Liquidity Coverage Ratio Research Articles

Liquidity coverage ratio and profitability: an inverted U-shaped pattern

Liquidity coverage ratio and profitability: an inverted U-shaped pattern

News Sentiment and Liquidity Risk Forecasting: Insights from Iranian Banks

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.

The repo market under Basel III: Effects of capital and liquidity regulations on market fragmentation

AbstractRegulatory requirements can affect banks' ability and willingness to intermediate in financial markets. Yet, evidence on how these requirements interact to affect bank behaviour is thin. We contribute by assessing the effects of Basel III regulatory ratios on financial market fragmentation using the UK repo market as an important case study. Using panel regressions with proprietary data on repo transactions and holdings backed by gilts and lower‐quality collateral, we find affirmative evidence of a fragmentation. The leverage ratio incentivises banks to net transactions which leads to a fragmentation across prices between netted and non‐netted trades. Central bank liquidity can ease market conditions during stress and benefit banks that use it and their counterparties via reduced prices. In addition, the liquidity coverage ratio incentivises banks to increase long‐term lending backed by gilts, but reduce lending backed by lower‐quality collateral. This results in a fragmentation across maturities.

A Comparative study of the Basel III liquidity framework’s “Liquidity Coverage Ratio”: Compliance and Performance between Islamic Banks and Conventional banks in the State of Kuwait

Aim of the Paper: To propose some recommendations based on the finding for the conventional and Islamic banks in the sample of the study and to submit the experience of the research sample, first, to all the relevant regulatory authorities who deal with the supervision and control of conventional and Islamic banks in their banking system and second, to the decision makers in the conventional and Islamic banks to gain their bank’s compliance and better performance of Liquidity Coverage Ratio.Study Design: Comparative study of Liquidity Coverage Ratio’s compliance and performance between 4 national Islamic banks and 4 national conventional banks.Sample and Data: The sample contains of 4 conventional and 4 Islamic banks in the Kuwaiti national banking system. The data were quantitative “LCR figures” of the sampled banks and were gathered from their official websites (secondary data).Results: Both the conventional and the Islamic banks showed that were compliant and had the same efficient and effective level of LCRs performanceConclusion: the paper presented recommendation on bank solo level, banking sector level, regulatory authority level and international organizations level.

Which One Is The Most Important In Bank: Liquidity Or Capital Resiliency?

This research aims to examine the fulfillment of the Liquidity Coverage Ratio (LCR) and Capital Adequacy Ratio (CAR) of banks towards bank credit growth in Indonesia. The researchers included macroeconomic factors (GDP and BI Rate) as control variables and bank size (core capital category) to support the research testing. The influence of LCR and CAR on bank credit growth with KBMI categories 2, 3, and 4 during quarterly periods (Q4 2018 - Q2 2023) is tested using multiple linear regression. The study findings indicate that banks that enhance liquidity management by increasing the LCR can lead to a reduction in credit distribution. However, the CAR does not have a major influence on credit growth. This is because bank capital in Indonesia is very robust. The relationship between the LCR and credit growth in all KBMI categories is not significantly influenced by the core capital category of banks. In addition, the KBMI has a little impact on the correlation between CAR and credit growth in KBMI banks 2 and 3, but it does have a moderating effect on KBMI 4 banks

Liquidity regulation, bank capital ratio, and interbank rate

We study the impact of the Basel III liquidity coverage ratio (LCR) on bank capital ratio and the interbank rate in a traditional banking model. We find that inappropriate parameters assigned to calculate High-Quality Liquid Assets (HQLAs) and Net Cash Flows (NCOs) would lower the equilibrium capital ratio especially when the required liquidity ratio is strengthened. In addition, these regulatory parameters may have macro-prudential effects to steer the interbank rate.

Bank liquidity creation, loan concentration and liquidity risk: a comparative analysis of dual banking system

Purpose Keeping in view the robust growth of Islamic banking around the globe, this study aims to comparatively analyze the association between liquidity creation and liquidity risk for Islamic banks (IBANs) and conventional banks (CBANs) in Pakistan and Malaysia over a period of 2004–2021. The moderating role of bank loan concentration on the aforementioned relationship is also studied. Design/methodology/approach Regression estimation methods such as fixed effect, random effect and generalized least square are deployed for obtaining results. Liquidity creation Burger Bouwman measure (cat fat and noncat fat) and Basel-III liquidity risk measure (liquidity coverage ratio) are also used. Findings The results give us insight that liquidity creation is positively and significantly related to liquidity risk in both IBANs and CBANs of Pakistan and Malaysia. This relationship has been moderated negatively (reversed) and significantly by credit concentration showing the importance of risk management and loan portfolio concentration. Practical implications It is analyzed that during the process of liquidity creation, IBANs in Pakistan faced more liquidity risk for both on and off-balance sheet transactions in the presence of moderation of loan concentration than IBANs in Malaysia necessitating strategic policy-making for important aspects of liquidity risk management and loan concentration while creating liquidity. Originality/value Such studies comparing IBANs and CBANs comparison keeping in view liquidity creation, liquidity risk and loan concentration are either limited or nonexistent.

The impact of adopting Basel III liquidity coverage ratio, stable funding ratio, and leverage ratio on lending in the Malawian banking sector

This paper examines the impact of adopting Basel III Liquidity Coverage Ratio, Stable Funding Ratio, and Leverage Ratio on lending in the Malawian banking sector. Malawi’s banking industry regulators are planning to transition to Basel III from the current Basel II regime. This paper pioneers an assessment of the implications of this move for the banking industry. The study uses monthly data for the period January 2010 to December 2022, the Feasible Generalised Least Square (FGLS) Panel Regression model with bank-specific variables (X) and macroeconomic controls (Z). The study finds that Tier 1 has a positive and significant impact on Malawi’s banking sector lending growth, while Tier 2 has a negative and insignificant impact on banking sector-wide lending growth effects. The non-risk weighted asset Basel III leverage ratios have significant and negative impacts on Malawi’s bank sector lending growth. And that the liquidity coverage ratio (LCR) had a positive and significant effect in explaining variability in lending in Malawi banking overall, while the introduction of the stable funding ratio (SFR) had a positive and significant impact on banking sector-wide lending growth effects. The study also found that the Basel III Capital and Liquidity Rules have different effects on firm-level lending for the 8 banks in Malawi.

Does promoters’ holding influence the liquidity risk of banks?

PurposeThis paper aims to evaluate whether promoter holding influences a bank’s liquidity in India’s leading emerging market. Furthermore, it also evaluates the moderating role of risk-weighted assets (RWA) on the relationship between promoter holding and liquidity.Design/methodology/approachThe data consists of 24 banks for the period of 12 years from 2010 to 2021. Static panel data is used to analyze the relationship between the liquidity coverage ratio (LCR) as the dependent variable, the promoter used as an explanatory variable and RWA used as a moderating variable in this study.FindingsThis study concludes that an increase in promoter holding helps to improve the liquidity of Indian banks. Moreover, it also shows that using RWA as a moderating term enhances the relationship between promoter holdings and Indian banks’ liquidity.Research limitations/implicationsThis study evaluated the impact of promoter ownership solely on the LCR, a statistic used to measure the short-term liquidity of banks in the Indian setting. Additional corporate governance factors, such as the makeup of the board of directors, relevant ownership concentration factors and external factors with the potential to affect the liquidity position of banks, could potentially be the subject of future investigations.Practical implicationsThis paper has both managerial and policy-level implications. It shows that it is advantageous for banks’ ownership composition to include more enormous promoter holdings to enhance banks’ liquidity. Policymakers can, thus, formulate policies to encourage banks to have more extensive promoter holdings.Originality/valueThe impact of promoter ownership on bank liquidity has not been evaluated in earlier research projects. Furthermore, the use of RWA as a moderating variable to determine this link has not been fully investigated, particularly in the context of a developing country like India.

Evolution of Risks Facing Commercial Banks in Kenya and Associated Strategic Responses

Purpose: The main objective of this study was to explore the evolution of risks facing commercial banks in Kenya and their strategic responses
 Methodology: The study adopted a desktop methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.
 Findings: The study found that the commercial banking sector in Kenya is operating within a highly dynamic and ever-evolving risk landscape. The risks faced by these banks are multifaceted and include economic, operational risk, regulatory, technological, systematic, sovereign risk and market-related challenges. It also added that the strategic responses adopted by commercial banks in Kenya are diverse and multifaceted. The conclusions drawn emphasize the need for continual vigilance and adaptation in risk management, the pivotal role of technology and digital transformation, and the significance of regulatory compliance. By taking these conclusions into account, commercial banks in Kenya can better position themselves to thrive in the dynamic and competitive financial landscape of the country.
 Unique Contribution to Theory, Practice and Policy: The Modern Portfolio theory, liquidity preference and the Liquidity Coverage Ratio (LCR), Agency theory, the term structure of interest rates and duration and Credit Scoring Model and the Resource Based View model may be used to anchor future studies on the evolution of risks facing commercial banks in Kenya and their strategic responses. This study makes significant contributions to theory by developing a risk evolution framework and strategic risk response models. It has practical implications by offering enhanced risk management strategies and guidance for financial decision-making for practitioners. Additionally, the research provides valuable insights for banking regulators policymakers, and investors in Kenya, supporting risk-based supervision and financial stability initiatives.

Monetary policy pass-through after the LCR

After the implementation of the Liquidity Coverage Ratio (LCR), trading in the federal funds market, which generally has a relatively favorable LCR treatment, became more driven by market liquidity. As a result, we document that pass-through of the federal funds rate to other short-term interest rates strengthened.

Using machine learning for detecting liquidity risk in banks

The accurate classification of banks’ Liquidity Risk (LR) for regulatory supervision is hindered by limitations in the measures, such as Minimum Liquid Assets (MLA), Net-Stable Funding Ratio (NSFR), and Liquidity Coverage Ratio (LCR). This study addressed two limitations on data integrity vulnerabilities and the narrow composition of LR factors excluding practical LR determinants such as credit portfolio quality, market conditions, strategies of assets and funding. Theoretical gaps included the eight new LR factors in this study, benchmarking study results with measures to interpret the studies’ contributions and the selection of suitable prediction methods for non-linear, imbalanced, scaling, and near real-time data. We used data from 38 Tanzanian banks (2010-2021) from the Bank of Tanzania (BOT). Extensive factors experimentation using Random Forest (RF) and Multi-Layer Perceptron (MLP) models identified ten features for Machine Learning (ML) analysis and LR rating as output. A hybrid RF-MLP model with a 199-tree RF and 10-512-250-120-80-60-6 MLP was developed. It increased LR sensitivity and reduced RF and MLP model limitations through generalisation, and demonstrated statistical and practical performance. It minimised classification errors with Type I and II errors, and Negative Likelihood of 0.8%, 9.1%, and 1%; Discriminant Power of 2.61; and 90% to 96% Accuracy, Balanced Accuracy, Precision, Recall, F1 Score, G-mean, Cohen’s Kappa, Youden Index, and Area Under the Curve. Past LR scenarios confirmed RF-MLP performance improvement over MLA. The unavailability of LCR and NSFR data hindered a comprehensive evaluation. This study extended LR factors and proposed a model to complement LR classification.

LCR Premium in the Federal Funds Market

We document the existence of a regulatory premium in the federal funds market related to the implementation of the Liquidity Coverage Ratio (LCR). We use difference-in-differences analysis and confidential bank level data on borrowing in the fed funds and Eurodollar markets to compare the interest rates paid by banks subject to daily reporting of their liquidity profile (daily reporters) relative to other banks. We find that, after the implementation of LCR, daily reporters paid a higher rate compared to other banks when borrowing in the fed funds market given the LCR-favorability of many of the lenders in this market. In addition, on the days that banks borrowed in both the fed funds and Eurodollar markets, daily reporters paid a higher rate than other banks for their borrowing in the fed funds market but not for their borrowing in the Eurodollar market.

An Empirical Analysis of the Dynamics Influencing Bank Capital Structure in Africa

Financial institutions, particularly banks, have long grappled with the dilemma of structuring their capital optimally. This process, commonly referred to as capital structure decision-making, is of paramount importance, especially within the financial services sector, where strict regulations are imposed by reserve and central banks in alignment with global Basel guidelines. This study unveils the key factors that determine the capital structure choices of African banks, using panel data encompassing 45 listed banks across six nations that had embraced the Basel III Accord spanning the years 2010 to 2019. The study used the system-generalised moment methods (sys-GMM) estimator to fit the formulated panel data regression model. The study findings showed positive associations between ZSCORE, an indicator of bank financial stability, and net interest margin ratio (NIMR) with bank leverage (TCTE). In addition, the results revealed positive correlations between earnings volatility (EV), profitability (P), and risk (R) with bank leverage (TDCE). This suggests that profitable banks are inclined to favour debt financing, a phenomenon driven by their ability to comfortably service debt obligations with free cash flows. This study’s overarching conclusion underscores the dominant influence of the Liquidity Coverage Ratio (LCR) on African bank capital structures. Whether assessing traditional or Basel III-prescribed measures of bank leverage, LCR consistently emerged as the primary determinant. This finding is of significant relevance to bank executives and regulators, offering them essential insights for informed decision-making by considering striking a balance between equity and debt financing based on financial stability, profitability, and risk profiles.

Impact of Covid-19 on Financial Ratio Banking Sector

The purpose of this research is to provide information on whether the COVID-19 pandemic had an impact on banking in Indonesia, especially for banks listed on the Indonesia Stock Exchange. The impact on banking was measured by using financial performance ratios, namely nonperforming loan (NPL), operating expenses to operating income (BOPO), net interest margin (NIM), and liquidity coverage ratio (LCR). Researchers used comparative data on financial statements, namely in 2019 and 2020. The tool used by researchers to process research data was SPSS 24. Researchers used different test methods to determine the impact of the Covid-19 pandemic on the financial performance of the banking sector. The results showed that the Covid-19 pandemic had affected the financial performance of the banking sector.
 Keywords: financial performance, Covid-19, banking sector

Banking Transparency, Financial Information and Liquidity Risk Management: Case of Saudi Banks

The article aims to assess the impact of banking transparency on liquidity risk. To do so, we first test the determinants of Liquidity Coverage Ratio (LCR) as well as ensure the resilience of the Saudi banking system over the period from 2014 to 2021. Using System GMM with bank-specific and macroeconomic variables, results show that capital adequacy ratio, SIZE, GDP growth as well as past LCR levels significantly influence the LCR.  Secondly, we adopt the Panel Vector Auto Regression (PVAR) approach to assess the response of the LCR to various shocks. Impulse Response Functions (IRF) and variance decomposition demonstrate that the shocks to past LCR, AQ, CAR and GDP increase future liquidity risk. Thirdly, we prove that Saudi banks implement less than 50% of the transparency dimensions. They mainly disclose financial information and information on information credibility. Barely 18% of information on non-financial components of banking activity is made available to the public. Information on liquidity risk and on the timeliness of information is not available either in annual reports or on the bank's website. On average, the banks in the sample do not give importance to the publication of reports. These results may undermine the effectiveness of the guidelines of the Basel Committee agreements to reduce risk-taking by Saudi banks.

Does Basel III – Liquidity Coverage Ratio Affect the Profitability of Indian Public Sector Banks?

The article analyses the interrelation between the Liquidity Coverage Ratio (LCR) and the profitability of Indian public sector banks from March 2015 to March 2022. It uses the panel data technique to explain these relations. Further, this article also looked at the interactive effect of LCR through advances and the interest rate. It has gone through pre- and post-diagnostic checks finalizing the model and variables. The findings of the result surprisingly imply that Basel III regulatory directives like LCR positively impact the bank profitability in India rather than general apprehension about the negative impact. However, the interactive effects of LCR through advances negatively influence the banks’ profitability. Variables such as deposits, Economic Policy Uncertainty (EPU) and Gross Domestic Product (GDP) have no statistically significant relation with banks’ profitability. This article recommends that Basel III guidelines should not be looked at negatively for the performance of banks.

Liquidity regulations, bank lending and fire-sale risk

We examine whether U.S. banks subject to the Liquidity Coverage Ratio (LCR) reduce lending (an unintended consequence) and/or become more resilient to liquidity shocks, as intended by regulators. We find that LCR banks tighten lending standards, and reduce liquidity creation that occurs mainly through lower lending relative to non-LCR banks. However, covered banks also contribute less to fire-sale externalities relative to exempt banks. For LCR banks, we estimate that the total after-tax benefits of reduced fire-sale risk (net of the costs associated with foregone lending) exceed $50 billion from 2013Q2 to 2017, mostly accruing to the largest LCR banks. Non-LCR regulations enacted during our sample period cannot fully account for these findings. For the banking sector as a whole, lending migrates to smaller, non-LCR banks so that lending shares increase but fire-sale risk does not decrease. Our results highlight the trade-off between liquidity creation and resiliency arising from liquidity regulations that underlie the debate on whether the LCR should be extended following the banking crisis of March 2023.

Impact of Liquidity on the Efficiency of Banks in India Using Panel Data Analysis

The current study investigates the impact of the liquidity coverage ratio (LCR) on the efficiency of Indian banks for the period 2010 to 2019. The study examines the effect of internal bank elements like ownership structure, transparency and disclosure, and technological advancement on the relationship between the LCR and efficiency. Bank efficiency proxied as technical efficiency is evaluated by applying the data envelope analysis approach. Applying the panel data regression technique, the authors discover that the LCR has a positive impact on the technical efficiency at a constant return to scale of banks. The relationship between the LCR and the technical efficiency at a variable return to scale is non-linear. Initially, as liquidity increases, the efficiency of banks improves, after reaching its optimum level, efficiency starts to decline. Furthermore, liquidity tends to improve efficiency of banks with higher promoter stakes, whereas opposing results are evidenced for institutional investors and technological advancement.

Liquidity Risk And Basel III Implementation In Southeast Asia Banking

Purpose: The objective of this study was to determine the effect of liquidity coverage ratio, net stable funding ratio, net interest margin, and cost of funds on return on assets in Southeast Asian countries' banking services. Methodology/approach: This research was a quantitative research method. Secondary data was used and collected from stock exchanges in each country. Samples were banks in Indonesia, Malaysia, Cambodia, Philippines, Singapore and Thailand. The data testing technique uses multiple linear regression analysis. Findings: The study inform that net stable funding ratio, liquidity coverage ratio, net interest margin and cost of funds have a significant effect on return on assets. Practical implications: The practical implications were BASEL III implementation to manage liquidity risk and capital in each country have successfully and encourage compliance with bank liquidity and capital aspects according to the framework of BASEL III to enhance the financial performance of banks in Southeast Asian countries. Originality/value: Research on the application of BASEL III in Southeast Asian Countries as a framework that establishes international standards for bank capital adequacy, stress testing, and liquidity requirements is the originality of this research.