Macro Stress Testing Research Articles

Macro Stress Testing the Credit Risk of Conventional and Participation Banks in Turkey: A Nonparametric Quantile Regression Approach

ABSTRACT This paper applies a novel time series-based additive nonparametric quantile regression technique to stress test the credit risk of conventional and participation banks in Turkey. We particularly examine the effects of the exchange rate, unemployment rate, the policy interest rate, and the public debt-to-GDP ratio on the non-performing loan ratio (NPL) of Turkish banks at distinct quantile levels. We find that their effects are heterogeneous and significantly vary across different types of banks and quantiles. Overall, participation banks are more vulnerable to negative scenarios associated with the exchange rate, unemployment rate, and public debt ratio than conventional banks.

How Micro Data Improve the Estimation of Household Credit Risk Within the Macro Stress Testing Framework

How Micro Data Improve the Estimation of Household Credit Risk Within the Macro Stress Testing Framework

DAMPAK PERUBAHAN VARIABEL EKONOMI MAKRO TERHADAP KINERJA KEUANGAN BUMN SEKTOR ENERGI

This study aims to analyze the impact of macroeconomic variables changes on the financial performance of energy SOE’s such as PT Pertamina (Persero), PT Perusahaan Gas Negara (Persero) Tbk, PT Perusahaan Listrik Negara (Persero). These impacts are projected by using Macro Stress Test model. The results showed that from five macroeconomic variables (GDP Growth, exchange rates, oil price, interest rates, and inflation), only two variables that significantly affected the financial performance of the energy SOE’s, there are exchange rate and oil prince that have positive impact on Pertamina and PGN while at the same time give the negative impact on PLN.

A Guide on the Application of Micro and Macro Stress Testing

A Guide on the Application of Micro and Macro Stress Testing

Macro-Stress Testing NPLs in the Banking Sector in Namibia

This paper examined the impact of macroeconomic variables, namely real GDP growth, house price growth and changes in the repo rate on the non-performing loan (NPL) ratio in Namibia using data from 2004Q1 to 2020Q1. The study used a vector auto-regressive (VAR) model and impulse response analysis to estimate the impact of changes in macroeconomic conditions on NPLs, and further conducted stress testings on NPL ratio over 4 - 6 quarter horizons. Empirical evidence from this study shows that macroeconomic variables such as real GDP growth rate, the house price growth rate and the repo rate have a statistically significant impact, and material impact on the non-performing loans in the banking sector in Namibia. Largely, a positive growth rate shock in a quarter will reduce NPL ratio by more than half percentage point over two quarters. Similarly, a positive shock of about 4.0 percent in a quarter will reduce NPL ratio by more than 1.2 percentage points over four quarter horizons. Macro-stress-testing results revealed that a deterioration of the GDP growth rate by more than one standard deviation will increase the NPL ratio from 2.46 to 2.78 over four quarter horizons. Meanwhile, the combined effects of deteriorating the GDP growth rate and falling house prices further exacerbated the vulnerability of the banking sector. This study contributes to our understanding of the interplay between macroeconomic conditions and financial sector resilience in Namibia. In practical application, it shows that macro-stress testing techniques are useful to study the importance of macro-financial and feedback effects from the financial sector to the real economy. Technically, central banks must develop models that capture important macro-financial and feedback effects, and regulatory attention must be devoted to monitoring spillover effects from worsening financial conditions to the real economy.

Exploring risks in syndicated loan networks: Evidence from real estate investment trusts

This study explores credit and systemic risks in the interconnected market for syndicated loans to Japan's real estate investment trusts (J-REITs). Although earlier studies have investigated various aspects of the syndicated loan market, few have considered the financial network and risk resilience perspectives. To bridge this gap, I conduct network analysis using credit exposures or Euclidean distance between loans and perform a macrostress test by extending Furfine's algorithm. The analysis results indicate that Japanese major banks, large regional banks, and J-REITs play a key role in terms of degree centrality. In addition, the test results show that no J-REIT's default causes default contagion of the lending institutions based on syndicated loans outstanding at the end of 2021. Overall, this study provides effective methodologies to evaluate the interconnectedness between loans as well as risk contagion from borrowers to lenders in a two-mode network for syndicated loans.

Stress Testing Financial Systems: Macro and Micro Stress Tests, Basel Standards and Value-at-Risk as Financial Stability Measures

Stress Testing Financial Systems: Macro and Micro Stress Tests, Basel Standards and Value-at-Risk as Financial Stability Measures

Nonlinear linkages between bank asset quality and profitability: evidence from dynamic and quantile approaches using a global sample

PurposeThe purpose of this study is to examine whether the relationship between asset quality and profitability is linear or nonlinear, using a global dataset containing 2,943 banks from advanced and emerging economies.Design/methodology/approachThe authors use the U-shape test to investigate the existence of a nonlinear relationship between asset quality and profitability. In addition, the dynamic panel generalised method of moments (GMM) and quantile regression are used to examine the nonlinear effect of profitability on nonperforming loans (NPLs).FindingsAfter controlling for macroeconomic and bank internal factors, the authors find empirical evidence supporting the existence of a nonlinear relationship in the form of a U-shape. This is also confirmed through the three-stage U test procedure. After distinguishing between advanced and emerging economies, the authors also find that, in advanced markets, the credit policy responds more rapidly to changes in credit market conditions than in emerging markets, providing insights into credit market dynamics.Research limitations/implicationsFurther research can check the robustness of this study’s findings in different markets and investigate the existence of nonlinearity in other bank variables.Practical implicationsIn a nutshell, the results demonstrate potential implications for policymakers who need to carefully monitor banks' lending behaviour to ensure that banks do not lower lending standards. In addition, banking regulators and supervisors should consider the possible nonlinear relationship in their risk assessments and macrostress tests. Further, these results are important for bank managers, who should monitor the performance of their loan portfolios to ensure that their credit officers do not lower credit standards. Likewise, for banks located in an emerging economy, investing in human capital and advanced technologies can enable them to respond more effectively to changes in the credit market.Originality/valueTo the best of the authors' knowledge, this study is considered the first to provide empirical evidence for the nonlinear relationship between asset quality and profitability.

Macro-stress testing dividend income. Evidence from euro area banks

This paper employs panel data methods to estimate a macro-financial model for dividend income for a sample of euro area banks, with results indicating that financial and macroeconomic variables help explain dividend income. Using the estimated parameters, the study conducts a scenario analysis projecting dividend income over a three-year horizon conditional on the baseline and adverse macroeconomic scenarios prepared for the 2020 EU-wide stress test. The resulting projections show that dividend income is markedly more conservative under the adverse scenario compared to the baseline scenario. This implies that it is important to take account of financial and macroeconomic variables when stress testing dividend income of banks. Relying on scenario-independent dividend income projections might lead to a misrepresentation of banking-sector soundness and resilience to shocks.

Construction of an Industry Cycle Indicator for Profitability Prediction Analysis of Aggregate Firms in Bangladesh

Purpose of this study: In the aggregate industrial sector, government intervention to influence demand within the economy is generally counterproductive, while the optimal policy is to concentrate on supply-side reforms that help the economy become efficient. The objective of this study was to construct a unique industry cycle indicator for Bangladeshi aggregate firms within this industrial sector. The specific objectives were to assemble a unique industry cycle indicator which recommends early signals of a firm’s industrial vulnerability, identify industry cycle indicator turning points and evaluate the predictive performance of the industry. The industry cycle indicator model demonstrates the macroeconomic fluctuations in the industrial sector. Methodology: The industry cycle indicator was constructed following the approach of the Conference Board (2000). The result wasthen tested for robustness with a macro-stress test. Lagged independent variables were used in this study to allow early predictions by the ICI for the year in which the financial crisis happened. Main Findings: The industry cycle indicator model underplays the role of aggregate industrial efficiency in influencing the economic cycle. By forecasting directional changes, this leading indicator allows policymakers to be made aware of revolutions in the financial industry and to undertake early precautionary steps to prevent vulnerability. Here, the constructed industry cycle indicator demonstrates a remarkable lead time of around 6 months for predictions and outperforms by the leading against the reference series. Research Limitations/Implications: The industry cycle indicator model rejects the Keynesian approach and also rejects monetarism. It tends to be associated with neo-classical economics. The ICI generally assumes that shocks to productivity lead to economic fluctuations. In other words, a temporary fall in output is an inevitable consequence of a drop in productivity within the industrial sector. It also leads to adjustments to this new equilibrium and enables resources to discover more productive uses. Novelty/Originality: This research demonstrates that enhanced knowledge of components of the macro-prudential policy framework combined with the existence of a certain degree of standardisation of the macro-prudential tools and indicators is essential. This can significantly develop the capability of the financial markets supervisory authorities to forecast systemic risk and to avoid or reduce the consequences of industrial crises. The present study reflects a situation for upcoming researchers who intend to study and develop their interests in this area.

Review Paper on Composite Leading Index Creation for Forecasting the Bangladeshi Financial Sector

In perspective of the economic vulnerability faced by banks in financial sector, this study mirrors the methodology used by Shumway (2001) – the dynamic hazard model that is able to forecast systemic risk in financial market arena. Here, the terminology followed is based on the CAMELS framework variables: capital adequacy, asset, management, earnings, liquidity and sensitivity to market risk. The objective of this study is to construct a macroprudential indicator (MPI) for the case of Bangladeshi financial market. The result will then be tested for robustness with macro-stress test. Lagged independent variables will be used in the simple hazard model to allow early prediction of MPI in the year in which the crisis happens. The empirical findings can be used as a guideline for the Bangladesh Government and policy makers in accessing, examining and forecasting the health of the Bangladeshi financial system and formulate suitable financial system policies for control. MPI generates information about systemic risk allowing the detection of potential economic crises functioning as an early warning indicator. Government and policy makers will be able to make early preparation in cushioning any potential crises by means of the MPI. Thus the impact of the crises could be minimized and eventually reduce its impact on the Bangladesh economy. The specific objectives are to assemble a novel MPI that is able to recommend early signals of financial market vulnerability, to identify the MPI turning points and establish a comprehensive reference chronology for Bangladeshi financial market and to evaluate the predictive performance of newly constructed MPI on characterizing Bangladeshi financial sector.

Resilience of Indian banks: Macroeconomic stress test modeling for credit risk

The macro stress testing is an integral part of the credit risk management exercise to judge the strength of banks in hypothetical stress situations. The present paper develops the macroeconomic stress testing model and checks the resilience of banks across different groups of banks in India like the public sector, private, and foreign banks in maintaining the minimum required regulatory capital at the time of stress situations. The stress testing exercise is undertaken by the use of panel data models to evaluate the impact of likely changes in macro parameters on the non‐performing loans under three stress scenarios like baseline, medium, and severe. The impact of these stress testing is substantial for the public sector banks as compared to private and foreign banks. Except for the few banks, all other public sector banks are not able to sustain the macro stress scenarios and became insolvent. In opposite to this, all the foreign banks are able to sustain all the stress scenarios. The private banks are also able to withstand the assumed crisis, except few banks failed to do so. The study may be useful for studying the preparedness of banks to face the crisis period and also helps them to get themselves equipped with the required capital to meet those circumstances.

A historical loss approach to community bank stress testing

Abstract We develop a top-down macro stress test that assesses a community bank's ability to withstand a severe and prolonged period of high credit losses. The model groups banks by geography and subjects them to the 90th percentile chargeoff rates that banks experienced between 2008 and 2012. Because of local data limitations, our historical loss approach better reflects patterns of community bank stress than a linear econometric approach that estimates the relationship between macroeconomic conditions and bank performance. We put all U.S. community banks at year-end 2017 through the test and highlight two results. First, banks are much better prepared to withstand an adverse shock than they were on the verge of the financial crisis because banks have shifted away from the riskiest loan types. Second, the Tax Cuts and Jobs Act of 2017 has increased bank insolvency risk from an adverse shock in 2018 because the higher bank capital is more than offset by the weaker automatic stabilizer effect from operating losses.

Macro Stress Testing Credit Risk: Case of Madagascar Banking Sector

Abstract This study proposes to assess the vulnerability of banking sector’s credit portfolio under macroeconomic shocks and to evaluate its impact on banking system capitalization. Our method uses the Global Vector Autoregressive (GVAR) Model to generate adverse macroeconomic scenarios. The GVAR model is combining by the satellite credit risk equation to find the non-performing loan under stress conditions. The advantage of using GVAR model is that on the one hand, it captures the transmission of global, external and domestic macroeconomic shocks on banks non-performing loans. On the other hand, this model considers the nonlinear pattern between business cycle and the bank credit risk indicator during the extreme events as highlighting by the macro stress test literature. The forecast of non-performing loan is then used to obtain stress projections for capital requirement for the banking system level. This article attempts to fill the lacks concerning the stress testing works about Madagascar which study is a recent framework, whose no study on dynamic macro stress testing was treated before. The Results outline the interaction of aggregate non-performing loan with macroeconomic evolution. The horizon of capital prediction shows that banking sector reacts most to a GDP shock. Also, Madagascar banking sector is quite resilient and remains sufficiently capitalized under all macroeconomic scenarios designed with a solvency ratio higher than the minimum regulatory CAR ratio.

Stress Testing: A Measure of Financial Stability across ASEAN-5

A banking operation is at the epicenter of financial intermediation, and there is no perfect substitute for it in capital markets. Because a banking operation revolves around a constant inventory of risks, in the event of a financial or economic crisis, banks therefore get hit as the first line of defense, and then the broader economic activity is adversely affected if the financial turmoil exacerbates. Today, all central banks of ASEAN-5 design and conduct own micro and macro stress tests as a measure of financial stability. The main results of all three stress scenarios (i.e. baseline, adverse, and severely adverse) are not only informative to central banks and regulatory supervisors, but they contribute positively to the policy decision-making process; stress testing results also help bank executives (and risk managers) better manage risks, and academia for research. Stress testing is overly misunderstood and often confused with macroeconomic forecasting and early-warning indicator. Stress testing is not a standalone tool and it does not supplant other tools in the central bank’s arsenal; quite the opposite, stress testing is indispensable when complemented by another analytical method, model, or technique such as value-at-risk (VaR). Even though the five founding members of ASEAN-5 have made remarkable strides since the late 1990s in bringing their respective domestic banking sectors in line with the international standards (i.e. Basel III), they must continue with introducing more structural reforms and stay away from instability-inflicting policies.

Управління валютним ризиком банку в умовах турбулентності на світових фінансових ринках

The article is aimed at researching the theoretical-methodological and practical aspects of the bank’s currency risk management. To solve the tasks set, the authors use general scientific and specific methods, in particular: logic-dialectical, mathematical and graphic. Based on generalization, analysis and comparison of different approaches, the methods and instruments for managing the bank’s currency risk are systematized. The bank’s currency risks are typed and the main determinants of their occurrence are identified. The types of currency risk hedging instruments are systematized and their contents are disclosed. The essence of the bank’s currency position, the methodology of its account are disclosed and the necessity of compliance with the methodology are substantiated. The main operations that influence the bank’s currency position are identified. An analytical assessment of the currency position of banks is performed (JSC CB «PrivatBank», JSC «Oschadbank», JSC «Raiffeisen Bank Aval», JSC «A-Bank»); the model of maximization of the bank’s profits is computed and appropriate conclusions about their activities are drawn. With the use of economic-mathematical instrumentarium the dynamics of the hryvnia currency exchange rate are forecasted and the indicators of VaR for banks (JSC CB «PrivatBank», JSC«Oschadbank», JSC «Raiffeisen Bank Aval», JSC «A-Bank») are calculated according to different time horizons. It is determined that the model of minimization of currency risk through currency position management serves as an effective instrument for analyzing and substantiating internal limits of currency risk and permissible ranges of changes in financial results of the bank’s activity. Prospects for further research are: 1) development of an instrumentarium for currency risk assessment based on ARCH and GARCH models of various modifications; 2) development of macro stress tests with a focus on currency risk and taking into account the systemic characteristic, which is the transmission of currency risk to other sectors of both the financial market and the economy.

Regional effect of monetary policy based on GVAR model and machine learning

Monetary policy is an important means for a country to regulate macroeconomic operations and achieve established economic goals. Moreover, a reasonable monetary policy improves the efficiency of financial operations on a global scale and effectively resolves the financial crisis. At present, scholars from various countries have begun to pay attention to the issue of differentiated formulation of monetary policy among regions. This paper combines machine learning to construct a monetary policy differentiation effect analysis model based on the GVAR model. Moreover, this paper uses the gray correlation analysis method to obtain the gray correlation matrix between industries, and then introduces the industry’s own characteristics, industry relevance and macroeconomic factors into the macro stress test of credit risk. In addition, this paper constructs a conduction model based on the industry GVAR model, and uses the first-order difference sequence of GDP growth rate, CPI growth rate and M2 growth rate of each economic region to construct a GVAR model to test the impulse response function. The results of the test show that the monetary policy shocks of various economic regions are significantly different. All in all, the research results show that the performance of the model constructed in this paper is good.

Random thinning model with a truncated credit quality vulnerability factor: Application to top-down-type credit risk assessment

In the top-down approach of intensity-based credit risk modeling, a procedure called “random thinning” is needed to obtain credit event intensities for sub-portfolios. This paper presents a random thinning model incorporating a risk factor called the credit quality vulnerability factor (CQVF) to capture time-series variation in credit event occurrence in a target sub-portfolio. In particular, we propose a type of CQVF that follows truncated normal distributions specified by macroeconomic variables. Using credit event samples of Japanese firms, our empirical analysis aims to clarify the applicability and effectiveness of the proposed model to practical credit risk management. Since macroeconomic variables are included in our model, it is applicable to the macro-stress testing of portfolio credit risk management within a top-down-type framework.

Macro stress testing euro area banks’ fees and commissions

This paper uses panel econometric techniques to estimate a macro-financial model for fee and commission income over total assets for a broad sample of euro area banks. Using the estimated parameters, it conducts a scenario analysis projecting the fee and commission income ratio over a three-year horizon conditional on the baseline and adverse macroeconomic scenarios used in the 2016 EU-wide stress test. The results indicate that the fee and commission income ratio is varying in particular with changes in its own lag, the short-term interest rate, stock market returns and real GDP growth. They also show that the fee and commission income ratio projections are more conservative under the adverse scenario than under the baseline scenario. These findings suggest that stress tests assuming scenario-independent fee and commission income projections are likely to be flawed.

A new macro stress testing approach for financial realignment in the Eurozone

Contrary to the common approach of stress-testing under which banks are evaluated whether they are distressed, this empirical study chooses to move from the micro stress test approach to a wider new macro stress test category. By being able to stress testing the entire economy of the Eurozone, it will permit big banks to fail and, at the same time, will open room for new banking players to enter the sector, promoting the essence of a healthy destruction. The analysis performs a battery of stress tests, by implementing VaR, Cornish-Fisher VaR, Monte Carlo VaR, Expected Shortfall, Cornish-Fisher Expected Shortfall, and Monte Carlo Expected Shortfall. At the same time, it explicitly considers the new regulatory approach of IFRS9 to incorporate extreme values from forecasted series in the distributions. The analysis also performs two versions of stress tests, one including TARGET2 and one without it. The results document that future stress tests should include TARGET2 values in order to capture a better picture of the stressed economy. The findings from these stress tests clearly illustrate that although there has been a trough after the distress call of 2008, this trough ended. These are results derived without including the TARGET2 transfers. By including the TARGET2 transfers we receive a different picture that possibly acts as a protective mechanism against any future crisis. Caution is still advised, possibly due to some lingering imbalances within the Eurozone.