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1. The need for assessing the contribution to systemic risk from each financial institution: During stress times, the failure of a systemically important financial institution can have catastrophic effects on the whole financial system and the real economy. Policy makers and financial regulators need to accurately assess the level of contribution to systemic risk from each institution.

2. Alternative methods for measuring systemic risk: The Financial Stability Board (FSB) currently uses an indicator-based model based on balance-sheet data to classify Systemically Important Banks (SIBs). However, this approach has been criticized for its lack of transparency and accountability. Researchers have proposed alternative methods based on statistical and mathematical fundamentals using market data to identify SIBs in a more satisfactory and verifiable way.

3. The use of CoVaR metric: The authors propose an advanced quantitative methodology based on copula function properties and Extreme Value Theory (EVT) principles. They use the Conditional VaR (CoVaR) metric, which measures the Value-at-Risk (VaR) of the financial system conditional on the distress of a single institution. This allows them to estimate the marginal contribution to systemic risk of each financial institution, quantifying how much an institution adds to the risk of the financial system. This approach takes into account the macro dimension of systemic risk and can be used to calibrate capital surcharges required for SIBs.

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此外,文章没有探讨其他可能存在的系统性风险度量方法。它只关注了CoVaR度量,并暗示这是评估金融机构系统性风险贡献最合适的方法。然而,有很多其他方法可用于评估系统性风险,如Delta CoVaR、MES等。忽略其他方法可能导致对系统性风险的全面理解不足。