Empirical essays on risk disclosures, multi-level governance, credit ratings, and bank value: evidence from MENA banks

This thesis contains four essays that examine the relationships among risk disclosures, multi-level governance, credit ratings, and bank value in the Middle East and North Africa (MENA) banks. These essays concentrate on four closely linked risk disclosures, and governance topics that quantitatively investigate the antecedents and informativeness of risk disclosures by banks from 14 countries in MENA region over the 2006–2013 inclusive period. The first essay aims at investigating the impact of multi-layer governance mechanisms on the level of risk disclosures by banks. The essay result suggests a variation between MENA banks in the level of risk disclosures with a significant improvement from 2006 to 2013. Specifically, the findings are three-fold. First, the results suggest that Sharia Supervisory Board (SSB) is positively associated with the level of risk disclosures by banks. Second and at the bank-level, the essay finds that ownership (governmental ownership and family ownership) and board (board size and non-executive directors) structures have a positive effect on the level of risk disclosures by banks, whilst CEO duality is negative, but insignificantly related to bank risk disclosures. At the country-level, the evidence suggests that control of corruption has a positive effect on the level of bank risk disclosures, whilst political stability and absence of violence have a negative, but insignificant association with the level of bank risk disclosures. In the second essay, the thesis investigates the relationships among national governance quality (NGQM), Islamic governance quality (ISGQ), including other bank-level governance mechanisms, and risk management and disclosure practices (RMDPs); and consequently ascertains whether NGQM has a moderating influence on the ISGQ -RMDPs nexus. The findings are four-fold. Firstly, this study finds that RMDPs are higher in banks from countries with higher NGQM. Secondly, this essay shows that RMDPs are higher in banks with better Islamic governance. Thirdly, the study finds that board size and non-executive directors have a positive effect on the level of RMDPs. Finally, this study finds evidence that suggests that NGQM has a moderating effect on the Islamic governance quality-RMDPs nexus. The third essay explores whether RMDPs have a predictive effect (informativeness) on banks’ credit ratings (BCRs); and consequently ascertains whether governance structures can moderate such an association. The findings suggest that RMDPs have a predictive effect on BCRs. The study finds that the quality of the BCR is higher in banks that have higher risk disclosures, board size, government ownership, board independence, women directors and established SSB. On the other hand, the results indicate that the BCR quality is lower in banks that have higher foreign ownership, and CEO role duality. Furthermore, the findings suggest that governance structures moderate the relation between RMDPs and BCRs. The final essay examines the extent to which RMDPs and multi-level governance can explain observable changes in bank value in a number of ways. First, this essay seeks to examine whether RMDPs can influence the value of banks. The second objective is to examine how NGQM may affect the bank value. Finally, this essay explores the relationship between operating in better- or poorly-governed countries and the market value of banks. The results confirm the substantial role of risk disclosures and multi-level governance in improving bank valuation in MENA. More specifically, the results indicate that market valuation is higher in banks with bigger foreign ownership, board size, board independence, Islamic governance, and NGQM. The results also show a significant negative relationship between CEO power and bank value. The research’s empirical findings are largely in line with the predictions of the multi-theoretical framework that incorporates insights from agency, signalling, legitimacy, institutional, and resource dependence theories. The study findings are robust to alternative firm- and country-level controls, alternative multi-level governance mechanisms, risk disclosure proxies, alternative estimation techniques, and endogeneity problems. In doing so, this study extends, as well as contributes to the banking and governance literature in a number of ways. First, to the best of the researcher’s knowledge, this thesis provides a first-time cross-country evidence on the level of risk disclosures in MENA countries, especially following the 2007/08 financial crisis in the banking industry. Second, this thesis offers first-time evidence on the informativeness of Islamic governance quality and risk disclosures from equity and debt markets. Third, this thesis offers evidence and extends prior research on the influence of multi-level governance on bank value, and credit ratings, using a multi-theoretical framework. Fourth, the study offers first-time evidence on the effect of national governance quality on banks’ risk disclosures, credit ratings, and bank value

Corporate accountability towards species extinction protection:insights from ecologically forward-thinking companies

This paper contributes to biodiversity and species extinction literature by examining the relationship between corporate accountability in terms of species protection and factors affecting such accountability from forward-thinking companies. We use triangulation of theories, namely deep ecology, legitimacy, and we introduce a new perspective to the stakeholder theory that considers species as a ‘stakeholder’. Using Poisson pseudo-maximum likelihood (PPML) regression, we examine a sample of 200 Fortune Global companies over three years. Our results indicate significant positive relations between ecologically conscious companies that are accountable for the protection of biodiversity and species extinction and external assurance, environmental performance, partnerships with socially responsible organizations and awards for sustainable activities. Our empirical results appear to be robust in controlling for possible endogeneities. Our findings contribute to the discussion on the concern of species loss and habitat destruction in the context of corporate accountability, especially in responding to the sixth mass extinction event and COVID-19 crisis. Our results can also guide the policymakers and stakeholders of the financial market in better decision making

The role of cryptocurrencies in predicting oil prices pre and during COVID-19 pandemic using machine learning

This study aims to explore the role of cryptocurrencies and the US dollar in predicting oil prices pre and during COVID-19 pandemic. The study uses three neural network models (i.e., Support vector machines, Multilayer Perceptron Neural Networks and Generalized regression neural networks (GRNN)) over the period from January 1, 2018, to July 5, 2021. Our results are threefold. First, our results indicate Bitcoin is the most influential in predicting oil prices during the bear and bull oil market before COVID-19 and during the downtrend during COVID-19. Second, COVID-19 variables became the most influential during the uptrend, especially the number of death cases. Third, our results also suggest that the most accurate model to predict the price of oil under the conditions of uncertainty that prevailed in the world during the bear and bull prices in the wake of COVID-19 is GRNN. Though the best prediction model under normal conditions before COVID-19 during an uptrend is SVM and during a downtrend is GRNN. Our results provide crucial evidence for investors, academics and policymakers, especially during global uncertainties

Would two-stage scoring models alleviate bank exposure to bad debt?

The main aim of this paper is to investigate how far applying suitably conceived and designed credit scoring models can properly account for the incidence of default and help improve the decision-making process. Four statistical modelling techniques, namely, discriminant analysis, logistic regression, multi-layer feed-forward neural network and probabilistic neural network are used in building credit scoring models for the Indian banking sector. Notably actual misclassification costs are analysed in preference to estimated misclassification costs. Our first-stage scoring models show that sophisticated credit scoring models, in particular probabilistic neural networks, can help to strengthen the decision-making processes by reducing default rates by over 14%. The second-stage of our analysis focuses upon the default cases and substantiates the significance of the timing of default. Moreover, our results reveal that State of residence, equated monthly instalment, net annual income, marital status and loan amount, are the most important predictive variables. The practical implications of this study are that our scoring models could help banks avoid high default rates, rising bad debts, shrinking cash flows and punitive cost-cutting measures

Offering flexible working opportunities to people with mental disabilities: The missing link between sustainable development goals and financial implications

YesA global response to Covid‐19 pandemic has triggered issues related to stress and social restrictions; thus, mental health is seen as a particular area of concern for social well‐being for both policymakers and corporate regulators/companies. Given that mental health intersects with most, if not all, of the 17 sustainable development goals (SDGs), this research brought to light issues surrounding employment of people with mental disabilities (PWMDs) and the financial merits of employing them. An online survey was administered to PWMDs to elicit what possible flexible opportunities could enable them to gain or stay at work. Interviews were also conducted with human resource managers and financial managers. Our results show that there are currently no flexible working opportunities available for PWMDs, which could enable them work effectively to improve both self and general economic growth

Assessing the Use of Gold as a Zero-Beta Asset in Empirical Asset Pricing: Application to the US Equity Market

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

The Corporate Governance–Risk Taking Nexus: Evidence from Insurance Companies

yesThis study examines the impact of internal corporate governance mechanisms on insurance companies’ risk-taking in the UK context. The study uses a panel data of all listed insurance companies on FTSE 350 over the 2005-2014 period. The results show that the board size and board meetings are significantly and negatively related to risk-taking. In contrast, the results show that board independence and audit committee size are statistically insignificant, but negatively related to risk-taking. The findings are robust to alternative measures and endogeneities. Our findings have important implications for investors, managers, regulators of financial institutions and effectiveness of corporate governance reforms that have been pursued