10-K Filings Research Articles

The impact of accelerating 20-F filing

This study examines the impact of the SEC’s decision to accelerate the 20-F filing deadline from six to four months after the fiscal year-end for foreign private issuers (FPIs). We find that only large FPIs experience a significant positive market reaction around the accelerated 20-F filing date, and such acceleration is associated with an improved reporting environment. We also find that only large FPIs benefit from further acceleration of 20-F filing deadline from four to three months after the fiscal year-end. Additionally, any further acceleration of 20-F filing does not benefit all sizes of the FPIs. Our results contribute to the debate about whether it is beneficial for the FPIs to accelerate their 20-F filing deadline to align with the 10-K filing deadlines.

Pay inequality and annual report readability

PurposeThis study examines the relation between pay inequalities in top management teams and how efficiently firms convey valuation-relevant information to investors. Given that reward comparisons with reference groups create feelings of inequity, top management team pay inequalities can impair the information environment. This manifests into lengthier or less readable financial reports.Design/methodology/approachThis paper employs an ordinary least squares (OLS) regression model to test whether and how the pay distribution in the top management team is associated with the readability of the annual report. It also employs a two-stage least squares (2SLS) regression model to further address the endogeneity concern. Lastly, it conducts cross-sectional analyses to examine heterogeneity in the observed relation.FindingsUsing the intra-firm pay gap as a proxy for pay inequality and file size, Bog Index and Fog Index of the 10-K filings as a proxy for financial report readability, the author finds that firms with larger pay gaps exhibit lengthier or less readable 10-K filings. The main findings are robust to the use of an instrumental variable approach. She finds some evidence that the relation is less pronounced when pay gaps are justified by explicit legal authority of CEOs or high ability of CEOs. The main results are robust to considerations of alternative explanations.Originality/valueThis paper adds a new dimension to the debate on pay inequality by studying pay gaps in the top management team and financial report readability. The author's findings have important implications for executive compensation policies and for corporate disclosure policies.

Climate-related discussions in firms’ 10-K: Who does it and what is its impact?

We examine the impact of climate-related discussions in the Management Discussion & Analysis (MD&A) section of the 10-K filings of S&P 500 firms from 2007 to 2018 and find that only firms from three specific industries (Energy, Utilities and Finance) have such discussions. We also find that the increase in mention of climate related words and ngrams is significantly associated with a fall in holding period return (HPR), post the filing date and especially post the Paris agreement. This suggests that investors perceive higher climate change discussion in a negative light even without any change in fundamentals. • We show that climate related discussions are only found in three industries. • The discussions and their impact have increased post the Paris Agreement (2009). • These discussions are negatively associated with filing date return.

Cost Stickiness and Stock Price Delay

ABSTRACT This study examines the effect of cost stickiness on stock price delay. Using a sample of U.S. firms in the period of 1984–2019, I find that the stickiness of Selling, General, and Administrative (SG&A) costs is positively associated with stock price delay. This finding is consistent with the notion that cost stickiness reduces the quality of information available to investors and causes stock price delay (the direct channel). Using a mediation test, I document that cost stickiness reduces the analyst following of the firm, thus increasing stock price delay (the indirect channel). Cross-sectional analyses reveal that the effect of cost stickiness on stock price delay is prominent in firms characterized ex-ante by a relatively poor information environment. Meanwhile, the effect is weak for firms with managers who use less uncertain and more positive words in Management Discussion and Analysis (MD&A) disclosures within 10-K filings. This study contributes to the growing literature on cost behavior by documenting the adverse consequences of managers’ cost decisions on the capital market and the role of the information environment in mitigating these negative implications.

The 15-day debate and the value of early release of information: Evidence from 10-K filings

We analyze the impact of enforcing a 60-day 10-K deadline on large accelerator filers (LAFs) relative to enforcing a 75-day deadline on accelerator filers (AFs) from 2006 to 2015. Using a regression discontinuity design, we find that LAFs are more likely to issue restatements after the 2006 SEC filing acceleration (“regulation”) has been introduced. The regulation causes LAFs to have lower information asymmetry, which is consistent with our finding that LAFs’ Internet search traffic for filings is lower. Overall, the market does not react stronger toward LAFs’ 10-K filings even though their 10-K filings are more timely. An unintended consequence of the regulation is an increase in filings by other firms during LAFs’ 10-K filing dates, which reduces investors overall attention toward these filings.

Efficient access to qualitative data: a case of MD&A analysis from 10-K with Python via SEC’s API

ABSTRACT A distinction between quantitative and qualitative data has been regarded as an inviolable separation for a long time, resulting in a significant restriction in setting research designs and methods. In this study, we propose a way to pull this stereotype down and to open more choices for upcoming studies: using Python with 10-K filings via the U.S. Securities and Exchange Commission’s application programming interface, we show how to broaden the source of data available for research. In particular, we focus on management’s discussion and analysis (MD&A) of 10-K filing. This part has not been fully incorporated due to considerable requirements for an access – substantial time and effort in case of hand collecting. The new perspective approach described in this paper provides significant implications for business practice as well as research in relation to the higher level of utilization of existing data than before.

Textual Analysis and Future Performance: Evidence From Item 1A and Item 7

Although there is previous research on textual analysis in accounting, little is understood about the effects of the tone and sentiments of the text disclosed in annual report filings (10-K) on the investor assessment of the future performance of the firm. This study inks the tone and sentiments of the text disclosed in the corporate annual reports and expectations regarding the future performance of the firm. We focus on two specific sections of 10-K filings the risk factor disclosures (Item 1A) and the management’s discussion (Item 7) filling a gap in the accounting literature. There are two competing predictions regarding how the tone and sentiments of the text could impact the investor assessment about the future performance of the firm. First, the tone and sentiments of the text in Items 1A and 7 may have an effect on the investor assessment of the future performance of the firm. Second, only the tone and sentiments of Item 7 may have an effect on the investor assessment, given the fact that Item 1A only discusses the general risk factors that are present and not necessarily any specific risk factors to the firm. We find that only the tone and sentiments of the text in Item 7 has an effect on the investor assessment of the firm. This result helps explain the channels through which the tone and sentiments of the text impacts the future performance.

Different Times Call for Different Measures: Using Retail Sales to Monitor the Tobacco Product Landscape

Different Times Call for Different Measures: Using Retail Sales to Monitor the Tobacco Product Landscape

Do financial performance indicators predict 10-K text sentiments? An application of artificial intelligence

In this study, we employ Natural Language Processing (NLP), a subdomain of artificial intelligence (AI), to predict the sentiments while analyzing 3729 annual 10-k financial reports of S&P 500 companies over the 2002–2019 time period. Our findings suggest that the firm’s financial performance indicators help reduce negativity in the textual part of 10-ks. In contrast, we do not observe any significant association between the firm’s financial performance indicators and 10-ks positivity. Our findings are robust to alternative econometric specifications and alternative measures of key variables. Our results contribute to the accounting and financial disclosure literature by indicating that corporate financial performance indicators can predict the tone of 10-k filings.

An Evaluation of SEC 10-K Charts

ABSTRACTThis project measured the effectiveness of charts in SEC 10-K filings. Amazon Mechanical Turk workers and business students participated in the online experiment. The first half of the study asked participants to interpret five charts rarely found in 10-K filings, including combo charts, scatterplots, stacked bars, relative waterfall charts, and absolute waterfall charts. While participants were successful with combo charts, stacked bars, and absolute waterfalls, half were unable to interpret a scatterplot, and only a handful understood relative waterfalls. The second half of the experiment tested the effects of the three most common design flaws found in 10-K charts. Users were influenced by each of the three flaws: line charts using a non-zero vertical axis, bar charts using an unlabeled non-zero vertical axis, and pie charts using a 3-D perspective. Accounting students should be better trained in deceptive chart designs, and companies should improve their 10-K charts.

Indirect effects of regulatory change: Evidence from the acceleration of the 10-K filing deadline

This study examines the indirect effects of regulatory change by studying the audit office effects of changes in client time pressure caused by the first acceleration of the 10-K filing deadline. The extant literature provides evidence that increased client time pressure adversely affects the timing and quality of individual engagements. We argue that because audit offices possess finite resources and production capacity in the short run, client-level pressure can have office-level effects. We document within-office differences related to changes in audit timeliness. In the same audit office, clients with no pressure (with pressure) experience an increase (a decrease) in audit report lag post-acceleration. This evidence suggests that auditors alter the timing of concurrent engagements in response to client pressure, and clients of the same office are affected differently by changes in time pressure. We also document across-office differences in audit/filing timeliness and audit quality. Clients of audit offices with more time pressure across the entire client portfolio experience a greater negative impact on audit timeliness, are more likely to file late, and experience lower audit quality. Taken as a whole, our results are consistent with client time pressure producing office effects as a result of the auditors' response to increased resource constraints. Further, we show that the time pressure documented during the first acceleration is transitory in nature. These results should be informative to regulators and practitioners because they suggest there are indirect costs associated with regulatory compliance, and such costs are not limited to directly affected clients.

Are Firms Biasing Stakeholder Expectations by Attributing Prior Poor Performance to COVID-19?

Item 503(c) of the United States Securities and Exchange Commission’s (SEC’s) Regulation S-K requires firms to disclose the ‘most significant’ factors that affect them in their Item 1A risk factor disclosures made in their 10-K (annual) or 10-Q (quarterly) SEC filings. Prior to COVID-19, firms discussed risk factors such as liquidity, competition, etc. as part of their Item 1A disclosures. The current pandemic has resulted in the COVID-19 risk factor being widely discussed as part of firms’ Item 1A risk factor disclosures. A ‘firm-specific’ discussion on this transient risk factor is unique in the sense that it can affect the salience of other, already disclosed, less transient but significant risk factors to investors and other stakeholders. Using a sample of 68 firms hard hit by COVID-19 with prior poor performance, I find that market reactions to their Item 1A risk factor disclosures were significantly more positive for firms that disclosed the COVID-19 risk factor in a certain firm-specific manner compared to those that didn’t. These results suggest that stakeholder perceptions of firms’ risk profiles are being biased to some extent as the less transient but other significant risk factors that were already affecting these firms seem to be underweighted by them in evaluating the firms’ risk profiles. I explain this bias further using the meta-theoretical framework of the elaboration likelihood model. I also propose a solution to this problem that involves making these disclosures in the form of risk matrices. JEL Classifications: G38, M10, M40, M41, M48

Social Washing or Credible Communication? An Analysis of Corporate Disclosures of Diversity, Equity, and Inclusion in 10-K Filings

Social Washing or Credible Communication? An Analysis of Corporate Disclosures of Diversity, Equity, and Inclusion in 10-K Filings

Using Machine Learning and 10-K Filings to Measure Innovation

Using Machine Learning and 10-K Filings to Measure Innovation

Majority of Fortune 500 Companies in 2018 Did Not Recognize Risk of Epidemics Such as COVID-19

Infectious disease threats, like the 2002 severe acute respiratory syndrome coronavirus (SARS-CoV) disease, 2009 pandemic influenza A (H1N1), and the current coronavirus disease 2019 (COVID-19), pose multisectoral risk with the potential for wide-ranging socioeconomic disruption. In our globally intertwined economy, the impact of such events can elicit economic shock waves that reach far beyond the country of origin. Review of the 2018 Fortune 500 company 10-K filings shows the majority did not document perceived risks associated with epidemics, outbreaks, or pandemics. Enhanced engagement and investment of the public and private sectors in advancing global health security is needed to effectively prevent, detect, and respond to infectious disease events and ensure U.S. economic security.

Does XBRL help improve data processing efficiency?

PurposeThe US Securities and Exchange Commission (SEC) requires public companies to file structured data in eXtensible Business Reporting Language (XBRL). One of the key arguments behind the XBRL mandate is that the technical standard can help improve processing efficiency for data aggregators. This paper aims to empirically test the data processing efficiency hypothesis.Design/methodology/approachTo test the data processing efficiency hypothesis, the authors adopt a two-sample research design by using data from Compustat: a pooled sample (N = 61,898) and a quasi-experimental sample (N = 564). The authors measure data processing efficiency as the time lag between the dates of 10-K filings on the SEC’s EDGAR system and the dates of related data finalized in the Compustat database.FindingsThe statistical results show that after controlling for potential effects of firm size, age, fiscal year and industry, XBRL has a non-significant impact on data efficiency. It suggests that the data processing efficiency benefit may have been overestimated.Originality/valueThis study provides some timely empirical evidence to the debate as to whether XBRL can improve data processing efficiency. The non-significant results suggest that it may be necessary to revisit the mandate of XBRL reporting in the USA and many other countries.

Deposit Supply and Bank Transparency

Does a bank’s dependence on different external funding sources shape its voluntary disclosure of information? We evaluate whether economic shocks that increase the supply of bank deposits alter the cost–benefit calculations of bank managers concerning voluntary information disclosure. We measure information disclosure using 10-K filings, 8-K filings, and earnings guidance. As for the funding shock, we use unanticipated technological innovations that triggered shale development and booms in bank deposits. Further analyses suggest that greater exposure to shale development reduced information disclosure by relaxing the incentives for managers to disclose information to attract funds from external capital markets. This paper was accepted by Kay Giesecke, finance.

Using Machine Learning to Analyze Merger Activity

An unprecedented amount of access to data, “big data (or high dimensional data),” cloud computing, and innovative technology have increased applications of artificial intelligence in finance and numerous other industries. Machine learning is used in process automation, security, underwriting and credit scoring, algorithmic trading and robo-advisory. In fact, machine learning AI applications are purported to save banks an estimated $447 billion by 2023. Given the advantages that AI brings to finance, we focused on applying supervised machine learning to an investment problem. 10-K SEC filings are routinely used by investors to determine the worth and status of a company–Warren Buffett is frequently cited to read a 10-K a day. We sought to answer–“Can machine learning analyze more than thousands of companies and spot patterns? Can machine learning automate the process of human analysis in predicting whether a company is fit to merge? Can machine learning spot something that humans cannot?” In the advent of rising antitrust discussion of growing market concentrations and the concern for decrease in competition, we analyzed merger activity using text as a data set. Merger activity has been traditionally hard to predict in the past. We took advantage of the large amount of publicly available filings through the Securities Exchange Commission that give a comprehensive summary of a company, and used text, and an innovative way to analyze a company. In order to verify existing theory and measure harder to observe variables, we look to use a text document and examined a firm’s 10-K SEC filing. To minimize over-fitting, the L2 LASSO regularization technique is used. We came up with a model that has 85% accuracy compared to a 35% accuracy using the “bag-of-words” method to predict a company’s likelihood of merging from words alone on the same period’s test data set. These steps are the beginnings of tackling more complicated questions, such as “Which section or topic of words is the most predictive?” and “What is the difference between being acquired and acquiring?” Using product descriptions to characterize mergers further into horizontal and vertical mergers could eventually assist with the causal estimates that are of interest to economists. More importantly, using language and words to categorize companies could be useful in predicting counterfactual scenarios and answering policy questions, and could have different applications ranging from detecting fraud to better trading.

Corporate Reconfiguration and Corporate Differentiation: Evidence from Divestitures and Acquisitions

The current study leverages firms’ product information from 10-K filings to examine whether divestiture and acquisition reconfiguration strategies affect the extent to which firms differentiate their products from their closest competitors’ products. Our empirical results suggest that after divestitures and sequences consisting of both, acquisition and divestiture moves, the similarity of a focal firm’s products to its competitors’ decreases. These findings are consistent with firms trying to stake out a (maximum) differentiation position in the product-market space after reconfiguration, suggesting that competition is a neglected factor in the corporate strategy literature. This study contributes to the extant literature on corporate reconfiguration by illustrating the effects of divestiture and acquisition reconfiguration strategies on the competitive positioning of firms.

Do short sellers anticipate late filings?

Exploiting the setting of firms that are unable to disclose timely financial reports and thus must file with the U.S. Securities and Exchange Commission (SEC) the NT 10-K (Q) report, this study examines whether short sellers target firms with financial reporting weaknesses. We find that short interest increases in firms prior to the NT 10-K (Q) filing, suggesting that short sellers identify and target firms that cannot file their financial reports in a timely manner. Short selling is positively significantly related to subsequent late filing status, and is more pronounced in late filers with high newswire activity and with accelerated filing deadlines. Short selling of late filing firms is significantly negatively related to subsequent performance thereby suggesting that short sellers' trades pertinent to late filers are profitable. Overall, the results underscore a high information processing ability of short sellers in the setting of firms that exhibit financial reporting deficiencies.