The finance sector is currently grappling with an unprecedented surge in data volumes, which are essential for informed decision-making (Fang and Zhang, 2016). Despite significant advancements in automated quantitative and text-analysis tools (De Prado, 2018) and the rise of FinTech (Philippon, 2016), the majority of financial information remains text-based, constituting approximately 80% of annual financial disclosures (Lo et al., 2017). This growing volume of text has raised concerns about the diminishing value of financial disclosures due to their sheer quantity. As early as 1994, Ray Groves noted, “The sheer quantity of financial disclosures has become so excessive that we’ve diminished the overall value of these disclosures” (Groves, 1994, p. 11). This sentiment was echoed by former SEC chairman Arthur Levitt, who stated, “Because many investors are neither lawyers, accountants, or investment bankers, we need to start writing disclosure documents in a language investors can understand: plain English” (SEC, 1998, p. 3). These statements are even more relevant today, as the average length of a 10-K report has nearly tripled since 1996.
Academic interest in the readability of 10-K reports has grown considerably in recent years. Li (2008) was a pioneer in this area, linking the readability of 10-K reports to company earnings. His work was expanded by Biddle, Hilary, and Verdi (2009), who found that more readable financial reports are associated with reduced investment errors. De Franco et al. (2015) and Hwang and Kim (2017) further established a link between the readability of analysts’ reports and trading volume, noting that less readable disclosures can reduce firm value by an average of 2.5% for each standard deviation decrease in readability.
The impact of readability extends beyond investor behavior. Lehavy et al. (2011) found that less readable reports result in greater analyst dispersion and less accurate recommendations. Lawrence (2013) observed that retail investors tend to favor companies with shorter, clearer financial reports. Nelson and Pritchard (2016) demonstrated that firms facing higher litigation risk tend to produce more readable reports, while Guay et al. (2016) found that firms use voluntary disclosure to mitigate the adverse effects of complex financial reports.
Recent studies have uncovered additional implications of readability. For example, Topal (2023) demonstrated the potential of using online news as a tool for language learning across a variety of educational settings. Boubaker et al. (2019) and Kim et al. (2019) linked less readable filings to reduced stock liquidity and increased stock price crash risk, respectively. Hsieh (2021) identified a negative correlation between readability scores and the conservatism of credit rating agencies. Furthermore, Xu et al. (2018, 2020) and Rjiba et al. (2021) explored the impact of readability on various factors such as management age, trade credit, and the cost of equity. In particular, Baxamusa et al. (2018) noted that poor readability in a partner firm’s 10-K negatively impacts stock returns when a strategic alliance is announced.
Moreover, Hasan (2020) found a positive relationship between managerial ability and readability in profitable firms. Abu Bakar and Ameer (2011) demonstrated that companies with good financial performance tend to report their CSR narratives in simpler language, using short sentences that are easy to comprehend.Footnote 5
Focusing on the evolving readability of financial reports over time, we hypothesize that readability has decreased, leading to increased complexity in these documents. This hypothesis is critical to ongoing discussions about the need for financial reports to be more accessible and transparent, emphasizing the importance of making financial information understandable for all stakeholders.
Hypothesis (H1): The readability of financial reports, particularly Item 7 of 10-K filings, has decreased over time, indicating a trend toward greater complexity in these documents.
This hypothesis underscores the significance of enhancing the clarity of financial reports to ensure that they remain accessible and informative for all users, thereby supporting transparency and informed decision-making in financial markets.
The evolving readability of financial reporting, a central investigation of this study, carries significant implications for how market participants process information. Cognitive Load Theory (CLT) provides a pertinent theoretical lens, positing that human cognitive capacity is limited. CLT distinguishes between intrinsic load, the inherent difficulty of the material (influenced by factors such as an individual’s financial literacy (Lusardi and Mitchell, 2014)); extraneous load, which is imposed by suboptimal presentation of information (e.g., poor disclosure design (Sweller, 1994)); and germane load, representing the constructive mental effort dedicated to schema acquisition and automation (Parte et al., 2018). An effective disclosure environment, therefore, should aim to manage intrinsic complexity while minimizing extraneous cognitive burdens to facilitate productive germane processing.
When financial disclosures induce high cognitive load, whether from inherent complexity, diminished readability, or inefficient presentation, the quality of investor information processing and subsequent decision-making tends to degrade (Asay et al., 2017). The considerable volume of information typically found in financial reports can further exacerbate this issue, potentially culminating in information overload—a state where the quantity of data surpasses an individual’s processing capacity, thereby impairing judgment (Eppler and Mengis, 2004).
Empirical research indicates that investors exhibit a attenuated response to information embedded within less readable disclosures (Cui, 2016). Experimental findings corroborate this, showing that investors confronted with such reports express lower comfort in evaluating firms and assign less weight to the information therein (Asay et al., 2017). This may also lead investors to increase their reliance on external information sources, diverting attention from difficult-to-process firm-specific disclosures (Asay et al., 2017). Such effects can be particularly acute for retail investors, who may possess fewer resources to decode complex financial narratives compared to their institutional counterparts (Lawrence, 2013). Kelton (2006) documented that heightened complexity results in individuals acquiring less relevant information and forming less accurate interpretations. Similarly, navigating information-dense financial reports can trigger cognitive overload, leading to curtailed information gathering and less precise investment choices (Hales et al., 2011). A constrained attentional capacity, when faced with an overabundance of information, not only compromises processing ability but also contributes to increased information asymmetry in the market (Bernales et al., 2023; Mugerman et al., 2022), potentially elevating perceived information risk and, consequently, the risk premiums demanded by investors.
The imposition of cognitive constraints often compels investors to adopt simplified decision strategies and rely on heuristics (Cui, 2016). As Kahneman (2011) established, cognitive strain typically promotes a shift from effortful “System 2” analytical processing to more intuitive “System 1” thinking. This can manifest through several documented biases:
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Sentiment reliance: With less readable disclosures, investors may place greater emphasis on the general tone of the document rather than on detailed financial data (Asay et al., 2017).
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Anchoring on salient information: Individuals may gravitate towards easily processed headline figures, potentially neglecting crucial contextual details (Kelton, 2006), a behavior consistent with selective attention under cognitive pressure (Payne et al., 1993).
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Dilution effects: The presence of convoluted presentations can impede investors’ ability to differentiate between pertinent and extraneous information (Kelton, 2006).
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Increased risk-taking: Under cognitive load, investors might default to simplified decision rules that inadequately account for downside risks, a tendency potentially amplified by affective responses (Lahav et al., 2025; Shiv and Fedorikhin, 1999).
The aggregation of these individual-level cognitive responses can precipitate observable market-level phenomena. Specifically, firms characterized by less readable disclosures have been found to exhibit delayed price adjustments and more pronounced post-announcement drift (Asay et al., 2017; You and Zhang, 2009). Bernales, Valenzuela, and Zer (2023) documented diminished trading activity during periods of heightened information load. The same study also associated market-wide information overload with increased subsequent returns, suggesting investors demand compensation for the elevated information risk. Furthermore, complex disclosures can exacerbate information asymmetry between sophisticated and retail investors, potentially impacting bid-ask spreads and firms’ cost of capital (Bernales et al., 2023; Bloomfield, 2002).
Illustrating the nuanced effects of disclosure volume, Impink, Paananen, and Renders (2022) reported an inverted-U relationship between the quantity of regulatory disclosures and the quality of analyst decisions. While initial increases in disclosure can be beneficial, excessive disclosure was associated with “an increase in analyst delay and dispersion and a decrease in accuracy,” an effect more pronounced for analysts with less experience or fewer resources.
Collectively, these findings underscore that substantial cognitive load, intensified by the characteristics of financial reports investigated in this paper, influences not only individual investor behavior but also broader market dynamics. Such an impediment to efficient information processing can diminish market efficiency and elevate perceived risk. Consequently, the readability and design of financial disclosures emerge as critical factors for fostering well-informed and efficient capital markets.