Stress Test Model Research Articles

How does carbon trading price matter for bank loans? Evidence from Chinese banking sector

This paper investigates the impact of carbon trading prices on Chinese commercial banks. We propose a stress test model to calculate the decline of firms’ liabilities and the climate-driven loss of commercial banks to different industries. The results indicate that State-Owned Banks suffer the highest climate-driven loss among all types of banks. City commercial banks suffer the highest climate-driven loss ratio since they maintain a relatively low level of Tier 1 core capital. Beijing, Shanghai, Jiangsu, and Zhejiang maintain the highest levels of climate-driven loss ratio. Furthermore, the allocation of loans portfolio across different industries also influences climate-driven loss of banks. The climate-driven loss to the electric power, heat, gas, and water production and supply sector is the largest in all industries. It is necessary for banks to incorporate climate factors into the risk assessment framework.

Spurious Default Probability Projections in Credit Risk Stress Testing Models

Spurious Default Probability Projections in Credit Risk Stress Testing Models

Stress testing of the development of Russian regions in the context of external economic restrictions

Purpose: is to develop the model for stress testing of the impact of external constraints of Russian regions in the context of foreign economic constraints 2022–2023.Methods: the research is based on the theory of economic dynamics, regional economy and spatial development, the concept of the BANI world; the methodological basis of the study is a scenario approach to the formation of the stress testing model and the algorithm for determining the expected impact based on the machine learning method – the artificial neural network.Results: the study of scientific publications on the research topic, analysis of shock events, post-shock consequences (2006–2022) made it possible to substantiate feasibility of testing and differentiating the response of Russian regions to external constraints, applying the criteria of “shock-resistant” development, classifying economic space and identifying the territory with “shock-resistant” and “non-shockresistant”reactions. The model of regions stress testing has been developed, industrial and sectoral (67.6% importance) and spatial (32.4%) stabilization factors have been identified, areas of vulnerability to the restrictions of 2022-2023 and industrial regions with the potential for “non-shock-resistant” type of reaction have been identified.Conclusions and Relevance: the reaction of regions to external economic shocks (the duration of the decline period and the intensity of recovery growth) is determined by the totality of the production and spatial characteristics of the regions. The results of the study are important for the development of the theory of regional economy; they can be used byfederal and regional executive authorities of the Russian Federation.

Interaction between liquidity risk and bank solvency, a crucial effect in a framework of simultaneous equations

The “2008-09” global financial crisis has underlined that the interaction between liquidity risk and bank solvency forms an important factor that makes banks particularly vulnerable to a global crisis. At the same time, stress-testing models do not consider the dynamics between solvency and liquidity risk the possibility of reducing the impact of stress on bank solvency and financial stability. In this context, the aim of this paper is to examine this highly relevant issue in the financial literature, and answer to the main question: Is the interaction between solvency and liquidity risk empirically significant in the context of the Algerian banks? Based on an econometric model using a simultaneous equation approach on panel data of 19 banks over 6 years running from (2016 to 2021). Our results validate our hypothesis about the interaction and show that these two risks are determined simultaneously. Building on this finding, we suggest that the authorities should emphasise developing integrated liquidity and solvency stress tests. Our results also show the need of the Algerian banks to set up a regulatory framework for liquidity in line with the international prudential regulations to enhance the performance of this sector.

Quantum monte carlo for economics: Stress testing and macroeconomic deep learning

Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. We are the first to study whether Quantum Monte Carlo (QMC) algorithm can improve the runtime of economic applications and challenges in doing so. We provide a detailed introduction to quantum computing and especially the QMC algorithm. Then, we illustrate how to formulate and encode into quantum circuits (a) a bank stress testing model with credit shocks and fire sales, (b) a neoclassical investment model solved with deep learning, and (c) a realistic macro model solved with deep neural networks. We discuss potential computational gains of QMC versus classical computing systems and present a few innovations in benchmarking QMC.

COVID-19 and financial institution stability: stress testing the Eastern Caribbean currency union

PurposeThis paper aims to simulate the potential impact of increasing non-performing loans (NPLs) on capital adequacy, interest income and firm value of banks and credit unions in the Eastern Caribbean Currency Union (ECCU) using stress tests.Design/methodology/approachA financial stress testing model was deployed at the levels of individual financial intermediary (FI), sectoral loan portfolio composition, individual member country, and the ECCU collectively, to investigate the impact of NPL shocks on FI stability.FindingsThe authors find that shocks impact the capital adequacy of banks less than that of credit unions, but that firm value of banks is more susceptible to increases in NPLs. Interest income responses to NPL shocks were linked to credit exposure from the tourism sector, which also reduced capital adequacy more than other economic sectors. Findings show that while the COVID-19 pandemic occasioned some increase in NPLs, the magnitude of impact was significantly mitigated by pro-stability policies including loan repayment moratoria and restructuring, guidance on the distribution of profits and deleveraging by financial institutions leading up to 2020.Originality/valueThe paper is among the first to use stress testing on the Caribbean in response to the COVID-19 pandemic. Past studies which have used stress test models in the region have not explicitly investigated the impact of credit shocks on risk-weighted assets or interest income as done herein, nor do they include credit unions in the modeling. The results offer novel evaluations as well as implications for FIs in other developing economies, especially those that share a comparable financial and economic architecture.

국내은행 스트레스테스트 모형개선에 관한 연구

Purpose - The main purpose of this study is to develop the stress test model for Korean banks by exploring the optimal Monte Carlo simulation and BIS forecasting model.
 Design/methodology/approach - This study selects 15 Korean banks as sample financial firms and collects relevant 76 quarterly data for the period between year 2000 and 2018 from KRX(Korea Excange), Bank of Korea, and FnGuide. The Regression analysis, Unit-root test, and Monte Carlo simulation are hired to analyze the data.
 Findings - First, most of the sample banks failed to keep 8% BIS ratio for the adverse and severely Adverse Scenarios, implying that Korean banks must make every effort to realize better BIS ratios under adverse market conditions. Second, we suggest the better Monte Carlo simulation model for the Korean banks by finding that the more appropriate volatility should be different depending on variables rather than simple two-sigma which has been used in the previous studies. Third, we find that the stepwise regression model is better fitted than simple regression model in forecasting macro-economic variables for the BIS variables. Fourth, we find that, for the more robust and significant statistical results in designing stress tests, Korean banks are required to construct more valid time-series and cross-sectional data-base.
 Research implications or Originality - The above results all together show that the optimal volatility in designing optimal Monte Carlo simulation varies depending on the country, and many Korean banks fail to pass sress test under the adverse and severely adverse scenarios, implying that Korean banks need to make improvement in the BIS ratio.

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.

The impact of macroeconomic scenarios on recurrent delinquency: A stress testing framework of multi-state models for mortgages

Transition probabilities between delinquency states play a key role in determining the risk profile of a lending portfolio. Stress testing and IFRS9 are topics widely discussed by academics and practitioners. In this paper, we combine dynamic multi-state models and macroeconomic scenarios to estimate a stress testing model that forecasts delinquency states and transition probabilities at the borrower level for a mortgage portfolio. For the first time, a delinquency multi-state model is estimated for residential mortgages. We explicitly analyse and control for repeated events, an aspect previously not considered in credit risk multi-state models. Furthermore, we enhance the existing methodology by estimating scenario-specific forecasts beyond the lag of time-dependent covariates. We find that the number of previous transitions have a significant impact on the level of the transition probabilities, that severe economic conditions affect younger vintages the most, and that the relative impact of the stress scenario differs by attributes observed at origination.

Abstract 5583: SUV39H1 disruption enhances the persistence and anti-tumor efficacy of CD28-costimulated human CAR T cells

Abstract Retrovirally encoded CD19-specific CARs that incorporate CD28 and CD3z signaling motifs (Rv-1928z) have induced remarkable responses in patients with refractory leukemia and lymphoma. These CARs induce a strong effector differentiation program in T cells that can limit their persistence and result in T cell dysfunction. This induction of terminal effector differentiation is accompanied by transcriptional and epigenetic changes resulting in induction of effector transcriptional factors, inhibitory receptors, and suppression of memory associated genes. In this study, we examine the effect of modulating the epigenome of human Rv-1928z CAR T cells by disruption of the histone methyl transferase, SUV39H1, which has been implicated in regulating memory to effector transition in murine T cells (Pace et al. 2018). To assess the impact of SUV39H1 on human Rv-1928z CAR T cells, we treated immune deficient mice bearing the human ALL cell line, NALM6, with limiting doses of SUV39H1-edited T cells. SUV39H1 editing (SUV39H1etd) significantly enhanced the anti-tumor efficacy of Rv-1928z CAR T cells relative to non-edited counterparts, with 9/10 NALM6 bearing mice treated with SUV39H1etd Rv-1928z surviving over the duration of observation (90 days) as compared to 1/12 mice treated with WT Rv-1928z. This enhanced tumor control in SUV39H1etd Rv-1928z CAR T cells was associated with greater initial CAR T cell proliferation upon tumor encounter and enhanced long-term CAR T cell persistence (> day 50). To assess whether the persisting SUV39H1etd Rv-1928z CAR T cells can mount an effective effector response upon tumor rechallenge, we modified the stress test model such that post primary tumor clearance (day 17), mice were rechallenged by tumor 5 times over 70 days. SUV39H1etd Rv-1928z CAR T cells outperformed WT Rv-1928z CAR T cells in eliminating NALM6 upon rechallenge. Paired genome accessibility (ATACseq) and transcriptional analysis revealed epigenetic changes associated with SUV39H1 loss in Rv-1928z CAR T cells that promote expression of memory associated transcription factors and receptors while reducing expression of inhibitory receptors and transcriptional factors associated with T cell dysfunction. In summary, we find that loss of SUV39H1 in human Rv-1928z CAR T cells enhances their anti-tumor efficacy by bringing about changes in their epigenome that enhance their functional persistence. Citation Format: Nayan Jain, Zeguo Zhao, Richard Koche, Yosi Gozlan, David Brocks, Tali Raveh-Sadka, Danny Wells, Anton Dobrin, Yuzhe Shi, Michael Lopez, Gertrude Gunset, Michel Sadelain. SUV39H1 disruption enhances the persistence and anti-tumor efficacy of CD28-costimulated human CAR T cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5583.

Adjustable-rate mortgages in the era of global reflation: How to model additional default risk?

We investigate the problem of interest rate risk transforming into default risk of adjustable-rate mortgage loans in the EU. Bank regulation is strikingly not neutral in this aspect, it explicitly favors short-duration adjustable-rate loans over long-duration fixed-rate loans in the framework of the gap management. This asymmetry in the regulation creates perverse incentives both for banks and households, which can lead to aggressive risk-taking, over-indebtedness of unhedged households, high procyclicality of mortgage markets, and increased systemic risks. We present a stress test model to quantify potential losses stemming from this specific risk from the perspective of lender institutions. We estimate the average extra capital that is needed to cover the additional risk of adjustable-rate mortgage loans in the EU to be 0.53% of the value of the total mortgage portfolio and 1.97% of the value of the adjustable-rate mortgage portfolio. We propose introducing a stress test model as a new mandatory element into banks’ risk management framework.

Updated Primer on the Forward-Looking Analysis of Risk Events (FLARE) Model: A Top-Down Stress Test Model

<ns2:p>While the bank stress test exercise conducted by the Federal Reserve System is a critical policy tool for assessing the health of large banks, the Federal Reserve has worked to build additional tools to assess the resiliency of the banking system as a whole and to address macroprudential goals. The Forward-Looking Analysis of Risk Events (FLARE) model is one such tool. This technical note describes the FLARE model, which is a top-down model that helps assess how well the banking system is positioned to weather exogenous macroeconomic shocks. FLARE estimates banking system capital under varying macroeconomic scenarios, time horizons, and other systemic shocks.</ns2:p>

Testing Bank Resiliency Through Time

<ns3:p>A resilient banking system meets the demands of households and businesses for financial services during both benign and severe macroeconomic and financial conditions. Banks' ability to weather severe macroeconomic shocks, and their willingness to continue providing financial services, depends on their levels of capital, balance sheet exposures, and ability to generate earnings. This note uses the Forward-Looking Analysis of Risk Events (FLARE) stress testing model to evaluate the resiliency of the banking system by consistently applying severe macroeconomic and financial shocks each quarter between 2014:Q1 and 2021:Q3.</ns3:p>

Effective Practices of Macroprudential Stress Testing as a Tool of Increasing the Stability of Russian Financial System in the Context of Macroeconomic Shocks

The article examines the evolution of the prudential approach to banking regulation, examines the practical contribution of the Basel Committee on Banking Supervision to the development and implementation of internationally unified practices and procedures for stress testing and supervision. The authors share the point of view that the existing methods and practices of stress testing still need improvements and methodological improvements, since they regularly allow the practical implementation of adverse scenarios leading to financial shocks and global crises. As a significant disadvantage of many actively used stress testing models, it is noted that they are often focused on complex, highly bureaucratic procedures for the preparation and analysis of financial statements, the main purpose of which is to assess the probabilities and sizes of losses and identify scenarios for the development of the situation for each specific bank, and no risks for the financial system as a whole. The authors come to the conclusion that it is advisable to prioritize the use of alternative stress testing models in crisis and post-crisis conditions, the forecasts within which are based on the actual values of financial market indicators, macroeconomic variables, and other open data. Special attention is paid to the stylized CLASS model, based on simple econometric models, as well as stress testing the current market value of V-lab. Based on the results of the study, the authors come to a number of conclusions that the role of the macroeconomic component in the procedures, methods, and algorithms for macroprudential stress testing used in Russia should increase, the degree of involvement and the sphere of responsibility for its results of key institutional units of the public administration system should expand, and macroprudential stress testing itself should not be limited to supervisory stress testing in everyday practice.

Assessing the financial condition and accounts receivable risk among US farmer cooperatives

PurposeThe purpose of this paper is to examine the financial condition and ability of farmer cooperatives to withstand significant increases in bad debt expense.Design/methodology/approachA unique data set of farmer cooperative financial statements that spans from 1996 to 2019 is used to examine the changes in profitability, solvency, liquidity and accounts receivable risk. Also, a deterministic stress test model is designed to shock bad debt expense and the resulting write-off of accounts receivable for farmer cooperatives. The stress test provides insights to the resiliency of farmer cooperatives.FindingsResults find that farmer cooperatives are in a strong financial position, which has improved over time. The majority of farmer cooperatives are able to absorb a substantial increase in bad debt expense because of their sizable, retained earnings position. However, cooperatives that have significant profitability challenges do experience much larger losses, especially mixed farmer cooperatives (roughly equally amounts of grain and farm supply sales) and large cooperatives with more than $500 million in sales.Practical implicationsThe stress test results suggest farmer cooperative managers and boards of directors could re-examine their credit policies and consider extending additional credit. Also, cooperatives should consider monitoring and identifying an optimal accounts receivable to retained earnings ratio, which is similar to how banks examine their tier 1 capital ratios.Originality/valueThe value of this study is having data that allows for the examination of the financial condition of farmer cooperatives over time. Also, having current data means the accounts receivable stress test results are more relevant and timelier. This is important because these accounts receivable are primarily tied to crop input supplies, and farmer cooperatives are a significant market participant in the crop input supply market.

ESTIMATION OF CREDIT RISK LOSSES AND MODELING OF BANK LIQUIDITY RISK

The recent crisis in the banking system has shown that the functions of banking risk management have not been given sufficient attention. This jeopardized the efficiency of the entire domestic banking system. Insufficient efficiency of the risk assessment and modeling system in domestic banks has led to a number of negative consequences for the Ukrainian economy as a whole. Therefore, the problem of developing scientific and methodological approaches to the assessment and modeling of banking risks is relevant and of practical importance. The purpose of the article is to assess credit risk losses, model liquidity risk of banks and develop practical recommendations for the introduction of modeling of liquidity risk in the activities of domestic banks. Approaches to defining the concept of banking risk are analyzed. It is established that banks operate in conditions of high credit risks which result in significant amounts of non-performing loans. Credit risk losses were assessed according to the scenarios of compromise and aggressive risk lending position. The Van Den-End liquidity stress testing model was used as a tool to identify negative market effects and financial liquidity shocks. The general tendency of the ratio of liquidity buffer to liquidity deficit taking into account the risk is determined and substantiated and the forecast for the future period is made. We found that the efficiency of the bank’s loan portfolio is low. However, there is a dynamic increase in the efficiency of the bank’s loan portfolio from 0.00982 at the beginning to 0.09447 at the end of the year. This trend is positive. According to the results of the simulation, we found that with a sufficient amount of liquidity buffers of assets in JSC “PrivatBank” their quality remains low, because the share of secondary reserves in the bank is critically low. The bank is state-owned and is constantly refinanced on the interbank credit market. This allows the bank to work only on the first stage of the scenario of this model. The bank is practically protected from risk shocks by government securities.

Systemic stress test model for shared portfolio networks

We propose a dynamic model for systemic risk using a bipartite network of banks and assets in which the weight of links and node attributes vary over time. Using market data and bank asset holdings, we are able to estimate a single parameter as an indicator of the stability of the financial system. We apply the model to the European sovereign debt crisis and observe that the results closely match real-world events (e.g., the high risk of Greek sovereign bonds and the distress of Greek banks). Our model could become complementary to existing stress tests, incorporating the contribution of interconnectivity of the banks to systemic risk in time-dependent networks. Additionally, we propose an institutional systemic importance ranking, BankRank, for the financial institutions analyzed in this study to assess the contribution of individual banks to the overall systemic risk.

Using stress testing model in measuring the impact of the financial crisis on the Jordanian commercial banks

This paper aims to answer multiple questions regarding Jordanian bank stability under credit, market, and liquidity shock scenarios in order to evaluate bank solvency and liquidity. The paper will use stress testing model to measure the effect of the financial crisis in 2008 on the Jordanian commercial banks. It will conduct various stress testing scenarios on 13 Jordanian banks with the aim of better understanding the risk profile of the Jordanian banking system. Two spreadsheet models are utilised to conduct credit, market and liquidity shocks to assess the performance of the banks under each shock. The findings of this paper demonstrate that the Jordanian banking system is generally able to withstand reasonable shocks of each type, with some addressable weaknesses such as collateral under-provisioning and liquid asset shortcomings.

Using stress testing model in measuring the impact of the financial crisis on the Jordanian commercial banks

Using stress testing model in measuring the impact of the financial crisis on the Jordanian commercial banks

Stress Testing the Financial Macrocosm

What should the next generation of financial stress tests look like? If recent crises are any guide, our strongly interlinked financial system, economy, and indeed wider society need to be viewed in unison – together, they make up a larger ‘financial macrocosm’. Studying the resilience of that larger macrocosm requires a new generation of stress testing models that capture the interconnections within the financial system, between the financial system and the real economy, and – particularly in the context of climate change – the interconnections between the natural world, the real economy, and the financial system. Such models, informed by large-scale data collection, would enable better evaluation of financial stability risks and support the design of new policy ideas to improve financial stability outcomes. In a rapidly evolving financial system that is constantly facing new threats, they would help policymakers and regulators get back into the driver’s seat. We appreciate that this vision is ambitious – the goal of this chapter is to make it plausible and to articulate what it would take to make it real. We introduce the modelling techniques and conceptual framework such an approach would be based on, outline the modelling innovations and the enabling conditions that are required, and conclude with a brief overview of the improvements to financial regulatory policy such stress tests would enable.