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The increasing availability of eXtensible Business Reporting Language (XBRL) financial statements motivates additional investigation of whether XBRL’s search-facilitating technology (SFT) and enhanced viewing capabilities facilitate information search and improve financial analysis decision quality and efficiency. This experiment investigates how using XBRL technology to view financial statements influences novice investors’ decision quality by affecting decision processes such as search strategy and effort, as well as decision efficiency (accuracy/effort) in a financial statement analysis task. In the experiment, randomly assigned student participants (n = 102) invested in companies using either static PDF-formatted or XBRL-enabled financial statements. No differences in decision quality (i.e., accuracy) due to technology use were observed. However, participants in the XBRL condition examined less information, used more directed search processes, and evidenced greater efficiency than did participants assigned to the PDF condition. Hence, the results suggest that XBRL SFT affects the use of differing decision processes relative to PDF technology.

In recent decades, interconnections between countries have increased substantially worldwide as the process of integration and globalisation intensifies, with a positive impact in terms of economic development, but, also with a vulnerability to external shocks, such as the financial contagion phenomenon. The analysis of this research field becomes even more relevant in the context of a new major exogenous shock, but which, this time, has different specificities, being a sanitary crisis. Thus, the chapter aims to investigate the impact of crises on capital market volatility for the period of 1995–2021, using the bibliometric analysis highlighting the dynamics of the literature and potential future research directions through a science mapping that enables investigating scientific knowledge. In order to explore the development of the research field in terms of publications, author impact, affiliated institutions and countries, citation patterns, trending topics, relationship between keywords–authors–journals, abstracts’ analysis, authors and documents clustering by coupling, multiple correspondence analysis of major research themes, keyword analysis, co-citation analysis and authors, institutions and countries collaboration analysis have been applied. Hence, almost 500 publications from Web of Science database covering the period 1995–2021 have been extracted. The empirical findings emphasise the conceptual structure, with clusters focussing mainly on long-term receivables, market efficiency, volatility, dynamic conditional correlation (DCC)-GARCH models, asymmetric effects. According to the intellectual structure of the field, Lambertides N., Zopiatis A., McAleer M. or Savva C. S. are the most representative authors for the sub-area of volatility topic; whilst Balcerzak A. P., Pietrzak M. B., Zinecker M., Meluzin T. and Faldzinski M. are the reference names for the whole spectrum of DCC-GARCH models’ topic. Jayasekera R., Lundblad C., Choundhry T., Gupta R. and Demirer R. are the authors mostly associated with asymmetric effects’ topic, whilst Thorp S., Bouchaud J. P. and Dungey M. with the quantitative finance. The Journal of Banking & Finance, the Journal of International Money and Finance and the International Review of Financial Analysis as well as Economic Modelling, Research in International Business and Finance and the International Journal of Finance & Economics are the most prolific journals in the field of capital flow and financial crises. This chapter’s main contribution is to build a structure of knowledge for the impact of crises on capital market volatility, elaborate and classify empirical research into relevant dimensions that can be used as a reference for comprehensively developing research. Finally, the bibliometric analysis results may provide insight into future research prospects. Our conclusions offer some recommendations for market practitioners and policy-making.

Purpose: The main aim of the study is to provide a tool for non-financial information in decision-making. We analysed the non-financial data in the annual reports in order to show the usage of this information in financial decision processes.

Need for the Study: Main financial reports such as balance sheets and income statements can be analysed by statistical methods. However, an expanded financial reporting framework needs new analysing methods due to unstructured and big data. The study offers a solution to the analysis problem that comes with non-financial reporting, which is an essential communication tool in corporate reporting.

Methodology: Text mining analysis of annual reports is conducted using software named R. To simplify the problem, we try to predict the companies’ corporate governance qualifications using text mining. K Nearest Neighbor, Naive Bayes and Decision Tree machine learning algorithms were used.

Findings: Our analysis illustrates that K Nearest Neighbor has classified the highest number of correct classifications by 85%, compared to 50% for the random walk. The empirical evidence suggests that text mining can be used by all stakeholders as a financial analysis method.

Practical Implications: Combining financial statement analyses with financial reporting analyses will decrease the information asymmetry between the company and stakeholders. So stakeholders can make more accurate decisions. Analysis of non-financial data with text mining will provide a decisive competitive advantage, especially for investors to make the right decisions. This method will lead to allocating scarce resources more effectively. Another contribution of the study is that stakeholders can predict the corporate governance qualification of the company from the annual reports even if it does not include in the Corporate Governance Index (CGI).

The global financial crisis has magnified the role of Financial Sector Surveillance (FSS) in the International Monetary Fund's activities. This chapter surveys the various steps and initiatives through which the Fund has increasingly deepened its involvement in FSS. Overall, this process can be characterised by a preliminary stage and two main phases. The preliminary stage dates back to the 1980s and early 1990s, and was mainly related to the Fund's research and technical assistance activities within the process of monetary and financial deregulation embraced by several member countries. The first ‘official’ phase of the Fund's involvement in FSS started in the aftermath of the Mexican crisis, and relates to the international call to include financial sector issues among the core areas of Fund surveillance. The second phase focuses on the objectives of bringing the coverage of financial sector issues ‘up-to-par’ with the coverage of other traditional core areas of surveillance, and of integrating financial analysis into the Fund's analytical macroeconomic framework. By urging the Fund to give greater attention to its member countries' financial systems, the international community's response to the global crisis may mark the beginning of a new phase of FSS. The Fund's financial sector surveillance, particularly on advanced economies, is of paramount importance for emerging market and developing countries, as they are vulnerable to spillover effects from crises originated in advanced economies. Emerging market and developing economies, which constitute the majority of the Fund's 187 members, are currently the recipients of over 50 programmes of financial support from the Fund (including those of a precautionary nature), totalling over $250 billion.

This chapter describes three active learning activities developed for use in the introductory financial accounting class: an interview with a financial statement user, an internal control paper, and a financial statement project where students analyze two competing businesses. We gathered student surveys and direct assessment data to see if these activities add value to the introductory accounting course.

The learning activities were originally developed using Fink’s (2003) Taxonomy of Significant Learning, aligning the activities with Fink’s learning dimensions, which also support the higher order learning skills in Bloom’s revised taxonomy. Students completed surveys by comparing how well traditional class activities (i.e., homework and tests) and the new activities support the core competencies of the American Institute for Certified Public Accountants (AICPA). We also asked students open-ended questions on how they felt about these new activities. Researchers then compared pre- and postadoption assessment data to investigate the impact of the new learning activities on class completion rates and grades.

Based on faculty comments and student survey results, the three active learning assignments appear to be more effective in developing many of the AICPA’s core competencies and real world skill sets valued by professionals, providing more value than traditional teaching methods. In addition, the passing rates in the course at the Youngstown State University increased by 12% after adopting the learning innovations.

Several developing economies witnessed a large number of systemic financial and currency crises since the 1980s that resulted in severe economic, social, and political problems. The devastating impact of the 1982 and 1994–1995 Mexican crises, the 1997–1998 Asian financial crisis, the 1998 Russian crisis, and the ongoing financial crisis of 2008–2009 suggests that maintaining financial sector stability through reduction in vulnerability is highly crucial. The world is now witnessing an unprecedented systemic financial crisis originated from the USA in September 2008 together with a deep worldwide economic recession, particularly in developed countries of Europe and North America. This calls for devising and using on a regular basis an appropriate and effective monitoring and policy formulation system for detecting and addressing vulnerabilities leading to crisis. This chapter proposes a macroprudential/financial soundness monitoring, analysis, and remedial policy formulation system that can be used by most developing countries with or without crisis experience as well as with limited data. It also discusses a process for identifying and compiling a set of leading macroprudential/financial soundness indicators. An empirical illustration using Philippines data is presented. There is an urgent need for increased coordination, collaboration, and partnership among central banks, banking and financial market supervision agencies, and ministries of finance, economic, and planning for proper macroprudential monitoring. A high-level national financial stability committee under the auspices of the head of the state as well as a ‘‘regional financial stability board’’ needs to be established to complement and support the activities of an “international stability board.”

We develop and test an innovative approach to teaching financial statement analysis (FSA) and assessing student learning outcomes based on making complex stock investment decisions compared to professional analysts. We train students to apply FSA and emphasize interdisciplinary factors and high integrative complexity. Our innovative FSA teaching approach, which we apply in an MBA financial reporting course, involves the instructor lecturing on FSA as a tool for integrative and complex decision making, students researching and applying FSA to public companies, and presenting the rationale for individual and group stock investment decisions. The instructor gives high-quality and timely feedback on the students’ application of FSA with a focus on investment judgments involving critical thinking, problem-solving, and teamwork skills. Our detailed efficacy analysis shows that our FSA teaching approach is effective. Students who perceive a public company to have credible management, effective competitive strategy, and an acceptable level of financial flexibility make comparable individual and group stock investment decisions as professional analysts.