information can inform investment decisions through their primary use as predictors of future firm performance, stock market performance, bankruptcy, corporate fraud, and volatility. Finally, financial statements contain many useful disclosures about risk and management estimates of uncertainties and discount rates. The chapter concludes with a brief discussion of the recent debate over the role of accounting in the financial crisis of 2007–2008.

SYNOPSISIn this paper, we (the Financial Reporting Policy Committee of the American Accounting Association's Financial Accounting and Reporting Section) consider the 2011 Plan to Establish the Private Company Standards Improvement Council authored by the Financial Accounting Foundation (FAF). The FAF's proposal called for a standard-setting approach more sensitive to the needs of private companies, with the likely outcome being different accounting and disclosure standards for these companies than for public companies.Members of the committee have differences of opinion about the FAF's proposal. Five members generally support the FAF's plan (though raising significant implementation issues), while six oppose it and instead argue against different reporting standards for private companies.In this paper, we discuss three issues and present points and counterpoints for each, along with other related standard-setting concerns. This approach is designed to present our differing views on these issues clearly, to help standard setters, preparers, users, and academics form their own views on this highly controversial matter.

We examine analysts’ GAAP earnings forecasts and illustrate their usefulness in two prominent research settings. First, we find that the availability of GAAP forecasts has increased dramatically since 2003, and they are now available for most I/B/E/S-covered firms. Next, we utilize GAAP forecasts to solve important measurement error problems in prior research that attempts to examine GAAP forecast errors without an explicit GAAP forecast. We begin with research exploring investors’ preferences for GAAP versus non-GAAP earnings. We find that traditionally-identified GAAP forecast errors are subject to 37% measurement error. Nevertheless, in contrast to the pervasive caveats in the non-GAAP literature, evidence of an investor preference for non-GAAP earnings relative to GAAP earnings is robust after correcting for this measurement error. Second, we revisit the literature identifying firms that use non-GAAP exclusions to meet or beat analysts’ forecasts when GAAP earnings fall short of expectations. We find that 34% of the traditionally-identified meet-or-beat firms are misidentified due to measurement error and this misidentification masks the inference that firms more frequently exclude transitory expenses rather than recurring expenses for meet-or-beat purposes.