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Big data and algorithmic trading against periodic and tangible asset reporting: The need for U-XBRL

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  • Pei, Duo
  • Vasarhelyi, Miklos A.

Abstract

The gradual but marked decline in the correspondence between aggregated accounting numbers and market valuations, such as stock returns, is a well-documented phenomenon in the research literature (Lev and Zarowin, 1999). Rapid advances in technology have paved the way for the collection of unprecedented volumes of data. Currently, the slow speed of information dissemination, laggard accounting systems, and a focus on high levels of aggregation are perhaps the largest contributors to waning relevance of financial reporting. The fight for trading superiority is leading users to seek relevant data elsewhere and may contribute to these observed effects. This paper proposes an accounting system known as User XBRL (U-XBRL) designed to overcome these issues. This system collects, analyzes, and displays information in such a way that caters to the speed, detail, and customization demands of modern-day stakeholders (Krahel and Titera, 2015). U-XBRL amalgamates all types of data pertinent to a business, including both internal company data and exogenous source data. Each piece of data is assigned to a firm resource according to the resource-based view. Then, U-XBRL standardizes the information according to data standards and feeds it to a central repository. This repository is primarily organized through XBRL tags and is governed secondarily by other standards and taxonomies. A number of applications can be used individually to select data from the repository for analysis. Using U-XBRL the recognition, monitoring, and assurance of resources are streamlined.

Suggested Citation

  • Pei, Duo & Vasarhelyi, Miklos A., 2020. "Big data and algorithmic trading against periodic and tangible asset reporting: The need for U-XBRL," International Journal of Accounting Information Systems, Elsevier, vol. 37(C).
    • Handle: RePEc:eee:ijoais:v:37:y:2020:i:c:s1467089520300208
    DOI: 10.1016/j.accinf.2020.100453
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    3. Emilio Abad-Segura & Mariana-Daniela González-Zamar, 2020. "Research Analysis on Emerging Technologies in Corporate Accounting," Mathematics, MDPI, vol. 8(9), pages 1-29, September.

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