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

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  • 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
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    References listed on IDEAS

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    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.
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    2. Bales, Stephan, 2022. "Policy uncertainty and the sovereign-bank nexus: A time-frequency analysis using wavelet transformation," Finance Research Letters, Elsevier, vol. 44(C).
    3. 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).
    4. 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).
    5. 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).
    6. Lee, Hyunchul & Kim, Hyunseok, 2024. "Time-varying co-movement of sovereign credit default swaps markets: Evidence from Asia-Pacific countries," Finance Research Letters, Elsevier, vol. 69(PB).
    7. 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).
    8. 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.
    9. Hau, Liya & Liu, Xiaoli & Wu, Xinyu, 2025. "Multiscale cross-sector tail credit risk spillovers in China: Evidence from EEMD-based VAR quantile analysis," Research in International Business and Finance, Elsevier, vol. 73(PA).

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