Automated Trading and Yearly Reporting: The Need for RT- XBRL
Transcript of Automated Trading and Yearly Reporting: The Need for RT- XBRL
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Automated Trading and Yearly Reporting: The Need for RT-XBRL
Dr. Miklos A. Vasarhelyi KPMG Distinguished Professor Rutgers Business School - Newark & New Brunswick Director, Rutgers Accounting Research Center & Continuous Auditing & Reporting Lab
PhD Student Rutgers Business School - Newark & New Brunswick
Duo (Selina) Pei
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Roadmap
The Current Accounting Dilemma Information Needs The RT-XBRL Schema RT-XBRL Extensions Directions for the Future
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What are some problems plaguing professionals in the field?
Ball and Brown (1968) found that income numbers encompassed 50% of the information reflected in market measures. Lev (1989) showed using data over a span of 20 years, earnings explained no more than 7% of the variation in stock returns The Financial Times reports in 2009 that 73% of U.S. trading volume can be attributed to high frequency trading (Link)
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Some other phenomena observed
Trump tweets about Toyota, its U.S. shares dropped close to 1%, representing $2 billion in market value. Not just Trump, computer algorithms have been created to compile tweets from famous and important people. (Los Angeles Times January 16, 2017)
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Some other phenomena observed
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We need a reporting schema…
- Which links more current measures, and measures of a much wider scope - Supports interoperability across the value chain - Standardizes data to facilitate analysis and usage of sophisticated tools - Provides real-time information to satisfy the current trend of information
demands
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We need a reporting schema that also integrates well with current advances in auditing
Figure: Data standardization, Apps, Business Process, and continuous Usage (adapted from Dai, 2017)
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We Need RT-XBRL
ADS Layer Other Standardization Schemes
Internal
External
Structuring Layer
Output System
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So what kind of information may be missing?
- Intangibles (Lev and Sougiannis, 1996; Demerjian et al., 2012; Bonacchi et al., 2015)
- Private information, under-the-table discussions which resulted in the issuance of Regulation Fair Disclosure (Bushee et al., 2004; Bailey et al., 2003)
- Interim information which resulted in introduction of the 8-K and its subsequent iterations (Lerman and Livnat 2010; Carter and Soo, 1999)
- Information which are actually used by current market participants and the market players of the future (algorithms)
- ETF tracking (Avellaneda and Lee, 2010)
- Investor sentiment (Baker and Wurgler, 2006)
- Volume, order book imbalances (Brogaard et al., 2014)
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So what kind of information may be missing?
- SASB metrics - Intellectual property and data privacy
- Integrity and sponsorship
- “The relationships between [an organization’s] various operating and functional units and the capitals that the organization uses or affects” in the International Integrated Reporting Council Framework (2013)
Figure: Integrated Reporting Framework with Information Flows from The International Integrated Reporting Framework
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A more value relevant reporting paradigm to cater to information needs and characteristics of the future
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RT-XBRL is…
- Concept of a widened corporate measurement and assurance network - Multi-sourced information extracted to a database and fitted to a data
standard - A database which supports applications that may be independent,
correlated, integrated or heterogeneous and oblique in nature - Modeled to fit a reporting structure that may be formal and prescribed by a
standard setter (e.g. FASB) or informal based on the different entity stakeholder needs
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RT-XBRL is…
Live XBRL Sheet: Reporting / Monitoring
ADS Layer Other Standardization Schemes
ERP SC
Internal
External
Social Media
Market
IoT
Competitor
Weather
Geolocational Apps
News Metrics
Structuring Layer
Output System Alerts App User App 1
User App 2
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RT-XBRL may…
- Have links to sources to display relevant information (e.g. momentum, share buybacks, recent patents, brand, customer satisfaction)
- Some links could reference specific line items (equipment, contingent liability, etc.)
- Present non-traditional information from exogenous data sources “in-line” with traditional financial information in a reporting format
- Require real-time displays (dashboards) connected to, for example, Bloomberg or the Wall Street Journal
- Calculate and show new bottom line similar to “Value Created” (Lev and Gu, 2016) - Show feeds to internal systems (continuous assurance, exceptions reporting) - For the future:
- Predictive analytics and other research studies could be used to determine what are the most important information sources
- Predictive algorithms could change the information categories based on certain thresholds (i.e. report only changes of more than 5% or equivalent)
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Why ADS?
- Compatibility with XBRL (Outlined in ADS Base Standard 2015) - ADS paves way for XBRL Global Ledger (Dalla Via and Garbellotto, 2015)
- Standardization - Automation
- Codifying audit-relevant organizational activities - Supports audit apps which can be integrated with RT-XBRL
- Includes aspects of the value creation cycle: inventory, order to cash, and the general ledger
- Easier for auditors to assure RT-XBRL statements
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Conceptualizing “RT” and “XBRL”
- Incorporate descriptive metrics, thresholds, exceptions detection - Periodicity of information gathering and dissemination should be based on
decision usefulness, cost-benefit, and user needs - On the internal end refers to real-time monitoring but not real-time reporting
- XBRL supports tagging and is machine-readable. - RT-XBRL supports cross-referencing between external and internal data sources creating an
interconnected web of information conducive to understanding both the business and the environment in which it operates
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The RT-XBRL approach to monitoring and reporting exceptions
- ADS tagging makes receipts and accounting entries easy to verify - “Filter-like” operations can single out anomalies quicker
- Ex. match purchase order to the invoice received, view all dates, individuals involved, product amount, type of product, purchase order and invoice IDs, and discounts given
- Identify with global and local events as well as upstream and downstream activities which may correlate with the exception
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Linking continuous reporting to continuous assurance
MOD – PERF = DELTA IF | DELTA > STDELTA THEN START ALERT
Dependent on the Pulse of Application
(Vasarhelyi et al., 2010)
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An ecosystem of corporate measurement and assurance
Diagram: Audit Ecosystem (modified from Kozlovski, 2017)
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Directions for the future: categorization of information types
- Facts and statistics that have significance in explaining trading behavior but may be difficult to collect
- Investor sentiment (Baker and Wurgler, 2006)
- Location (Balakrishnan et al., 1990)
- Weather (Yoon et al., 2017)
- Value should be substantiated through further research or predictive analytics and modeling.
- Social media (Luo et al., 2013)
- Managerial expertise - Attempt made through network theory (Larcker et al., 2013)
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Appendices: References
Avellaneda, M., & Lee, J. H. (2010). Statistical arbitrage in the US equities market. Quantitative Finance, 10(7), 761-782. Bailey, W., Li, H., Mao, C. X., & Zhong, R. (2003). Regulation fair disclosure and earnings information: Market, analyst, and corporate responses. The Journal of Finance, 58(6), 2487-2514. Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680. Balakrishnan, R., Harris, T. S., & Sen, P. K. (1990). The predictive ability of geographic segment disclosures. Journal of Accounting Research, 305- 325. Ball, R., & Brown, P. (1968). An empirical evaluation of accounting income numbers. Journal of Accounting Research, 159-178.
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Appendices: References
Bonacchi, M., Kolev, K., & Lev, B. (2015). Customer franchise—A hidden, yet crucial, asset. Contemporary Accounting Research, 32(3), 1024-1049. Brogaard, J., Hendershott, T., & Riordan, R. (2014). High-frequency trading and price discovery. The Review of Financial Studies, 27(8), 2267-2306. Bushee, B. J., Matsumoto, D. A., & Miller, G. S. (2004). Managerial and investor responses to disclosure regulation: The case of Reg FD and conference calls. The Accounting Review, 79(3), 617-643. Carter, M. E., & Soo, B. S. (1999). The relevance of Form 8-K reports. Journal of Accounting Research, 37(1), 119-132. Dai, J. (2017) Three Essays on Audit Technology: Audit 4.0, Blockchain and Audit Apps, PhD Dissertation, Rutgers Business School, Newark, NJ, 07102
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Appendices: References
Dalla Via, N., & Garbellotto, G. (2015). Internal Reporting with XBRL Global Ledger. Strategic Finance, 97(4), 46. Demerjian, P., Lev, B., & McVay, S. (2012). Quantifying managerial ability: A new measure and validity tests. Management Science, 58(7), 1229-1248. International Integrated Reporting Committee. (2013). The International Integrated Reporting Framework (Publication). Retrieved August 29, 2017, from International Integrated Reporting Committee website: https://integratedreporting.org/wp-content/uploads/2013/12/13-12-08-THE- INTERNATIONAL-IR-FRAMEWORK-2-1.pdf Larcker, D. F., So, E. C., & Wang, C. C. (2013). Boardroom centrality and firm performance. Journal of Accounting and Economics, 55(2), 225-250.
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Appendices: References
Lerman, A., & Livnat, J. (2010). The new Form 8-K disclosures. Review of Accounting Studies, 15(4), 752-778. Lev, B. (1989). On the usefulness of earnings and earnings research: Lessons and directions from two decades of empirical research. Journal of Accounting Research, 153-192. Lev, B., & Gu, F. (2016). The end of accounting and the path forward for investors and managers. John Wiley & Sons. Lev, B., & Sougiannis, T. (1996). The capitalization, amortization, and value- relevance of R&D. Journal of Accounting and Economics, 21(1), 107-138. Luo, X., Zhang, J., & Duan, W. (2013). Social media and firm equity value. Information Systems Research, 24(1), 146-163.
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Appendices: References
Sustainability Accounting Standards Board. (2017, February). SASB Conceptual Framework (Publication). Retrieved August 29, 2017, from Sustainability Accounting Standards Board website: http://library.sasb.org/wp-content/uploads/2017/02/SASB-Conceptual- Framework.pdf?hsCtaTracking=3b37ee09-f32f-4cb3-ae50- 89c55a6eebb4%7C302f7abc-aaba-42a7-ab7d-8a4e22f43900 Yoon, K., Kogan, A., & Vasarhelyi, M. A. (2017). Weather Records as Big Data Audit Evidence. Working Paper.