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Measuring the probability of a financial crisis

Author

Listed:
  • Robert F. Engle

    (Stern School of Business, New York University, New York, NY 10012)

  • Tianyue Ruan

    (NUS Business School, National University of Singapore, Singapore 119245)

Abstract

When financial firms are undercapitalized, they are vulnerable to external shocks. The natural response to such vulnerability is to reduce leverage, and this can endogenously start a financial crisis. Excessive credit growth, the main cause of financial crises, is reflected in the undercapitalization of the financial sector. Market-based measures of systemic risk such as SRISK, which stands for systemic risk, enable monitoring how such weakness emerges and progresses in real time. In this paper, we develop quantitative estimates of the level of systemic risk in the financial sector that precipitates a financial crisis. Common approaches to reduce leverage correspond to specific scaling of systemic risk measures. In an econometric framework that recognizes financial crises represent left tail events for the economy, we estimate the relationship between SRISK and the financial crisis severity for 23 developed countries. We develop a probability of crisis measure and an SRISK capacity measure based on our estimates. Our analysis highlights the important global externality whereby the risk of a crisis in one country is strongly influenced by the undercapitalization of the rest of the world.

Suggested Citation

  • Robert F. Engle & Tianyue Ruan, 2019. "Measuring the probability of a financial crisis," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(37), pages 18341-18346, September.
  • Handle: RePEc:nas:journl:v:116:y:2019:p:18341-18346
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    Citations

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    Cited by:

    1. Olivier Mesly & Hareesh Mavoori & Nicolas Huck, 2023. "The Role of Financial Spinning, Learning, and Predation in Market Failure," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(1), pages 517-543, March.
    2. Ghufran Ahmad & Muhammad Suhail Rizwan & Dawood Ashraf, 2021. "Systemic risk and macroeconomic forecasting: A globally applicable copula‐based approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1420-1443, December.
    3. Vasile Brătian & Ana-Maria Acu & Diana Marieta Mihaiu & Radu-Alexandru Șerban, 2022. "Geometric Brownian Motion (GBM) of Stock Indexes and Financial Market Uncertainty in the Context of Non-Crisis and Financial Crisis Scenarios," Mathematics, MDPI, vol. 10(3), pages 1-23, January.
    4. Li, Wei-Zhen & Zhai, Jin-Rui & Jiang, Zhi-Qiang & Wang, Gang-Jin & Zhou, Wei-Xing, 2022. "Predicting tail events in a RIA-EVT-Copula framework," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    5. Kakuho Furukawa & Hibiki Ichiue & Yugo Kimura & Noriyuki Shiraki, "undated". "Too-big-to-fail Reforms and Systemic Risk," Bank of Japan Working Paper Series 21-E-1, Bank of Japan.
    6. Huck, Nicolas & Mavoori, Hareesh & Mesly, Olivier, 2020. "The rationality of irrationality in times of financial crises," Economic Modelling, Elsevier, vol. 89(C), pages 337-350.

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