IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v48y2016i48p4635-4654.html
   My bibliography  Save this article

Strength of co-movement between sector CDS indexes and relationship with major economic and financial variables over time and during investment horizons

Author

Listed:
  • Besma Hkiri
  • Shawkat Hammoudeh
  • Chaker Aloui

Abstract

The main purpose of this article is to analyse the co-movement in both time and frequency between financial sector CDS indexes and between these indexes and their main economic and financial control variables for the period 2004–2014. Empirically, we implement the wavelet-squared coherence methodology to analyse the co-movement through time, frequency and power. Our results unveil that the co-movement between the three financial sectors’ CDSs changes through time and investment horizons, stressing the importance of hedging portfolios in real time. Also, we uncover that the changes in co-movement to relatively higher frequencies coincide with the inception of the recent global financial crisis. This result is collaborated with the co-movement between each CDS index and other global risk factors, including crude oil prices, interest rates and equity market volatility. Finally, we compare the wavelet coherence results with those of the DCC-FIAPARCH model and find that the two different approaches provide quite similar conditional correlations over time. Our results are important for investors, debtors, creditors and other decision-makers which are interested in CDS spread co-movements at different frequencies or investment horizons. It would be useful for all market participants to resort to an appropriate frequency domain to have better understanding of the sector CDS interrelationship behaviour in this domain.

Suggested Citation

  • Besma Hkiri & Shawkat Hammoudeh & Chaker Aloui, 2016. "Strength of co-movement between sector CDS indexes and relationship with major economic and financial variables over time and during investment horizons," Applied Economics, Taylor & Francis Journals, vol. 48(48), pages 4635-4654, October.
    • Handle: RePEc:taf:applec:v:48:y:2016:i:48:p:4635-4654
    DOI: 10.1080/00036846.2016.1161723
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00036846.2016.1161723
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00036846.2016.1161723?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. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Staff Working Papers 02-3, Bank of Canada.
    2. Lahiani, Amine & Hammoudeh, Shawkat & Gupta, Rangan, 2016. "Linkages between financial sector CDS spreads and macroeconomic influence in a nonlinear setting," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 443-456.
    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. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Spillover effects in oil-related CDS markets during and after the sub-prime crisis," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    2. Bales, Stephan & Burghartz, Kaspar & Burghof, Hans-Peter & Hitz, Lukas, 2023. "Does the source of uncertainty matter? The impact of financial, newspaper and Twitter-based measures on U.S. banks," Research in International Business and Finance, Elsevier, vol. 65(C).
    3. Bales, Stephan, 2022. "Policy uncertainty and the sovereign-bank nexus: A time-frequency analysis using wavelet transformation," Finance Research Letters, Elsevier, vol. 44(C).
    4. Rodríguez-Caballero, Carlos Vladimir & Caporin, Massimiliano, 2019. "A multilevel factor approach for the analysis of CDS commonality and risk contribution," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    5. Bales, Stephan, 2022. "Sovereign and bank dependence in the eurozone: A multi-scale approach using wavelet-network analysis," International Review of Financial Analysis, Elsevier, vol. 83(C).
    6. Bales, Stephan & Burghof, Hans-Peter, 2024. "Public attention, sentiment and the default of Silicon Valley Bank," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    7. Jiang, Yonghong & Lao, Jiashun & Mo, Bin & Nie, He, 2018. "Dynamic linkages among global oil market, agricultural raw material markets and metal markets: An application of wavelet and copula approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 265-279.

    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. Yushu Li & Fredrik N. G. Andersson, 2021. "A simple wavelet-based test for serial correlation in panel data models," Empirical Economics, Springer, vol. 60(5), pages 2351-2363, May.
    2. Prashant Parab, 2022. "Exchange rate pass-through in India," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2022-012, Indira Gandhi Institute of Development Research, Mumbai, India.
    3. Shahzad, Syed Jawad Hussain & Naifar, Nader & Hammoudeh, Shawkat & Roubaud, David, 2017. "Directional predictability from oil market uncertainty to sovereign credit spreads of oil-exporting countries: Evidence from rolling windows and crossquantilogram analysis," Energy Economics, Elsevier, vol. 68(C), pages 327-339.
    4. Boubaker Heni & Canarella Giorgio & Gupta Rangan & Miller Stephen M., 2017. "Time-varying persistence of inflation: evidence from a wavelet-based approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    5. Luca De Benedictis & Marco Gallegati, 2005. "Trade balance and terms of trade in U.S.: a time-scale decomposition analysis," International Trade 0512016, University Library of Munich, Germany.
    6. Neeraj, & Panigrahi, Prasanta K., 2017. "Causality and correlations between BSE and NYSE indexes: A Janus faced relationship," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 284-313.
    7. Muhammad Azmat Hayat & Huma Ghulam & Maryam Batool & Muhammad Zahid Naeem & Abdullah Ejaz & Cristi Spulbar & Ramona Birau, 2021. "Investigating the Causal Linkages among Inflation, Interest Rate, and Economic Growth in Pakistan under the Influence of COVID-19 Pandemic: A Wavelet Transformation Approach," JRFM, MDPI, vol. 14(6), pages 1-22, June.
    8. Ozun, Alper & Cifter, Atilla, 2007. "Modeling Long-Term Memory Effect in Stock Prices: A Comparative Analysis with GPH Test and Daubechies Wavelets," MPRA Paper 2481, University Library of Munich, Germany.
    9. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    10. Kuşkaya, Sevda & Bilgili, Faik & Muğaloğlu, Erhan & Khan, Kamran & Hoque, Mohammad Enamul & Toguç, Nurhan, 2023. "The role of solar energy usage in environmental sustainability: Fresh evidence through time-frequency analyses," Renewable Energy, Elsevier, vol. 206(C), pages 858-871.
    11. Liang, Chin Chia & Troy, Carol & Rouyer, Ellen, 2020. "U.S. uncertainty and Asian stock prices: Evidence from the asymmetric NARDL model," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    12. Erick Lahura & Marco Vega, 2011. "Evaluation of Wavelet-based Core Inflation Measures: Evidence from Peru," Documentos de Trabajo / Working Papers 2011-320, Departamento de Economía - Pontificia Universidad Católica del Perú.
    13. Crowley, Patrick M., 2005. "An intuitive guide to wavelets for economists," Bank of Finland Research Discussion Papers 1/2005, Bank of Finland.
    14. Mensi, Walid & Shahzad, Syed Jawad Hussain & Hammoudeh, Shawkat & Hkiri, Besma & Hamed Al Yahyaee, Khamis, 2019. "Long-run relationships between US financial credit markets and risk factors: Evidence from the quantile ARDL approach," Finance Research Letters, Elsevier, vol. 29(C), pages 101-110.
    15. Gallegati, Marco & Ramsey, James B., 2013. "Structural change and phase variation: A re-examination of the q-model using wavelet exploratory analysis," Structural Change and Economic Dynamics, Elsevier, vol. 25(C), pages 60-73.
    16. Javier Fernandez-Macho, 2013. "A wavelet approach to multiple cointegration testing," Economics Series Working Papers 668, University of Oxford, Department of Economics.
    17. Joanna Bruzda, 2011. "Business cycle synchronization according to wavelets – the case of Poland and the euro zone member countries," Bank i Kredyt, Narodowy Bank Polski, vol. 42(3), pages 5-32.
    18. Cortés Espada Josué Fernando & Sámano Daniel & Gutiérrez Villanueva Rubí, 2019. "Dynamics of Mexican Inflation: A Wavelet Analysis," Working Papers 2019-17, Banco de México.
    19. Dhaoui Abderrazak & Chevallier Julien & Ma Feng, 2021. "Identifying asymmetric responses of sectoral equities to oil price shocks in a NARDL model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-19, April.
    20. Li, Yushu & Shukur, Ghazi, 2009. "Testing for Unit Root against LSTAR Model: Wavelet Improvement under GARCH Distortion," CAFO Working Papers 2009:6, Linnaeus University, Centre for Labour Market Policy Research (CAFO), School of Business and Economics.

    More about this item

    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:taf:applec:v:48:y:2016:i:48:p:4635-4654. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    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.