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How does issuing contingent convertible bonds improve bank's solvency? A Value-at-Risk and Expected Shortfall approach

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  • Jaworski, Piotr
  • Liberadzki, Kamil
  • Liberadzki, Marcin

Abstract

This paper examines how issuing an innovative financial instrument called contingent convertible bond (CoCo) may enhance bank's solvency in comparison to issuing a conventional bond. CoCos convert automatically into common equity or have a principal write-down when bank's regulatory capital fails to meet a predetermined level. They have been invented and put into legislation with an objective to absorb losses thus preventing institutions from bankruptcy. From the standpoint of an issuer CoCos bring about two counter effects regarding his solvency: on one hand they recapitalize a bank approaching insolvency on the other hand CoCos pay much higher coupon comparing to conventional bonds. In our model a bank has two funding alternatives: either to issue CoCos or conventional bonds. We measure issuer's default risk using the concept of Value-at-Risk (VaR) and Expected Shortfall (ES). We conclude that CoCos have the potential to strengthen the resilience of the issuer on the condition that the probability of conversion triggering is higher than the VaR's significance level. Our findings can be helpful to the policymakers and banks to better understand the impact of CoCos on issuer's solvency.

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  • Jaworski, Piotr & Liberadzki, Kamil & Liberadzki, Marcin, 2017. "How does issuing contingent convertible bonds improve bank's solvency? A Value-at-Risk and Expected Shortfall approach," Economic Modelling, Elsevier, vol. 60(C), pages 162-168.
  • Handle: RePEc:eee:ecmode:v:60:y:2017:i:c:p:162-168
    DOI: 10.1016/j.econmod.2016.09.025
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    References listed on IDEAS

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    Cited by:

    1. Caporale, Guglielmo Maria & Kang, Woo-Young, 2021. "On the preferences of CoCo bond buyers and sellers," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    2. Philippe Oster, 2020. "Contingent Convertible bond literature review: making everything and nothing possible?," Journal of Banking Regulation, Palgrave Macmillan, vol. 21(4), pages 343-381, December.
    3. Naimoli, Antonio & Gerlach, Richard & Storti, Giuseppe, 2022. "Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators," Economic Modelling, Elsevier, vol. 107(C).
    4. Piotr Jaworski & Kamil Liberadzki & Marcin Liberadzki, 2021. "On Write-Down/ Write-Up Loss Absorbing Instruments," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 1204-1219.

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