Search Results (51)

Value-at-Risk (VaR) is a key metric widely applied in market risk assessment and regulatory compliance under the Basel III framework. This study compares two Monte Carlo-based VaR models using publicly available equity data: a return-based model calibrated to historical portfolio volatility, and a CAPM-style factor-based model that simulates risk via systematic factor exposures. The two models are applied to a technology-sector portfolio and evaluated under historical and rolling backtesting frameworks. Under the Basel III backtesting framework, both initially fall into the red zone, with 13 VaR violations. With rolling-window estimation, the return-based model shows modest improvement but remains in the red zone (11 exceptions), while the factor-based model reduces exceptions to eight, placing it into the yellow zone. These results demonstrate the advantages of incorporating factor structures for more stable exception behavior and improved regulatory performance. The proposed framework, fully transparent and reproducible, offers practical relevance for internal validation, educational use, and model benchmarking. Full article

This study examines the role of supervisory frameworks in shaping the risk management behavior of Greece’s four systemic banks during the period of 2015–2024. It explores how regulatory reforms under Capital Requirements Regulation II, Basel III, and European Central Bank oversight influenced capital adequacy, asset quality, and liquidity metrics. Employing a quantitative methodology, this study analyzes secondary data from Pillar III disclosures, annual financial reports, and supervisory statements. Key risk indicators (capital adequacy ratio, non-performing exposure ratio, liquidity coverage ratio, and risk-weighted assets) are evaluated in conjunction with regulatory interventions, such as International Financial Reporting Standards 9 transitional relief, the Hercules Asset Protection Scheme, and European Central Bank liquidity measures. The findings reveal that enhanced supervision contributed to improved resilience and regulatory compliance. International Financial Reporting Standards 9 transitional arrangements were pivotal in maintaining capital thresholds during stress periods. Supervisory flexibility and extraordinary European Central Bank support measures helped banks absorb shocks and improve risk governance. Differences across banks highlight the impact of institutional strategy on regulatory performance. This study offers a rare longitudinal assessment of supervisory influence on bank risk behavior in a high-volatility Eurozone context. Covering an entire decade (2015–2024), it uniquely links institutional strategies with evolving regulatory frameworks, including crisis-specific interventions such as International Financial Reporting Standards 9 relief and asset protection schemes. The results provide insights for policymakers and regulators on how targeted supervisory interventions and transitional mechanisms can enhance banking sector resilience during protracted crises. Full article

The market risk measurement of a trading portfolio in banks, specifically the practical implementation of the value-at-risk (VaR) and expected shortfall (ES) models, involves intensive recalls of the pricing engine. Machine learning algorithms may offer a solution to this challenge. In this study, we investigate the application of the Gaussian process (GP) regression and multi-fidelity modeling technique as approximation for the pricing engine. More precisely, multi-fidelity modeling combines models of different fidelity levels, defined as the degree of detail and precision offered by a predictive model or simulation, to achieve rapid yet precise prediction. We use the regression models to predict the prices of mono- and multi-asset equity option portfolios. In our numerical experiments, conducted with data limitation, we observe that both the standard GP model and multi-fidelity GP model outperform both the traditional approaches used in banks and the well-known neural network model in term of pricing accuracy as well as risk calculation efficiency. Full article

This research investigates the relationship between Basel capital regulations, bank risk, and bank efficiency in the context of Pakistani and Indian commercial banks. This study examines the period from 2009 to 2022 and specifically analyses the impact of Basel III capital requirements on risk and efficiency. Quantitative methods are employed, utilising data from central bank websites and the BankScope database to construct a comprehensive sample of commercial banks in Pakistan and India. The system-generalised method of moments (GMM) estimation technique addresses potential endogeneity issues in the regression models. The findings shed light on the effectiveness of these regulations and provide insights for policymakers and regulators in both countries. The results indicate that Basel capital regulations have generally increased banks’ risk-taking behaviour in Pakistan and India. However, they have not improved the overall efficiency of the banking sector in either country. Bank efficiency declined during the study period, highlighting the limited effectiveness of Basel capital regulations in enhancing efficiency. Furthermore, the impact of these regulations on risk and efficiency varies between the two countries. In Pakistan, the regulations do not significantly affect bank efficiency, while in India, they decrease efficiency. Additionally, Basel III capital regulations do not significantly impact the risk taken by banks in either country. This study concludes by emphasising the need for alternative mechanisms or policies to improve the banking industry’s efficiency, as Basel capital regulations alone have proven ineffective. The findings offer valuable insights for central banks and regulators in assessing the relationship between capital regulations, risk, and efficiency and implementing appropriate measures to enhance the performance of the banking sector. This study recommends the following key points: the adoption of tailored regulatory approaches to address specific challenges, achieving an optimal balance between risk management and operational efficiency, enhancing the effectiveness of management roles, considering the influence of macroeconomic factors, and evaluating the implications of long-term policy development for sustainable progress. The present study adds to the prevalent literature on the impact of capital regulations on bank risk and efficiency nexus. This study focuses on Pakistan and India, which are two important developing nations. Moreover, another important contribution of this study lies in the effect of Basel III capital regulation on bank risk, as these capital regulations are different from other Basel capital requirements. Full article

The paper examines the key determinants of European banks’ profitability by analyzing the return on assets (ROA), return on equity (ROE), net interest margin (NIM), and the risk-adjusted measures of profitability, RAROAA and RAROAE, across 34 European countries during the period from 2013 to 2018—a time characterized by economic recovery and significant regulatory reforms, including the implementation of Basel III standards. Using the Generalized Method of Moments (GMM) approach and data of 3076 European banks, the research addresses the complex interplay between internal (bank-specific) factors and external factors, including macroeconomic and industry-specific factors. The results show that profitability is positively associated with a higher capital adequacy, liquidity risk, and income diversification, but not for risk-adjusted profitability ratios. Credit risk, management efficiency, and excessive size have a negative effect on all studied profitability measures. Macroeconomic conditions, in particular, GDP growth and inflation, also have a significant impact on profitability. The findings offer valuable insights for policymakers, regulators, and financial institutions aiming to enhance profitability while maintaining the stability of the European banking sector. Full article

The Basel III regulations turned the banking industry around worldwide and created new challenges for banks’ financial stability, particularly in liquidity management. As the demand for compliance with the rules started to grow, the inability of banks worldwide to meet the Basel III requirements about liquidity shifted the way they work. This paper highlights the complex relationship between liquidity and bank profitability in the post-Basel III era. Based on market presence and influence, 10 publicly traded UK commercial banks were selected for 2015–2021. Panel data, using FGLS regression models, were tested to elaborate in detail how the liquidity risk indicators determine banks’ performance, as measured by different profitability indicators. The findings were diversified: some showed that the relationship between liquidity risk indicators and bank profitability is contingent upon the interaction of several dimensions that range from the internal aspects of the banks themselves to general macroeconomic factors. This study provides vital insights into the current literature on risk management, especially about liquidity risks and their effect on bank performance. The findings of this study contribute meaningfully to the knowledge base for banks, regulators, and policymakers. This will contribute to better decision-making, financial stability, and long-term development within the UK’s banking industry. Full article

Counterparty risk, which combines market and credit risks, gained prominence after the 2008 financial crisis due to its complexity and systemic implications. Traditional management methods, such as netting and collateralization, have become computationally demanding under frameworks like the Fundamental Review of the Trading Book (FRTB). This paper explores the combined application of Gaussian process regression (GPR) and Bayesian quadrature (BQ) to enhance the efficiency and accuracy of counterparty risk metrics, particularly credit valuation adjustment (CVA). This approach balances excellent precision with significant computational performance gains. Focusing on fixed-income derivatives portfolios, such as interest rate swaps and swaptions, within the One-Factor Linear Gaussian Markov (LGM-1F) model framework, we highlight three key contributions. First, we approximate swaption prices using Bachelier’s formula, showing that forward-starting swap rates can be modeled as Gaussian dynamics, enabling efficient CVA computations. Second, we demonstrate the practical relevance of an analytical approximation for the CVA of an interest rate swap portfolio. Finally, the combined use of Gaussian processes and Bayesian quadrature underscores a powerful synergy between precision and computational efficiency, making it a valuable tool for credit risk management. Full article

This study addresses the critical challenge of predicting liquidity risk in the banking sector, as emphasized by the Basel Committee on Banking Supervision. Liquidity risk serves as a key metric for evaluating a bank’s short-term resilience to liquidity shocks. Despite limited prior research, particularly in anticipating upcoming positions of bank liquidity risk, especially in Iranian banks with high liquidity risk, this study aimed to develop an AI-based model to predict the liquidity coverage ratio (LCR) under Basel III reforms, focusing on its direction (up, down, stable) rather than on exact values, thus distinguishing itself from previous studies. The research objectively explores the influence of external signals, particularly news sentiment, on liquidity prediction, through novel data augmentation, supported by empirical research, as qualitative factors to build a model predicting LCR positions using AI techniques such as deep and convolutional neural networks. Focused on a semi-private Islamic bank in Iran incorporating 4,288,829 Persian economic news articles from 2004 to 2020, this study compared various AI algorithms. It revealed that real-time news content offers valuable insights into impending changes in LCR, particularly in Islamic banks with elevated liquidity risks, achieving a predictive accuracy of 88.6%. This discovery underscores the importance of complementing traditional qualitative metrics with contemporary news sentiments as a signal, particularly when traditional measures require time-consuming data preparation, offering a promising avenue for risk managers seeking more robust liquidity risk forecasts. Full article

The goal of this research is to investigate whether taxation affects the leverage decisions of banks and if the response of leverage to tax increases depends on profit-shifting opportunities available to individual banks. This topic remains controversial since it is often believed that banking regulation is such an essential driver of leverage choices that little room is left for other considerations studied in the corporate finance literature. Using a difference-in-differences setup encompassing the period from 2006 to 2017, we exploit two exogenous income tax rate increases applicable to 225 Brazilian banks, employing novel identification strategies based on the intricacies of local taxation rules and on the distinctions between individual banks and financial conglomerates. We find stark differences in the behavior of banks around the two events, with a substantial increase in leverage following the first tax hike but no leverage response following the second. In addition, we find no evidence of heterogeneous effects based on the amount of profit-shifting opportunities available to individual banks. Regulatory concerns possibly became more relevant for leverage decisions during the period around the second tax hike because it coincided with the implementation of stricter capital requirements associated with the Basel III framework. Taken together, our results suggest that financial institutions balance considerations regarding the tax-shield benefits of debt against regulatory concerns specific to the banking industry when making capital structure choices. Full article

For a bank-based economy like Vietnam, the commercial banking sector’s conduct greatly influences Vietnamese economic and social prosperity. In Vietnam, net income from credit activities hold the largest portion of the total revenue of Vietnamese commercial banks. Therefore, in the context of Vietnam, credit risk obviously also plays a pivotal important role in the banking sector. Hence, the risk of credit failure can lead to a bank’s collapse and have a profound effect on a country’s societal structure. As seen in the previous literature, there are many macroeconomic and bank-level factors that have commonly affected the level of credit risk; however, these factors may change in the recent development era of the banking industry, especially the new impacts of digital transformation and the transition to full Basel III adoption. The overall aim of this study is to analyze the impacts of digital transformation and Basel III implementation on the credit risk level of Vietnamese commercial banks during the period from 2017 to 2023, with a sample of 21 Vietnamese listed commercial banks. This study employs the pooled OLS, fixed effect model (FEM), and random effect model (REM) methods to reach the finding that investing in technology for the readiness of digital transformation and implementing Basel III could adversely affect credit risk. Based on this finding, the authors give some recommendations for commercial banks to enhance the sustainability, safety, and better management of credit risk. Full article

Purpose. The purpose of this research is to propose a tool for designing a microcredit risk pricing strategy for borrowers of microfinance institutions (MFIs). Design/methodology/approach. Considering the specific characteristics of microcredit borrowers, we first estimate and measure microcredit risk through the default probability, applying a parametric technique such as logistic regression and a non-parametric technique based on an artificial neural network, looking for the model with the highest predictive power. Secondly, based on the Basel III internal ratings-based (IRB) approach, we use the credit risk measurement for each borrower to design a pricing model that sets microcredit interest rates according to default risk. Findings. The paper demonstrates that the probability of default for each borrower is more accurately adjusted using the artificial neural network. Furthermore, our results suggest that, given a profitability target for the MFI, the microcredit interest rate for clients with a lower level of credit risk should be lower than a standard, fixed rate to achieve the profitability target. Practical implications. This tool allows us, on the one hand, to measure and assess credit risk and minimize default losses in MFIs and, secondly, to promote their competitiveness by reducing interest rates, capital requirements, and credit losses, favoring the financial self-sustainability of these institutions. Social implications. Our findings have the potential to make microfinance institutions fairer and more equitable in their lending practices by providing microcredit with risk-adjusted pricing. Furthermore, our findings can contribute to the design of government policies aimed at promoting the financial and social inclusion of vulnerable people. Originality. The personal characteristics of microcredit clients, mainly reputation and moral solvency, are crucial to the default behavior of microfinance borrowers. These factors should have an impact on the pricing of microcredit. Full article

This paper aimed to investigate the effects of government borrowing banks’ capital structure using a sample of banks registered in South Africa from 2012 to 2021. Despite the extensive literature on this association, few prominent researchers have studied this phenomenon in the banking sector. Applying the generalised method of moments (GMM) model, the study established a positive but significant effect on the South African banks’ capital structure from total government borrowing, local government borrowing and foreign government borrowing, and capital structure. Contrary to the crowding-out effects detected, the results revealed a positive and significant relationship between government borrowing and banks’ capital structure. The crowding-in effect better explains these results, where government borrowing stimulates the local market for goods and services, motivating banks to borrow more in order to meet the demand for loans. Future research should test the cointegrating and causality relationship between government borrowing and bank capital structure. Also, given that the banking sector is constrained by Basel III’s capital adequacy requirement, controlling for this factor is critical in future research. Full article

The risk of lending money collected from savers is that it leaves banks liable to default with depositors if events (and hence repayment demands) become ‘abnormal’. Even though international and national regulation has been introduced to ensure that a certain level of capital is retained by banks, such regulation can be subverted. The current system of international regulation based on the Basel III agreements does not stipulate a standardised approach for inspection frequency or penalty magnitude. This leaves the potential for regulatory arbitrage. The scientific value of an analysis to optimise regulatory efficiency and reduce such arbitrage is therefore considerable. This work therefore assesses the results of the empirical testing of a model based on the Von Neumann–Morgenstern utility function and consequently proposes that this model be used as a basis for standardising capital adequacy limit infraction penalties on an international level to prevent regulatory arbitrage. A survey is undertaken in order to test the responses of participants on the level of penalty which would deter them from regulatory transgression under different theorised levels of profit and probability of discovery. Based on the responses of two distinct subject groups (‘bankers’ and ‘non-bankers’) in different scenarios of hypothetical capital adequacy violation, the Von Neumann–Morgenstern utility function is reviewed against empirical results and revealed to show a semi-strong correlation. Lastly, the analysis reveals the striking similarities of the two groups’ responses, posing regulatory implications for the industry. Full article

The aim of this paper is to analyze the evolution of bank liquidity regulations, considering the global regulatory framework applicable to financial institutions, from the beginning of the banking and liquidity crisis in 2007–2008 to the present. The new liquidity requirements under Basel III regulations are defined. An analysis is made of the recent evolution of credit institutions in Spain from different banking prisms to determine how the new banking regulation and supervision, following the start of supervisory powers by the European Central Bank at the end of 2014, has affected them. The methodology applied has been firstly the literature review, followed by a compilation and analysis of the financial and statistical evidence available on the main Spanish financial institutions, from the European Central Bank and the Bank of Spain, as well as information published by other agencies and the financial institutions themselves. It concludes with a reflection and analysis of the outlook for the sector once the most recent impacts, derived from COVID-19, and the supply crisis with the rise in global inflation and the increase in interest rates have been overcome. It can be stated that credit institutions in Spain have significantly improved their liquidity position over the last 15 years. Full article

This research investigates whether banks that adopted new regulatory requirements earlier, such as Basel III, are more profitable, as well as more efficient, than banks that adopted these requirements later. In addition, all 138 banks are based in the G7 member countries, which are the most developed countries in the world. Also, banks are categorized into early and late adopters based on Basel III Leverage Ratio performance by using Fitch Connect. Moreover, profitability ratios, such as the Return on Equity, Return on Assets and efficiency ratio Operating Efficiency, were collected from Fitch Connect to analyze if early adopters were more profitable and efficient than the late adopters. Also, STATA is used to analyze descriptive statistics and a univariate analysis of both groups. Furthermore, the finding is that early adopters of the Basel III Leverage Ratio are not the more profitable or efficient firms compared to late adopters as anticipated. In addition, the results of early and late adopters do not differ that much in the analysis regarding profitability and efficiency ratios. This implies that it is not necessarily correct to assume that stricter regulation, such as Basel III, will negatively affect the profitability or efficiency of banks. In addition, these results are useful to regulators and policymakers of the G7 member countries for two reasons. Also, regulators can clearly see how banks are adopting new stricter regulation. Full article