J. Risk Financial Manag., Volume 14, Issue 11 (November 2021) – 62 articles

Unintended bias against protected groups has become a key obstacle to the widespread adoption of machine learning methods. This work presents a modeling procedure that carefully builds models around protected class information in order to make sure that the final machine learning model is independent of protected class status, even in a nonlinear sense. This procedure works for any machine learning method. The procedure was tested on subprime credit card data combined with demographic data by zip code from the US Census. The census data serves as an imperfect proxy for borrower demographics but serves to illustrate the procedure. Full article

In this paper, we offer a novel contribution to Islamic accounting literature by examining the determinants of Investment Account Holder (IAH) disclosure in Islamic banks’ annual reports. Using data from Islamic banks around the world, our regression analysis shows that the level of IAH funds, the return on IAH funds, adoption of AAOIFI standards, liquidity level, bank size and ownership have a positive significant relationship with IAHs’ disclosure level. Our findings can be useful for IAHs, regulatory bodies and information users in general as they help them to understand IAH practices in Islamic banks and the main incentives of managers to disclose IAHs’ information. The present study offers an original contribution to the Islamic accounting literature as it is the first one—to the best of our knowledge—that investigates the relationship between the specificities of Islamic banks and the extent of IAH disclosure. Full article

Presently, there is a growing concern about implementing sustainable practices among businesses worldwide. Risk management is observed to contribute to the promotion of exercised business sustainability significantly. The study aims to examine published articles focusing on the role of risk management in promoting business sustainability practices and its advancement in the Cambridge online database to determine the current trend direction of this field. The paper’s conducted analysis is based on bibliographic co-word clustering analysis of the collected studies from the database. The research’s output disclosed four keyword clusters in the gathered articles’ titles and identified the most interested journals, countries, authors, subject areas, and organizations in the said topic and its popular research period. Based on the research output, recommendations regarding future research were provided, including expanding the list of databases for the data collection phase and utilizing the bibliographic coupling relations approach in the bibliometric analysis. Full article

US crop insurance is subsidized to encourage producers to participate and reduce their risk exposure. However, what has been the impact of these subsidies on insurance demand and crop acres planted? Using a simultaneous system of two equations, we quantify both insurance participation and acreage response to subsidized crop insurance for cotton-producing counties across the US at the national and regional levels. We also quantify the impact of both the realized rate of return and the expected subsidy per pound, plus the combined effects of expected yield and price while accounting for the adoption of Bacillus thuringiensis (Bt) technology and other factors. Results show that both the rate of return and the expected subsidy per unit of production have a statistically significant and positive effect on the percentage of arable acres planted. Furthermore, the marginal effect of expected price on insurance participation is much more significant for low- than high-yield counties. Results indicate that not all regions respond the same to subsidized crop insurance and that subsidies should be based on dollars per expected unit of production rather than expected production to be less distorting. Overall, US cotton acreage response is estimated to be inelastic (0.58) to insurance participation. Full article

Efforts are being exerted in many developing countries to promote financial inclusion by increasing individuals’ access to financial products and services. However, literature suggests that increasing the supply of financial products and services per se may not help in expanding financial inclusion unless concerted efforts are exerted in enhancing financial literacy. This is because financially literate individuals are more likely to appreciate the value of financial services and hence take up financial products. This paper reports the link between financial literacy and inclusion using data from a demand side financial inclusion survey conducted in Kenya and Tanzania in 2016 covering a total of 6029 individuals. Results from our instrumental variable regression analysis confirmed that financial literacy is a strong driver of financial inclusion. This implies that efforts to promote financial inclusion need to be accompanied with financial literacy campaigns in both countries. Full article

In this paper, we examined the changes in volatility overflow among the exchange rate of the Japanese yen (JPY), the Nikkei Stock Average (Nikkei), the Tokyo Stock Price Index (TOPIX) and the TOPIX sectoral indices for the period of 10 February 2016 to 24 March 2017. We employed the exponential generalised autoregressive conditional heteroscedasticity (EGARCH) model, the cross-correlation function, and the daily logarithmic returns of JPY, Nikkei, TOPIX and the TOPIX components with a weight of 5% and more in estimations (banks, chemicals, electric appliances, information and communication, machinery and transportation equipment indices). The findings highlighted causality in variance (volatility spillover) among the variables. We revealed that volatility could also spread indirectly among the variables (from one variable to another through a third variable). We demonstrated how the impact of news about the results of the Brexit referendum (BR) and the United States presidential election (USE) in 2016 might spread among the variables indirectly within a week. Full article

This aim of this work is to study the relationship between foreign direct investment (FDI) and trade. FDI is a driving force for economic growth for host countries. The positive effects of FDI are seen in many aspects of the economy. However, the implications of FDI on foreign trade are questionable. Therefore, this study uses a Granger causality technique to test whether the relationship between FDI and foreign trade is complementary or substitutive. The findings of this study indicate that this relationship appears to be complementary, and FDI investment does cause an increase in trade flow in the countries that are taken into consideration. This research aims to make a comparison between the relations of FDI flows of three groups of countries from the European Union (EU)—Romania and Bulgaria, the Visegrád Group and the Euro area—for the period of 2005 to 2019. However, the results indicate that this link between the variables is not yet found for the three group of countries, and further research is required in this aspect. This leads to the conclusion that the FDI impact on foreign trade of the host country depends on the type of investment and absorptive capacity of the receiver, the economic development of host and home countries, and not every type of FDI leads to more trade. Full article

The onset of the COVID-19 pandemic and lockdown announcements by governments have created uncertainty in business operations globally. For the first time, a health shock has impacted the stock markets forcefully. India, one of the major emerging markets, has witnessed a massive fall of around 40% in its major stock indices’ value. Therefore, we examined the short-term impact of the pandemic on the Indian stock market’s major index (NIFTY50) and its constituent sectors. For our analysis, we used three different models (constant return model, market model, and market-adjusted model) of event study methodology. Our results are heterogeneous and largely depend on the sectors. All the sectors were impacted temporarily, yet the financial sector faced the worst. Sectors like pharma, consumer goods, and IT had positive or limited impacts. We discuss the potential explanations for the same. These results may be useful for investors in safeguarding equity portfolios from unforeseen shocks and making better investment decisions to avoid large, unexpected losses. Full article

The humanitarian sector has gone through a major shift toward injection of cash into vulnerable communities as its core modality. On this trajectory toward direct currency injection, something new has happened: namely the empowerment of communities to create their own local currencies, a tool known as Complementary Currency systems. This study mobilizes the concepts of endogenous regional development, import substitution and local market linkages as elaborated by Albert Hirschman and Jane Jacobs, to analyze the impact of a group of Complementary Currencies instituted by Grassroots Economics Foundation and the Red Cross in Kenya. The paper discusses humanitarian Cash and Voucher Assistance programs and compares them to a Complementary Currency system using Grassroots Economics as a case study. Transaction histories recorded on a blockchain and network visualizations show the ability of these Complementary Currencies to create diverse production capacity, dense local supply chains, and data for measuring the impact of humanitarian currency transfers. Since Complementary Currency systems prioritize both cooperation and localization, the paper argues that Complementary Currencies should become one of the tools in the Cash and Voucher Assistance toolbox. Full article

This paper reviews the up-to-date theoretical, empirical, and experimental literature related to the trading venue choice in the context of the fragmented equity markets. We provide a brief background on the history of trading fragmentation in the equity market and its determinants. We discuss the direct and indirect impacts of the market fragmentation on market quality in various dimensions, including liquidity, volatility, and price efficiency. Next, we identify possible determinants and channels from theoretical and empirical studies that could explain order routing decisions and present the possible directions for future research. Finally, we discuss the major regulatory reforms in the U.S. equity market on routing venue decisions. This topic is relevant in current times when phenomena such as “GameStop Frenzy” have drawn significant attention to commission-free trading venues. Full article

Risk capital or capital at risk (CaR) refers to the amount of capital set aside and maintained by banks to cover different types of risk. For banks, it is used as a buffer against claims or expenses in the event that ordinary capital is not enough to cover them. Thereby, risk capital can also be recognized as risk-bearing capital or surplus funds. Risk capital may generate very high costs, but on the other hand it protects against insolvency. That’s why a bank needs to find the ‘Gold mean’—the optimal value of risk capital that will not lower its efficiency, but still ensure financial security. The main objective of the study is identification of interdependencies between bank risk capital and effectiveness of the aggregated Eurozone banking sector and selected national banking sectors of the euro area. The paper tries to answer the research question whether the risk capital supports or lowers banks’ operational effectiveness. The adopted research hypothesis stated that there is a positive correlation between profitability and size of bank risk capital. To verify the hypothesis regression models were used. The results indicate that the size and structure of bank capital impact on the credit institutions’ effectiveness in the analyzed banking sectors, however with different intensity. Thereby, the article fulfils a research gap in the field of research studies that take into account how capital at risk and specific capital adequacy regulations may impact on a bank’s efficiency. Full article

We investigate the effects of adopting enterprise risk management (ERM) on the performance and risks of European publicly listed insurance firms. Using a dataset for 24 years, we report new results which show that ERM adopters realize significant ERM premiums after controlling for other covariates and endogeneity. Several firm characteristics such as size, opacity, and the choice of external monitoring agents such as auditors are significant determinants of adopting ERM. We fill a gap in the literature by assessing the impact of adopting ERM on firm risks and report new findings for our sample, which show that ERM adopters effectively reduce firm total and systematic risks and, to a greater extent, idiosyncratic risk. Firm-level variables such as size, leverage, dividend payments events, and diversification impact firm total risk. Insurers use corporate events such as dividend payments to signal information about reducing risk. Industry and international diversification reduce firm total risk and idiosyncratic risk, respectively. Full article

This paper examines the relationship between overconfidence and losses from under-diversification among Dutch investors. We find that a lack of proper portfolio diversification is positively associated with overconfidence. Part of this relationship is mediated through the lower propensity of overconfident individuals to hire a professional financial adviser. We use data from the 2005 wave of the DNB Dutch Household Survey that provides us with detailed portfolio data of 257 investors. We proxy for overconfidence by exploiting the difference between measured and self-assessed financial literacy, and use this proxy in a regression model (with and without mediation) to explain the difference between the actual households return and the return that could have been obtained by selecting a portfolio on the efficient frontier with equivalent risk. Our results contribute to the current discussion among policy makers on the role of financial advice and self-perceptions in household financial decision-making. Full article

We investigate the effect of geopolitical risk on the returns of firms in the Information Technology, Communication Services, and Consumer Staples sectors within the S&P 500 index. We use the event study methodology and perform more than 17,000 regressions to provide empirical evidence at sector level that geopolitical risk leads to different responses across these three sectors. The response of the Information Technology sector is negative for all event windows under study, except the one spanning 10 days prior to the geopolitical event and 10 days after. The Communication Services sector has positive returns as a result of geopolitical events for all event windows, except the one from the geopolitical event date and 5 days after. The Consumer Staples sector shows a negative impact on geopolitical risk for all event windows except the one from the geopolitical event date and 5 days after, demonstrating a negative correlation to the Communication Services sector. Full article

Using extensive and comprehensive databases to select a subset of research papers, we aim to critically analyze previous empirical studies to identify certain patterns in determining the optimal number of stocks in well-diversified portfolios in different markets, and to compare how the optimal number of stocks has changed over different periods and how it has been affected by market turmoil such as the Global Financial Crisis (GFC) and the current COVID-19 pandemic. The main methods used are bibliometric analysis and systematic literature review. Evaluating the number of assets which lead to optimal diversification is not an easy task as it is impacted by a huge number of different factors: the way systematic risk is measured, the investment universe (size, asset classes and features of the asset classes), the investor’s characteristics, the change over time of the asset features, the model adopted to measure diversification (i.e., equally weighted versus optimal allocation), the frequency of the data that is being used, together with the time horizon, conditions in the market that the study refers to, etc. Our paper provides additional support for the fact that (1) a generalized optimal number of stocks that constitute a well-diversified portfolio does not exist for whichever market, period or investor. Recent studies further suggest that (2) the size of a well-diversified portfolio is larger today than in the past, (3) this number is lower in emerging markets compared to developed financial markets, (4) the higher the stock correlations with the market, the lower the number of stocks required for a well-diversified portfolio for individual investors, and (5) machine learning methods could potentially improve the investment decision process. Our results could be helpful to private and institutional investors in constructing and managing their portfolios and provide a framework for future research. Full article

In asset management, the portfolio leverage affects performance, and can be subject to constraints and operational limitations. Due to the possible leverage aversion of the investors, the comparison between portfolio performances can be incomplete or misleading. We propose a procedure to unleverage the mean-variance efficient portfolios to satisfy a leverage requirement. We obtain a class of unleveraged portfolios that are homogeneous in terms of leverage, so therefore properly comparable. The proposed unleverage procedure permits isolating the pure allocation return, i.e., the return component, due to the qualitative choice of portfolio allocation, from the return component due to the portfolio leverage. Theoretical analysis and empirical evidence on actual data show that efficient mean-variance portfolios, once unleveraged, uncover mean-variance dominance relations hidden by the leverage contribution to portfolio return. Our approach may be useful to practitioners proposing to take long positions on “short assets” (e.g. inverse ETF), thereby considering short positions as active investment choices, in contrast with the usual interpretation where are used to overweight long positions. Full article

The European Commission has launched numerous recovery plans for Member States to try to mitigate the damage caused by COVID-19. The most important element of this program is the Recovery and Resilience Facility (RRF), which is worth EUR 672.5 billion in loans and grants. Seventy per cent of the RRF grants will be distributed between 2021 and 2022, with the remaining 30 per cent in 2023. The allocation of grants for the period 2021–2022 has been made according to different socioeconomic criteria. In this context, the aim of our work is to assess the recovery policies jointly developed by EU countries and to analyze which of the criteria adopted for the allocation of the grants included in the RRF for the period 2021–2022 has been most decisive in the distribution of these funds. In addition, we also examine whether other health indicators directly related to the pandemic can also be related to the amount of funding that EU countries will receive in this period by carrying out regression analysis. Our results show that the countries that will receive more RRF grants are those with larger populations, Gross Domestic Product (GDP) per capita and higher unemployment rates. Furthermore, it is noted that health criteria, as well as those of a socioeconomic nature, may be relevant in the allocation of recovery funds. In this way, our results can be the start of a debate in the literature on whether the socioeconomic criteria adopted in the distribution of these funds have been appropriate. or whether other criteria, such as those of a health nature, should have been taken into account. Full article

This paper studies the reaction of share prices in the Chilean securities market at the sectoral level to the arrival of COVID-19 in the country. The following question is answered: Did the Chilean market act efficiently before the arrival of COVID-19? To answer this question, an event study using a 10-day investment return window was applied to the industrial sectors that make up the IPSA (Selective Stock Price Index). To obtain the abnormal returns (AR) and cumulative abnormal returns (CAR) for the event window, three models were used: (1) adjusted average return, (2) adjusted market return, and (3) the market model. The results of the study show an overreaction to market losses, except in the utilities industry, causing greater losses after the event, which shows that information is slow to be incorporated in the previous stage and suggests that the prices of the assets do not reflect all the information available in the market. A significant finding is that the Chilean stock market responded inefficiently in the face of the arrival of the pandemic. This information is useful for investors in the formation of portfolios and/or investment strategies with a view to the long term. Full article

Affordable housing policy in the developed world has been undergoing a systematic commodification for several decades, including a push for homeownership as the normalized tenure and a commodity unto itself. Scholars suggest this push for homeownership is part and parcel of a neoliberal asset-based welfare to supplement, or even outright replace, traditionally defined benefit pension schemes. These policies individualize risk and re-fashion individual citizens as long-term financial planners, navigating the uncertainty inherent in international financial markets and general financial management. Less deeply explored, however, are the perverse incentives this system creates for homeowners to protect their home “investment” by leveraging planning policies, zoning, and land-use restrictions to preserve the community status quo and lock in the value of their home. In a policy environment in which long-term financial risk is individualized and public social welfare and pension systems are relegated to the smallest number of individuals possible, this type of NIMBYism (Not in My Backyard) is rather rational behavior, even as it simultaneously staunches the supply of new housing and drives up prices for non-homeowners. As such, this analysis synthesizes the existing research to make a formal theoretical connection between the neoliberal push for commodified housing, asset-based welfare, and the intractable political problem of NIMBYism. Full article

The results of empirical analyses confirm that analysed unsystematic factors, the Stock-to-Flow index (S2F), and information on the Bitcoin (BTC) are directly correlated with BTC values. These results are expected and in line with the economic theory; however, this research paper aimed to investigate the impact of unsystematic factors on the value of decentralised virtual cryptocurrency BTC. Its aim was also to analyse the reasons for significant oscillations of market values in relation to the S2F and S2FX model and thus confirm the reliability of these models in the estimation of BTC value. The research further confirms the strong influence of non-technical information directly linked with the BTC. The limitations of this paper are the lack of possibilities for examining the impact of non-technical information affecting the Bitcoin price deviation regarding the S2F model. In addition to all mentioned limitations, the research results indicate the relevance of the S2F and S2FX models and show a strong impact of (half) the information on the value of cryptocurrencies. Full article

Prior theory suggests a positive relation between volatility and market depth, while past empirical research finds contrasting results. This paper examines the relation between the volatility and the limit order book depth in commodity and foreign exchange futures markets during a turbulent time using the generalized method of moments (GMM). Results indicate a negative relation between volatility and depth and suggest that the depth in the limit order book decreases as volatility increases. Findings help to understand how market participants provide liquidity in response to shifts in prices. Full article

The goal of the paper is to present the framework for combining clustering and classification for churn management in telecommunications. Considering the value of market segmentation, we propose a three-stage approach to explain and predict the churn in telecommunications separately for different market segments using cluster analysis and decision trees. In the first stage, a case study churn dataset is prepared for the analysis, consisting of demographics, usage of telecom services, contracts and billing, monetary value, and churn. In the second stage, k-means cluster analysis is used to identify market segments for which chi-square analysis is applied to detect the clusters with the highest churn ratio. In the third stage, the chi-squared automatic interaction detector (CHAID) decision tree algorithm is used to develop classification models to identify churn determinants at the clusters with the highest churn level. The contribution of this paper resides in the development of the structured approach to churn management using clustering and classification, which was tested on the churn dataset with a rich variable structure. The proposed approach is continuous since the results of market segmentation and rules for churn prediction can be fed back to the customer database to improve the efficacy of churn management. Full article

I estimate the effect that growth in countries’ GDP per capita has on the growth rate of infrastructure. In order to extract exogenous variation in GDP per capita growth, I use the growth of the international oil price multiplied with countries’ GDP shares of oil net-exports as an instrumental variable. My instrumental variables estimates show that, for both democracies and autocracies, GDP per capita growth has a significant positive effect on infrastructure growth. This effect is significantly smaller in anocracies—so much so that, in anocracies, GDP per capita growth has no significant effect on the growth rate of infrastructure. Full article

We empirically test predictability on asset price using stock selection rules based on maximum drawdown and its consecutive recovery. In various equity markets, monthly momentum- and weekly contrarian-style portfolios constructed from these alternative selection criteria are superior not only in forecasting directions of asset prices but also in capturing cross-sectional return differentials. In monthly periods, the alternative portfolios ranked by maximum drawdown measures exhibit outperformance over other alternative momentum portfolios including traditional cumulative return-based momentum portfolios. In weekly time scales, recovery-related stock selection rules are the best ranking criteria for detecting mean-reversion. For the alternative portfolios and their ranking baskets, improved risk profiles in various reward-risk measures also imply more consistent prediction on the direction of assets in future. Moreover, turnover rates of these momentum/contrarian portfolios are also reduced with respect to the benchmark portfolios. In the Carhart four-factor analysis, higher factor-neutral intercepts for the alternative strategies are another evidence for the robust prediction by the alternative stock selection rules. Full article

Tourism is one of the economic sectors that contributes the most to the gross domestic product in many countries, moving, in turn, other economic sectors such as transport. In particular, the automotive industry constitutes an economic subsector that moves vast amounts of money. Concerning tourism and transport sectors, car rental is a crucial element contributing considerably to gross domestic product and job creation. Due to the effects that vehicle rental seems to have on various economic sectors, it seems interesting to know why a tourist chooses to rent a car during their vacation in a specific destination. This work aims to study those factors that can be considered relevant and affect the probability of renting a vehicle. The document addressed the following research topics: (a) identifying significant variables; and (b) can information on these factors help car rental firms? Empirically, it is shown that more tourists do not rent a car and this fact has to be considered. Thus, the classical logistic and Bayesian regression models do not seem adequate in this case, so that the authors will consider an asymmetric logistic regression model. This work analyzes 28,235 tourists who visited the Canary Islands during 2017. From a Bayesian point of view, asymmetric logistics regression is chosen as the best model because it detects relevant development factors not seen by standard logistic regressions. In light of the document’s findings, various practice recommendations improve decision-making in this field. The asymmetric logit link is a helpful device that can help rental companies make decisions about their clients. Full article

Developments in the world of finance have led the authors to assess the adequacy of using the normal distribution assumptions alone in measuring risk. Cushioning against risk has always created a plethora of complexities and challenges; hence, this paper attempts to analyse statistical properties of various risk measures in a not normal distribution and provide a financial blueprint on how to manage risk. It is assumed that using old assumptions of normality alone in a distribution is not as accurate, which has led to the use of models that do not give accurate risk measures. Our empirical design of study firstly examined an overview of the use of returns in measuring risk and an assessment of the current financial environment. As an alternative to conventional measures, our paper employs a mosaic of risk techniques in order to ascertain the fact that there is no one universal risk measure. The next step involved looking at the current risk proxy measures adopted, such as the Gaussian-based, value at risk (VaR) measure. Furthermore, the authors analysed multiple alternative approaches that do not take into account the normality assumption, such as other variations of VaR, as well as econometric models that can be used in risk measurement and forecasting. Value at risk (VaR) is a widely used measure of financial risk, which provides a way of quantifying and managing the risk of a portfolio. Arguably, VaR represents the most important tool for evaluating market risk as one of the several threats to the global financial system. Upon carrying out an extensive literature review, a data set was applied which was composed of three main asset classes: bonds, equities and hedge funds. The first part was to determine to what extent returns are not normally distributed. After testing the hypothesis, it was found that the majority of returns are not normally distributed but instead exhibit skewness and kurtosis greater or less than three. The study then applied various VaR methods to measure risk in order to determine the most efficient ones. Different timelines were used to carry out stressed value at risks, and it was seen that during periods of crisis, the volatility of asset returns was higher. The other steps that followed examined the relationship of the variables, correlation tests and time series analysis conducted and led to the forecasting of the returns. It was noted that these methods could not be used in isolation. We adopted the use of a mosaic of all the methods from the VaR measures, which included studying the behaviour and relation of assets with each other. Furthermore, we also examined the environment as a whole, then applied forecasting models to accurately value returns; this gave a much more accurate and relevant risk measure as compared to the initial assumption of normality. Full article

This study investigated the financial signals that have been ignored or have failed to be controlled by J. Crew Inc. from 2013 until 2019. Exploratory research is carried out with the help of secondary data which was collected from the downloaded formal documents submitted by J. Crew Inc. to the Securities Exchange Commission (SEC). Researchers analyzed these documents and prepared statements on vertical income statement, vertical balance sheet, horizontal income statement, horizontal balance sheet, trend analysis of income statement, and trend analysis of balance sheet, as well as ratio analysis on liquidity, long-term solvency, profitability, and turnover ratios with the help of excel. This paper has identified total of 15 alarming signs that companies either ignored, could not control, or did not act with alertness towards to stop the business being taken out of hands. In this research paper, the establishment of J. Crew Inc. was presented in four sections: Crew Retail Stores, Crew Factory Stores, Crew Mercantile Stores, and Crew Madewell Stores. The results of this study show that it was not the COVID-19 pandemic that pushed this retail giant into bankruptcy, but numerous reasons and financial turbulences. J. Crew’s financial performance gave plenty of alarming signals that the showed the company was not on track, but these were ignored by the company. Right from net profit, operating expenses, total revenue, goodwill, return on assets, liquidity, and solvency, all 15 indicators were not meeting the industry ideal standard for a continuous period of 5 years. Whether or not the organization can rebuild and contend in a post-pandemic world, is not yet clear. Full article

The 2011 Egyptian revolution was associated with significant political and social upheaval, followed by societal changes and attempts by policymakers to reduce the marginalisation of women and promote their inclusion in the economy. Drawing on this background, the authors compare the effect of board gender diversity before and after the revolution. Results indicate that gender diversity in corporate boards is coupled with improvements in firm performance in the immediate post revolution phase. This evidence provides insights into the contextual factors related to diversity and performance relationship and supporting arguments for regulatory changes to further encourage women’s representation on boards. Full article

With the application of the agency theory and institutional theory, this study is intended towards the measurement of sustainable corporate governance (SCG) impact on internal audit function (IA) within Omani public listed companies. This study will also theoretically consider the Chinese investment in Oman and its potential impact on Oman’s corporate governance. For this study, SCG is an independent variable and IA is the dependent variable. This study used a descriptive cross-sectional survey design. Data is collected by an internet-based tool and analyzed via PLS-SEM and SPSS. Result suggests that SCG has a significant and direct relationship with IA. In order to attract and sustain Chinese investment and to achieve SCG, this study can assist regulators, professional bodies, and organizations in amending their codes of corporate governance and organizational policies by introducing SCG clauses into their policies and codes with emphasis on the protection of foreign investors. To the best of the knowledge of the researcher, this study is unique, as previous studies demonstrate the IA on SCG, whereas this study emphasizes that SCG can impact the control functions within organizations that also include IA. Full article

This paper proposes a new approach toward understanding the financial performance dynamics in the EU retail sector (pre-pandemic); we focus on the connection between indebtedness and solvency risk and other areas of corporate performance (e.g., liquidity, assets efficiency, and profitability). Its contribution resides in identifying the drivers behind solvency risk in a sector that went through significant transformations in recent decades, as well as the links between the various areas of performance of retailers, and their impacts on solvency risk, using the machine-learning random forest methodology. The results indicate a declining trend for solvency risk of EU food retailers after the global financial crisis and up until the beginning of the pandemic, which may reflect their maturity on the market, but also an adjustment to legal changes in the EU, meant to equalize the tax advantages of debt versus equity financing. Solvency risk accompanied by liquidity risk is a mark of the retail sector, and our results indicate that the most critical trade that EU retailers face is between solvency risk and liquidity, but is fading over time. The volatility of liquidity levels is an important predictor of solvency risk; hence, sustaining a stable and good level of liquidity supports lower risks of financial distress, and may mitigate the shock impacts for EU retailers. A higher solvency risk was accompanied by increased efficiency of asset use, but reduced profitability levels, which led to higher returns available to shareholders for high solvency risk retailers. Overall, retailers should focus on operational performance evidenced by financial indicator levels than on the volatility of these indicators as predictors of solvency risk. Full article