J. Risk Financial Manag., Volume 16, Issue 3 (March 2023) – 72 articles

Over the last decade, social media (SM) has dramatically influenced the tourism sector, and information exchange via SM platforms may affect tourists’ intentions to revisit a tourist destination. In the present study, we investigated the impact of content shared on SM on tourists’ intentions to revisit Saudi Arabia as a neighboring destination to Qatar during the period of a mega-event (Football World Cup). We also assessed the potential mediation effects of the perceived values and trust in local tourism services on such a relationship. A structured survey was distributed to football fans who came to visit Saudi Arabia (n = 300), and a partial least squares structural equation model was constructed to validate this study’s model. Results showed that SM content did not significantly impact the revisit intentions directly. SM content was a significant antecedent predictor of the perceived trust, and the perceived trust predicted future intentions to revisit Saudi Arabia. Therefore, the perceived trust in tourism services was a significant mediator of tourism SM’s effects on tourists’ intentions. However, the mediation path of the perceived value was not statistically significant. Tourism marketers had to ensure that they appropriately convey engaging content that focuses on supporting the trust in a destination, particularly during the periods of mega-events. Full article

The application of blockchain technology in the field of environmental economics is still in its inception so it is not sufficiently used in a holistic and integrated life cycle sustainability assessment (HILCSA). The capability of the blockchain to provide a verifiable and transparent record can make it a good tool in environmental economics for an agile reflection in doing business and production. The research is focused on the advantages and challenges in the inclusion of blockchain technology into a holistic life cycle assessment. Based on the existing possibilities of using blockchain technology in environmental economics and life cycle assessments (LCAs), a framework and a model for applying the blockchain in the holistic life cycle sustainability assessment are proposed. A Design Science methodology was used as a research strategy. Particular emphasis in this paper is put on risk management when integrating blockchain methodologies through environmental economics into the life cycle sustainability assessment (LCSA) in order to use all the advantages of the blockchain technology optimally. Full article

Two modifications of a modern theory of capital structure—the Brusov–Filatova–Orekhova (BFO) theory—with variable income are considered: (1) with the income tax payments at the end of periods and (2) with advance income tax payments. BFO formulas for the WACC, and for company capitalization, V, were derived for these two cases. Using the obtained formulas, the dependence of the weighted average cost of capital, WACC; the discount rate; WACC–g (here, g, is the growth rate); company value, V; and the equity cost, ke, on the leverage level, L, at different values of g, at different values of the debt capital cost, kd, and at different values of company age, n, were studied. Comparing the results for cases (1) and (2) shows that case (2) is always preferable for both the company and the regulator. Recommendations have been developed for both parties to expand the practice of advance income tax payments. The managerial implications are as follows. Companies may choose to pay income tax either in advance or at the end of the reporting period in accordance with current results and tax laws. The developed methodology makes it possible to study companies with growing profits and companies with falling profits, which is very important in practice. It also allows the study of companies for which profits could rise and fall in different periods. Full article

This paper examines how the initiation of credit default swap (CDS) trading affects the product market competition faced by the referenced firms in the US. The trading of CDS provides an avenue for creditors to hedge default risks, thereby weakening the incentives to monitor the borrowers. Our paper shows that the trading of CDS increases firm-level product market competition because a reduced creditor monitoring effect can lead to growing shareholder demand for information disclosure, revealing strategic information that may undermine the product market competency of the firm when disclosed. While prior literature shows that CDS-traded firms increase both the likelihood and frequency of earnings forecasts as a direct response to shareholder demand, we observe that firms made their mandatory disclosure (i.e., Form 10-K) less readable as a potential way to reduce strategic disclosure. We also find that the presence of institutional investors generally reduces a firm’s competition, but this positive effect is overturned in the presence of CDS trading. Full article

The importance of data assets as intangible corporate assets is being emphasized as more business activities based on digital technology are being carried out. This study proposes the development of a data valuation model that can enable companies to use data assets as collateral for loans in financial transactions. To this end, a model was designed with a focus on the cost approach, which is less likely to involve arbitrariness and error among other valuation model approaches. Furthermore, a model simulation was conducted after securing transaction data of a Korean secondhand marketplace provider. Among the total costs of this marketplace provider, the cost of using data reflecting the ratio of data activities was derived, focusing on financial statements and tangible and intangible assets for the last five years. The data asset acquisition costs were derived, and the data replacement costs were calculated by reflecting the past price and wage growth rates. The results revealed that simulation companies could use a total of KRW 26.8 billion worth of data as collateral for a loan. Accordingly, the data valuation model developed in this study will contribute to reinforcing the value of corporate data assets and proposing a new means of corporate financing. Full article

This study aimed to examine the impact of enterprise risk management (ERM) on the firm performance of capital markets in developing nations such as Iran, Saudi Arabia, and Iraq. In order to achieve the study’s primary purpose, the economic environments of Iran, Iraq, and Saudi Arabia, three neighboring and developing nations, were examined from 2012 to 2019. The hypotheses were tested using panel regression analysis. According to the data, ERM might boost the return on assets and lower the total assets of Iranian enterprises while raising the total assets of Iraqi firms. In addition, the data demonstrated that ERM decreased sales growth and boosted net profit margins in Saudi Arabian companies. ERM enhanced the return on assets in Iranian enterprises and sales growth in Saudi Arabian firms while lowering sales growth in Iraqi firms. In addition, it was shown that total asset turnover increased in non-fraudulent Iranian companies but fell in their Iraqi counterparts. The outcomes of this study revealed substantial evidence regarding the financial conditions and performance of companies operating in emerging nations. As a result, it can be inferred that ERM efficiency and firm performance can be influenced by the firm’s nature and structure, as the findings in these three economic environments were fundamentally distinct. This research contributed to the literature on ERM as one of the essential elements influencing business performance in emerging economies with varying capital market laws. In addition, the literature and acquired data demonstrate the scope of fraud and its influence on the performance of businesses in developing nations. Full article

This paper examines the use of the return on gold instead of treasury bills in empirical asset pricing models for the US equity market. It builds upon previous research on the safe-haven, hedging, and zero-beta characteristics of gold in developed markets and the close relationship between interest rates, stock, and gold returns. In particular, we extend this research by showing that using gold as a zero-beta asset helps to improve the time-series performance of asset pricing models when pricing US equities and industries between 1981 and 2015. The performance of gold zero-beta models is also compared with traditional empirical factor models using the 1-month Treasury bill rate as the risk-free rate. Our results indicate that using gold as a zero-beta asset leads to higher R-squared values, lower Sharpe ratios of alphas, and fewer significant pricing errors in the time-series analysis. Similarly, the pricing of small stock and industry portfolios is improved. In cross-section, we also find improved results, with fewer cross-sectional pricing errors and more economically meaningful pricing of risk factors. We also find that a zero-beta gold factor constructed to be orthogonal to the Carhart four factors is significant in cross-section and helps to improve factor model performance on momentum portfolios. Furthermore, the Fama–French three- and five-factor asset pricing models and the Carhart model are all improved by these means, particularly on test assets which have been poorly priced by the traditional versions. Our results have salient implications for policymakers, governments, central bank rate-setting decisions, and investors. Full article

Bayesian inference has gained popularity in the last half of the twentieth century thanks to the wider applications in numerous fields such as economics, finance, physics, engineering, life sciences, environmental studies, and so forth. In this paper, we studied some key benefits of Bayesian inference and how they can be used in predicting loan default in the banking sector. Various traditional classification techniques are also presented to draw comparisons primarily in terms of the ease of interpretability and model performance. This paper includes the use of non-informative priors to attempt to arrive to the convergence of posterior distribution. Finally, with the Bayesian techniques proven to be an alternative to the classical approaches, the paper attempted to demonstrate that Bayesian techniques are indeed powerful in financial data analytics and applications. Full article

Adding pictures to instructional materials that are relevant and representational supports meaningful learning. However, it is not always straightforward to generate such pictures, for example, for abstract concepts. It is much easier to make representational pictures of concrete concepts, “table” or “chair”, compared to abstract concepts, “loyalty” or “democracy”. The field of finance is full of abstract or complex financial concepts, such as pension, market value, and asset valuation—to name a few. How do we then make pictures of such financial concepts that can represent them? In this regard, visual metaphors could provide hints as to how complex financial concepts can be presented in the form of pictures. For this purpose, this study analyzed the representation of complex financial concepts in terms of visual metaphors. Visual metaphors of five financial concepts were selected from the financial learning content online. These included: (1) risk diversification, (2) inflation, (3) compound interest, (4) time value of money, and (5) financial risk. Using the content analysis approach, each of the visual metaphors were analyzed to determine how different features of the given financial concept were mapped onto the visual metaphor, making them representational. Results indicate that visual metaphors could be an effective and creative way to present complex financial concepts in the form of representational pictures. Full article

The research objective of this article is to train a computer (agent) with market information data so it can learn trading strategies and beat the market index in stock trading without having to make any prediction on market moves. The approach assumes no trading knowledge, so the agent will only learn from conducting trading with historical data. In this work, we address this task by considering Reinforcement Learning (RL) algorithms for stock portfolio management. We first generate a three-dimension fuzzy vector to describe the current trend for each stock. Then the fuzzy terms, along with other stock market features, such as prices, volumes, and technical indicators, were used as the input for five algorithms, including Advantage Actor-Critic, Trust Region Policy Optimization, Proximal Policy Optimization, Actor-Critic Using Kronecker Factored Trust Region, and Deep Deterministic Policy Gradient. An average ensemble method was applied to obtain trading actions. We set SP100 component stocks as the portfolio pool and used 11 years of daily data to train the model and simulate the trading. Our method demonstrated better performance than the two benchmark methods and each individual algorithm without fuzzy extension. In practice, real market traders could use the trained model to make inferences and conduct trading, then retrain the model once in a while since training such models is time0consuming but making inferences is nearly simultaneous. Full article

This paper empirically tests the determinants of closed-end fund (CEF) prices by employing cointegration and error-correction modeling with an advanced ARDL framework. Since CEF shares generally trade at discounts to their net asset value (NAV), we modeled CEF prices, including volatility and economic policy indices along with their NAVs. The present study consists of 31 monthly frequency CEF discount data from January 1999 to April 2018 and economic policy uncertainty (EPU) with ten subindices. This paper finds evidence for cointegration in many of the series and statistically significant coefficients in the short- and long-run estimates of the included subindices. Full article

This study aims to investigate the effect of mergers and acquisitions (M&A) on shareholders’ wealth. Additionally, this study investigates the impact of the economic crisis during 2007–2008 on the shareholders’ perceptions of gaining additional value from mergers and acquisitions. In this paper, a sample of 84 M&As from 2006 to 2015 in Greece are studied to investigate the effect on shareholders of bidder companies. We find significantly negative abnormal returns just before the announcement of M&A, which negatively affects the bidder firms’ value. It is also observed that after 2009 M&A cases decreased, maybe because of the crisis in Greece that changed the investors’ perception of a value-destroying event. Companies that engage in M&A activities during economic downturns tend to experience a decline in shareholder value. This could be due to various factors, such as increased uncertainty and risk associated with such activities during economic uncertainty. By understanding the potential impact of such activities on shareholder value, companies can make more informed decisions about whether and when to pursue M&A opportunities. Full article

This article focuses on risks while supporting creativity. This represents a knowledge gap that is addressed. The employees’ creativity is desired, but there is often no approach process to its support. The implementation is affected by risks needed to be managed. The aim was to create a mechanism for managing risks within the support of creativity in organizations, including commercial companies and others, e.g., sports clubs. Content analysis, case studies, questionnaire surveys, or models were applied. The results combined secondary (cases) and primary data (survey with two groups of respondents). The findings showed that when creativity is supported, people are willing to increase their performance (50% of academicians, 88.78% of students). The process is negatively affected by the lack of managerial skills and the interconnectedness of processes. Organizations should increase their managers’ skills. A proactive approach to risk prevention leads to continuous improvement. A procedure was selected when the potential of applying findings from the academic environment to other organizations was identified. A generalization of the findings was performed so that the research results can be applied in different environments after considering their specificities. The recommendations include the process for supporting creativity, the identification of risks, and the risk management mechanism. Full article

Cash ownership emits a powerful positive signal. We examine four sources of cash in firms, i.e., cash flows, cash holdings, cash proceeds from debt, and cash proceeds from equity. We examine the effects of cash ownership for firms growing by disruption, and firms growing by acquisition. Information signaling theory maintains that free cash flows may be used to increase shareholder wealth. Two-stage least squares regressions determined the impact of cash funding on disruptors and size of acquisition in the first stage, and cash-funded disruption or cash-funded acquisition in the second stage, for a US sample of 832 disruptor firms and 924 acquirers, from 2000–2020. Disruptions funded by cash holdings, cash flow, and cash proceeds from debt, significantly increased stock returns. A size effect was observed, with small disruptors showing significant effects. Acquisitions funded by cash holdings, cash flow, and cash proceeds from debt, significantly increased stock returns and return on assets. Agency costs significantly reduced returns and profits. Results for disruptions and acquisitions support signaling theory with free cash flows signaling higher share prices for both disruptors and acquirers, and higher profits for acquirers. Full article

Cultural heritage is a particularly significant resource in creating tourism. When a local community recognizes its cultural heritage (small historic towns, buildings, castles, and forts), it is possible to create new value to meet the needs of tourists, using the principles of a circular economy. Adapting, reusing and restoring heritage sites can contribute to the revitalization of the local economy by creating jobs (increased employment), increased spending, economic development, etc. Adaptive reuse, as one of the principles of a circular economy, represents how the circular economy can pave the way to create new tourism products. The three basic principles of sustainable waste management are reduce, reuse, and recycle (3R). This paper tackles the reuse principle by analyzing case studies involving the application of a circular economy to cultural heritage in the Kvarner tourism destination (Croatia) in the context of reusing resources to create a sustainable destination. The goal is to determine to what extent the reuse of heritage sites makes them useful for the local community, and for tourists to stay in the destination. The research showed positive examples in the Kvarner tourism destination, primarily of a cultural tourism nature and that were achieved in the last ten years; however, the conclusion is that this is still insufficient. By aggregating knowledge and research results, the paper emphasizes the importance of applying the concept of the circular economy to cultural heritage in tourism destinations, with special emphasis on the role of all stakeholders in creating sustainable heritage tourism (local self-government, destination management, local population, and entrepreneurship). Full article

The present study investigates the effect of business ethics on happiness, aggression and inconsistency of effort and reward of auditors in Iran and Iraq. The statistical population of the present study includes all partners, managers and auditors working in audit institutions in Iran and partners of the audit institutions, assistant auditors, auditors, individual second rank and individual first rank, with a total of 365 questionnaires completed by Iranian respondents out of 450 questionnaires and 250 questionnaires completed by Iraqi respondents out of 350 questionnaires, a total of 615 questionnaires from the two countries in 2022. Also, the methods of variance analysis and ordinary least squares regression and Smart PLS 3 and Stata 15 software were used to analyze the data and test the hypotheses. The results from testing this research’s hypotheses indicate a negative and significant relationship between business ethics and aggression, effort-reward mismatch and a positive and significant relationship between business ethics and happiness. Since the current research was conducted in the emerging financial markets of Iran and Iraq, which are highly competitive, along with having special economic conditions, and since the occupation of the ISIS terrorist group, the civil wars in Iraq, severe world economic sanctions against Iran and the global crisis of Covid-19 in Iran and Iraq have led to special conditions, the current research can bring helpful information to readers and help the development of science and knowledge in this field. Full article

In a default event, several obligors simultaneously experience financial difficulty in servicing their debt to the point where the entire market can experience a sudden yet significant jump to a credit default. To help protect lenders against a jump-to-default event, regulators require banks to hold capital equivalent to the default risk charge as a buffer against the losses they may incur. The Basel regulatory committee has articulated and set default risk modelling guidelines to improve comparability amongst banks and enable a consistent bank-wide default risk charge estimation. Emerging markets are unique because they usually have illiquid markets and sparse data. Thus, implementing an emerging market default risk model and, at the same time, complying with the regulatory guidelines can be non-trivial. This research presents a framework for modelling the default risk charge in emerging markets in line with the regulatory requirements. The default correlation model inputs are derived and empirically calibrated using emerging market data. The paper ends with some considerations that regulators, supervisors, and banks can use to get financial institutions to adopt an emerging markets default risk charge model. Full article

The impact of the climate change response on the labour market is an important question for policymakers, while the net positive effect of green policies on the labour market is seen as one of the arguments in favour of a green transition. This is particularly important for the tourism labour market, which was severely hit by the COVID-19 pandemic. This study examined the effect of carbon taxes on tourism employment for European countries that have levied a carbon tax over the past thirty years. A macroeconomic panel data regression model ex-post study was applied by contrasting the obtained results via a robustness check. The estimation results indicate a slightly positive and significant association between the carbon tax and tourism employment, which was additionally tested by considering revenue recycling, early adopters of the carbon tax, and a higher carbon tax compared to countries with a lower carbon tax. We cannot conclude that these factors matter for tourism employment, proving the robustness of the results. Revenue-neutral carbon taxation, policies to address the skills gap, push and pull incentives, and active labour market policies to facilitate the quick re-integration of jobseekers into employment are viewed as pivotal to ensure a smoother transition toward a sustainable tourism labour market. Full article

It has been recognized that volatility in commodity markets fluctuates significantly depending on the demand–supply relationship and geopolitical risk, and that risk and financial management using multivariate derivatives are becoming more important. This study illustrates an application of multi-layered neural networks for multi-dimensional Bermudan option pricing problems assuming a multi-asset stochastic volatility model in commodity markets. In addition, we aim to identify continuation value functions for these option pricing problems by implementing smooth activation functions in the neural networks and evaluating their accuracy compared with other activation functions or regression techniques. First, we express the underlying asset dynamics using the multi-asset stochastic volatility model with mean reversion properties in the commodity market and formulate the multivariate Bermudan commodity option pricing problem. Subsequently, we apply multi-layer perceptrons in the neural network to represent the continuation value functions of Bermudan commodity options, wherein the entire neural network is trained using the least-squares Monte Carlo simulation method. Finally, we perform numerical experiments and demonstrate that applications of neural networks for Bermudan options in a multi-dimensional commodity market achieve sufficient accuracy with regard to various aspects, including changing the exercise dates, the number of layers/neurons, and the dimension of the problem. Full article

This research examines the capital budgeting practices used by small and medium-sized firms (SMEs) in two Portuguese industries, footwear and metalworking, aiming at answering the following research questions: How much knowledge do managers have about capital budgeting practices? What are the most used practices? How much importance do they attribute to applying them? The research was conducted through an online survey with a response rate of 14.9%. The results document that most companies in both industries are familiar with capital budgeting practices, despite differences between the two. The footwear industry recognizes the importance of these indicators but makes little use of them, and many companies prefer using payback period (PBP). The metalworking industry, on the other hand, makes greater use of capital budgeting practices, with net present value being the favored indicator and PBP being used as supplementary. This study contributes to the capital budgeting literature in two ways: first, by focusing on SMEs instead of only large firms, and second, by exploring data from two industries rather than multiple, heterogeneous industries. Full article

This study revisits the widely researched area of the consumption function using Bayesian Model Averaging (BMA) for a panel of EU countries to deal with the uncertainty of potential determinants, using the convergence club analysis to construct homogeneous groups by income. BMA suggests that income is the only variable that is found to be a strong determinant across different country groups, whereas other variables have varying importance for different country groups. Full article

In this research paper, the impact of macroeconomic uncertainty on stock returns in the United States of America is examined. To measure this macroeconomic uncertainty, a survey of Consensus Economics with data ranging from 1989 until 2019 was employed. The survey consists of monthly forecasts for several macroeconomic variables for multiple countries. Four uncertainty measures were developed, based on the standard deviation, interquartile range, high-minus-low and an AR- and GARCH model. By performing linear regressions, a positive relationship between macroeconomic uncertainty and stock returns was identified for, on average, 13 out of 49 sectors, which is consistent with economic theory. Furthermore, the standard deviation of stock returns was regressed on macroeconomic uncertainty. A positive relationship was found for, on average, 41.7 out of 49 sectors. The results are discussed at a general level, at the level of the macroeconomic variables and at the sector level. Full article

Fundamentally, the term premium in long-term nominal yields is compensation to investors for bearing interest rate risk. There is substantial evidence of sizable and time-varying term premia. As opposed to yields, term premia are not directly observable. In this paper, we estimate term premia in Norwegian interest rate swaps from a set of dynamic term structure models, covering the period from 2001/04 until 2022/06. In line with international studies, we find evidence of declining term premia over the sample period. Furthermore, our estimates indicate that term premia have been close to zero, as well as negative in periods, during the last decade of global extraordinary monetary policy measures. We find that the recent rise in Norwegian interest rate swaps is partly caused by increases in term premia. From a practitioner’s perspective, our term premia estimates can be utilized as part of applied management of both investment and debt portfolios. Full article

Progress on asymmetric correlations of asset returns has recently advanced considerably. Asymmetric correlations can cause problems in hedging effectiveness and overstate the value of diversification. Furthermore, considering the asymmetric correlations in portfolio construction significantly enhances performance. The purpose of this paper is to trace developments and identify areas that require further research. We examine three aspects of asymmetric correlations: first, the existence of asymmetric correlations between asset returns and their significance tests; second, the test on the existence of asymmetric correlations between different markets and financial assets; and third, the root cause analysis of asymmetric correlations. In the first part, the contents of extreme value theory, the H statistic and a model-free test are covered. In the second part, commonly used models such as copula and GARCH are included. In addition to the GARCH and copula formulations, many other methods are included, such as regime switching, the Markov switching model, and the multifractal asymmetric detrend cross-correlation analysis method. In addition, we compare the advantages and differences between the models. In the third part, the causes of asymmetry are discussed, for example, higher common fundamental risk, correlation of individual fundamental risk, and so on. Full article

We generalize the naive estimator of a Poisson regression model with a measurement error as discussed in Kukush et al. in 2004. The explanatory variable is not always normally distributed as they assume. In this study, we assume that the explanatory variable and measurement error are not limited to a normal distribution. We clarify the requirements for the existence of the naive estimator and derive its asymptotic bias and asymptotic mean squared error (MSE). The requirements for the existence of the naive estimator can be expressed using an implicit function, which the requirements can be deduced by the characteristic of the Poisson regression models. In addition, using the implicit function obtained from the system of equations of the Poisson regression models, we propose a consistent estimator of the true parameter by correcting the bias of the naive estimator. As illustrative examples, we present simulation studies that compare the performance of the naive estimator and new estimator for a Gamma explanatory variable with a normal error or a Gamma error. Full article

This research paper aims to evaluate the effectiveness of internal audit standards as a foundation for carrying out and promoting a wide variety of value-added tasks in emerging markets. Three Jordanian telecommunications firms were the subject of the study. In each firm, the non-executive directors, who serve on the Audit Committee, also received a questionnaire that was designed for this objective. In total 85 questionnaires were accepted and analyzed using traditional statistical methods such as descriptive statistics, arithmetic means, standard deviations, and percentages, and resolution data were examined using the statistical application SPSS. According to the annual report for the year 2021, telecommunication businesses generally followed IIA International Internal Audit Standards. Application Standards were employed to a high degree in second place, after Attribute Standards, which were used primarily in the first place. In those firms, performance standards were not used. The study also found that this form of application is moderately constrained by a few challenges and barriers. The study recommended that these organizations broaden the scope and scale of internal auditing standards, particularly performance requirements. Finally, the generalization of research findings is limited because the study is limited to three Jordanian telecommunication companies. Full article

The blue bond market has emerged as one of the latest additions in the sustainable debt market. Its goal is to channel funding toward sustainable blue economy projects related to the ocean and freshwater. While the protection of hydric resources has gained importance within the problem of climate change, Sustainable Development Goals linked to water remain the most underfunded. Since the issuance of the first blue bond in the Seychelles in 2018, multiple public and private organizations have turned to the blue bond market to raise funds. However, unlike the green bond market, no comprehensive market overview exists, preventing stakeholders from judging whether this label has been effective in protecting water resources and drawing conclusions on its future potential. This paper draws on an extensive review of academic research and complements it with a unique and comprehensive analysis of blue bonds issued to date, providing a contribution to the literature on sustainable finance. Between 2018 and 2022, 26 blue bond transactions took place, amounting to a total value of USD 5.0 billion, with a 92% CAGR between those years. Currently, blue bonds represent less than 0.5% of the sustainable debt market. The use of proceeds has mostly focused on waste management, biodiversity, and sustainable fisheries, but also ranges across other areas of the sustainable blue economy. Only two-thirds of blue bond issuers report on impact metrics, providing further opportunity to add detail and rigor. We draw comparisons to the more mature green bond market and conclude that a lack of standardized definitions, metrics, and expertise by issuers and investors are significant barriers to the blue bond market. Resolving these barriers is crucial to attract corporations and ensure continued growth of the blue bond market. Full article

The main objective of this article is to determine the internal factors of maritime transportation accidents using a comprehensive approach through robust regression and Gaussian/mixed-Markov graphical models. Globally, this could be a strong incentive for the employees to negotiate higher compensation and for the insurance companies to impose higher premiums to cover the risk for these kinds of accidents. The article uses a dataset consisting of 166 real cases (human injuries) in the period 2014–2022 in different ships owned by a shipping company indexed in the New York Stock Exchange. The results of the study support the hypotheses as have been set in the article, connecting the internal factors with the injuries of any type. The practical implementation of the study is its ability to be used by policy makers in shipping to compensate employees depending on the risk of their work on board and at the same time to calculate the insurance premiums in a more accurate way. The originality of the research lies in the fact that this is a unique study in maritime transportation related to human accidents and not on ship or cargo casualties. The idea came from the results of another study conducted on a bibliometric analysis of the factors related to maritime transportation accidents. The findings of the current study can provide valuable insights to stakeholders and shipping planners in formulating effective policies for better wage packages and insurance premiums. Full article

This paper examines the systematic contagion effects of the global financial crisis of 2007–2009 on the world’s largest advanced and emerging equity markets, using the conditional factor model of Dungey and Renault (2018) and and the adjusted correlation coefficient approach of Forbes and Rigobon (2002). Our findings indicate that when applying the Forbes and Rigobon approach, no evidence of contagion is found, while using the conditional factor model, we observe significant evidence of contagion in the aggregate equity markets of both advanced and emerging markets. Furthermore, the results from the conditional factor model suggest that the structural relationship across the financial sectors of advanced and emerging markets was significantly disrupted during the crisis period. Full article

Financial well-being is a key component of quality of life and overall well-being and is likely to affect other aspects of quality of life, such as health and health care. The COVID-19 pandemic presents an immense crisis of financial well-being among low-income entrepreneurs and has left many small-scale entrepreneurs financially fragile. We argue that promoting the financial capability of low-income entrepreneurs is effective in protecting their financial well-being from a crisis. To examine the association between financial capability and the financial well-being of low-income entrepreneurs, we use the 2016 National Financial Well-Being Survey, which provides the latest and comprehensive measurement of financial capability, including financial knowledge, financial skills, and access to financial products and services. Our analyses show that, compared to their higher-income counterparts, low-income entrepreneurs have statistically lower levels of financial well-being, financial knowledge, financial skills, and access to mainstream financial products; they also have a statistically higher risk of using high-fee alternative financial products. In addition, low-income entrepreneurs have larger barriers to accessing mainstream financial products than low-income non-entrepreneurs. The results indicate that financial capability plays a significant role in promoting the financial well-being of low-income entrepreneurs. Full article