Stress Test Methodology Research Articles

Citlivost českých domácností na úrokový a příjmový šok. Aplikace na mikroúdajích

We present a set of practical applications of the household sector stress testing approach used at the Czech National Bank. The aim is to test households' ability to repay their loans in the event of extremely adverse economic developments. Besides this, the household sector stress test methodology has so far been used for two other purposes: (i) to construct a simple reverse stress test and explore the sensitivity of Czech households to a rise in loan interest rates and a decline in income, and (ii) to provide some supportive evidence for the calibration of debt service-to-income limits.

Correction: Type-2 diabetic aldehyde dehydrogenase 2 mutant mice (ALDH 2*2) exhibiting heart failure with preserved ejection fraction phenotype can be determined by exercise stress echocardiography.

[This corrects the article DOI: 10.1371/journal.pone.0195796.].

Road Network Resilience: How to Identify Critical Links Subject to Day-to-Day Disruptions

Disruptive events occur on road networks on a daily basis and affect traffic flow. Resilience analysis aims to assess the consequences of such disruptions by quantifying the ability of a network to absorb and react to adverse events. In this paper, we advance a methodological approach based on resilience stress testing and a dynamic mesoscopic simulator. We aim to identify and rank the links most critical to the overall performance of the road network, taking into account the dynamic properties of road traffic and focusing on day-to-day disruptions. As a metric to quantify road network performance in the presence of such disruptions, we use the increase in overall travel cost. We then compare our approach with purely topological approaches. We discuss the advantages and drawbacks of the different analyzed metrics. We prove that link ranking varies greatly depending on the metric. Specifically, the proposed stress testing methodology can produce very accurate results by taking into account demand and congestion, but requires computationally intensive simulations, being therefore prohibitive even on medium-sized networks. Conversely, purely static topological metrics can be inaccurate if they do not take into account traffic demand and network dynamics. Our study highlights the need for joining traditional traffic-agnostic topological resilience analysis with demand-aware dynamic stress testing techniques.

A review of stress test methodology

After a general introduction of the concept of bank stress testing, and the possible applications by different stakeholders, the paper provides an overview of the European Banking Authority (EBA) EU-wide stress test. It explains its main features, the scope of risks assessed, the different actors involved and the benefits of the exercise. It also explains the role of the EBA in the different stages of the exercise, the evolution of the exercise and its purpose as a tool to assess potential vulnerabilities of banks and their resilience to adverse market developments, provide transparency on banks’ exposures and as a supervisory tool. The paper then focuses on the 2018 EBA stress test and explains the main changes applied to the EBA stress test methodology in 2018 for the different risks. The paper pays special attention to the changes linked to the implementation of the new International Financial Reporting Standard (IFRS 9). It elaborates on the effects of IFRS 9 and the implications of the IFRS 9 rules for the credit risk stress test in terms of lifetime expected credit losses, the definition of stages and the movement of exposures between stages.

Type-2 diabetic aldehyde dehydrogenase 2 mutant mice (ALDH 2*2) exhibiting heart failure with preserved ejection fraction phenotype can be determined by exercise stress echocardiography.

E487K point mutation of aldehyde dehydrogenase (ALDH) 2 (ALDH2*2) in East Asians intrinsically lowers ALDH2 activity. ALDH2*2 is associated with diabetic cardiomyopathy. Diabetic patients exhibit heart failure of preserved ejection fraction (HFpEF) i.e. while the systolic heart function is preserved in them, they may exhibit diastolic dysfunction, implying a jeopardized myocardial health. Currently, it is challenging to detect cardiac functional deterioration in diabetic mice. Stress echocardiography (echo) in the clinical set-up is a procedure used to measure cardiac reserve and impaired cardiac function in coronary artery diseases. Therefore, we hypothesized that high-fat diet fed type-2 diabetic ALDH2*2 mutant mice exhibit HFpEF which can be measured by cardiac echo stress test methodology. We induced type-2 diabetes in 12-week-old male C57BL/6 and ALDH2*2 mice through a high-fat diet. At the end of 4 months of DM induction, we measured the cardiac function in diabetic and control mice of C57BL/6 and ALDH2*2 genotypes by conscious echo. Subsequently, we imposed exercise stress by allowing the mice to run on the treadmill until exhaustion. Post-stress, we measured their cardiac function again. Only after treadmill running, but not at rest, we found a significant decrease in % fractional shortening and % ejection fraction in ALDH2*2 mice with diabetes compared to C57BL/6 diabetic mice as well as non-diabetic (control) ALDH2*2 mice. The diabetic ALDH2*2 mice also exhibited poor maximal running speed and distance. Our data suggest that high-fat fed diabetic ALDH2*2 mice exhibit HFpEF and treadmill exercise stress echo test is able to determine this HFpEF in the diabetic ALDH2*2 mice.

Climate-Finance and Climate Transition Risk: An Assessment of China's Overseas Energy Investments Portfolio

The role of development finance institutions in low-income and emerging countries is fundamental to provide long-term capital for investments in climate mitigation and adaptation. Nevertheless, development finance institutions still lack sound and transparent metrics to assess the exposure of their projects to climate risks, as well as their impact on climate action. This information is crucial to allow them to deliver on their mandate, to preserve their financial position and to align beneficiary countries' economies to the climate goals. We contribute to fill in this gap by developing a novel climate stress-test methodology applied to the portfolios of overseas energy projects of two main Chinese policy banks. We estimate their exposure to two types of shocks, i.e. climate policy and balance sheet shocks, for individual energy projects across regions and energy sectors, under milder and tighter climate policy scenarios. Then, we provide several risk metrics. We find that the negative shocks are mostly concentrated on coal and oil projects and vary across regions between 4.2% and 22% of total loans value. Given the current leverage of Chinese policy banks, these losses are not negligible in comparison to banks' capital.

What do central counterparty default funds really cover? A network-based stress test answer

In the last years, increasing efforts have been put into the development of effective stress tests to quantify the resilience of financial institutions. Here we propose a stress test methodology for central counterparties based on a network characterization of clearing members, whose links correspond to direct credits and debits. This network constitutes the ground for the propagation of financial distress: equity losses caused by an initial shock with both exogenous and endogenous components reverberate within the network and are amplified through credit and liquidity contagion channels. At the end of the dynamics, we determine the vulnerability of each clearing member, which represents its potential equity loss. We apply the proposed framework to the Fixed Income asset class of CC&G, the central counterparty operating in Italy whose main cleared securities are Italian Government Bonds. We consider two different scenarios: a distributed, plausible initial shock, as well as a shock corresponding to the cover 2 regulatory requirement (the simultaneous default of the two most exposed clearing members). Although the two situations lead to similar results after an unlimited reverberation of shocks on the network, the distress propagation is much more hasty in the latter case, with a large number of additional defaults triggered at early stages of the dynamics. Our results thus show that setting a default fund to cover insolvencies only on a cover 2 basis may not be adequate for taming systemic events, and only very conservative default funds, such as CC&G's one, can face total losses due to the shock propagation. Overall, our network-based stress test represents a refined tool for calibrating default fund amounts.

Human Cardiac 31P-MR Spectroscopy at 3 Tesla Cannot Detect Failing Myocardial Energy Homeostasis during Exercise.

Phosphorus-31 magnetic resonance spectroscopy (31P-MRS) is a unique non-invasive imaging modality for probing in vivo high-energy phosphate metabolism in the human heart. We investigated whether current 31P-MRS methodology would allow for clinical applications to detect exercise-induced changes in (patho-)physiological myocardial energy metabolism. Hereto, measurement variability and repeatability of three commonly used localized 31P-MRS methods [3D image-selected in vivo spectroscopy (ISIS) and 1D ISIS with 1D chemical shift imaging (CSI) oriented either perpendicular or parallel to the surface coil] to quantify the myocardial phosphocreatine (PCr) to adenosine triphosphate (ATP) ratio in healthy humans (n = 8) at rest were determined on a clinical 3 Tesla MR system. Numerical simulations of myocardial energy homeostasis in response to increased cardiac work rates were performed using a biophysical model of myocardial oxidative metabolism. Hypertrophic cardiomyopathy was modeled by either inefficient sarcomere ATP utilization or decreased mitochondrial ATP synthesis. The effect of creatine depletion on myocardial energy homeostasis was explored for both conditions. The mean in vivo myocardial PCr/ATP ratio measured with 3D ISIS was 1.57 ± 0.17 with a large repeatability coefficient of 40.4%. For 1D CSI in a 1D ISIS-selected slice perpendicular to the surface coil, the PCr/ATP ratio was 2.78 ± 0.50 (repeatability 42.5%). With 1D CSI in a 1D ISIS-selected slice parallel to the surface coil, the PCr/ATP ratio was 1.70 ± 0.56 (repeatability 43.7%). The model predicted a PCr/ATP ratio reduction of only 10% at the maximal cardiac work rate in normal myocardium. Hypertrophic cardiomyopathy led to lower PCr/ATP ratios for high cardiac work rates, which was exacerbated by creatine depletion. Simulations illustrated that when conducting cardiac 31P-MRS exercise stress testing with large measurement error margins, results obtained under pathophysiologic conditions may still lie well within the 95% confidence interval of normal myocardial PCr/ATP dynamics. Current measurement precision of localized 31P-MRS for quantification of the myocardial PCr/ATP ratio precludes the detection of the changes predicted by computational modeling. This hampers clinical employment of 31P-MRS for diagnostic testing and risk stratification, and warrants developments in cardiac 31P-MRS exercise stress testing methodology.

Integration of stress testing with graph theory to assess the resilience of urban road networks under seismic hazards

Transportation networks daily provide accessibility and crucial services to societies. However, they must also maintain an acceptable level of service to critical infrastructures in the case of disruptions, especially during natural disasters. We have developed a method for assessing the resilience of transportation network topology when exposed to environmental hazards. This approach integrates graph theory with stress testing methodology and involves five basic steps: (1) establishment of a scenario set that covers a range of seismic damage potential in the network, (2) assessment of resilience using various graph-based metrics, (3) topology-based simulations, (4) evaluation of changes in graph-based metrics, and (5) examination of resilience in terms of spatial distribution of critical nodes and the entire network topology. Our case study was from the city of Kathmandu in Nepal, where the earthquake on April 25, 2015, followed by a major aftershock on May 12, 2015, led to numerous casualties and caused significant damage. Therefore, it is a good example for demonstrating and validating the developed methodology. The results presented here indicate that the proposed approach is quite efficient and accurate in assisting stakeholders when evaluating the resilience of transportation networks based on their topology.

A quantitative framework for testing the resilience of Islamic finance portfolios under IFSB and Basel capital rules

PurposeThis paper aims to introduce a model-based stress-testing methodology for Islamic finance products. The importance of stress testing was indeed clearly underlined by the adverse developments in the global finance industry. One of the key takeaways was the need to strengthen the coverage of the capital framework. Cognisant of this fact, Basel III encapsulates provisions to enhance the financial sector’s ability to withstand shocks arising from possible stress events, thereby reducing adverse spillovers into the real economy. Similarly, the Islamic Financial Services Board requires Islamic financial institutions to run stress tests as part of capital planning.Design/methodology/approachThe authors perform thorough backtests on Islamic and conventional portfolios under widely used risk models, which are characterised by an underlying conditional volatility framework and distribution, to identify the most suitable risk model specification. Associated with an appropriate initial shock and estimation window size, the paper also conducts a model-based stress test to examine whether the stress losses estimated by the selected models compare favourably to the historical shocks.FindingsThe results suggest that the model-based framework, when combined with an appropriate risk model and distribution, can successfully reproduce past stress periods. The conditional empirical risk model is the most effective one in both long and short portfolio cases – particularly when combined with a long-enough estimation window. The relative performance of normal vs heavy-tailed distributions and symmetric vs asymmetric risk models, on the other hand, is highly dependent on whether the portfolio is long or short. Finally, the authors find that the Islamic portfolio is generally associated with lower historical stress losses as compared to the conventional portfolio.Originality/valueThe model-based framework eliminates some of the key problems associated with traditional scenario-based approaches and is easily adaptable to Islamic finance.

A climate stress-test of the financial system

The urgency of estimating the impact of climate risks on the financial system is increasingly recognized among scholars and practitioners. By adopting a network approach to financial dependencies, we look at how climate policy risk might propagate through the financial system. We develop a network-based climate stress-test methodology and apply it to large Euro Area banks in a ‘green’ and a ‘brown’ scenario. We find that direct and indirect exposures to climate-policy-relevant sectors represent a large portion of investors’ equity portfolios, especially for investment and pension funds. Additionally, the portion of banks’ loan portfolios exposed to these sectors is comparable to banks’ capital. Our results suggest that climate policy timing matters. An early and stable policy framework would allow for smooth asset value adjustments and lead to potential net winners and losers. In contrast, a late and abrupt policy framework could have adverse systemic consequences.

System stress testing of bank liquidity risk

Using a stress test methodology for bank liquidity risk we estimate the aggregate liquidity shortfall in the U.S. commercial banking system at the height of 2007–09 crisis, identifying key sources of funding vulnerabilities and the dominant composition of liquid asset holdings against liquidity shocks. The largest liquidity shocks to the system are estimated in the first half of the crisis, in line with Acharya and Mora (2015). Large banks experience the largest liquidity shortfall in 2008:Q1 ($154billion or 14% of total assets) and small banks in 2007:Q4 ($117billion or 11% of total assets). The dominant funding vulnerability to the system stems from large time deposits, while government securities largely dominate other classes of liquid assets as liquidity backstop. The analysis draws on detailed bank-level data on balance sheet flows of funds and applies stochastic dominance efficiency methods to capture liquidity risk diversification effects across assets and liabilities.

A proximity based macro stress testing framework

Abstract In this a paper a non-linear macro stress testing methodology with focus on early warning is developed. The methodology builds on a variant of Random Forests and its proximity measures. It is embedded in a framework, in which naturally defined contagion and feedback effects transfer the impact of stressing a relatively small part of the observations on the whole dataset, allowing to estimate a stressed future state. It will be shown that contagion can be directly derived from the proximities while iterating the proximity based contagion leads to naturally defined feedback effects. Since the methodology is Random Forests based the framework can be estimated on large numbers of risk indicators up to big data dimensions, fostering the stability of the results while reducing inaccuracies in estimated stress scenarios by only stressing a small part of the observations. This procedure allows accurate forecasting of events under stress and the emergence of a potential macro crisis. The framework also estimates a set of the most influential economic indicators leading to the potential crisis, which can then be used as indications of remediation or prevention.

Proximity Based Stress Testing and Scenario Construction

In this a paper a non-linear macro stress testing methodology with focus on early warning is developed. The methodology builds on a variant of Random Forests and its proximity measures. It is embedded in a framework, in which naturally defined contagion and feedback effects transfer the impact of stressing a relatively small part of the observations on the whole dataset, allowing to estimate a stressed future state. It will be shown that contagion can be directly derived from the proximities while iterating the proximity based contagion leads to naturally defined feedback effects. Since the methodology is Random Forests based the framework can be estimated on large numbers of risk indicators up to big data dimensions, fostering the stability of the results while reducing inaccuracies in estimated stress scenarios by only stressing a small part of the observations. This procedure allows accurate forecasting of events under stress and the emergence of a potential macro crisis. The framework also estimates a set of the most influential economic indicators leading to the potential crisis, which can then be used as indications of remediation or prevention.

Lapse risk in life insurance: Correlation and contagion effects among policyholders’ behaviors

The present paper proposes a new methodology to model the lapse risk in life insurance by integrating the dynamic aspects of policyholders’ behaviors and the dependency of the lapse intensity on macroeconomic conditions. Our approach, suitable to stable economic regimes as well as stress scenarios, introduces a mathematical framework where the lapse intensity follows a dynamic contagion process, see Dassios and Zhao (2011). This allows to capture both contagion and correlation potentially arising among insureds’ behaviors. In this framework, an external market driven jump component drives the lapse intensity process depending on the interest rate trajectory: when the spread between the market interest rates and the contractual crediting rate crosses a given threshold, the insurer is likely to experience more surrenders. A log-normal dynamic for the forward rates is introduced to build trajectories of an observable market variable and mimic the effect of a macroeconomic triggering event based on interest rates on the lapse intensity. Contrary to previous works, our shot-noise intensity is not constant and the resulting intensity process is not Markovian. Closed-form expressions and analytic sensitivities for the moments of the lapse intensity are provided, showing how lapses can be affected by massive copycat behaviors. Further analyses are then conducted to illustrate how the mean risk varies depending on the model’s parameters, while a simulation study compares our results with those obtained using standard practices. The numerical outputs highlight a potential misestimation of the expected number of lapses under extreme scenarios when using classical stress testing methodologies.

The NBU Approach to Stress Testing the Ukrainian Banking System

This paper gives a review of the stress testing methodology developed by the National Bank of Ukraine (NBU) in cooperation with the International Monetary Fund (IMF) for assessing the robustness of the Ukrainian banking sector, following one of the largest economic downturns in Ukrainian history. It starts with a brief summary of stress testing approaches and methods used throughout the world, their classifications, and key features. It then moves on to give an overview of the stress testing approach applied by the NBU, concluding with remarks as to the specificity of this approach and avenues for further development.

Testy warunków skrajnych jako element oceny bezpieczeństwa sektora bankowego

The article presents the latest approach to stress tests applied by the EuropeanBanking Authority and national supervisory authorities, including methodology,scenarios, key assumptions and results of a study. The results of stress testsindicate that the banking sector in Poland is in good condition as banks showedhigher level of capital adequacy than most of the banks from the European Union,reflecting the stability of the banking sector. Stress test methodology used by theEuropean Central Bank is also contained in the paper. The role of stress tests asan instrument for enhancing the stability of financial institutions and the needfor further work on stress testing are also discussed.

Stress testing and model validation: application of the Bayesian approach to a credit risk portfolio

Following the recent global financial crisis, regulators have recognized the importance of stress testing, in part due to the impact of model risk, and have implemented supervisory requirements in both the revised Basel framework and the Comprehensive Capital Analysis and Review (CCAR) program. We contribute to the literature by developing a Bayesian-based credit risk stress-testing methodology, which can be implemented by small-to-medium-sized banks, as well as presenting empirical results using data from the recent CCAR implementations. Through the application of a Bayesian model, we can formally incorporate exogenous scenarios and also quantify the uncertainty in model output that results from stochastic model inputs. We contribute to the model validation literature by comparing the proportional model risk buffer measure of the severely adverse cumulative nine-quarter loss estimate - a common way to estimate, being a measure of statistical uncertainty generated by a model - obtained from our empirical implementation of the Bayesian to the frequentist model. We find it to be 40% higher in the former than in the latter. As for the model validation exercise, the Bayesian model outperforms the frequentist model statistically significantly, according to the cumulative percentage error metric, by 2% (1.5%) over the entire sample (downturn period).

Forecasting the reliability of the mechanism of guaranteeing retirement savings in Russia using stress testing

This article outlines the methodology and results of stress testing for financial stability in the mechanism being created in Russia for securing retirement savings. The authors have come to the conclusion about the sufficiency of a guaranteed coverage in the forthcoming 20 years for an economic shock comparable with the 2008–2009 crisis. The forecast reserve of stability allows us to calculate the rate of contributions to funds for guaranteeing pension accumulations at the minimum level under the law, but the calculations prove the necessity of introducing differentiated contributions for different investment institutions.

Liquidity at Risk for Mutual Funds

We explicitly show what should be taken into account when the liquidity measure Liquidity at Risk (LaR) is applied to mutual funds. We adapt the LaR such that it is able to cover certain issues arising when dealing with fund redemption data from the real world and give guidelines what has to be considered in practice. We also give an automated procedure for determining the threshold parameter of a generalized Pareto distribution (GPD) by means of a given data set. Moreover, we supplement our findings by a thorough backtesting analysis and introduce a suitable stresstesting methodology for the fund adapted LaR.