The Need to Adapt to New Financial Accounting Technologies Information in the Context of Global Economic Crisis

Today, accounting is a necessity and not a desire. Concerns for the improvement of accounting practices are necessary, especially in Romania, where these activities are strengthened with the progress of the Romanian economy integration into the structures of the European Union. This paper carried an objective analysis of how the web report is now being made by financial and accounting information, presents the disadvantages of this approach to reporting introduced, but the potential benefits that could be created by the rapid adoption of international standards for reporting financial information website, too. At the same time, the paper tries to create new opportunities as soon as possible regarding the adoption of intelligent technologies, which, coupled with language Web reporting financial information.economic crisis, web reporting, intelligent financial-accounting systems

The Effects of Information Acquisition on Mergers and Acquisitions: Evidence from SEC EDGAR Web Traffic

I test the impact of information acquisition (proxied by SEC EDGAR web traffic) on market informativeness about deal value creation in mergers and acquisitions (M&As). Information acquisition about merging firms, industry rivals, and supply-chain firms enhance short-term market reactions informativeness about long-term merger operating synergies. The effects are more pronounced among M&As with more sophisticated investors, new information, and pre-merger information asymmetry. Furthermore, information acquisition about merging firms improves the market’s assessment of financial synergies. In addition, non-deal related firms with more downloads experience an increase in subsequent takeover probability. The evidence from difference-in-differences analysis and instrumental approach analysis suggests potential casual effects of information acquisition on market reaction informativeness. Overall, this paper demonstrates that information acquisition improves the market’s assessment of value creation in M&As

Implications of XBRL Adoption in Nigeria: Perception of Professional Accountants

XBRL is a recent development in the world of financial reporting. In view of its emerging preeminence in some countries of the world contrasted with the apparent backwardness of most African countries in respect of this move, this study sought to examine the implications of XBRL adoption in Nigeria. Adopting a survey design, mean scores and t-test statistic were employed to compare the perceptions of Nigerian professional accountants on the benefits and challenges of XBRL adoption in Nigeria. All these were based on questionnaire responses elicited from 54 out of the 100 copies of questionnaire generated for the study. The findings of the study, among others, revealed that there were perceptual differences among the respondents on the two issues. It is suggested that professional, national and sponsored international XBRL awareness and training would be of the essence if Nigerian Accountants are to find a space on the global map of professional relevance. Keywords: XBRL, XBRL adoption in Nigeria, Financial Reportin

Empirical investigations into corporate reporting in Europe: A financial market perspective on determinants and consequences of sustainability and digital reporting

This paper-based dissertation comprises five essays dealing with corporate sustainability and digital reporting and is structured in six chapters. The first chapter is the introduction and provides an overview of the structure and aims of the dissertation, lays out the contribution of the work, and introduces the five manuscripts. The second chapter, respectively the first manuscript, deals with the consequences of mandatory sustainability reporting in Europe. Specifically, the study deals with the question whether Directive 2014/95/EU has achieved its objectives of increasing reporting quantity and quality. In the third chapter, the sustainability reports of the largest European firms are analyzed using computer-aided text analysis. This study investigates whether and how external assurance of sustainability reports is beneficial from the viewpoint of report transparency, which is proxied by reporting scope, optimism, and readability. In the fourth chapter, the role of corporate sustainability in the context of M&A transactions is examined, precisely whether sustainability influences the premia paid in M&A transactions. The fifth and the sixth chapters center around the voluntary usage of online financial reporting (OFR) in Europe. While the fifth chapter is concerned with the usage and empirical determinants of OFR, the analysis in the sixth chapter examines the impact of OFR on the financial market, specifically on analyst following and stock liquidity

Information Processing Costs and Corporate Tax Aggressiveness: Evidence from the SEC’s XBRL Mandate

Managers, subject to agency conflicts, may deviate from the optimal level of tax aggressiveness that shareholders would prefer. We use the SEC’s XBRL mandate to draw causal inferences about the relation between investors’ information processing costs and shareholder monitoring of managers’ tax-aggressive behavior. We find that after XBRL reporting which reduces information processing costs to outside stakeholders, firms with low levels of tax avoidance in the pre-XBRL period become more tax-aggressive. In contrast, firms with high levels of tax avoidance are less tax-aggressive after XBRL reporting. These results suggest that reduced information processing costs and stronger shareholder monitoring in the post-XBRL period change tax strategies for firms at both tails of the tax avoidance distribution, which are more likely to signify under- and over-investments in tax avoidance by managers. Further analyses show that the effect of XBRL reporting on extreme levels of tax aggressiveness is stronger for firms with higher information asymmetry and lower competition over information among investors

Integrating Big Data Analytics with U.S. SEC Financial Statement Datasets and the Critical Examination of the Altman Z’-Score Model

The main aim of this thesis is to document the process of developing Big Data analytical applications and their integration with financial statement datasets. These datasets are publicly available on the U.S. SEC (Security and Exchange Commission) website which contains the annual and quarterly reports of approximately 8000 companies. Through its Electronic Data Gathering, Analysis and Retrieval (EDGAR) system, the SEC receives several terabytes of data in the mandatory filings from its registrants. This vast amount of data can potentially provide a valuable resource for those parties (such as investors, analysts, regulators and researchers) who are interested in assessing the financial performance and position of companies. Traditionally, the quarterly and annual reports were submitted in standard PDF, HTML and Text files. The data from these files could be manually extracted and analysed, but this process (still used by some analysts and researchers) is costly and time-consuming. In 2009, the SEC mandated all listed companies to use a digital reporting format known as XBRL (eXtensible Business Reporting Language). The intention of this was to improve financial reporting in terms of transparency and efficiency. In order to take advantage of structured data contained in the XBRL format, a variety of methods such as novel extraction algorithms and data mining techniques have been developed. However, several limitations and issues have emerged. These include a lack of automated connectivity between the EDGAR web interface and the terms used in structured taxonomies, and the inability to provide access to multiple files in a single query. Given the challenging and complex nature of these issues, this research project used the financial statement datasets available on the SEC website to extract relevant financial information from the company’s annual reports. The novel aspect of this research is providing big data analytical applications using cloud technologies that can efficiently perform datasets integration and transformation into a format suitable for further analysis. The result of this is that the extracted financial data can be analysed to assess the performance of companies, and this facilitates the critical examination of widely used credit assessment models such as the Altman Z’-Score

The determinants and trading consequences of automated information acquisition

I examine the determinants and trading consequences of automated acquisition of financial reports. Prior literature predominately studies human-based information acquisition, yet capital market participants are increasingly relying on automation to acquire financial reports. Using a novel approach to identify automated downloads of 10-Ks, I find strong evidence that automated and human downloads are positively correlated, suggesting that humans’ own interests influence how machines are programmed. I also find that machines selectively download the 10-Ks for firms with higher expected information frictions and/or misvaluation (e.g., smaller, value firms with complex filings). Using staggered XBRL adoption as an instrument for automated downloads, I find that automated downloads increase trading volume, particularly for firms with information frictions. However, I do not find evidence that automated downloads impact price movements or price efficiency. Taken together, the evidence suggests that automated acquisition of 10-Ks leads to differential interpretations, resulting in more trading but not necessarily more informed trading.Accountin

Three essays on corporate narrative disclosures

Accounting is the measurement, processing, and communication of economic activities and their results. Apart from numbers, a large amount of information is disclosed through narratives. This thesis presents three studies on the determinants, properties and consequences of firms’ narrative disclosures. In Chapter 1, “Firms’ Disclosure Strategies and Users’ Information Acquisition”, I study how firms’ disclosure strategies, i.e., smoothing and bundling, affect users’ decisions to acquire information. In Chapter 2, “Narrative Conservatism” (coauthored with Juan Manuel García Lara and Beatriz García Osma), we define narrative conservatism as narratives reflecting bad news in a more news-consistent, timely and complete manner than good news, and we find empirical evidence that corporate narrative disclosures is conservative. In Chapter 3, “Missing Narratives: Sample Selection Bias and Variable Choice in Textual Analysis Research” (coauthored with Andrea Bafundi, Beatriz García Osma and Encarna Guillamón-Saorín), we examine plausible biases in textual analysis studies of 10-K files. We provide detailed step-by-step guidance on how to download and prepare these files for analysis, and study the plausible biases introduced by a number of work-flow decisions regarding sample construction, data preparation, and variable choice.Programa de Doctorado en Empresa y Finanzas / Business and Finance por la Universidad Carlos III de Madrid. Mención InternacionalPresidente: Mark A. Clatworthy.- Secretario: Bing Guo.- Vocal: Marco Trombett

Data Quality Problems Troubling Business and Financial Researchers: A Literature Review and Synthetic Analysis

The data quality of commercial business and financial databases greatly affects research quality and reliability. The presence of data quality problems can not only distort research results, destroy a research effort but also seriously damage management decisions based upon such research. Although library literature rarely discusses data quality problems, business literature reports a wide range of data quality issues, many of which have been systematically tested with statistical methods. This article reviews a collection of the business literature that provides a critical analysis on the data quality of the most frequently used business and finance databases including the Center for Research in Security Prices (CRSP), Compustat, S&P Capital IQ, I/B/E/S, Datastream, Worldscope, Securities Data Company (SDC) Platinum, and Bureau Van Dijk (BvD) Orbis and identifies 11 categories of common data quality problems, including missing values, data errors, discrepancies, biases, inconsistencies, static header data, standardization, changes in historic data, lack of transparency, reporting time issues and misuse of data. Finally, the article provides some practical advice for librarians to facilitate their scholarly communications with researchers on data quality problems

Interactive Data and Information Visualization: Unpacking its Characteristics and Influencing Aspects on Decision-making

Background: Interactive data and information visualization (IDIV) enhances information presentations by providing users with multiple visual representations, active controls, and analytics. Users have greater control over IDIV presentations than standard presentations and as such IDIV becomes a more popular and relevant means of supporting data analytics (DA), as well as augmenting human intellect. Thus, IDIV enables provision of information in a format better suited to users’ decision-making. Method: Synthesizing past literature, we unpack IDIV characteristics and their influence on decision-making. This study adopts a narrative review method. Our conceptualization of IDIV and the proposed decision-making model are derived from a substantial body of literature from within the information systems (IS) and psychology disciplines. Results: We propose an IS centered model of IDIV enhanced decision-making incorporating four bases of decision-making (i.e., predictors, moderators, mediators, and outcomes). IDIV is specifically characterized by rich features compared with standard information presentations, therefore, formulating the model is critical to understanding how IDIV affects decision processes, perceptual evaluations, and decision outcomes and quality. Conclusions: This decision-making model could provide a meaningful frame of reference for further IDIV research and greater specificity in IS theorizing. Overall, we contribute to the systematic description and explanation of IDIV and discuss a potential research agenda for future IDIV research into IS. Available at: https://aisel.aisnet.org/pajais/vol11/iss4/4