1. SEC & THE EFFECTIVENESS OF XBRL
Kshitij
Deshpande
MS Analytics
Georgia State
University
Krishna
Vijaywargiy
MS Analytics
Georgia State
University
Sabari
Mukunthan
MS Analytics
Georgia State
University
Shijie
Wang
MS Analytics
Georgia State
University
Summary of the SEC filings
The Security Exchange Commission (SEC) was formed as per the Securities Exchange Act of
1934 together with the Securities Act of 1933. The goal of the SEC was to bring back the
confidence of the investors in the capital markets. They accomplished it by catering the investors
and the market with dependable information and clear guidelines of honest dealing.
The responsibilities of the SEC according to their website includes the following:
 Define and implement the Federal Securities laws
 Issue new rules and enhance the existing rules
 Oversee the inspection of securities firms, brokers, investment advisers and rating agencies
 Oversee private regulatory organizations in the securities, accounting, and auditing fields
 Coordinate U.S. securities regulation with federal, state and foreign authorities.[1]
Division of Corporate Finance
It is one of the division of the commission which takes care of the corporate disclosure of the
essential information to the people who invest based on that information. The staffs who work
under the Division of Corporate Finance periodically inspects the documents that the publicly held
companies are required to file under the SEC. The staffs also lend help the companies in
understanding the existing rules and also recommend new rules for the SEC to adopt.
SEC requires publicly held companies to file the following:
 Registration statements for newly offered securities
 Annual (Form 10-K) and quarterly(Form 10-Q) filings
 Proxy materials sent to shareholders before an annual meeting
 Annual reports to shareholders
 Documents related to tender offers
 Filings related to mergers and acquisitions[1]
Form 10-K: A Form 10-K is a report in which the wealth of the company is filed annually. The
10-K report includes the audited financial statement and also gives a broad outline of the
company’s business and the financial condition. Currently, the deadline for the 10-K form to be
filed is 60 days after the company’s fiscal year. For the other accelerated filers and the non-
accelerated filers the deadline for filing the 10-K form is 75 days and 90 days respectively after
the company’s fiscal year.[2]

2. Form 8-K: The Form 8-K is a report which is used for notifying the investors about the events
that happened in the public company which may be important to the shareholders of the company,
or the SEC. The form 8-K is to be filed after an important event happening in the company like
when the company goes bankrupt or if a new CEO is elected to the company, the company must
file the 8-K report within four days to renew the previously filed 10-K (annual report) or 10-Q
(quarterly report).[3]
XBRL effectiveness and research
What is XBRL..?? XBRL (Extensible Business Reporting Language) is open XML (Extensible
Markup Language) based standard which is used for the electronic communication of the financial
and business information that consists of four components i) XML standard, ii) XBRL taxonomy,
iii) Instance documents and iv) XBRL specification.
Since April 2009, SEC’s interactive data rules for operating companies Rule 33 9002 has mandated
that companies worldwide which submit financial statements under US GAAP (general accepted
accounting principles) to SEC EDGAR system must provide it in XBRL format. The Extensible
Markup Language (XML) is a markup language which defines set of rules for the encoding of the
documents. The sole purpose of using XBRL is to facilitate the exchange and analysis of the
various financial statements which are filed in SEC. [4]
XBRL uses the XML syntax and other XML related
technologies for conceptual association amongst the
financial data and reports. The actual financial data is
represented as an instance document which is a list of facts
and data points associated with the XBRL Taxonomy.
The actual financial data is represented in an instance
document. An instance document is a list of facts/data-
points associated with conceptual information defined by
the associated taxonomy.[4]
Fig 1) XBRL Taxonomy

3. Does it add up? Early evidence on the data quality of XBRL filings to the SEC
Short Summary: Data quality is not satisfactory. 26% filings have errors.
Data quality includes the attributes of availability, validity, completeness, accuracy, etc., and is
very important in accessing, assuring and analyzing any company documents. Hence, data quality
of XBRL files is an essential measurement of the effectiveness of the filings. In 2010, Roger et al.
looked into the data quality of XBRL filings, using the first round of filings of 10-Q reports in
XBRL files. Due to the complexity of extended taxonomies files and a required professional
accounting knowledge, information retrieved from instance documents could be distorted. The
team’s research question is to find out whether the first round of interactive data filings would
suffer from avoidable computational errors.
The data are 435 XBRL filings from 406 individual companies up to September 1, 2009. First, a
customized software tool computed the sums of all relationships in the financial statements. After
that, errors are inspected and further categorized by two members of the research team, by
comparing the software generated concepts and original HTML filings. [5]
The research showed that the data qualify of XBRL are not very satisfactory. 26% of filings had
calculation error, with an average of 1.8 errors per filings. The interesting part is the nature of
errors showed in the table 1.[5]
Table 1: Nature of errors
43% of all errors are the debit/credit reversals. The errors reside in the different of debit/credit
definitions between financial statement and the GAAP taxonomies. For example, Treasury Stock
is often treated as a subtraction in the computation of Stockholder’s Equity, but it is a debit concept
assigned the calculation relationship -1 in the taxonomy. Such inconsistency between the filers
and common practice caused errors when doing calculations. Also, the specialist in XBRL
preparation software have varying levels of error warnings. Besides the debit/credit reversal errors,
there are also 15% of missing fact value errors and 13% wrong fact errors. Higher quality of data
requires SEC to provide better validation tools before submission, and require the companies to
develop assurance process when generating instance documents. For the XBRL software vendors,
they should develop better diagnostic functions and error warning methods. Such measure would
help tract the computational errors and make sure the quality is high when adopting the
technology.[5]
XBRL Mandate: Thousands of Filings Error and So What?
After first six quarterly filings after the implementation of the XBRL, it was found that there were
more than 4000 errors made by more than 1000 filers. When the same data of errors were checked

4. in the second six quarterly filings, it was found that there were 4,260 errors in 4,532 filings. Which
implies that the learning curve is exhibited by the XBRL filers. This suggests that the users who
file the XBRL learn from their experience to improve in filing by reducing the number of errors.[6]
For the measurement of the learning curve, the number of errors per filing from the XBRL Cloud
EDGAR Dashboard dataset was used. In the above dataset, the errors are defined as “SEC will not
(or should not) accept the document according to EDGAR Filing Manual.”
Using a ZINB regression, a model was built on the number of errors in the XBRL filing with the
following equation:
# OF ERRORS = f(β0 + β1NUMBER of TIMES FILED IN PHASE 1 + β 2PHASE2 + β
3NUMBER of TIMES FILED IN PHASE2 + ∑ β(Control Variable)n). [6]
All the variables in the equation above are defined in the Table 1. In the model above, the
dependent variable is the # of Errors which is a count variable with many zero values. The prime
reason for using the ZINB method is to address the excess zeros in the #of Errors. [6]
Table 2: Variable Definitions and Expected Relation with the number of XBRL Reporting Errors

5. Table 3: Descriptive Statistics
A1
The Descriptive data showed in the table 2 gives an evidence that the distribution of the dependent
variable of # of Errors may be misinterpreted with many outliers which implies that the output
from the regression might be biased. To address this concern, instead of a continuous variable, an
indicator variable was used for XBRL filing errors. In accordance with the above concerns, the
probability of the error was calculated using a logistic regression shown below:
Prob(ERRORS )= f(β0 + β1NUMBER of TIMES FILED IN PHASE 1 + β 2PHASE2 + β
3NUMBER of TIMES FILED IN PHASE2 + ∑ β(Control Variable)n).

6. In the above model, the variable Error is an indicator variable. It is equal to 0 if there is no error
and it’s equal to 1 if there is an error. All other variables are same as the equation before.
The results of the equation with number of errors is presented in table 4. [6]
Table 4: Logistic Regression of the Probability of XBRL Filings
From the results obtained in from the two regressions, we can confirm that even though there are
a large number of errors initially, the errors in the subsequent filing are significantly decreasing.[6]
Benefits of XBRL on Financial Statement Auditing
The association of data points in financial reports with referential information of companies is
staunchly aided by the tagging process used in XBRL. These XBRL instance documents (financial
reports) help in mapping relationships and processing rules between financial accounting concepts
using XBRL tags which extensively improve the financial reporting transparency while assisting
the auditing practices which primarily focuses on accumulating and evaluating the financial
statements in accordance with the pertaining financial reporting framework. [7]
The three vital benefits from XBRL are i) efficient and regular tracking assessment of the effects
of control evaluation of business processes on accounts in financial reports, ii) flexible assessment
of interdependencies between control objectives, initiatives and risks involved with reference to
investments and iii) reliable tracing and analyzing of auditing trails across different organizations
and different financial frameworks. This helps to reduce audit engagement costs whilst drastically
minimizing manual effort involved with internal control tests, eventually decreasing the overall
auditing costs for both the companies and investors.

7. According to various prior studies, the overall auditing costs are inversely proportional to the
firm’s size. However, recent analysis of this correlation suggests that higher political visibility,
complexity and risks association with larger firms, in contrast to their smaller counterparts,
contribute to broader challenges in maintaining the financial accounts and detecting frauds. This
has led to an increase in high quality disclosures from these companies to respond to higher public
scrutiny, which results in potentially higher auditing costs. Although, the increased adoption of
XBRL has helped in keeping a check on these costs. These factors have been represented by Yuan
George Shan and Indrit Troshani by the following multi-linear regression model:[7]
AUDITFEESi = α + β1XBRLi + β 2FIRMSIZEi + (β 3XBRLi * FIRMSIZEi) + β 4DERATIOi
+ β 5EPSi + β 6SALESi + β 7ROAi + β 8TOBINSQi + β 9LOSSi + β 10BIG4i + β 11NYSEi + γj∑(j=1
to 3)YEARi + ηk∑(j=1 to 11)INDUSTRYi + Ɛi
With firm size (FIRMSIZE) and XBRL as independent variables, the relationship with the audit
fees (AUDITFEES) can be explained with the above model. The firm size is measured as the
natural algorithm of total assets at the end of a fiscal year and XBRL is measured as a boolean
variable coded as 1, if firm is an XBRL filer or 0, if otherwise. The ratio of long term debt to total
equity (DERATIO), change in earnings per share (ΔEPS), sales ratio (ΔSALES), ratio of net profits
to total assets (ROA), ratio of market value of stock and book value of debt divided by book value
of total assets (TOBINSQ), boolean loss (LOSS), boolean for audit by one of the big 4 (BIG4) and
boolean stock exchange listing status (NYSE) are some other control variables that are affecting
the audit fees of the organization.
Using descriptive statistics, the authors also deduced that mean and median of audit fees at NYSE
were much higher than NASDAQ and that the negative debt-to equity ratio in the United States
improved after the XBRL mandate. The research conclusively validates that the auditing costs in
business information supply chains including financial statements drafters, auditors, and regulators
is reduced by the implementation of XBRL hence benefitting the reporting community holistically.
XBRL enhances the credibility and reliability of financial statements for all stakeholders of the
organization by allowing continuous auditing and real time assurance opportunities. This
conclusion can help stakeholders to reform audit policies and practices while promoting the overall
implementation of the XBRL mandate across the world. [7]
XBRL impact on Analyst forecast behavior
The information is critical for the functioning of a capital market (Saudagaran and Diga 1997) for
increasing the transparency of corporate affairs to stakeholders, for reducing uncertainty in
investment decisions and for facilitating efficient allocation of resources. The examination of about
1430 firms over the years 2005-2010 from those listed in the US reveals that the XBRL mandatory
adoption has led to the significant improvement in the quality and quantity of information provided
and as measured by an analyst and forecast the accuracy. The advances in the quality of
information technology (IT) has facilitated the dissemination of information and has made
collaboration and communication easy amongst them. (Debreceny et al. 2002; Rossignoli et al.
2009) The adoption of the mandated XBRL by the US firms by 2011 guidelines has led to the most
significant changes in the disclosure environment in the US capital markets (Debreceny et al. 2010)
and has expectedly evolved into the global data standard for financial reporting (Chang and
Jarvenpaa 2005). So the question is what is the XBRL mandate on the quantity and quality of

8. financial information environments, as reflected in analyst forecast behavior? The financial
analysts also do play an important and influential role as information intermediaries and economic
agents whose overall behaviour and actions affect the security pricing environment as the users of
the financial reports. (Mikhail et al. 1999; Yu 2010). The key take away from the mandated SEC
program is to develop an ecosystem that supports the production, collection, and distribution of
accurate data to information consumers as a proxy for the quality of financial information
environments, analysts’ forecast accuracy provides a critical measure of the effectiveness of the
SEC’s mandate. Also the implications from research on the value realization from XBRL adoption
have immediate benefits for regulators, filers, information consumers, accountants and other
stakeholders XBRL has been highly expected for analyzing information faster (Hannon 2002),
being vital for the democratization of capital markets (Debreceny et al. 2005), thus streamlining
internal and external financial reporting services, as well as reducing potential disparities between
firms with regards to disclosure level and content (Premuroso and Bhattacharya 2008). XBRL also
provides the possibility to build information systems that enhance comparison of financial reports
of different companies within one or more sets of GAAP.[8]
With the mandated usage of the XBRL the quality of the data transfer, automatic ratio, cross
instance document analysis, business metric analysis are improved which in turn is significantly
improves the quality of the financial reporting value chain. In the same vein, many expect the
development of standards like XBRL to improve data accuracy (Wigand et al. 2005) by reducing
re-keying information for e-Commerce and diminishing errors in duplicated data entry. Some
studies disclosed the overall quality improvement and decreased information asymmetry resulting
from the mandated XBRL adoption. [8]
The implementation of XBRL do entail certain uncertainties (Doolin and Troshani 2007). It goes
without saying that the IT is not without limitation. For example, Microsoft estimates that 90
percent of Internet transactions need to be re-keyed on the backend of e-Commerce
operations.(Matherne and Coffin 2001) Since financial analysts in the capital market can be used
as proxies for informed traders, as well as signals of information asymmetry because of their
superior information processing capabilities (e.g., Core 2001; Francis et al. 2002; Roulstone 2003),
the examination of XBRL’s effects on analyst forecast behavior can uncover the effectiveness in
value realization from XBRL adoption. As XBRL has potentially reduced the costs of processing
information (Hannon 2002), and on the other had increased the transparency of a firm (Debreceny
et al. 2005), and improves the quality of financial reporting (Kim et al. 2011; Yoon et al. 2011), it
is expected that the mandatory adoption of XBRL will increase the supply of analyst services and
thus increase the number of analyst following (e.g., Core 2001; Francis et al. 2002; Roulstone
2003). [8]
Hypothesis 1: The early mandated XBRL adoption in the US is associated positively with the
number of analysts following the firm.
Since analysts use the information from financial statements which is an important source while
determining their forecasts (Acker et al. 2002; Baker and Iman 2008; Chang and Most 1985; Peek
2005; Schipper 1991; Vergoossen 1993), financial statements of which are of higher quality leads
to more accurate forecasts. In addition, Hunton and McEwen (1997) reveal that directive
information search strategy, enabled by XRBL, is associated with accurate analyst forecasts.
Hypothesis 2: The mandated adoption of the XBRL in the US has positive association with the
analyst forecast accuracy.

9. As per SEC (2009) guidelines the filers should not involve the third parties, such as auditors, for
the creation of their overall interactive data filings. Further Amendments are made to exclude
interactive data from the officer certification requirements of Rules 13a-14 and 15d-14, which
further mandates the officers to certify in periodic reports the matters related to internal control,
disclosure control, and other procedures. The data file which is subjected to the modified liability
treatment as it is deemed to be furnished but not filed and also does not require auditor assurance.
Also it is found that the Corporate Governance is associated with the firms’ decision to be an early
and voluntary filer of the financial information in the XBRL format. (Callaghan and Nehmer 2009;
Premuroso and Bhattacharya 2008). Corporate governance is also found to interact with analyst
forecast behavior (Bushman and Smith 2001; Kelton and Yang 2008).
The mandated XBRL guidelines enables the capacity of automated production and consumption
of large volumes of information which on the other hand increases the supply of analyst services
and thus increases the quantity of information in the capital market. However the overall usefulness
of XBRL formatted information which is accessible needs to be improved. The overall practice of
the usage of the extensions has reduced the comparability of the XBRL reports. The generation of
the taxonomy which covers most of the common extensions and do limit the flexibility in creating
the further extensions the comparison amongst the documents will improve the quality of the data
analysis and its usage. Now as the firms rely more and more on the service providers and the
automated review steps to validate the XBRL information. Even though the service providers
might be the XBRL experts, the firm is responsible to disseminate and evaluate the information to
the stakeholders. Thus internal quality control amongst the firms would further robust the
usefulness of the XBRL information. The end user community should be further educated and
made aware of the causes of the errors and techniques to prevent the errors in the adoption process.
As the findings suggest, effective promotion and the proper curriculum design will definitely help
users to completely understand XBRL and its overall math. [8]
Does XBRL adoption reduce information asymmetry?
The mandatory disclosure by XBRL format has been conducted in Korea since 2007. This study
examines whether the adoption of XBRL has reduced the level of information asymmetry in the
Korean stock market. The information asymmetry is one of the most important reasons caused
investors to make uninformative decisions, and is also the reason why SEC requires information
disclosure. It is believed that increased level of corporate information disclosure can reduce
information asymmetry, including bid-ask spread.[9]
The study used relative spread as a proxy for information asymmetry, and used firm size, stock
turnover rate, volatility and price as controlling variables. Multi-regressions were employed to
examine the effect of XBRL adoption on capital market. The data include transaction data of
common stocks from Dec 2007 to Aug 2008.
Table 5: Results of multiple regression analysis

10. Table 5 shows that generally, the XBRL adoption is significantly negative correlated to
information asymmetry. The regression has R square of 0.86 so it is significant.
Table 6: Results of multiple regression analysis depending upon firm’s equity
The study also looked into whether the effect will vary by firm size. Table 6 is the multiple
regression result based on company size. The larger a company is, it is harder integrate business
reporting procedures. It shows that even though for all sized companies, the effect of XBRL
adoptions are negative, the effect is strongest for large-sized companies. The estimated parameter
is -0.09, and p-value is 0.00, supporting that XBRL adoption reduces the information asymmetry
of large companies in capital market the most. Finally, this study found that the XBRL adoption
was not significant for medium size and small size companies, indicating that a broader conduct
for XBRL-enabled applications and service needs to be developed.
References:
1) https://www.sec.gov/about/whatwedo.shtml
2) https://en.wikipedia.org/wiki/Form_10-K
3) https://en.wikipedia.org/wiki/Form_8-K
4) XBRL: Impacts, Issues and Future Research Directions: https://www.wiso.uni-
hamburg.de/fileadmin/wiso_fs_wi/Publikationen/FinanceCom_-_2012_-_XBRL.pdf
5) Does it add up? Early evidence on the data quality of XBRL filings to the SEC:
http://www.sciencedirect.com/science/article/pii/S0278425410000219
6) Hui Du, Miklos A. Vasarhelyi, and Xiaochuan Zheng (2013) XBRL Mandate: Thousands of Filing Errors
and So What? Journal of Information Systems: Spring 2013, Vol. 27, No. 1, pp. 61-78.
7) Does XBRL benefit Financial Statement Auditing: http://iacis.org/jcis/articles/JCIS54-4-2.pdf
8) An Empirical Study of XBRL’s Impact on Analyst Forecast Behavior:
http://www.centerforpbbefr.rutgers.edu/2012PBFEAM/papers/001-PBFEAM.pdf
9) Does XBRL adoption reduce information asymmetry?:
http://www.sciencedirect.com/science/article/pii/S0148296310000251