From Print to Practice: XBRL Extension Use and Analyst Forecast Properties

Kirk, Marcus; Vincent, James; Williams, D.L.

doi:10.2139/ssrn.2826159

Cited by 7 publications

(3 citation statements)

References 27 publications

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“…They find that the likelihood of restatements, internal control weaknesses and abnormal accruals are higher for firms with higher extension rate. Similarly, Kirk et al (2016) find a negative relation between abnormal extension rates and forecast accuracy, and a positive relation with forecast dispersion. All these studies suggest that extensions could be prejudicial to the quality of firms' reporting.…”

Section: Background and Hypothesesmentioning

confidence: 75%

The relevance of XBRL extensions for stock markets: evidence from cross-listed firms in the US

Cormier

Teller

Dufour

2022

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PurposeThe study investigates the relevance for stock markets of voluntary disclosure of eXtensible Business Reporting Language (XBRL) extensions [based on International Financial Reporting Standards (IFRS) or US-GAAP] for an international sample of US cross-listed firms.Design/methodology/approachThe study examines if the disclosure of XBRL extensions by a firm provides relevant information to market participants. Towards that end, this paper investigates whether this type of disclosure affects the level of information asymmetry between insiders and investors and if it is value relevant. This study measures information asymmetry by bid-ask spread and value relevance by stock price or Tobin's Q.FindingsAfter a certain level of disclosure of XBRL extensions, the impact on stock pricing is negative (creates noise on stock markets). Controlling for that phenomenon, both IFRS and US-GAAP XBRL extensions are value relevant. Second, results indicate that XBRL extensions are positively (negatively) related to stock market value for firms that exhibit positive (negative) earnings. This suggests a complementary effect between earnings and XBRL extensions on their relation with stock price or Tobin's Q. Finally, the results also indicate that both IFRS extensions and US-GAAP extensions are associated with lower information asymmetry (i.e. bid-ask spread).Originality/valueTo the best of the authors’ knowledge, this study is the first to investigate the relevance of XBRL extensions under IFRS for US cross-listed firms since the availability of the IFRS taxonomy for foreign private issuers that prepare financial statements under IFRS standards.

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Section: Background and Hypothesesmentioning

confidence: 75%

The relevance of XBRL extensions for stock markets: evidence from cross-listed firms in the US

Cormier

Teller

Dufour

2022

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show abstract

“…Plumlee and Plumlee (2008), Boritz and No (2009), Debreceny et al (2010), Harris and Morsfield (2012), Cohen et al (2014), Basoglu and White (2015) and Hoffman (2017) describe XBRL data as error-prone and unreliable. Moreover, custom XBRL tags hinder cross-firm comparability (Boritz & No, 2009), are associated with larger analyst dispersion and larger earnings surprise (Felo et al, 2018;Kirk et al, 2016) and are used by managers to strategically obfuscate poor performance (Huang et al, 2019). 7 Harris and Morsfield (2012) find little usage of XBRL by analysts and professional investors because of the low reliability of XBRL data, excessive use of custom tags and complex and cumbersome technology underlying XBRL.…”

Section: Readability and 10-k File Sizementioning

confidence: 99%

The roles of XBRL and processed XBRL in 10‐K readability

Cahan

Chang

Siqueira

et al. 2021

Business Fin & Account

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The size and composition of the 10-K file have changed dramatically since the mandatory adoption of XBRL. We reexamine 10-K file size as a readability proxy by decomposing 10-K file size into its main components, which include XBRL, processed XBRL (a twin to XBRL that allows XBRL information to be accessed using viewer software) and text. We find that 10-K file size reduces readability before XBRL's adoption in 2012 but enhances readability after adoption and that the XBRL-related components can explain the reversal of this relation. As the XBRL-related components only include financial statement information, our results indicate that more XBRL data improves users' understanding of the financial statements, which is in contrast to the text component of the 10-K where a larger file size is associated with lower readability. As such, our study identifies financial statement readability as a distinct and important dimension of disclosure quality that has been overlooked in the prior literature.

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“…research documenting errors and unnecessary extensions in XBRL filings (Debreceny et al [2010(Debreceny et al [ , 2011) and the associated adverse consequences in the capital markets (Li andNwaeze [2015, 2018], Kirk et al [2016]). Our paper provides direct evidence indicating that XBRL filings still inform investors' forecasts and investment decisions despite the data quality issues.…”

Section: Introductionmentioning

confidence: 99%

Predicting Future Earnings Changes Using Machine Learning and Detailed Financial Data

CHEN

CHO

Dou

et al. 2022

J of Accounting Research

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We use machine learning methods and high‐dimensional detailed financial data to predict the direction of one‐year‐ahead earnings changes. Our models show significant out‐of‐sample predictive power: the area under the receiver operating characteristics curve ranges from 67.52% to 68.66%, significantly higher than the 50% of a random guess. The annual size‐adjusted returns to hedge portfolios formed based on the prediction of our models range from 5.02% to 9.74%. Our models outperform two conventional models that use logistic regressions and small sets of accounting variables, and professional analysts’ forecasts. Analyses suggest that the outperformance relative to the conventional models stems from both nonlinear predictor interactions missed by regressions and the use of more detailed financial data by machine learning.

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From Print to Practice: XBRL Extension Use and Analyst Forecast Properties

Cited by 7 publications

References 27 publications

The relevance of XBRL extensions for stock markets: evidence from cross-listed firms in the US

The relevance of XBRL extensions for stock markets: evidence from cross-listed firms in the US

The roles of XBRL and processed XBRL in 10‐K readability

Predicting Future Earnings Changes Using Machine Learning and Detailed Financial Data

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