Bank Default Research Articles

Estimating volatility clustering and variance risk premium effects on bank default indicators

Default risk increases substantially during financial stress times due to mainly the two reasons: volatility clustering and investors’ desire to protect themselves from such increases in volatility. It manifested in the aftermath of the Global Financial Crisis of 2008–2009 with unpleasant outcomes of many bankruptcies and severe financial distress. To account for these features, we adapted the structural credit risk approach to include both time-varying (return) volatility and risk premium about the return volatility itself. By applying the model to US banks, we obtain better bank default indicators in comparison to the benchmark models.

Home Bias in Sovereign Exposure and the Probability of Bank Default - Evidence from EU Stress Test Data

Since the European debt crisis economists and politicians discuss intensively the sovereign-bank nexus. The high activity in sovereign bond issuance required to mitigate the burden of the Covid19 crisis will rather intensify this debate than calm it down. Surprisingly, however, we still have only limited knowledge about the impact of a home bias in sovereign exposure on bank stability. This paper provides a new way to use European stress test data to study this relationship. In addition, we explore the effect on a bank’s probability of default if the existing capital requirement privilege for EU sovereign exposures were abolished. Our results support the conceptual idea behind the nexus theory. Interestingly, the effect of a home bias on bank stability is contingent on the home country’s solvency. If the home country is sufficiently solvent, investments in home sovereign bonds may improve bank stability. The findings clearly support the benefits of additional CET1 capital buffers. Regulation focusing on the home bias should account for heterogeneous effects depending on the home country’s solvency.

Implementation of Composite Index to Determine Risk Tend to Bank Default at Rural Bank

This study aims to identify risk tend to bank default using a composite index at rural banks in Indonesia. The method used in this study uses logit. The data used are primary and secondary. Primary data is used when weighting the composite index by respondents who are representatives of banking associations, bank authorities and directors. Secondary data obtained from Bank publication reports during period 2009 - 2018. The population used in this study is rural banks in East Java and sample selection based on purposive sampling. The results showed that NIM, NPL, OR and ROA have significant affect to risk of tend to bank default. Meanwhile, LDR have no significant affect to risk of tend to bank default. Rural bank must pay attention to the variables that are indicators of the risk tend to bank default.This study is useful for providing a different perspective in identifying bank default using a composite index that has never been conducted before.

The effect of the balance sheet approach on the usefulness of accounting information in assessing bank default risk

This study investigates the effect of the balance sheet approach, where financial reporting focuses on asset and liability valuation, on the usefulness of the capital adequacy ratio in the evaluation of bank default risk by credit rating agencies. We examine Japanese banks, which play the central role in the Japanese economy, and whose capital adequacy ratios are affected by the fair value measurement under the balance sheet approach. We adopt Demerjian’s (2011) approach to develop a bank-level measure of balance sheet focus. Although we find a significant positive correlation between the slack of the regulatory capital adequacy ratio and issuer rating, we find that this positive correlation is significantly weakened as a bank’s dependence on the balance sheet approach increases. The results suggest that the regulatory capital adequacy ratio based on a bank’s accounting information provides useful information for the evaluation of default risk but that rating agencies discount capital information that relies heavily on the balance sheet approach when estimating a bank’s default risk.

The Role of Financial Analysis in Mitigating Banking Default " Study on Yemeni Islamic Banks"

The study problem was that Yemeni Islamic banks did not rely on the results and outputs of financial analysis to predict failure before it occurs. Accordingly, the study aimed to find out to what extent Yemeni banks depend on financial analysis as a tool for predicting the default, and the extent of its ability to mitigate bank default at these banks. It also aimed to identify whether these banks use all financial analysis tools for making credit decisions. The researchers used the descriptive analytical method and distributed a questionnaire to the sample (50) of the credit employees at Yemeni Islamic banks. The data were analyzed using SPSS. The findings revealed that the Yemeni Islamic banks depend on financial analysis as a basis for disclosure of default, which has a main role in mitigating banking default. The banks usually use multi financial analysis tools when evaluating the credit status of clients; they do not use predicting financial default models as a main tool to predict failure before it occurs; and they do not have early warning systems to predict any possibility of customers’ default.

The Role of Financial Analysis in Mitigating Banking Default " Study on Yemeni Islamic Banks"

The study problem was that Yemeni Islamic banks did not rely on the results and outputs of financial analysis to predict failure before it occurs. Accordingly, the study aimed to find out to what extent Yemeni banks depend on financial analysis as a tool for predicting the default, and the extent of its ability to mitigate bank default at these banks. It also aimed to identify whether these banks use all financial analysis tools for making credit decisions. The researchers used the descriptive analytical method and distributed a questionnaire to the sample (50) of the credit employees at Yemeni Islamic banks. The data were analyzed using SPSS. The findings revealed that the Yemeni Islamic banks depend on financial analysis as a basis for disclosure of default, which has a main role in mitigating banking default. The banks usually use multi financial analysis tools when evaluating the credit status of clients; they do not use predicting financial default models as a main tool to predict failure before it occurs; and they do not have early warning systems to predict any possibility of customers’ default.

Predicting Bank Defaults in Ukraine: A Macro-Micro Perspective

This paper develops an early warning model (EWM) for a micro-macro analysis of individual and aggregated bank vulnerabilities in Ukraine. We applied a stepwise logit for predicting defaults at Ukrainian banks based on a panel bank and macro-level data from Q1 2009 to Q3 2019. Next, we aggregated individual bank default probabilities to provide policymakers with information about the general state of the financial system with a particular focus on generating a signal for countercyclical capital buffer (CCB) activation. Our key findings suggest that the probability of default exceeding 11% could signal about a vulnerable state in a bank and, in the aggregated model, in a financial system in general. The aggregated model successfully issues an out-of-sample signal of a systemic crisis four periods ahead of the start of the 2014-2015 turmoil.

Diversification Can Control Probability of Default or Risk, but Not Both

One of the controversies of diversification is that it may not be beneficial to banks, as it tends to increase systemic risk. Recent theoretical and empirical work have addressed this problem. We argue, from a theoretical perspective, that this controversy ultimately depends on how risk is assessed or measured. In particular, we observe that when one talks about random losses (risk) there are two intertwined approaches. On the one hand, one can fix the loss level and ask with what probability does that occur. On the other, one can fix a confidence level (or probability of loss) and ask, for example, what is the smallest loss with that probability. In a banking system, a systemic crisis occurs when all banks default simultaneously. Using the theoretical work of Wagner, where he proposed a simple model of a banking system in which a systemic crisis increases with diversification, we extend his analysis to show that if one allows for short positions; then the probability of default decreases, but the risk, measured by the value at risk (a non-coherent risk measure) increases. This brings up an interesting methodological question for risk management: Should we consider the probability of a given (acceptable) loss or, should we consider the minimum loss with an acceptable probability? We show that, within Wagner’s model and depending on which question is asked, a different answer can be obtained. This, in turn, lead us to discuss some implications of these results for risk managers and regulators.

Loans from my neighbours: East Asian commercial banks, financial integration, and bank default risk

This study investigates the impact of financial integration on recipient country bank default risk and, in particular, if that relationship is moderated by the type of financial integration. Using the system generalized method of moments (GMM), the study finds that financial integration lowers bank default risk in the recipient countries. The impact is primarily driven by the foreign claims extended by Asian lenders and the foreign claims extended via local affiliates. These results show that the close proximity of lenders and borrowers or ‘local’ knowledge via an affiliate presence alleviates information asymmetry, allowing for effective monitoring and disciplining of the loan relationship. The result supports the fostering of financial integration, promoting deeper intra-regional connectedness throughout East Asia. When foreign claims come from outside East Asia, policy makers should encourage presence through local affiliates, as this has an equivalent impact.

Valuasi One Period Coupon Bond dengan Aset Mengikuti Model Geometric Brownian Motion with Jump Diffusion

<p>One period coupon bond gives coupon once a bond life together with the principal debt. If the firm’s asset value on maturity date is insufficient to meet the debtholder’s claim, then the firm is stated as default. The well-known model for predicting default probability is KMV-Merton model. Under this model, it is assumed that the return on the firm’s assets is distributed normally and their behaviour can be described with the Geometric Brownian Motion (GBM) formula. In practice, most of the financial data tend to have heavy-tailed distribution. It indicates that the data contain some extreme values. GBM with Jump is a popular model to capture the extreme values. In this paper, we evaluate a corporate bond which has some extreme condition in their asset value and predicts the default probability in the maturity date. Empirical studies were carried out on bond that is issued by CIMB Niaga Bank that has a payment due in November 2020. The result shows that modelling the asset value is more appropriate by using GBM with Jump rather than GBM modelling. Estimation to CIMB Niaga Bank equity in November 2020 is IDR 246,533,573,844,229.00. The liability of this company is IDR 4,205,751,155,771.00. The prediction of CIMB Niaga Bank default probability is 1.065812 ´ 10<sup>-8</sup> at the bond maturity. It indicates that the company is considered capable of fulfilling the obligations at the maturity date.</p><p><strong>Keywords: </strong>jump diffusion, extreme value, probability default, equity, liability</p>

Stress Testing of Banking Systems: an examination against the Shocks of Macroeconomic Variables

In the past years, overdue due receivables of the banks have increased in an unprecedented way compared to all the facilities granted in Iran’s banking network, showing the not very acceptable quality of bank assets that decrease the bank credit and make them financially unstable. The macroeconomic variables in this article are as follow: GDP growth rate, economic growth, exchange rate, inflation rate, unemployment rate, government debt. The decrease in this amount of arrears shows the ability of banks to maintain their resources. At this research, after identifying the macroeconomic variables affecting the default of banks using the stress test and applying one standard deviation with the help of the historical scenario, the study examined the banks’ resilience to the shocks of these variables from 2006 to 2019. The results indicated that the shock of the economic growth rate had the greatest effect. In other words, the decrease in the economic growth rate had the greatest effect on the increase of borrowers’ default rates. In addition to this, shocks of economic growth and government debt have highly effect on the borrowers’ default rates and inflation rate, unemployment rate, GDP growth rate and exchange rate have a significant impact upon borrowers’ default rates.

ИССЛЕДОВАНИЕ ДИСКРИМИНАЦИОННОЙ СПОСОБНОСТИ ФИНАНСОВЫХ КОЭФФИЦИЕНТОВ ROA И ROE ВЫЯВЛЯТЬ ПРОБЛЕМНЫЕ БАНКИ (РОССИЙСКИЙ ОПЫТ)

The approach is to construct a generalized linear regression model with a dependent variable of the indicator of default of the Bank. The explanatory variables in this model are the financial coefficients ROA and ROE. According to the constructed model, the ROC curve is reconstructed and the Gini coefficient is calculated, which serves as a quantitative measure of the discriminative ability of the exogenous variables ROA and ROE to explain the bank default.

Liquidity Regulation and Bank Risk

In this paper, we investigate the impact of liquidity requirements on bank risk. We take advantage of the implementation of the Liquidity Balance Rule (LBR) in the Netherlands in 2003 and analyze its impact on bank default risk. The LBR was imposed on Dutch banks only and did not apply to other banks operating elsewhere within the Eurozone. Using this differential regulatory treatment to overcome identification concerns, we find that following the introduction of the LBR, the risk of Dutch banks declined relatively to counterparts not affected by the rule. Concomitantly, despite the lower cost of funding driven by the LBR, the profitability of Dutch banks decreased in comparison with other banks in Europe, as a result of a decrease in income accruing from interest-bearing activities. Our findings also indicate that relatively to unaffected banks, Dutch banks might not have actively tried to offset their loss in interest income by increasing interest rates of loans. However, better financing conditions allowed Dutch banks to increase the shares of deposits and capital on the liability side of their balance sheets.

Risk, Inside Money, and the Real Economy

In modern economies, most money takes the form of inside money; deposits created by commercial banks to fund credit extension. Because inside money is used as a payment instrument, doubts about the risks associated with credit extension can affect aggregate outcomes. This paper constructs and analyzes a model of risky credit extension, inside money creation, and monetary exchange. When credit extension is sufficiently risky, a positive probability of bank default arises and this affects the return characteristics of inside money. Depositors then demand a risk premium for holding inside money, which drives a wedge between bankers' funding costs and the social benefits of money creation. This wedge negatively affects credit extension, output, and welfare. A government can restore efficiency by swapping risky inside money for risk-free forms of government debt.

АNALYTICAL EVALUATION OF INDICATORS OF BANKING SYSTEM CAPITALIZATION AND MACROECONOMIC STABILITY IN UKRAINE

Current trends in economic development of both the state as a whole and its individual sectors lead to a more detailed assessment of indicators of banking sector capitalization as indicators of system financial stability. Also, socio-economic fluctuations at the international level instigate a revision of macroeconomic stability indicators, which will allow analyzing the possibility of further development of Ukraine. It is important to note that a sufficient level of banking system capitalization is the basis for covering potential risks. With a high level of capitalization, the risk of bank default decreases, which has a positive effect on macroeconomic stability. The purpose of the study is to conduct an analytical assessment of capitalization and macroeconomic stability, to determine the forecast values of bank capital and GDP of Ukraine for 2021-2022 and to develop practical recommendations for improving the level of these indicators. The main tools used during the study are: methods of grouping, comparison and generalization, the method of exponential smoothing of time series, construction of an additive model, graphical method. STATISTICA was used for forecasting. The article provides an analytical review of the main indicators of banking system capitalization of Ukraine. Indicators of macroeconomic stability are studied. It is determined that the main indicators of capitalization in Ukraine are: H1 and H2 standards, the amount of balance capital of banks. The forecast of the volume of capital of banks of Ukraine and GDP for 2021-2022 by the method of exponential smoothing is carried out. Forecasting is performed with and without taking into account the seasonal component. The constructed models are adequate, so the results can be used in practice. Having forecast values of capital, banks will be able to adjust their resource policy and determine the deficit or surplus of this indicator. The projected values of GDP will help to adjust the state policy in terms of the formation of the indicator and to develop appropriate measures to further improve its level. Thus, the analytical review should be conducted on an ongoing basis, taking into account changes in the socio-economic policy of the state, fluctuations in the banking sector and changes in the world economy.

IS CREDIT DEFAULT SWAP SPREAD A LEADING INDICATOR OF BANK DEFAULT RISK : Evidence of Indian banks during the COVID -19 Pandemic

IS CREDIT DEFAULT SWAP SPREAD A LEADING INDICATOR OF BANK DEFAULT RISK : Evidence of Indian banks during the COVID -19 Pandemic

Oligopoly Banking, Risky Investment, and Monetary Policy

Oligopolistic competition in the banking sector and risk in the real economy are important characteristics of developed economies, but have so far mostly been abstracted from in monetary economics. We build a dynamic general equilibrium model of monetary policy transmission that incorporates both of these features and document that including them leads to important insights in our understanding of the transmission mechanism. Various equilibrium cases can occur, and policies have differing effects in these cases. We calibrate the model to the U.S. economy in 2016-2019 in order to study how changes in the degree of banking competition or the policy rate would have affected equilibrium outcomes. We find that doubling banking competition would have increased welfare by 1.02\%, but at the cost of increasing the probability of bank default from 0.02\% to 0.44\%. We further find that the policy rate was set optimally to minimize the probability of bank default, but that a decrease in the policy rate by 1pp would have increased welfare by 0.40\%. We also show that bank profits are increasing in the policy rate, in particular when interest rates are low. Thus, a 1pp reduction in the policy rate would have reduced profits per bank by 35.5\% in our calibrated economy. Finally, we document that monetary policy pass-through is incomplete under imperfect competition in the banking sector, as a change in the policy rate by 1pp leads to a change of only 0.92pp in the loan rate, while pass-through to the deposit rate is nearly complete for rate increases, but almost zero for rate reductions due to the zero-lower bound.

Solvency Distress Contagion Risk: Network Structure, Bank Heterogeneity and Systemic Resilience

We systematically analyse how network structure and bank characteristics affect solvency distress contagion risk in interbank networks. As interbank networks become more connected and more regular in structure, the contagion risk of system-wide shocks and individual bank defaults initially increases and then decreases, all else being equal. The low density heterogeneous network structures that typify real interbank networks are particularly prone to solvency distress contagion risk, when banks are similar in balance sheet size and capitalisation. However, when networks are calibrated to UK data, the higher capitalisation of large, highly-connected banks relative to their interbank exposures significantly increases the resilience of the system and reduces the importance of network structure. These findings reinforce the importance and effectiveness of imposing higher capital buffers on systemically important banks and of policies that limit interbank exposures. We also demonstrate that for real-world interbank networks, simple network metrics other than individual bank connectedness do not provide robust indicators for monitoring solvency contagion risk, suggesting that policymakers should continue efforts to model these risks explicitly rather than rely on simple aggregate indicators.

Counterparty Default Risk and Monetary Policy in Unsecured Interbank Lending Markets

Banks bargain over the cost of unsecured loans in a model of interbank lending markets characterized by counterparty default risk. The risk an individual bank defaults depends on both idiosyncratic and aggregate factors and impacts loan rates and participation in the interbank loan market. After a deterioration of the aggregate factor affecting default risk, participation in interbank lending markets declines, and both individual and the average interbank loan rates rise. The model suggests that some policy actions enacted during the late-2000s financial crisis may have reduced participation and increased spreads in unsecured interbank loan markets.

The transmission of default risk between banks and countries based on CAViaR models

This study investigates the relationship between country and bank credit default swap spreads by employing CAViaR models proposed by White et al.. By choosing a sample of six major European economies, we find that the bank default risk plays an important role in determining the country default risk in the Netherlands and Germany. By illustrating the time-varying VaRs, we find that the VaRs in these countries are significant from 2010 onward, showing a greater exposure to common shocks during the European debt crisis. Our results would be useful for investors and monetary authorities.