Investors are central to the incorporation of firm information in capital markets, yet it is challenging to observe the particular information they use and struggle with. Lee and Zhong (2022) use online investor interactions with Chinese public firms to document evidence that investors face significant processing costs. They find that when investor interactions occur, capital markets behave as if the information environment has improved, with increased trading activity, liquidity, and timely pricing of the quarter's earnings in returns. My discussion highlights the contributions of Lee and Zhong's findings to the processing cost, retail investor, and investor interactions literatures. I also describe empirical challenges faced by this and similar studies. I encourage using the details of interactions to disentangle the nature of processing costs and to increase support for causal conclusions more generally. Finally, I note several topics related to investor interaction that would benefit from further research.

I provide a general framework of firms’ financial communication process and investor response to information, moving from disclosure through dissemination to investor response and management response. I then discuss the entrance of social media into firm communications, highlighting both classic and unique aspects of social media in the communication process. I place Cade (2018) in this literature and discuss areas ripe for future research. Finally, I encourage researchers interested in social media to acknowledge and embrace the unique opportunities and challenges in this area.

This paper examines the effect of market participants’ information processing costs on firms’ disclosure choice. Using the recent eXtensible Business Reporting Language (XBRL) regulation, I find that firms increase their quantitative footnote disclosures upon implementation of XBRL detailed tagging requirements designed to reduce information users’ processing costs. These results hold in a difference‐in‐difference design using matched nonadopting firms as controls, as well as two additional identification strategies. Examination of the disclosure increase by footnote type suggests that both regulatory and nonregulatory market participants play a role in monitoring firm disclosures. Overall, these findings suggest that the processing costs of market participants can be significant enough to impact firms’ disclosure decisions.

This paper reviews the literature examining how costs of monitoring for, acquiring, and analyzing firm disclosures – collectively, “disclosure processing costs” – affect investor information choices, trades, and market outcomes. The existence of disclosure processing costs means that disclosures are not “public” information as traditionally defined, but instead can be a form of costly private information. Conceptualizing disclosures as private information makes it clear that learning from disclosures is an active economic choice and that disclosure pricing cannot be perfectly efficient. We review the analytical and empirical literature on sources of processing costs and how these costs affect equity market outcomes, primarily within rational equilibria. We also discuss studies of the feedback effects of investors' processing costs on managers’ choices about disclosure and corporate actions. We conclude that disclosure processing costs have implications for a wide array of accounting research and phenomena, but we are only just beginning to understand their effects.

Firm disclosures often reach only a portion of investors, which results in information asymmetry among investors and, therefore, lower market liquidity. This issue is particularly salient for firms that are not highly visible, as they tend not to receive broad news dissemination via traditional intermediaries, such as the press. This paper examines whether firms can reduce information asymmetry by more broadly disseminating their news. To isolate the impact of dissemination, we focus our analysis on firms' use of Twitter and exploit the 140-character message restriction. Specifically, using a sample of technology firms, we examine the impact of using Twitter to send market participants links to press releases that are provided via traditional disclosure methods. We find this additional dissemination of firm-initiated news via Twitter is associated with lower abnormal bid-ask spreads and greater abnormal depths, consistent with a reduction in information asymmetry. Moreover, this result holds mainly for firms that are not highly visible, consistent with them being in greater need of this additional dissemination channel. We also examine the impact of dissemination on a volume-based measure of liquidity, and find that dissemination is positively associated with liquidity. Data Availability: All data are publicly available from the sources indicated in the paper.

Many have argued that financial statements created under an accounting model that measures financial instruments at fair value would not fairly represent a bank's business model. In this study we examine whether financial statements using fair values for financial instruments better describe banks' credit risk than less fair-value-based financial statements. Specifically, we assess the extent to which various leverage ratios, which are calculated using financial instruments measured along a fair value continuum, are associated with various measures of credit risk. Our leverage ratios include financial instruments measured at (1) fair value; (2) U.S. GAAP mixed-attribute values; and (3) Tier 1 regulatory capital values. The credit risk measures we consider are bond yield spreads and future bank failure. We find that leverage measured using the fair values of financial instruments explains significantly more variation in bond yield spreads and bank failure than the other less fair-value-based leverage ratios in both univariate and multivariate analyses. We also find that the fair value of loans and deposits appear to be the primary sources of incremental explanatory power. Data Availability: All data are publicly available from the sources indicated in the paper.

We examine firm disclosure choice during the initial public offering (IPO) roadshow presentation to understand the informativeness of a management presentation designed to attract investors. Although firms submit a comprehensive registration filing during the IPO, managers also prepare a roadshow presentation, which is shorter and typically allows managers more autonomy to select the information released and how it is discussed. We find that IPO roadshows have significantly more positive, less negative, and less uncertain language than the SEC filing. Using machine learning to classify roadshow sentences into five major topics from the registration statement, we find that roadshows differ in both the topics selected and the language used within each topic. We then examine the predictive ability of the roadshow language, finding that roadshow language predicts future accounting performance, whereas filing language does not. These results highlight the informational role of management presentations, despite the flexibility they grant managers.