Asset growth has been shown to be negatively associated with future returns. Cooper, Gulen, and Schill (2008) argue that an aggregation of all asset growth components as total asset ( TA ) growth leads to the strongest association with future negative returns. Based on their study, the literature now employs TA growth as an umbrella proxy for “the growth effect.” I hypothesize that not all types of growth imply negative future returns. Specifically, I show that growth financed by suppliers is positively associated with future performance and returns. Removing this growth component from TA growth makes it evident that the TA growth anomaly is simply a noisy manifestation of the net operating asset growth anomaly. Consequently, I suggest caution when using TA growth to control for the growth effect.

Asymmetric information is a fundamental friction that results in mismatches and efficiency losses in the labor market. In this study, we posit that more disaggregated financial disclosure by a CEO candidate's prior employer can help the hiring firm better assess the possible fit between its operational needs and the candidate's skill set. Using a mandatory segment reporting reform in the United States (SFAS 131) as an exogenous shock to disclosure disaggregation, we find a significant increase in the firm‐CEO match quality when the hiring firm has access to more disaggregated segment information about the external candidate's past employment. Furthermore, the improvement in firm‐CEO matching is greater when segment information is incrementally more useful for evaluation of candidate skills. These findings reveal a novel labor market benefit of disaggregated financial disclosure: alleviating pre‐hiring information deficiencies and facilitating efficient allocation of CEO talent across firms.

This paper provides first evidence of negative peer disclosure (NPD), an emerging corporate strategy to publicize adverse news of industry peers on social media. Consistent with NPDs being implicit positive self-disclosures, disclosing firms experience a two-day abnormal return of 1.6–1.7% over the market and industry. Further exploring the benefits and costs of such disclosures, we find that NPD propensity increases with the degree of product market rivalry and technology proximity and disclosing firms outperform nondisclosing peers in the product markets in the year following NPDs. These results rationalize peer disclosure and extend the scope of the literature beyond self-disclosure.

Prior research documents that asset growth is negatively associated with future firm performance. In contrast, we show that growth financed by product market stakeholders (i.e., “operating growth”) is positively associated with future firm performance. Investors and security analysts underestimate the positive effects of operating growth on future performance, resulting in return predictability and overly pessimistic earnings forecasts for firms with high operating growth. Future stock returns largely concentrate around subsequent earnings announcements with declining magnitudes, consistent with the error-in-expectation explanation. Results from cross-sectional tests further support the hypothesis that operating growth signals high future performance but investors underreact to it.

Growing AI readership (proxied for by machine downloads and ownership by AI-equipped investors) motivates firms to prepare filings friendlier to machine processing and to mitigate linguistic tones that are unfavorably perceived by algorithms. Loughran and McDonald (2011) and BERT available since 2018 serve as event studies supporting attribution of the decrease in the measured negative sentiment to increased machine readership. This relationship is stronger among firms with higher benefits to (e.g., external financing needs) or lower cost (e.g., litigation risk) of sentiment management. This is the first study exploring the feedback effect on corporate disclosure in response to technology.

We synthesize evidence from six papers presented at the 2025 Journal of Accounting Research Conference on how generative artificial intelligence (GenAI) is reshaping capital‐market information flows. Our discussion is organized around an economic framework with three layers: information production by firms and accounting professionals, information dissemination through intermediaries, and information processing by investors. Across these layers, the conference papers show that GenAI can lower preparation costs, improve intermediary productivity, and reduce investors’ processing costs. At the same time, they point to a common constraint: whether GenAI improves the information environment depends critically on information verification costs. We also highlight gaps in current evidence and outline future research opportunities within and across the three layers.

We examine whether firms that imitate peer companies’ strategies (copycats) profit from such behavior and how their success may cause competitive harm to disclosing companies. We identify copycat companies by tracking the digital footprints of investment companies that view disclosures on the SEC EDGAR Web site. We find that copycat companies are able to identify profitable trades that outperform other trades disclosed by the copycatted companies by 5.5% annually. Such stock‐screening skills are related to investment sophistication and research intensity. Furthermore, copycats inflict greater damage on the performance of disclosing companies when they possess superior copycat skills, when disclosed trading strategies take longer to complete, and when disclosed stock holdings are characterized by high information asymmetry.

We introduce a firm-specific measure of the technological aspect of competition—technological peer pressure—and examine firm-initiated product development-related press releases. We argue that empirical examinations of the theorized negative relation between competition and disclosure require the type of voluntary disclosure to be relevant to the dimension of competition under examination to ensure that firms incur significant proprietary costs of disclosure. In other words, many types of disclosure do not provide actionable information to competitors and, thus, should not be affected by that dimension of competition. We expect a negative relation between technological peer pressure and product disclosure because the latter reveals firms' strategies, allocations, and progress of technological investments in product development to competitors. In contrast, we do not expect a negative relation between technological peer pressure and management earnings forecasts—the most common type of voluntary disclosure used in accounting research. Our test results are consistent with these expectations. Data Availability: All data are available from public sources. Our TPP Measure is available for download, please see the link in Appendix G.