Bank asset allocation and finance structure under uncertainty in Vietnam

PurposeThe paper investigates the link between uncertainty and banks' balance sheet reactions.Design/methodology/approachThe study employs bank-level data in Vietnam during 2007–2019 to measure micro uncertainty in banking through the dispersion of bank-level shocks. Empirical regressions are performed by the two-step system generalized method of moments (GMM) estimator and then verified using the least squares dummy variable corrected (LSDVC) technique.FindingsBanks tend to reduce risky loans, hoard more liquidity and decrease financial leverage in response to higher uncertainty. The relationship between uncertainty and banks' balance sheet reactions is more pronounced for banks that suffer more credit risk and overall risk, thus supporting the precautionary motive of banks. Additionally, uncertainty also leads to a decline in the Net Stable Funding Ratio (NSFR) under Basel III, implying that banks may fail to find a more stable source of funding and be more subject to maturity mismatch during periods of higher uncertainty.Originality/valueThe paper is the first to explore comprehensively the relationship between uncertainty and banks' balance sheet aspects as simultaneously estimated by bank loans, bank liquidity and bank leverage. While many other uncertainty measures display aggregate uncertainty sources, an important contribution in this study is to anatomize uncertainty originating exclusively from banking at a disaggregate level. Besides, shedding light on how uncertainty drives bank funding liquidity as captured by the NSFR under Basel III is entirely novel in the literature.

Relationship between Selic rate and Basel III parameters - A statistics approach and a fuzzy forecasting model

In this work the relationship between the Selic rate and some bank parameters defined by the so-called Basel Accords is studied. The cross-correlation between the Selic rate and the parameters is used to explain how these parameters affect the Selic rate and vice-versa so as to define the predictability of the Selic rate using (some of) these parameters as inputs. A model is then proposed for predicting the Selic rate based on some specific parameters using fuzzy logic ideas, which dealt with a partitioning of the universe of discourse using clusters related to the output data distribution. The proposed model is compared to four other known models in the literature and showed to have better performance in average compared to all other models.

The Basel III net stable funding ratio and a risk-return tradeoff: Bank-level evidence from Vietnam.

The Net Stable Funding Ratio (NSFR) liquidity rule under Basel III guidelines is designed to handle long-term liquidity risk, promoting the sustainable structures of bank funding. This study estimates the NSFR and analyses the impact of this liquidity ratio on banks according to a risk-return trade-off in Vietnam prior to the Basel III implementation. Using yearly data for commercial banks from 2007 to 2018, I find that banks with higher NSFR gain more potential benefits than banks with lower NSFR. Concretely, a rise in NSFR increases bank profitability and decreases bank funding costs, credit risks and liquidity creation, as evidenced by a comprehensive set of alternative measures. The findings of this study offer insightful implications on the bank policy framework advocating the Basel III liquidity regulation in Vietnam as well as other emerging markets.

Central Counterparties and Liquidity Provision in Cash Markets

This paper investigates increased liquidity provision by market makers resulting from their ability to reduce balance sheet encumbrance through the use of central counterparties (CCPs). The introduction of the Basel III leverage rule constitutes a shock to market makers’ balance sheets and thus affects their capacity to intermediate trades. Using trade-by-trade data from sovereign bond markets, we show that liquidity provision by CCP members decreased to a lesser extent following the rule change. We attribute these findings to balance sheet reductions due to the netting enabled by CCPs, thereby highlighting their importance in cash markets.

Changes in New Private Law of the Czech Republic and Implementation of Basel III

Competition in the financial market puts currently new requirements for cost reduction on financial institutions. Available sources of cost reduction are seen i.a. in minimizing legal risks, which can reduce the uncertainty associated with enforcement and interpretation of legal acts, treaties and regulations in the field of contractual obligations. In this regard, banks in the Czech Republic are looking for new ways to reduce costs in the ongoing implementation of Basel II and preparation for implementation of Basel III. The central problem to which attention is focused is to ensure the required level of capital adequacy. This is conditioned i.a. by their risk management system. Capital adequacy may affect credit risk substantially. Besides others, the level of credit risk may be affected to a considerable extent by application of hedging instruments. This paper presents conclusions of the executed comparison of the existing and new private law provisions in the Czech Republic and, based on that, draws new opportunities and difficulties for banks in managing their credit risk and capital adequacy. The focus is only on the hedging instruments that may affect the activities of banks in a significant way.

Bank capital, liquidity and risk in Ghana

Purpose Capital, risk and liquidity are the vitality of the banking industry, which can improve the efficiency of banking and promote the efficiency of resource allocation. The purpose of this study is to examine how Basel III new liquidity ratios affect bank capital and risk adjustments and how banks respond to the new liquidity rules. Design/methodology/approach The authors adopted the system generalized method of moments (GMM) to examine how Basel III new liquidity ratios affect bank capital and risk adjustments and how banks respond to the new liquidity rules. Based on the call reports data from banks, GMM was used to test the hypotheses that new liquidity ratios affect bank capital and risk adjustments, as well as how banks respond to the regulation. Findings The results indicate banks targeted capital, risk and liquidity and simultaneously coordinate short-term adjustments in capital and risk. New liquidity measures enable banks to coordinate risk and liquidity decisions. Short-term adjustments in new liquidity rules inversely impact bank capital. Short-term adjustments in new liquidity rules inversely impact bank capital and capital adjustments adversely affect changes in the liquidity coverage ratio (LCR). Research limitations/implications The primary results revealed that Ghanaian banks simultaneously coordinate and target capital, risk exposure and liquidity level. Also, capital adjustments positively influence risk adjustments and vice versa while bidirectional negative coordination exists between bank capital and risk on one hand and liquidity on the other hand. Short-term adjustments in new liquidity rule inversely impact bank capital and capital adjustments adversely affect changes in the LCR. The findings partially confirm the theoretical predictions of Repullo (2005) regarding the negative links between capital, risk and liquidity but the authors have higher capital induces higher risk. Practical implications Banks should balance off their targeted risk and liquidity in order not to sacrifice capital accumulation for liquidity. Originality/value This research offers new contributions in the research of bank management of capital and liquidity toward banks during a financial crisis from a theoretical perspective and trust management from an applicative perspective.

Deep Learning-Based Method for Computing Initial Margin

Following the guidelines of the Basel III agreement (2013), large financial institutions are forced to incorporate additional collateral, known as Initial Margin, in their transactions in OTC markets. Currently, the computation of such collateral is performed following the Standard Initial Margin Model (SIMM) methodology. Focusing on a portfolio consisting of an interest rate swap, we propose the use of Artificial Neural Networks (ANN) to approximate the Initial Margin value of the portfolio over its lifetime. The goal is to find an optimal configuration of structural hyperparameters, as well as to analyze the robustness of the network to variations in the model parameters and swap features.

Basel III liquidity regulatory framework and bank liquidity creation in MENA countries

Purpose This paper aims to investigate the potential impact of the Basel III liquidity requirements, namely, the net stable funding ratio (NSFR) and the liquidity coverage ratio (LCR), on bank liquidity creation. Design/methodology/approach The authors developed a dynamic panel model using the Quasi-Maximum Likelihood estimation on an unbalanced panel dataset of 129 commercial banks operating in 10 Middle Eastern and North African (MENA) countries from 2009 to 2017. Findings The results show that the NSFR significantly negatively affects liquidity creation. Similarly, the LCR exerts a substantial negative impact on the liquidity creation of the sampled MENA banks. These findings suggest that complying with both liquidity requirements tends to curtail liquidity creation. Moreover, further regression analysis of large and small bank sub-samples uncovered results similar to the overall MENA sample. Research limitations/implications The findings raise interesting policy implications and suggest a trade-off between the benefits of the financial resiliency induced by implementing liquidity requirements and the creation of liquidity essential for promoting economic growth in the region. Originality/value Most empirical research focuses on the relationship between bank capital and liquidity creation. To the knowledge, this paper is the first to provide empirical evidence on the effect of both the NSFR and LCR regulatory liquidity standards on bank liquidity creation in the MENA region.