IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v43y2021ics1544612321000969.html
   My bibliography  Save this article

The price determinants of contingent convertible bonds

Author

Listed:
  • Zeitsch, Peter J.
  • Davis, Tom P.

Abstract

The relationships between contingent convertible (CoCo) bonds and their underlying equities, credit default swap spreads (CDS), interest rates, implied volatilities and foreign exchange rates are studied. Starting with the dynamic correlation of the DCC-GARCH method, it is found that CoCo bonds are most highly correlated to CDS. By constructing the minimum spanning tree of the resulting correlations, the primary link to CDS is confirmed. Implied volatility is found to be a secondary to tertiary link, alternating in importance with equities. Interest rates and FX have little impact.

Suggested Citation

  • Zeitsch, Peter J. & Davis, Tom P., 2021. "The price determinants of contingent convertible bonds," Finance Research Letters, Elsevier, vol. 43(C).
    • Handle: RePEc:eee:finlet:v:43:y:2021:i:c:s1544612321000969
    DOI: 10.1016/j.frl.2021.102015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612321000969
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2021.102015?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    2. Djauhari, Maman Abdurachman & Gan, Siew Lee, 2015. "Optimality problem of network topology in stocks market analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 108-114.
    3. León, Carlos & Leiton, Karen & Pérez, Jhonatan, 2014. "Extracting the sovereigns’ CDS market hierarchy: A correlation-filtering approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 407-420.
    4. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    5. Guillermo J. Ortega & David Matesanz, 2006. "Cross-Country Hierarchical Structure And Currency Crises," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 17(03), pages 333-341.
    6. Tumminello, Michele & Lillo, Fabrizio & Mantegna, Rosario N., 2010. "Correlation, hierarchies, and networks in financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 75(1), pages 40-58, July.
    7. Peter J. Zeitsch, 2017. "Capital Structure Arbitrage under a Risk-Neutral Calibration," JRFM, MDPI, vol. 10(1), pages 1-23, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liwei Jin & Xianghui Yuan & Li Peiran & Hailun Xu & Feng Lian, 2023. "Option features and price discovery in convertible bonds," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(3), pages 384-403, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. David Matesanz Gomez & Guillermo J. Ortega & Benno Torgler, 2011. "Measuring globalization: A hierarchical network approach," CREMA Working Paper Series 2011-11, Center for Research in Economics, Management and the Arts (CREMA).
    2. Bastidon, Cécile & Parent, Antoine & Jensen, Pablo & Abry, Patrice & Borgnat, Pierre, 2020. "Graph-based era segmentation of international financial integration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    3. Bastidon, Cécile & Parent, Antoine & Jensen, Pablo & Abry, Patrice & Borgnat, Pierre, 2020. "Graph-based era segmentation of international financial integration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    4. Sensoy, Ahmet & Tabak, Benjamin M., 2014. "Dynamic spanning trees in stock market networks: The case of Asia-Pacific," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 387-402.
    5. Pang, Raymond Ka-Kay & Granados, Oscar M. & Chhajer, Harsh & Legara, Erika Fille T., 2021. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    6. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    7. M. Raddant & T. Di Matteo, 2023. "A look at financial dependencies by means of econophysics and financial economics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(4), pages 701-734, October.
    8. Coletti, Paolo, 2016. "Comparing minimum spanning trees of the Italian stock market using returns and volumes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 246-261.
    9. David Matesanz Gomez & Benno Torgler & Guillermo J. Ortega, 2013. "Measuring Global Economic Interdependence: A Hierarchical Network Approach," The World Economy, Wiley Blackwell, vol. 36(12), pages 1632-1648, December.
    10. Deviren, Seyma Akkaya & Deviren, Bayram, 2016. "The relationship between carbon dioxide emission and economic growth: Hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 429-439.
    11. repec:hal:spmain:info:hdl:2441/ps168627s85g86i5u1aj5akpm is not listed on IDEAS
    12. Teh, Boon Kin & Goo, Yik Wen & Lian, Tong Wei & Ong, Wei Guang & Choi, Wen Ting & Damodaran, Mridula & Cheong, Siew Ann, 2015. "The Chinese Correction of February 2007: How financial hierarchies change in a market crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 225-241.
    13. Ondřej Filip & Karel Janda & Ladislav Krištoufek, 2018. "Ceny biopaliv a souvisejících komodit: analýza s použitím metod minimální kostry grafu a hierarchických stromů [Prices of Biofuels and Related Commodities: an Analysis Using Methods of Minimum Span," Politická ekonomie, Prague University of Economics and Business, vol. 2018(2), pages 218-239.
    14. Nicoló Musmeci & Tomaso Aste & T Di Matteo, 2015. "Relation between Financial Market Structure and the Real Economy: Comparison between Clustering Methods," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-24, March.
    15. Carlos León & Geun-Young Kim & Constanza Martínez & Daeyup Lee, 2017. "Equity markets’ clustering and the global financial crisis," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1905-1922, December.
    16. Giuseppe Brandi & Ruggero Gramatica & Tiziana Di Matteo, 2019. "Unveil stock correlation via a new tensor-based decomposition method," Papers 1911.06126, arXiv.org, revised Apr 2020.
    17. Danau, Daniel, 2020. "Prudence and preference for flexibility gain," European Journal of Operational Research, Elsevier, vol. 287(2), pages 776-785.
    18. Tan T. M. Le & Franck Martin & Duc K. Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Economics Working Paper Archive (University of Rennes 1 & University of Caen) 2018-04, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
    19. Zhang, Xin & Podobnik, Boris & Kenett, Dror Y. & Eugene Stanley, H., 2014. "Systemic risk and causality dynamics of the world international shipping market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 43-53.
    20. Marianna Siničáková & Veronika Šuliková & Ľubica Štiblárová, 2018. "Tradičný a alternatívny pohľad na synchronizáciu hospodárskych cyklov v Európskej únii [Traditional and Alternative Look at the Business Cycle Synchronisation in the European Union]," Politická ekonomie, Prague University of Economics and Business, vol. 2018(2), pages 260-277.
    21. Heiberger, Raphael H., 2014. "Stock network stability in times of crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 376-381.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:43:y:2021:i:c:s1544612321000969. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.