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This 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.

The 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.

The 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.

The model-based framework eliminates some of the key problems associated with traditional scenario-based approaches and is easily adaptable to Islamic finance.

The purpose of this paper is to measure the systemic importance of industry in the world economic system under the system-wide event – the crisis of 2008-2009, by viewing this system as a weighted directed network of interconnected industries.

First, the authors investigate this crisis at three different levels based on network-related indicators: the “macro” global level, the “meso” country level, and the “micro” industry level. This investigation not only provides evidence for the systemic influence, that is, systemic risk, of the crisis, but also reveals the contagion mechanism of the crisis, which supports the stress testing. Second, the authors use a network-related business intelligence algorithm, the combined hyperlink-induced topic search (HITS) algorithm, to measure the contribution of a given individual industry to the overall risk of the economic system or, in other words, the systemic importance of the individual industry.

The HITS algorithm considers both the market information and the interconnectedness of the industries. Based on the stress testing, the performance of the combined HITS is compared with the purely market-based systemic risk measurement. The results show that the combined HITS outperforms the baseline in finding the top N systemically important industries.

The combined HITS algorithm provides a novel network-based perspective of systemic risk measurement.

Measuring the systemic importance based on the combined HITS algorithm can help managers and regulators design effective risk management policies. In this respect, the work initiates a research direction of studying the systemic risk in a business system based on a network-related business intelligence algorithm because the business system can be viewed as an interconnected network.

The Iranian banking industry has been greatly affected by dramatic changes in macroeconomic conditions over the past several decades owing to volatile oil revenues, changing fiscal and monetary policies, and the imposition of US sanctions. The main objective of this paper is to estimate potential credit losses in the Iranian banking sector due to macroeconomic shocks and assess the minimum economic capital requirements under the baseline and distressed scenarios. The paper also contrasts the applications of linear and nonlinear models in estimating the impacts of macroeconomic shocks on financial institutions.

The paper uses a multistage approach to derive the portfolio loss distribution for banks. In the first step, the dynamic relationship between the selected macroeconomic variables are estimated using a VAR model to generate the stress scenarios. In the second step, the default probabilities are estimated using a quantile regression model and the results are compared with those of the conventional linear models. Finally, the default probabilities are simulated for a one-year time horizon using Monte-Carlo method and the portfolio loss distribution is calculated for hypothetical portfolios. The expected loss includes the loss given default for loans drawn randomly and uniformly distributed and exposed at default values when loans are assigned a fixed value.

The results indicate that the loss distributions under all scenarios are skewed to the right, with the linear model results being very similar to those of quantile at the 50% quantile, but very unlike those at the 10% and 90% quantiles. Specifically, the quantile model for the 90% (10%) quantile generates estimates of minimum economic capital requirement that are considerably higher (lower) than those using the linear model.

The study has focused on credit risk because of lack of data on other types of risk at individual bank level. The future studies can estimate the aggregate economic capital using a risk aggregation approach and a panel data (not presently available), which could further improve the accuracy of the estimates.

The fiscal and monetary authorities in developing countries, specially oil-exporting countries, can follow the risk assessment approach to assess the health of their banking system and adapt policies to mitigate the impacts of large macroeconomic shocks on their financial markets.

This is the first paper estimating the portfolio loss distribution for the Iranian banks under turbulent macroeconomic conditions using linear and nonlinear models. The case study can be applied to other developing and emerging countries, particularly those highly dependent on natural resources, prone to extreme macroeconomic shocks.

This paper aims to provide a methodology for designing and conducting solvency stress tests, under the standardised approach as per IFSB-15, including the establishment of macro-financial links, running scenarios with variation of assumptions and stress scenario parameters; apply and illustrate this methodology by providing a stylised numerical example through a tractable Excel-based framework, through which Islamic Commercial Banks (ICBs) can introduce additional regulatory requirements and show that they would remain in compliance with all capital requirements after a moderate to severe shock; and identify the potential remedial actions that can be envisaged by an ICB.

The paper uses the data of the one of the groups to which certain amendments and related assumptions are applied to develop a stylised numerical example for solvency stress-testing purposes. The example uses a Stress Testing Matrix (STeM; a step-by-step approach) to illustrate the stress-testing process. The methodology of the paper uses a two-stage process. The first stage consists of calculating the capital adequacy ratio (CAR) of the ICB using the IFSB formulae, depending on how the profit sharing investment account (PSIA) are treated in the respective jurisdiction. The second stage is the application of the stress scenarios and shocks.

Taking into account the specificities of ICBs such as their use of PSIA, the results highlighted the sensitivity of the CAR of an ICB with respect to the changes in the values of alpha and the proportion of unrestricted PSIA on the funding side. The simulation also indicated that an ICB operating above the minimum CAR could be vulnerable to shocks of various degrees of gravity, thus bringing the CAR below the minimum regulatory requirement and necessitating appropriate remedial actions.

The paper highlights various implications and relationships arising out of stress testing for ICBs, including the vulnerability of an ICB under defined scenarios, demanding appropriate immediate remedial actions on future capital resources and capital needs. The findings of the paper provide a preliminary discussion on developing a comprehensive toolkit for the ICBs similar to what is developed by the International Monetary Fund Financial Sector Assessment Programme.

This paper focuses on the gap with respect to the stress testing of capital adequacy. The main contribution of the paper is twofold. The first is the development of an STeM – a step-by-step approach, which provides a method for simulating solvency (i.e. capital adequacy) stress tests for ICBs; the second is the demonstration of the potentially crucial impact of profit-sharing investment accounts and the way they are managed by ICBs (notably the smoothing of profit payouts) in assessing the capital adequacy of the ICBs.

The purpose of this paper is to present an innovative model to evaluate the fair price of a subset of structured products for a hypothetical US structured bond.

The authors assume that interest rates dynamics are described by the Cox–Ingersoll–Ross process. They conduct robustness checks by stress testing against parameter and model uncertainty.

The fair value of the bond is robust under any parameter or model misspecification. In addition, a change in the price seems to be more sensitive to long-term yields rather than short-or mid-term yields. The authors provide a better understanding of the relationship between bond prices and business cycles: a slight change in the current structure would have a significant effect on the bond price only during economic expansions.

The recent global financial crisis has led policymakers and the financial press to blame financial innovation through accusations of structured products being highly complex. Much of the criticism is based on the fact that investors were not able to properly price and fully understand the risks of their investments. Regulators should ensure proper pricing of these products to protect both the investors and the system. Fair pricing is important for bond issuers, governments or corporations to design their product at an attractive price for investors.

This paper fills a gap in the extant literature by providing an innovative model based on an Euler–Maruyama Monte Carlo scheme to price structured products.

Capital is key to any financial institution. Companies in other industries need capital to buy property and production equipment. For financial institutions, the primary function of capital is to cover unexpected credit and market risks losses, because risk of such losses inevitably accompanies a bank’s core business of lending money and making markets. David Rowe, Dean Jovic and Richard Reeves explain why it is crucial for financial institutions to build an advanced economic capital framework and how that plays into current initiatives to implement the Basel II Capital Accord.

Commercial banks face several risks, including credit, liquidity, operational and disruptive risks. In addition to these risks that are challenging for banks to control and manage, crises and disasters can exert substantially more destructive shocks. These shocks can exacerbate internal risks and cause severe damage to the bank's performance, leading banks to bankruptcy and closure. This study aims to facilitate achieving resilient banking policies through a model-based assessment of business continuity management (BCM) policies.

By applying a system dynamics (SD) methodology, a systemic model that includes a causal structure of the banking business is presented. To build a simulation model, data are collected from a commercial bank in Iran. By presenting the simulation model of the bank's business, the consequences of some given crises on the bank's performance are tested, and the effectiveness of risk and crisis management policies is evaluated. Vensim Personal Learning Edition (PLE) software is used to construct the simulation model.

Results indicate that the current BCM policies do not show appropriate resilience in the face of various crises. Commercial banks cannot create sustainable value for the banks' shareholders despite the possibility of profitability, as the shareholders lack adequate resilience and soundness. These commercial banks do not have the appropriate resilience for the next pandemic after coronavirus disease 2019 (COVID-19). Moreover, the robustness of the current banking business model is very fragile for the banking run crisis.

A forward-looking view of resilient banking can be obtained by combining liquidity coverage, stable funding, capital adequacy and insights from stress tests. Resilient banking requires a balanced combination of robustness, soundness and profitability.

The present study is a combination of bank business management, risk and resilience management and SD simulation. This approach can analyze and simulate the dynamics of bank resilience. Additionally, present of a decision support system (DSS) to analyze and simulate the outcomes of different crisis management policies and solutions is an innovative approach to developing effective and resilient banking policies.