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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.

The study aims to analyze, realize and identify the extent of research on financial literacy (FL) and to reveal the study trends, growth and evolution in the Scopus database from a bibliometric analysis. Principally, the primary purpose of this study is to conduct a comprehensive bibliometric review of studies focusing on the use, identification, network structure and conceptual structure of FL.

The most relevant articles were found using an electronic search. The studies that would be reviewed were sourced from the Scopus database. A total of 1,211 articles were found and refined to 768 papers between 1997 and 2021. Every composition has been analyzed in different dimensions such as co-authorship, co-citation, conceptual structure, co-word occurrence, trend topics analysis, thematic map, topic dendrogram, three field plot diagram and visualization analysis with the help of R programming language and VOSviewer software.

Motor themes, basic transverse, niche, and emerging and declining themes were identified using (Callon, 1991) a strategic thematic map. The analysis’s results showed that, over the past 20 years, FL literature has advanced remarkably. It also acts as a reference means for future researchers. This study adopted relational techniques such as co-word, co-author, co-citation analysis, bibliographic coupling and thematic map analysis revealing the emerging topics for future research. The relational approach indicates that “FL” and “human” are two central parts that connect to other frequently used words in the studies examined.

The study deploys bibliometric analysis appropriate for deriving insights from the vast extant literature. However, a meta-analysis might offer deeper insights into specific dimensions of the research topic. It expands the previous literature and shows study topics that are more focused by examining the abstracts and contents of articles published in journals in different Scopus categories. For future researchers to derive a solid theoretical framework, a systematic review of the literature and meta-analysis would be helpful. Science mapping for this study is limited to the Scopus database owing to its more comprehensive coverage of good-quality journals.

For future researchers to derive a solid theoretical framework, a systematic review of literature and meta-analysis would be helpful. Science mapping for this study is limited to the Scopus database owing to its more comprehensive coverage of good-quality journals. The authors offer suggestions for promising directions for future research that could address some of the inconsistencies found from the bibliometric analysis study.

This study can help both budding and established researchers to find new research focus, relevant sources, and collaboration opportunities and make informed decisions. Findings related to evaluative and relational techniques can serve as helpful information for researchers who are new to the field.

It shows the indicators used to benchmark institutes, authors, journals or articles. The increase in researchers’ collaborative, multi-authored and interdisciplinary efforts also revealed an annual growth rate of 23.77%. Overall, this study enhanced the understanding of the FL phenomenon and provided an experience and interpret a wide range of publication- and citation-based statistics. This study contributes to understanding the collaborative networks of various researchers and institutions and the benefits/detriments of collaborating cross-disciplinary, internationally, or with industry or corporate institutions.

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).

Presents a case study demonstrating financial statement ratio analysis (FSRA). This analysis matches company to industry data and builds sales forecasting models. FSRA imputes forecast standards of sales and costs, and applies them to a budgeted financial statement variance analysis for the EE (electronic and electrical) industry. Develops the concept of industry base standards, integrating them into the more traditional statistical and accounting concepts of quality control standards. Provides an implementation example, and reviews possible improvements to the current methodology and approach. Uses a similar methodology to forecast the stock market value with some exceptions. Models sales and costs of an individual company and an industry based largely on aggregate industry databases. For this purpose, uses a multivariate linear trend regression analysis for the sales forecasting model. Defines and tests related hypotheses and evaluates their significance and confidence levels. For an illustration uses the EE industry and the APM company. Also demonstrates a microcomputer‐based FSRA software that speeds, facilitates, and helps to accomplish the stated objectives. The FSRA software uses industry financial statement databases, computes financial ratios and builds forecasting models.

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.

The purpose of this paper is to investigate whether financial companies of the USA are inclined to manipulate the management discussion and analysis (MD&A) tone and thus to follow impression management behaviours. Also, the paper proposes a tone analysis of MD&As conducted by comparing the tone of MD&As of one year with financial conditions of the same year and the next.

The tone analysis is conducted on two sub-samples of US-listed financial companies, unhealthy firms and healthy firms, which experienced different financial conditions between 2002 and 2011.

With regard to healthy firms, MD&A tone is useful to explain the current year’s performance and helps to predict next year performance, whereas, with reference to unhealthy companies, managers use the tone to pursue impression management strategies, by using more positive words and more future-oriented words than healthy companies.

This study analyses the correlation between MD&A tone at time t and financial performance at time t and t+1, it does not investigate other time spans. The empirical results of this study cannot be generalized to other countries.

Main implications are addressed to regulators and policy makers, which may contrast impression management through a more effective regulation. Another implication regards investors, who cannot fully rely on MD&As of unhealthy companies.

This study analyses financial companies, rather neglected by the literature on MD&A tone. Results suggest that financial firms are also inclined to engage in impression management. This research would be useful for investors who base their decisions on qualitative analysis, interested in understanding to what extent the MD&A narratives are reliable.

This study seeks to evaluate the stability of financial ratios across industry and over time. The sample comprises companies listed on the Stock Exchange of Singapore from 1980 to 1991 over six industry groupings. A set of 29 most commonly used ratios was selected for the study. Descriptive statistics, factor analysis and analysis of variance were performed. From the factor analysis results, eight representative ratios were identified. Analysis of variance and multiple comparisons were subsequently performed for each representative ratio to test if it is significantly different across industry and over time. The results indicate that financial ratio averages of the various industries are significantly different. This implies that the appropriate benchmark for evaluating company performance and position should be industry‐specific instead of economy based. Also, five of the representative ratios are significantly different over time and not all the industrial averages move consistently over time (i.e., interaction effects of industry and time exist). Thus, industry averages are not necessarily appropriate benchmarks for setting and evaluating performance through time.

This study aims to critically review recent contributions to the methodology of financial economics and discuss how they relate to one another and directions for further research.

A critical review of recent literature on new methodologies for financial economics.

Recent books have made important contributions to the study of financial economics. They suggest new approaches that include an emphasis on radical uncertainty, adaptive markets, agent-based modeling and narrative economics, as well as extensions of behavioral finance to include concepts such as diagnostic expectations. Many of these contributions can be seen more as complements than substitutes and provide fruitful directions for further research. Efficient markets can be seen as holding under particular circumstances. A major them of most of these contributions is that the study of financial crises and other aspects of financial economics requires the use of multiple theories and approaches. No one approach will be sufficient.

There are great opportunities for further research in financial economics making use of these new approaches.

These recent contributions can be quite useful for improved analysis by researchers, private participants in the financial sector and macroeconomic and regulatory officials.

Provides an introduction to these new approaches and highlights fruitful areas for their extensions and applications.