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Macroeconomic shocks and credit risk stress testing the Iranian banking sector

机译:宏观经济冲击和信用风险压力测试伊朗银行业

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Purpose- 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. Design/methodology/approach - 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. Findings - 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. Research limitations/implications - 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. Practical implications - 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. Originality/value - 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.
机译:目的 - 由于石油收入,不断变化的财政和货币政策,改变美国制裁,伊朗银行业在过去几十年中受到宏观经济条件的显着变化的影响。本文主要目的是由于宏观经济冲击,估算伊朗银行业的潜在信贷损失,并评估基线和苦恼情景下的最低经济资本要求。本文还对比线性和非线性模型在估计宏观经济冲击对金融机构的影响的效果。设计/方法/方法 - 本文采用多级方法来导出银行的投资组合损失分配。在第一步中,使用VAR模型估计所选择的宏观经济变量之间的动态关系以生成应力场景。在第二步中,使用量级回归模型估计默认概率,并将结果与​​传统线性模型的结果进行比较。最后,使用Monte-Carlo方法模拟默认概率,使用Monte-Carlo方法来计算,并且为假设组合计算了组合损耗分布。预期损失包括在贷款分配固定值时随机绘制并在默认值下绘制的贷款给出的丢失默认丢失。结果表明,结果表明,所有场景下的损耗分布都偏向于右侧,线性模型导致与50%分位数的分量值非常相似,但与10%和90%的量级不同。具体地,90%(10%)定位物的量子模型产生最小经济资本要求的估计,其比使用线性模型更高的(更低)。研究限制/影响 - 该研究由于在个人银行级别缺乏关于其他类型的风险数据而缺乏信用风险。未来的研究可以利用风险聚合方法和面板数据(未目前提供的)估算总经济资本,这可以进一步提高估计的准确性。实际意义 - 发展中国家的财政和货币当局专门的石油出口国可以遵循风险评估方法,以评估银行制度的健康,并适应政策,以减轻大型宏观经济冲击对金融市场的影响。原创性/值 - 这是使用线性和非线性模型在湍流宏观经济条件下估算伊朗银行的第一个纸张损失分布。案例研究可以应用于其他发展中国家和新兴国家,特别是那些高度依赖自然资源的国家,容易出现极度宏观经济震动。

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