Can the tone or sentiment of an SEC comment letter provide a signal to investors about the quality of an underlying firm? In a new study, I examine that question in the context of Reg A filings.
My study, though still at a preliminary stage, suggests an intriguing relationship between the sentiment expressed in SEC staff comment letters and the likelihood of qualification for proposed Reg A offerings. Insights from private company filings reveal a strong linkage between SEC comment letter sentiment and eventual registration approval.
A comment letter is a communication sent by the SEC following its review of a company’s financial statements, periodic reports, or registration statements. Its purpose is to address any concerns, seek clarification, or request additional information regarding the company’s financial disclosures and reporting. Comment letters facilitate effective communication between the SEC and companies, playing a vital role in promoting transparency, compliance, and informed decision-making by stakeholders.
Sentiment measures can be computed using natural language processing techniques that analyze text within a document to determine the overall tone expressed. My analysis used this approach to compute sentiment scores, which ranged from positive to negative, for each filing based on the tone of the words contained within the regulator’s correspondence.
Earlier research has revealed that submitting audited financial statements to the SEC and engaging legal and financial advisors during the registration process provide a positive signal to potential investors about the issue and the company’s compliance with regulations.  My current research on Reg A offerings expands upon the idea that positive sentiment within SEC correspondence signals higher quality and indicates the likelihood of a more successful filing. The information from this study provides additional insights into a company’s future financial health and performance, making sentiment analysis a useful tool for individual investors and analysts.
The study, which covers the period from July 2015 through December 2017, investigates the potential of SEC comment letters to serve as quality signals for investors and firms in the context of Reg A offerings. By analyzing text-based communications of 215 filings, I sought to determine if the sentiment within comment letters can help predict the SEC’s qualification decision of proposed offerings.
I present the results using one of the most basic methods of statistical analysis, which is the two-way chi-square tests. This approach is a straightforward examination of whether there is a statistical relationship between the observed and expected frequencies of two variables.
The findings are displayed in Table 1 and indicate there is a strong and positive relationship between sentiment scores and SEC qualifications. The statistics support that this observation is highly unlikely to have occurred by chance alone. In other words, the results suggest a significant link between sentiment and an offering’s qualification by the SEC at a 99 percent confidence level. While this is a limited sample and different sentiment methods can be employed, the results are consistent with prior research on the tone of SEC correspondence and issuer quality of public firms
Chi-Square Analysis of Reg A Offerings
(observed / expected totals)
|Status||Below Avg. Sentiment Score||Above Avg. Sentiment Score||Total Count|
|SEC Qualified||81 / 90||98 / 89||179|
|Non-Qualified||27 / 18||9 / 18||36|
Chi-square statistic = 10.61 (p-value = .002)
SEC comment letters for Reg A filings can be a useful tool for potential investors to evaluate an offering and the company’s compliance with regulations, but these should only be considered in conjunction with other relevant information. Nevertheless, this study offers implications for investors, issuers, and policymakers in the context of Reg A offerings. Overall, while only covering 30 months, this study presents the first use of textual analysis of SEC communications and the role it plays in signaling the quality of Reg A offerings.
As it turns out, this research is more than just an academic exercise. The U.S. Congress is currently considering raising the maximum amount for a Reg A offering to $150 million per year. In April, the House Financial Services Committee passed The Expanding Access to Capital Act of 2023 bill, which aims to double the current limit of $75 million. If passed, this bipartisan legislation would significantly increase the attractiveness of Reg A offerings as an early-stage funding option – and, in the process, boost job creation and enhance the economy.
SEC comment letters for Reg A filings can provide valuable signals to investors about the quality of a firm, as evidenced by the strong relationship found between sentiment in SEC correspondence and the qualification of Reg A offerings. While further research is warranted, these initial insights contribute to the understanding of how SEC comment letters can assist in evaluating offerings and promoting transparency and compliance. As policymakers consider raising the maximum amount for Reg A offerings, the study’s implications become even more relevant, as an increased limit could enhance the attractiveness of Reg A offerings, stimulate job creation, and strengthen the economy.
 Artificial intelligence and machine learning have transformed sentiment and textual analysis, allowing for efficient processing and interpretation of large volumes of text data. These advancements are providing analysts and researchers with scalable and accurate tools to gain deeper insights into firms as potential investments.
 A study by Bozanic, Dietrich, and Johnson (2017) found that firms that received more negative comment letters were likely to have lower earnings quality and to experience more accounting restatements in the future.
 Dechow, Lawrence, and Ryans (2016) reported that insiders engaged in higher trading activity before the public disclosure of SEC comment letters, which was then followed by negative returns after the comment release date.
 In previous research discussed in a CLS Blue Sky post, Krause noted that the average number of annual qualified Reg A filings increased significantly after the implementation of the JOBS Act in 2015.
 Sentiment can be measured by examining the linguistic features and context of a text, assigning positive or negative values to words and phrases, and then combining them to calculate an overall sentiment score.
 A chi-square test of independence is a statistical method used to determine if there is a significant association between two categorical variables by comparing observed frequencies with expected frequencies.
 As a result of the JOBS Act, the maximum amount for Reg A offerings was set at $50 million. This limit allowed small businesses to raise capital from the public without undergoing the full registration process with the SEC.
This post comes from David Krause, an emeritus professor of finance at Marquette University. It is based on his recent paper, “Can SEC Comment Letters of Regulation A Offerings Serve as Quality Signals for Investors and Firms? Preliminary Results are Encouraging,” available here.