IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v46y2022ipbs1544612321004141.html
   My bibliography  Save this article

The network structure of overnight index swap rates

Author

Listed:
  • Fang, Ming
  • Taylor, Stephen
  • Uddin, Ajim

Abstract

Graph theoretical techniques are utilized to examine the centrality structure of overnight index swap (OIS) networks. Correlation based graphs are constructed to encode pairwise relationships between distinct OIS rates. Multiple notions of graph centrality are considered, and the time evolution of these measures is studied. A principal component analysis based centrality measure is constructed to examine comovements between full OIS curves. Numerical examples demonstrating these ideas are provided.

Suggested Citation

  • Fang, Ming & Taylor, Stephen & Uddin, Ajim, 2022. "The network structure of overnight index swap rates," Finance Research Letters, Elsevier, vol. 46(PB).
    • Handle: RePEc:eee:finlet:v:46:y:2022:i:pb:s1544612321004141
    DOI: 10.1016/j.frl.2021.102425
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612321004141
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2021.102425?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. Onnela, J.-P. & Chakraborti, A. & Kaski, K. & Kertész, J., 2003. "Dynamic asset trees and Black Monday," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 247-252.
    2. Bouchaud,Jean-Philippe & Potters,Marc, 2009. "Theory of Financial Risk and Derivative Pricing," Cambridge Books, Cambridge University Press, number 9780521741866.
    3. Bouri, Elie & Cepni, Oguzhan & Gabauer, David & Gupta, Rangan, 2021. "Return connectedness across asset classes around the COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 73(C).
    4. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    5. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    6. Dubecq, Simon & Monfort, Alain & Renne, Jean-Paul & Roussellet, Guillaume, 2016. "Credit and liquidity in interbank rates: A quadratic approach," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 29-46.
    7. So, Mike K.P. & Chu, Amanda M.Y. & Chan, Thomas W.C., 2021. "Impacts of the COVID-19 pandemic on financial market connectedness," Finance Research Letters, Elsevier, vol. 38(C).
    8. G. Bonanno & G. Caldarelli & F. Lillo & S. Micciché & N. Vandewalle & R. Mantegna, 2004. "Networks of equities in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 363-371, March.
    9. M. Tumminello & T. Di Matteo & T. Aste & R. N. Mantegna, 2007. "Correlation based networks of equity returns sampled at different time horizons," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 55(2), pages 209-217, January.
    10. Driessen, J.J.A.G. & Melenberg, B. & Nijman, T.E., 2003. "Common factors in international bond returns," Other publications TiSEM 06a83942-b625-4d3c-808c-a, Tilburg University, School of Economics and Management.
    11. Matthew Elliott & Benjamin Golub & Matthew O. Jackson, 2014. "Financial Networks and Contagion," American Economic Review, American Economic Association, vol. 104(10), pages 3115-3153, October.
    12. 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.
    13. Bikbov, Ruslan & Chernov, Mikhail, 2010. "No-arbitrage macroeconomic determinants of the yield curve," Journal of Econometrics, Elsevier, vol. 159(1), pages 166-182, November.
    14. Joslin, Scott & Le, Anh & Singleton, Kenneth J., 2013. "Why Gaussian macro-finance term structure models are (nearly) unconstrained factor-VARs," Journal of Financial Economics, Elsevier, vol. 109(3), pages 604-622.
    15. Fase, M. M. G., 1973. "A principal components analysis of market interest rates in The Netherlands, 1962-1970," European Economic Review, Elsevier, vol. 4(2), pages 107-134, June.
    16. 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).
    17. Samuel Ronnqvist & Peter Sarlin, 2014. "Bank Networks from Text: Interrelations, Centrality and Determinants," Papers 1406.7752, arXiv.org, revised Jul 2015.
    18. Pierre Collin‐Dufresne & Robert S. Goldstein & Christopher S. Jones, 2008. "Identification of Maximal Affine Term Structure Models," Journal of Finance, American Finance Association, vol. 63(2), pages 743-795, April.
    19. Hamilton, James D. & Wu, Jing Cynthia, 2012. "Identification and estimation of Gaussian affine term structure models," Journal of Econometrics, Elsevier, vol. 168(2), pages 315-331.
    20. Wenxin Du & Alexander Tepper & Adrien Verdelhan, 2018. "Deviations from Covered Interest Rate Parity," Journal of Finance, American Finance Association, vol. 73(3), pages 915-957, June.
    21. Juneja, Januj, 2012. "Common factors, principal components analysis, and the term structure of interest rates," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 48-56.
    22. Baumöhl, Eduard & Shahzad, Syed Jawad Hussain, 2019. "Quantile coherency networks of international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 119-129.
    23. repec:hal:journl:peer-00732517 is not listed on IDEAS
    24. François-Louis Michaud & Christian Upper, 2008. "What drives interbank rates? Evidence from the Libor panel," BIS Quarterly Review, Bank for International Settlements, March.
    25. Sène, Babacar & Mbengue, Mohamed Lamine & Allaya, Mouhamad M., 2021. "Overshooting of sovereign emerging eurobond yields in the context of COVID-19," Finance Research Letters, Elsevier, vol. 38(C).
    26. Raymond Ka-Kay Pang & Oscar Granados & Harsh Chhajer & Erika Fille Legara, 2020. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Papers 2009.13390, arXiv.org, revised Feb 2021.
    27. Driessen, Joost & Melenberg, Bertrand & Nijman, Theo, 2003. "Common factors in international bond returns," Journal of International Money and Finance, Elsevier, vol. 22(5), pages 629-656, October.
    28. Hamilton, James D. & Wu, Jing Cynthia, 2014. "Testable implications of affine term structure models," Journal of Econometrics, Elsevier, vol. 178(P2), pages 231-242.
    29. Leite, André Luís & Filho, Romeu Braz Pereira Gomes & Vicente, José Valentim Machado, 2010. "Forecasting the yield curve: A statistical model with market survey data," International Review of Financial Analysis, Elsevier, vol. 19(2), pages 108-112, March.
    30. Lai, Yujie & Hu, Yibo, 2021. "A study of systemic risk of global stock markets under COVID-19 based on complex financial networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    31. Samuel R�nnqvist & Peter Sarlin, 2015. "Bank networks from text: interrelations, centrality and determinants," Quantitative Finance, Taylor & Francis Journals, vol. 15(10), pages 1619-1635, October.
    32. Li, Wenwei & Hommel, Ulrich & Paterlini, Sandra, 2018. "Network topology and systemic risk: Evidence from the Euro Stoxx market," Finance Research Letters, Elsevier, vol. 27(C), pages 105-112.
    33. Tse, Chi K. & Liu, Jing & Lau, Francis C.M., 2010. "A network perspective of the stock market," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 659-667, September.
    34. Le, Trung Hai & Do, Hung Xuan & Nguyen, Duc Khuong & Sensoy, Ahmet, 2021. "Covid-19 pandemic and tail-dependency networks of financial assets," Finance Research Letters, Elsevier, vol. 38(C).
    35. 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.
    36. L. C. G. Rogers & L. A. M. Veraart, 2013. "Failure and Rescue in an Interbank Network," Management Science, INFORMS, vol. 59(4), pages 882-898, April.
    37. Michael Boss & Helmut Elsinger & Martin Summer & Stefan Thurner, 2004. "Network topology of the interbank market," Quantitative Finance, Taylor & Francis Journals, vol. 4(6), pages 677-684.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Juneja, Januj, 2012. "Common factors, principal components analysis, and the term structure of interest rates," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 48-56.
    3. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    4. 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.
    5. Peralta, Gustavo & Zareei, Abalfazl, 2016. "A network approach to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 157-180.
    6. 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.
    7. Gogas, Periklis & Papadimitriou, Theophilos & Matthaiou, Maria-Artemis, 2016. "Bank supervision using the Threshold-Minimum Dominating Set," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 23-35.
    8. Jean-Baptiste Hasse, 2022. "Systemic risk: a network approach," Empirical Economics, Springer, vol. 63(1), pages 313-344, July.
    9. Kumar, Sudarshan & Bansal, Avijit & Chakrabarti, Anindya S., 2019. "Ripples on financial networks," IIMA Working Papers WP 2019-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    10. 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.
    11. Jean-Baptiste Hasse, 2020. "Systemic Risk: a Network Approach," Working Papers halshs-02893780, HAL.
    12. Chen, Yanhua & Li, Youwei & Pantelous, Athanasios A. & Stanley, H. Eugene, 2022. "Short-run disequilibrium adjustment and long-run equilibrium in the international stock markets: A network-based approach," International Review of Financial Analysis, Elsevier, vol. 79(C).
    13. Biplab Bhattacharjee & Muhammad Shafi & Animesh Acharjee, 2017. "Investigating the Evolution of Linkage Dynamics among Equity Markets Using Network Models and Measures: The Case of Asian Equity Market Integration," Data, MDPI, vol. 2(4), pages 1-28, December.
    14. Leonidas Sandoval Junior, 2011. "A Map of the Brazilian Stock Market," Papers 1107.4146, arXiv.org, revised Mar 2013.
    15. Juneja, Januj, 2017. "How Germany benefits the most from its Eurozone membership," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1074-1088.
    16. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    17. Chuangxia Huang & Xian Zhao & Renli Su & Xiaoguang Yang & Xin Yang, 2022. "Dynamic network topology and market performance: A case of the Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1962-1978, April.
    18. Dror Kenett & Shlomo Havlin, 2015. "Network science: a useful tool in economics and finance," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 14(2), pages 155-167, November.
    19. Sandoval, Leonidas, 2014. "To lag or not to lag? How to compare indices of stock markets that operate on different times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 227-243.
    20. Vishwas Kukreti & Hirdesh K. Pharasi & Priya Gupta & Sunil Kumar, 2020. "A perspective on correlation-based financial networks and entropy measures," Papers 2004.09448, arXiv.org.

    More about this item

    Keywords

    Fixed income; Graph centrality; Overnight index swap rates; Principal component analysis;
    All these keywords.

    JEL classification:

    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

    Statistics

    Access and download statistics

    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:46:y:2022:i:pb:s1544612321004141. 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.