This study aims to investigate the complex link between carbon emissions, firm value, and financial choice in regard to the GCC, a dynamic emerging economy. It also seeks to answer the question on whether the financial structure of a firm moderates the correlation between carbon emissions and firm value. We focus on analyzing data from non-financial firms registered on the GCC stock markets between 2010 and 2020. By applying the GLS technique, we assess the impact of carbon emissions on firm value and examine the manner in which a firm’s financial structure either enhances or hinders this relationship. The results demonstrate that there is a strong and adverse connection between carbon emissions and corporate value, as increased emissions translate into lower corporate value. The study then moves on to emphasize the critical role that capital financing plays in mitigating the detrimental effects of carbon emissions. This is accomplished by balancing both debt and equity in terms of their proper proportions (optimal capital structure). However, excessive borrowing could have adverse consequences in terms of carbon emissions on company value. Moreover, the GMM estimator is also applied to carry out a robustness check and the results are consistent with the main findings. This study highlights the significance of financial strategy in advancing sustainability and protecting business value. These findings are supported by both stakeholder and signaling theory, proving that companies can use their capital financing to signal their dedication to sustainability. These results could be used by GCC policymakers to create rules and regulations that encourage environmentally friendly corporate activities and efforts to lower emissions. The research expands the existing literature by examining the difficulties and opportunities faced by GCC firms when combining financial strategy with environmental objectives. It may be necessary to perform additional research in regard to various circumstances and for an extended period, because this study is restricted to non-financial sectors.

There was an error in the original publication (Fanelli 2024) [...]

Our objective is to test for evidence of information asymmetry in the mortgage servicing market. Does the sale of mortgage servicing rights (MSR) by the initial lender to a second servicing institution unveil any residual asymmetric information? We are the first to analyze the originator’s selling choice of MSR. We use a large sample of U.S. mortgages that were securitized through the private-label channel during the period of January 2000 to December 2013 (more than 5 million observations). We propose a new nonparametric instrumental variable testing procedure to account for potential endogeneity. For robustness, we present parametric analyses to corroborate our results using instrumental variables. Our empirical results provide strong support for the presence of second-stage asymmetric information in the mortgage servicing market during the period of analysis and before the risk retention reform of 2014.

We address the problem of asset pricing in a market where there are no risky assets. Previous work developed a theoretical model for a shadow riskless rate (SRR) for such a market, based on the drift component of the state-price deflator for that asset universe. Assuming that asset prices are modeled by correlated geometric Brownian motion, in this work, we develop a computational approach to estimate the SRR from empirical datasets. The approach employs principal component analysis to model the effects of individual Brownian motions, singular value decomposition to capture abrupt changes in the condition number of the linear system whose solution provides the SRR values, and regularization to control the rate of change of the condition number. Among other uses such as option pricing and developing a term structure of interest rates, the SRR can be used as an investment discriminator between different asset classes. We apply this computational procedure to markets consisting of various groups of stocks, encompassing different asset types and numbers. The theoretical and computational analysis provides the drift as well as the total volatility of the state-price deflator. We investigate the time trajectory of these two descriptive components of the state-price deflator for the empirical datasets.

The aim of this study is to explore the influence of environmental, social, and governance (ESG) factors on business failure in Brazil by employing advanced machine learning techniques. We collected data from 235 companies and conducted principal component analysis (PCA) on 40 variables already used in the bankruptcy failure literature, resulting in the formation of seven variables that predict business failure. The results indicate that ESG factors significantly predict business failure in Brazil. This study has implications for investors, policymakers, and business leaders, offering a more precise tool for risk assessment and strategic decision-making.

Over time, companies have faced many crises that have impacted their capacity to remain operational in the market. When going through periods of financial distress, companies must find solutions to face the risks and to fulfill the going concern assumption, which is an essential principle in accounting and also of major importance in financial-statements auditing. The research objective is to identify the research trends and approaches in the fields of going concern and financial distress. To achieve this purpose, a bibliometric analysis was carried out of the articles published in the journals indexed in Web of Science Clarivate Analytics (WoS) for the period 2004–2023. The selection criteria was based on instances of the keywords “going concern” and “financial distress” appearing in a sample of 2.859 articles. The results highlighted that these fields represent a domain of interest in the research, with the trend being most pronounced in the area of financial distress, since 2018. Based on the content analysis of the most influential articles, the main topics addressed were related to audit quality and aspects related to management and corporate governance. Thus, it is confirmed that the area of financial distress and going concern assessment is a widely studied one, and the studies made can provide essential information to overcome the difficult periods that a company can go through.

We use dynamic programming, finite elements, and parallel computing to design and evaluate two-dimensional financial derivatives. Our dynamic program is flexible, as it divides the evaluation process into two components: one related to the dynamics of the underlying process and the other to the characteristics of the financial derivative. It is efficient as it uses local polynomials at each step of the backward recursion to approximate the option value function, while it assumes only a numerical (but not a statistical) error and a state (but not a time) discretization. Parallel computing is used to speed up the model resolution and enhance its overall efficiency. To support our construction, we evaluate American options, which are subject to market risk, and exchangeable bonds, which are subject to default risk.

The motivation for this research was the desire to disclose the social nature of the financial risks of global companies: the authors attempted a scientific explanation of the influence of corporate social responsibility, which is manifested through the preservation and creation of additional jobs, on the financial risks of global companies. The research aims to establish the interdependence between financial risks and sustainable employment in global companies. This goal is achieved using the SEM (structural equation modeling) method based on corporate statistics from the Fortune “Global 500” rankings for 2021–2023. As a result, the consequences of global companies’ CSR (corporate social responsibility) practices in personnel management and financial risk management are modeled and described through quantitative and qualitative patterns. The established regularities proved that for developed and developing countries, the larger the number of employees, the lower the financial risks of global companies—the risk of a decrease in profitability, the risk of loss of profit, and the risk of depreciation of assets. The main conclusion is that there is a close systemic relationship between the financial risks of global companies and their workforce size, suggesting that CSR is key to highly effective financial risk management. A clear distinction between the practices of financial risk management through CSR in developed and developing countries forms the basis of the theoretical significance of the research results. The authors provide recommendations to improve the current practice of financial risk management in global companies by integrating it more closely with personnel management practices, highlighting their managerial relevance. It is proposed that corporate strategies for global companies in developed countries should focus on reducing the risk of declining profitability, as CSR has the most pronounced and consistent impact on this particular financial risk. In developing countries, corporate strategies are recommended to be structured by diversifying the areas of CSR application, with the most promising in financial risk management being the reduction in asset depreciation risk and the reduction in profitability risk. The findings of this research have practical significance because they enhance the predictability of CSR activities of global companies and open up opportunities for highly accurate forecasting of the financial risk implications of ensuring sustainable employment by global companies, considering the specificities of developed and developing countries.

This work provides an economic exploration of the multifaceted world of medical malpractice risk. Third party liability insurance plays a central role in protecting healthcare providers and public care institutions from the financial consequences of medical malpractice claims, although in recent years, the industry landscape has been characterised by periods of distress for this type of protection, with rising litigations and reimbursement costs, resulting in a peculiarly complex market. For the Italian context, the study focuses on the financial repercussions for healthcare institutions of the growing trend towards risk retention practises, legally empowered by the introduction of Law No. 24/2017. The analysis employs Generalised Linear Models for the regressive approach to incorporate the structural and organisational characteristics of hospitals and uses quantitative simulations to explore different scenarios at a regional aggregate level. Due to the limited existing literature and data on the topic, this research aims to provide new methods for effectively understanding and managing this type of risk, thereby supporting decision-making processes in the healthcare sector.

This systematic literature review (SLR) explores the role of community-based catastrophe insurance (CBCI) as a tool for sustainable economic loss risk mitigation. Utilizing bibliometric analysis and a literature review, this study aims to reveal the methods employed in CBCI schemes from a novel perspective, highlighting their effectiveness in mitigating catastrophe risks. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology was employed to systematically collect and analyze articles sourced from the Scopus, ScienceDirect, and Dimensions databases. The findings provide a comprehensive summary of the CBCI implementation, including various considerations such as risk-sharing mechanisms, premium determination, and policy frameworks. This research offers a fresh perspective on CBCI as a sustainable approach to catastrophe risk mitigation, contributing valuable insights to policymakers, practitioners, and researchers interested in community resilience and disaster risk management.