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Measuring the liquidity impact on catastrophe bond spreads

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  • Zhao, Yang
  • Yu, Min-Teh

Abstract

This study measures liquidity in the catastrophe (CAT) bond market and the liquidity premium embedded in CAT bond spreads. The empirical results show that time to maturity, yield volatility, and yield dispersion from the primary market are the three most effective liquidity proxies. Given these three proxies, the average estimated liquidity premium in the CAT bond market is 67.57bps, accounting for only 9.42% of the average CAT bond spread (717.37bps) in the secondary market during the period 2002-2016. The average CAT bond liquidity premium is higher than the corporate bond liquidity premium of a similar risk class by about 35bps during the pre-crisis period. The more significant part of the high-yield spreads, 90.58%, is attributed to other risk natures of CAT bonds. Lastly, the liquidity premium increases dramatically after occurrences of severe natural catastrophes as well as during the 2008 financial crisis.

Suggested Citation

  • Zhao, Yang & Yu, Min-Teh, 2019. "Measuring the liquidity impact on catastrophe bond spreads," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 197-210.
    • Handle: RePEc:eee:pacfin:v:56:y:2019:i:c:p:197-210
    DOI: 10.1016/j.pacfin.2019.06.006
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    Cited by:

    1. Raluca Maran, 2023. "Do Sovereign Catastrophe Bonds Improve Fiscal Resilience? An Application of Synthetic Control Method to Mexico," Economics of Disasters and Climate Change, Springer, vol. 7(3), pages 431-455, November.
    2. Su, Tong & Lin, Boqiang, 2022. "The liquidity impact of Chinese green bonds spreads," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 318-334.
    3. Carolyn W. Chang & Jack S. K. Chang & Min‐Teh Yu & Yang Zhao, 2020. "Portfolio optimization in the catastrophe space," European Financial Management, European Financial Management Association, vol. 26(5), pages 1414-1448, November.
    4. Chang Carolyn W. & Feng Yalan, 2021. "Hurricane Bond Price Dependency on Underlying Hurricane Parameters," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 15(1), pages 1-21, January.
    5. Zhao, Yang & Yu, Min-Teh, 2020. "Predicting catastrophe risk: Evidence from catastrophe bond markets," Journal of Banking & Finance, Elsevier, vol. 121(C).
    6. Lo, Chien-Ling & Chang, Carolyn W. & Lee, Jin-Ping & Yu, Min-Teh, 2021. "Pricing catastrophe swaps with default risk and stochastic interest rates," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    7. Markus Herrmann & Martin Hibbeln, 2023. "Trading and liquidity in the catastrophe bond market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(2), pages 283-328, June.
    8. Kung, Ko-Lun & Hsieh, Ming-Hua & Peng, Jin-Lung & Tsai, Chenghsien Jason & Wang, Jennifer L., 2021. "Explaining the risk premiums of life settlements," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    9. Adlane Haffar & Éric Le Fur, 2022. "Dependence structure of CAT bonds and portfolio diversification: a copula-GARCH approach," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 297-309, July.

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    More about this item

    Keywords

    Catastrophes; Catastrophe bond; Liquidity proxy; Liquidity premium; Yield spread; Insurance-linked derivatives;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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