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Banking stability measures

Author

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  • Segoviano, Miguel A.
  • Goodhart, Charles

Abstract

The recent crisis underlined that proper estimation of distress-dependence amongst banks in a global system is essential for financial stability assessment. We present a set of banking stability measures embedding banks’ linear (correlation) and nonlinear distress-dependence, and their changes through the economic cycle, thereby allowing analysis of stability from three complementary perspectives: common distress in the system, distress between specific banks, and cascade effects associated with a specific bank. Our approach defines the banking system as a portfolio of banks and infers its multivariate density from which the proposed measures are estimated. These can be provided for developed and developing countries.

Suggested Citation

  • Segoviano, Miguel A. & Goodhart, Charles, 2009. "Banking stability measures," LSE Research Online Documents on Economics 24416, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:24416
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    References listed on IDEAS

    as
    1. Charles Goodhart & Boris Hofmann & Miguel Segoviano, 2004. "Bank Regulation and Macroeconomic Fluctuations," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 20(4), pages 591-615, Winter.
    2. Segoviano, Miguel A., 2006. "Consistent information multivariate density optimizing methodology," LSE Research Online Documents on Economics 24511, London School of Economics and Political Science, LSE Library.
    3. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1999. "Multivariate Density Forecast Evaluation And Calibration In Financial Risk Management: High-Frequency Returns On Foreign Exchange," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 661-673, November.
    4. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    5. Miguel A. Segoviano, 2006. "Portfolio Credit Risk and Macroeconomic Shocks: Applications to Stress Testing Under Data-Restricted Environments," IMF Working Papers 2006/283, International Monetary Fund.
    6. Philip Lowe & Miguel A. Segoviano, 2002. "Internal ratings, the business cycle and capital requirements: some evidence from an emerging market economy," BIS Working Papers 117, Bank for International Settlements.
    7. Segoviano, Miguel A. & Lowe, Philip, 2002. "Internal ratings, the business cycle and capital requirements: some evidence from an emerging market economy," LSE Research Online Documents on Economics 24948, London School of Economics and Political Science, LSE Library.
    8. Segoviano, Miguel A., 2006. "Conditional probability of default methodology," LSE Research Online Documents on Economics 24512, London School of Economics and Political Science, LSE Library.
    9. De Vries, C.G., 2005. "The simple economics of bank fragility," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 803-825, April.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Financial stability; portfolio risk; copula functions; entropy distribution.;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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