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The equity risk posed by the too-big-to-fail banks: a Foster–Hart estimation

Author

Listed:
  • Abhinav Anand

    (University College Dublin)

  • Tiantian Li

    (SUNY Stony Brook)

  • Tetsuo Kurosaki

    (Bank of Japan)

  • Young Shin Kim

    (SUNY Stony Brook)

Abstract

The measurement of financial risk relies on two factors: determination of riskiness by use of an appropriate risk measure; and the distribution according to which returns are governed. Wrong estimates of either, severely compromise the accuracy of computed risk. We identify the too-big-to-fail banks with the set of “Global Systemically Important Banks” (G-SIBs) and analyze the equity risk of its equally weighted portfolio by means of the “Foster–Hart risk measure”—a bankruptcy-proof, reserve based measure of risk, extremely sensitive to tail events. We model banks’ stock returns as an ARMA–GARCH process with multivariate “Normal Tempered Stable” innovations, to capture the skewed and leptokurtotic nature of stock returns. Our union of the Foster–Hart risk modeling with fat-tailed statistical modeling bears fruit, as we are able to measure the equity risk posed by the G-SIBs more accurately than is possible with current techniques.

Suggested Citation

  • Abhinav Anand & Tiantian Li & Tetsuo Kurosaki & Young Shin Kim, 2017. "The equity risk posed by the too-big-to-fail banks: a Foster–Hart estimation," Annals of Operations Research, Springer, vol. 253(1), pages 21-41, June.
    • Handle: RePEc:spr:annopr:v:253:y:2017:i:1:d:10.1007_s10479-016-2309-y
    DOI: 10.1007/s10479-016-2309-y
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    Cited by:

    1. Kurosaki Tetsuo & Kim Young Shin, 2019. "Foster-Hart optimization for currency portfolios," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-15, April.
    2. Young Shin Kim & Kum-Hwan Roh & Raphael Douady, 2022. "Tempered stable processes with time-varying exponential tails," Quantitative Finance, Taylor & Francis Journals, vol. 22(3), pages 541-561, March.
    3. Jiro Hodoshima & Toshiyuki Yamawake, 2021. "Sensitivity of Performance Indexes to Disaster Risk," Risks, MDPI, vol. 9(2), pages 1-22, February.
    4. Young Shin Kim, 2022. "Portfolio optimization and marginal contribution to risk on multivariate normal tempered stable model," Annals of Operations Research, Springer, vol. 312(2), pages 853-881, May.
    5. Kurosaki, Tetsuo & Kim, Young Shin, 2022. "Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk," Finance Research Letters, Elsevier, vol. 45(C).
    6. Young Shin Kim, 2020. "Portfolio Optimization on the Dispersion Risk and the Asymmetric Tail Risk," Papers 2007.13972, arXiv.org, revised Sep 2020.
    7. Tetsuo Kurosaki & Young Shin Kim, 2020. "Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk," Papers 2010.08900, arXiv.org.
    8. Young Shin Kim & Frank J. Fabozzi, 2024. "Portfolio optimization with relative tail risk," Annals of Operations Research, Springer, vol. 341(2), pages 1023-1055, October.
    9. Kim, Sung Ik, 2023. "A comparative study of firm value models: Default risk of corporate bonds," Finance Research Letters, Elsevier, vol. 56(C).
    10. Young Shin Kim, 2023. "Portfolio Optimization with Relative Tail Risk," Papers 2303.12209, arXiv.org, revised Mar 2023.

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