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Modeling and Estimating the Risk of the Banking System in Form of a Network Model Using CoVaR (in Persian)

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Listed:
  • Sadeghi sharifi, Seyed jalal

    (Shahid Behshti University)

  • ,

    (Tehran of University)

  • Ostadhashemi, Ali

    (Shahid Behshti of University)

Abstract

In this paper, a multi-layered network model of the banking system is designed to explain the systemic risk of the banking system of Iran. This model shows how the dependence of the balance sheet structure of banks results in the crisis from one bank to another, and ultimately causes a crisis in the economy as a whole. It is assumed that the banking system is composed of banks with their balance sheet structure dependent on each other. To estimate the systemic risk of the banking system, the daily index data of banks indexes are used between December 2008 and April 2018 and the value at risk of returning daily index data is estimated using an exponential GARCH model. The daily returns of the stock market index are taken as representative of the real economy, Quantile regression is estimated at two levels of 50% and 1%. In the following, based on the estimated parameters in quantum regression and also on the basis of the CoVar Adrian and Brunnermeier (2016), the risk of the banking system is estimated. The results show that the average CoVaR is estimated at -0.8587, which is consistent with negative expectations and represents a high systemic risk of the banking system.

Suggested Citation

  • Sadeghi sharifi, Seyed jalal & , & Ostadhashemi, Ali, 2018. "Modeling and Estimating the Risk of the Banking System in Form of a Network Model Using CoVaR (in Persian)," Journal of Monetary and Banking Research (فصلنامه پژوهش‌های پولی-بانکی), Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 11(36), pages 183-210, September.
    • Handle: RePEc:mbr:jmbres:v:11:y:2018:i:36:p:183-210
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    References listed on IDEAS

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    1. Gauthier, Céline & Lehar, Alfred & Souissi, Moez, 2012. "Macroprudential capital requirements and systemic risk," Journal of Financial Intermediation, Elsevier, vol. 21(4), pages 594-618.
    2. Girardi, Giulio & Tolga Ergün, A., 2013. "Systemic risk measurement: Multivariate GARCH estimation of CoVaR," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3169-3180.
    3. Céline Gauthier & Alfred Lehar & Moez Souissi, 2010. "Macroprudential Regulation and Systemic Capital Requirements," Staff Working Papers 10-4, Bank of Canada.
    4. Samuel G. Hanson & Anil K. Kashyap & Jeremy C. Stein, 2011. "A Macroprudential Approach to Financial Regulation," Journal of Economic Perspectives, American Economic Association, vol. 25(1), pages 3-28, Winter.
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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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