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This paper aims to test whether the extent of compliance with International Financial Reporting Standards (IFRS) 7 requirements is value relevant and whether it influences the value relevance of the firm's accounting information (book value of shareholders' equity and net income).

The sample for this paper consists of 288 financial institutions listed on the Toronto Stock Exchange (TSX) from 2016 to 2019. Panel regressions have been used in this study.

The findings reveal that compliance with IFRS 7 is positively associated with the firm's market value. After making a classification between high-compliance and low-compliance companies, the authors' results indicate that the compliance level is positively associated with the value relevance of net income. Surprisingly, when examining the value relevance of financial instruments disclosures (FID) supplied after the adoption of IFRS 9, the authors find that book values of shareholders' equity and earnings are not more value relevant in the post-IFRS 9 period.

Given that the authors' analysis has been restricted to the Canadian setting, the regression results might not be generalized for other countries with different capital markets features.

The authors' findings point out that FID can affect investors' decisions as well as their confidence in the companies in which they invest. Hence, the regulatory bodies should gear more efforts to ensure high-compliance levels.

To the best of the authors' knowledge, this research is among the first attempts to investigate whether the new FID (after the adoption of IFRS 9) improves the firm disclosure quality and enhances the value relevance of accounting information.

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.

This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

This paper is motivated by the ongoing debate on the value relevance of cash flow statement (CFS) between bank regulators, on one hand, and accounting standard setters, on the other hand. The importance and usefulness of cash flows during economic turmoil exacerbated by the Covid-19 pandemic has recently gained attention. Hence, this paper investigates the impact of Covid-19 pandemic on the value relevance of cash flows (CF) beyond accounting earnings and book equity.

A panel of 236 bank-year observations is examined for value relevance in emerging capital markets of Gulf Cooperation Council (GCC) countries. Using value relevance regression, operating and non-operating CF items are tested for value relevance beyond earnings and book value of equity during the periods 2018–2019 (pre-pandemic) and 2020–2021 (pandemic).

There is limited value relevance of CF beyond accounting earnings and the book value of equity. The distinction between operating and non-operating CF is not informative. However, the value relevance is significant during the pandemic, indicating that investors rely on CF for valuation purposes at times of uncertainty, corroborating further research on CF distress predictive ability.

This paper provides novel evidence on value relevance of CF and its superiority to accounting earnings and equity values during times of uncertainty. It extends a small body of research in the banking sector in emerging markets. Hence, it complements prior literature and has practical implications to accounting standard setters and bank regulators in emerging markets.

This study aims to investigate the effect of accounting conservatism and business strategies as mitigating tools for bankruptcy risk. It determines the association among these factors and provides insights into the effectiveness of accounting discretion and business strategies in decision-making.

The study uses a sample of 83 nonfinancial listed firms in ASE for the period from 2013 to 2019. Bankruptcy risk is measured using the Altman Z-score (1968). Accounting conservatism is measured using the accrual-based approach, and optimal business strategies are identified through cluster analysis.

The results indicate that accounting conservatism has a significant negative effect on bankruptcy risk. Increased application of accounting conservatism practices leads to a decrease in the level of bankruptcy risk. However, the type of business strategy adopted by firms does not have a significant impact on bankruptcy risk, suggesting that firms are not effectively implementing their strategies to mitigate this risk.

This study focuses on nonfinancial listed firms in the ASE, limiting the generalizability of the findings to other contexts. The study's findings contribute to the understanding of the role of accounting conservatism in reducing bankruptcy risk but highlight the need for further research on the effectiveness of business strategies in mitigating this risk.

This study lies in understanding of the role of accounting discretion in financial evaluations and emphasizes the importance of accounting conservatism as a tool for mitigating bankruptcy risk. The study's insights provide valuable guidance to practitioners, regulators and researchers in this field.

This study aims to assess the evolution of the value relevance of book value, earnings and its components in Mauritius, an African developing country, focusing on value relevance changes after International Financial Reporting Standards (IFRS) adoption and subsequent local reforms.

The study relies on a data set of 567 firm-year observations (2001–2018) and the Ohlson valuation model to investigate value relevance after IFRS adoption, the implementation of institutional reforms and enforcement reforms.

Firstly, the authors find support for a rise in the combined value relevance of earnings and book value, albeit that book value significantly contributes to changes over time. The findings highlight the combined importance of IFRS adoption with institutional and enforcement reforms to improve value relevance. Secondly, the authors do not find evidence of a shift in value relevance between earnings and book value. Third, the cash flow model reveals a higher level of significance relative to the earnings model.

The authors extend the value relevance literature in the context of African developing countries. The present findings underpin the need for a reinforcing of relevant institutional and enforcement frameworks to ensure the benefits of IFRS adoption materialise. The findings also offer a contribution of how developing countries’ experience IFRS post-adoption while adding to the dearth of studies analysing IFRS enforcement practices.

Following the growing adoption of social media, many entrepreneurs are launching personal social media channels. This study focuses on the effect of entrepreneurs' shared information on We Media platforms on the value relevance of their earnings.

Using entrepreneurs' We Media data collected from A-share-listed companies on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2018, this study investigates the effect of the data on the value relevance of earnings using the modified Ohlson model. The authors applied textual analysis to retrieve entrepreneurial We Media data acquired manually from Weibo.

We Media platforms can increase the value relevance of earnings. Entrepreneurs can enhance investor trust by establishing social ties with investors. Investors are more likely to recognize earnings information publicized by enterprises, owing to internal consistency. Particularly, value relevance improves significantly with more personal information being posted and more “likes” being acquired on entrepreneurs' We Media accounts. This positive effect is more obvious in privately owned and highly marketized regions.

The findings extend the research on the economic consequences of We Media as an important information channel, enrich the research on the social media posting behavior of entrepreneurs and provide a reference for enterprises to instill trust using new information disclosure methods and for governments to establish a safe internet environment to promote the sustainable development of the capital market.

Are franking credit balances priced? This paper aims to investigate the valuation of franking credit balances via a determinant analysis and value relevance analysis.

The determinant analysis examines the factors that contribute to the increasing cumulative level of franking credit balances. Value relevance studies explore whether franking credit balances are priced in the market.

The results provide strong evidence of a size effect that the level of franking credit balances increases with firm size and weak evidence of an international focus effect that the level of franking credit balances increases with international ownership. They also find an individual dividend clientele effect that the level of franking credit balances decreases with individual ownership. They find significant evidence that franking credit balances are priced in the market. One dollar of franking credit is worth 1.4 dollars in firm value. That franking balances are capitalized at more than their face value suggests that franking credits signal firms' future dividend policy. They also find that the market valuation of franking balances increases with firm size but decreases with international focus.

This study provides direct evidence that franking credit balances are capitalized into equity prices. In the determinant analysis, this paper improves Heaney's (2009) model by using the percentage of international ownership as the proxy of international focus, thus addressing the limitation of his measure. In the value relevance tests, the study uses a modified model that includes log-transformation to reduce the skewness of variables based on Tanza's (2014) value relevance model. Moreover, the study suggests that the market valuation of franking credit balances increases with firm size, which contradicts Heaney's (2009) findings.

This study investigates the implementation challenges and economic consequences of the International Financial Reporting Standards 9 (IFRS 9) Financial Instruments.

Descriptive evidence on equity asset reclassifications and estimated impairment using the new expected credit loss (ECL) model are presented. Multivariate analyses on the disposal of available-for-sale (AFS) and fund investment post-announcement and the value relevance of impairments to financial assets post-implementation are performed.

Over 60% of sample firms report inconsistent equity asset reclassifications and do not change estimated impairment using the new expected credit loss model. Firms also switch from AFS to equity fund investments post-announcement. Lastly, impairments to financial assets increase in value relevance to investors’ post-implementation, but only in financial institutions and firms with Big 4 auditors.

This study's findings suggest that IFRS 9 presents implementation challenges and changes equity investment strategies. They also indicate cross-sectional differences in firms' ability to effectively apply the new standards. This study is valuable for policymakers, business leaders, investors and academics.

This study aims to examine the determinants and consequences of integrated reporting (IR) disclosures of listed non-financial firms in an emerging economy.

This study uses data from 39 listed non-financial firms that had adopted IR disclosure framework in Sri Lanka for the period from 2011 to 2018. Firm size, growth opportunity, profitability and firm age are considered significant determinants of IR disclosure, while their consequences are measured in terms of share price, Tobin’s Q, return on assets and return on equity. The authors used the results of the correlation and panel regression analyses to draw this study’s conclusions.

This study finds that firm size and age are the significant determinants of IR disclosure, which is consistent with this study’s expectations. Considering the consequences of IR disclosure, only share price and Tobin’s Q show significant results as per the panel regression analyses.

The findings of this study would be useful in the decision-making processes of existing and prospective investors, regulators, policymakers and society at large. Further, the findings of this study communicate the benefits of this new reporting paradigm in shaping their disclosures in the annual corporate reporting process.

Although existing studies attempted to examine the determinants of IR disclosure and its consequences as isolated studies, this study provides new insights by merging these two aspects into a single study and consider several determinants and consequences as well.