Academic literature on the topic '10-Q filings'

Purpose Prior studies suggest that non-timely 10-Q filings indicate higher potential risks than non-timely 10-K filings. Furthermore, larger audit firms tend to be more risk-averse and conservative about reporting. Inspired by these research streams, this paper aims to investigate the influence of non-timely 10-Q filings on audit fees and the impact of audit firm size on this association. Design/methodology/approach The cross-sectional audit fee regression model used in this study is similar to that used in prior audit fee research (Simunic, 1980; Francis et al., 2005; Hay et al., 2006; Wang et al., 2013). The model includes the following five major characteristics that would influence auditors’ fee decisions: auditee size (LNAT), complexity (REIVAT, FOREIGN, SEG), financial condition (LOSS, ROA, GROWTH, ZSCORE), special events (ICW, RESTATE, INITIAL, GC) and auditor type (BIG4). To examine the effect of non-timely 10-Q filings on audit fees, the variable NT10Q is included in the audit fee model. Findings The results indicate that when both non-timely 10-K and non-timely 10-Q filings are included in the regression model, only non-timely 10-Q filings are significantly associated with higher audit fees, suggesting that the presence of non-timely 10-Q filings signals more serious underlying problem than non-timely 10-K filings in the audit fees decision processes. In addition, we find that audit fees for firms audited by Big 4 auditors are 26.4 per cent higher when those firms file non-timely 10-Q reports, whereas there is no significant association between non-timely 10-Q filings and audit fees for firms audited by non-Big 4 auditors. Practical implications As no attention has been paid to the investigation of the impact of non-timely 10-Q filings on audit fees, with the aim of filling the gap of this specific research area, this study examines the association between non-timely 10-Q filings and audit fees and the influence of audit firm size on this association. Originality/value The contribution of this paper is threefold: first, it is the first study to examine the association between non-timely 10-Q filings and audit fees. The results show that non-timely 10-Q filings are a better and earlier indicator of audit risk than non-timely 10-K filings. Second, the results reveal that the relationship between non-timely 10-Q filings and audit fees is affected by audit firm size. Specifically, Big 4 auditors tend to charge higher audit fees in the presence of non-timely 10-Q filings, reflecting that they are more sensitive to audit risk than smaller audit firms are. Third, an examination of the quarterly effect of non-timely 10-Q filings on audit fees indicates a stronger effect from the first quarter’s non-timely 10-Q filings, compared to the second or third quarter.

Purpose – The purpose of this paper is to investigate the relation between voluntary accounting changes (VACs) and post-earnings announcement drift. In addition, the authors examine how accounting choice heterogeneity moderates such association. Design/methodology/approach – The authors collect VAC firms in the US in the period from 1994 to 2008 and identify the heterogeneity of accounting choices between VAC and non-VAC firms. To test the hypotheses, the authors consider a 10-Q filing window and a post-filing drift window. The 10-Q filing window begins from one trading day before and ends on one trading day after the quarterly report filing date. The post-filing drift window begins from two trading days after the filing date and ends on 60 trading days with respect to the earnings announcement date. Findings – The results demonstrate that, overall, VAC does not affect the three-day market reactions to 10-Q filings. However, after taking into account the accounting choice heterogeneity, the authors observe that VAC is positively related to the market reactions to surprises and negatively associated with the post-filing period drift. Originality/value – The paper contributes to the literature by showing that VACs affect the market’s responses to 10-Q filings only when such change results in different accounting practices compared to the VAC firm’s major competitors. Furthermore, given the change with heterogeneity requires more time to process, VACs are related to post-filing announcement drift.

Purpose To the authors’ knowledge, this paper is the first to use Detail I/B/E/S to study directly the timeliness of security analysts’ next-year earnings-per-share (EPS) estimates relative to the SEC filings of annual (10-K) and quarterly (10-Q) financial statements. Although the authors do not prove a causal relationship, they provide evidence that the average time from firms’ filings of 10-Ks and 10-Qs to the release of analysts’ annual EPS forecasts during short timeframes (for example, 15-day timeframe from a 10-K’s SEC file date) subsequent to the 10-K and 10-Q filing dates significantly shortened with XBRL implementation and then remained relatively constant following implementation. Design/methodology/approach Using filing dates hand-collected from the SEC website for 10-Ks during 2009-2011 and filing dates for 10-Ks and 10-Qs during 2003-2014 input from Compustat along with analysts’ estimated values for next year EPS, actual estimated next year EPS realized and estimate announcement dates in Detail I/B/E/S, the authors study the days from 10-K and 10-Q file dates to announcement dates and the per cent errors for individual estimates during per- and post-XBRL eras. Findings The authors find that analysts are announcing next-year EPS forecasts significantly more frequently and in significantly shorter time in zero to 15 days immediately following 10-K and 10-Q file dates post-XBRL as compared to pre-XBRL. However, the authors do not find a significant change in forecast accuracy post-XBRL as compared to pre-XBRL. Research limitations/implications Because this study uses short timeframes immediately following the events (filings of 10-Ks and 10-Qs), the relationship between 10-Ks and 10-Qs with and without XBRL and improved forecast timeliness is strengthened. However, even this strengthened difference-in-difference methodology does not establish causality. Future research may determine whether XBRL or other factors cause the improved forecast timeliness the authors’ evidence. Practical implications This improved efficiency may become critical if financial statement reporting expands as a result of new innovations such as Big Data and continuous reporting. In the future, users may be able to electronically connect to financial statement data that firms are maintaining on a perpetual basis on the SEC website and continuously monitor and analyze the financial statement data dynamically in real time. If so, then unquestionably, XBRL will have played a critical role in bringing about this future innovation. Originality/value Whereas previous studies have utilized Summary IBES data to assess the impact of XBRL on analyst forecasts, the authors use Detail IBES to study the effects of XBRL adoption directly by measuring days from 10-K and 10-Q file dates in Compustat to each estimate’s announcement date recorded in IBES and by computing the per cent error using each estimate’s VALUE and ACTUAL recorded in Detail IBES. The authors are the first to evidence a significant shortening in average days and an increase in per cent of 30-day counts in the zero- to 15-day timeframe immediately following the fillings of 10-K s and 10-Qs.

This case is designed to provide you with the opportunity to examine several reporting issues, in the period between an IPO and bankruptcy filing, for a “dotcom” company that failed. You will consider the information provided to outside users of financial statements in several company reporting mechanisms including the financial disclosures made by the company in its 10-Q and 10-K filings to the SEC, the pro forma earnings reported in press releases, and the information available to the public to evaluate a going concern assumption. Further, you will also examine the impact of analysts' forecasts on management's release of financial information to the public.

SYNOPSIS I examine whether recently required risk factor update disclosures in quarterly reports provide investors with timely information regarding potential future negative economic events. Specifically, I examine whether risk factor updates in 10-Q filings are associated with negative abnormal returns at the time the updates are disclosed and whether quarterly updates are followed by negative earnings shocks. I find that firms presenting updates to their risk factor disclosures have significantly lower abnormal returns around the filing date of the 10-Q relative to firms without updates. I also find that firms with updates to their risk factors section have significantly lower future unexpected earnings and are more likely to experience future extreme negative earnings shocks. These findings suggest that the recent disclosure requirement mandated by the SEC was successful in generating timely disclosure of bad news. JEL Classifications: M41; M48; D80; G18. Data Availability: Please contact the author for data availability.

ABSTRACT We use daily page views of analyst estimates, ratings, and target prices on Yahoo Finance to understand when users seek sell-side analyst research. Demand for this information is most pronounced on days with earnings announcements, management guidance, and All-Star analyst reports. Surprisingly, demand does not increase at Form 10-K and Form 10-Q filings. While the overall demand for analyst estimates is 19.9 percent less than for analyst ratings and target prices, on earnings announcement and management guidance days, this preference is reversed. Moreover, the demand for analyst information substantially trumps that of SEC filings and financial statement information. JEL Classifications: M41; G14; G24.

The U.S. Securities and Exchange Commission (SEC) recently made timely reviews of quarterly financial statements mandatory for all registrants. The objective is to improve corporate quarterly reporting. However, formal review reports are not required to be included in 10-Q filings, and may not even be issued by auditors. A priori, one would expect these reports to be useful to investors if they imply added auditor diligence or if they contain modifications to the standard report. We find that only 5.7 percent of the companies in our sample attached the auditor's review report in their 10-Q filings. Also the majority of these reports are “clean,” suggesting that clients may not be disclosing the reports when they are modified. After controlling for factors such as auditor type, agency costs, capital market transactions, and company size, we find a significant negative association between auditors' litigation risk and disclosure of the review report. In addition, we find that the disclosure of the review report is associated with auditor type and company size.

L’objectif de la thèse est d’étudier à quel point les données en langage naturel peuvent être utiles pour mieux comprendre les relations entre le sentiment public et les entreprises, ainsi qu’entre ce sentiment et les changements de prix sur les marchés. Pour ce faire, nous étudions des données NLP provenant de différentes sources : Twitter, les rapports des entreprises et Reddit. Nous obtenons des résultats prometteurs pour certaines sources, tandis que d’autres n’ont qu’une utilité limitée en ce qui concerne l’évolution des cours des actifs. Elles restent cependant pertinentes pour comprendre les réactions du public aux scandales d’entreprises
The goal of the thesis is to investigate whether natural language data can be useful in better understanding the relationships between the public and the companies, as well as the public and the stock market price changes. In order to do so, we investigate natural language data derived from various sources: Twitter, company filings, and Reddit. We show case promising results for some sources, while others happen to have limited use as far as stock price changes go. Although they remain relevant for understanding public’s reactions to company scandals

Environmental, Social, and Governance (ESG) are non-financial factors that are garnering attention from investors as they increasingly look to apply these as part of their analysis to identify material risks and growth opportunities. Some of this attention is also driven by clients who, now more aware than ever, are demanding for their money to be managed and invested responsibly. As the interest in ESG grows, so does the need for investors to have access to consumable ESG information. Since most of it is in text form in reports, disclosures, press releases, and 10-Q filings, we see a need for sophisticated natural language processing (NLP) techniques for classification tasks for ESG text. We hypothesize that an ESG domain specific pre-trained model will help with such and study building of the same in this paper. We explored doing this by fine-tuning BERT’s pre-trained weights using ESG specific text and then further fine-tuning the model for a classification task. We were able to achieve accuracy better than the original BERT and baseline models in environment-specific classification tasks.