IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v161y2017icp5-9.html
   My bibliography  Save this article

Predictability dynamics of emerging sovereign CDS markets

Author

Listed:
  • Sensoy, Ahmet
  • Fabozzi, Frank J.
  • Eraslan, Veysel

Abstract

We compare the time-varying weak-form efficiency of Credit Default Swap (CDS) markets of 15 emerging countries by using permutation entropy approach. We find that CDS markets have different degrees of time-varying efficiency. Using several robustness test, we find that Thailand, China, South Korea and Malaysia have the most efficient CDS markets while South Africa, Colombia and Turkey are the least efficient. Our results show that CDS markets can be efficient even in the crisis episodes. Our findings also suggest a strong negative relation between sovereign risk and CDS market efficiency.

Suggested Citation

  • Sensoy, Ahmet & Fabozzi, Frank J. & Eraslan, Veysel, 2017. "Predictability dynamics of emerging sovereign CDS markets," Economics Letters, Elsevier, vol. 161(C), pages 5-9.
    • Handle: RePEc:eee:ecolet:v:161:y:2017:i:c:p:5-9
    DOI: 10.1016/j.econlet.2017.09.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176517303828
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2017.09.015?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. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    2. Avino, Davide & Nneji, Ogonna, 2014. "Are CDS spreads predictable? An analysis of linear and non-linear forecasting models," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 262-274.
    3. Lo, Andrew W. & MacKinlay, A. Craig, 1989. "The size and power of the variance ratio test in finite samples : A Monte Carlo investigation," Journal of Econometrics, Elsevier, vol. 40(2), pages 203-238, February.
    4. Nicole Thorne Jenkins & Michael D. Kimbrough & Juan Wang, 2016. "The extent of informational efficiency in the credit default swap market: evidence from post-earnings announcement returns," Review of Quantitative Finance and Accounting, Springer, vol. 46(4), pages 725-761, May.
    5. Bassler, Kevin E. & Gunaratne, Gemunu H. & McCauley, Joseph L., 2006. "Markov processes, Hurst exponents, and nonlinear diffusion equations: With application to finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 369(2), pages 343-353.
    6. Gündüz, Yalin & Kaya, Orcun, 2013. "Sovereign default swap market efficiency and country risk in the eurozone," Discussion Papers 08/2013, Deutsche Bundesbank.
    7. López, Fernando & Matilla-García, Mariano & Mur, Jesús & Marín, Manuel Ruiz, 2010. "A non-parametric spatial independence test using symbolic entropy," Regional Science and Urban Economics, Elsevier, vol. 40(2-3), pages 106-115, May.
    8. Sensoy, Ahmet & Aras, Guler & Hacihasanoglu, Erk, 2015. "Predictability dynamics of Islamic and conventional equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 222-248.
    9. Kiesel, F. & Kolaric, S. & Schiereck, D., 2016. "Market integration and efficiency of CDS and equity markets," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77819, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    10. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    11. Zunino, Luciano & Fernández Bariviera, Aurelio & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2012. "On the efficiency of sovereign bond markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4342-4349.
    12. Zhang, Gaiyan & Zhang, Sanjian, 2013. "Information efficiency of the U.S. credit default swap market: Evidence from earnings surprises," Journal of Financial Stability, Elsevier, vol. 9(4), pages 720-730.
    13. Kevin E. Bassler & Gemunu H. Gunaratne & Joseph L. McCauley, 2006. "Markov Processes, Hurst Exponents, and Nonlinear Diffusion Equations with application to finance," Papers cond-mat/0602316, arXiv.org.
    14. Matilla-Garci­a, Mariano & Ruiz Mari­n, Manuel, 2008. "A non-parametric independence test using permutation entropy," Journal of Econometrics, Elsevier, vol. 144(1), pages 139-155, May.
    15. Kiesel, Florian & Kolaric, Sascha & Schiereck, Dirk, 2016. "Market integration and efficiency of CDS and equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 209-229.
    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. Saker Sabkha & Christian Peretti & Dorra Hmaied, 2019. "On the informational market efficiency of the worldwide sovereign credit default swaps," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 581-608, December.
    2. Gök, Remzi & Bouri, Elie & Gemici, Eray, 2023. "Volatility spillovers between sovereign CDS and futures markets in various volatility states: Evidence from an emerging economy around the pandemic," Research in International Business and Finance, Elsevier, vol. 66(C).
    3. Giacomo Bulfone & Roberto Casarin & Francesco Ravazzolo, 2021. "Corporate CDS spreads from the Eurozone crisis to COVID-19 pandemic: A Bayesian Markov switching model," Working Paper series 21-09, Rimini Centre for Economic Analysis.
    4. Miguel Henry & George Judge, 2019. "Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series," Econometrics, MDPI, vol. 7(1), pages 1-16, March.
    5. Sensoy, Ahmet, 2019. "The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies," Finance Research Letters, Elsevier, vol. 28(C), pages 68-73.
    6. Won Joong Kim & Gunho Jung & Sun-Yong Choi, 2020. "Forecasting CDS Term Structure Based on Nelson–Siegel Model and Machine Learning," Complexity, Hindawi, vol. 2020, pages 1-23, July.
    7. Mariya Gubareva, 2019. "Weight of the Default Component of CDS Spreads: Avoiding Procyclicality in Credit Loss Provisioning Framework," Complexity, Hindawi, vol. 2019, pages 1-19, July.
    8. Mensi, Walid & Sensoy, Ahmet & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Pricing efficiency and asymmetric multifractality of major asset classes before and during COVID-19 crisis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    9. Sun, Xiaolei & Wang, Jun & Yao, Yanzhen & Li, Jingyu & Li, Jianping, 2020. "Spillovers among sovereign CDS, stock and commodity markets: A correlation network perspective," International Review of Financial Analysis, Elsevier, vol. 68(C).

    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. Sensoy, Ahmet & Aras, Guler & Hacihasanoglu, Erk, 2015. "Predictability dynamics of Islamic and conventional equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 222-248.
    2. Saker Sabkha & Christian Peretti & Dorra Hmaied, 2019. "On the informational market efficiency of the worldwide sovereign credit default swaps," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 581-608, December.
    3. Shahzad, Syed Jawad Hussain & Nor, Safwan Mohd & Mensi, Walid & Kumar, Ronald Ravinesh, 2017. "Examining the efficiency and interdependence of US credit and stock markets through MF-DFA and MF-DXA approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 351-363.
    4. Sensoy, Ahmet & Tabak, Benjamin M., 2016. "Dynamic efficiency of stock markets and exchange rates," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 353-371.
    5. Alena Audzeyeva & Xu Wang, 2023. "Fundamentals, real-time uncertainty and CDS index spreads," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 1-33, July.
    6. Mynhardt, H. R. & Plastun, Alex & Makarenko, Inna, 2014. "Behavior of Financial Markets Efficiency During the Financial Market Crisis: 2007-2009," MPRA Paper 58942, University Library of Munich, Germany.
    7. Sensoy, Ahmet, 2019. "The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies," Finance Research Letters, Elsevier, vol. 28(C), pages 68-73.
    8. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2017. "Adaptive markets hypothesis for Islamic stock indices: Evidence from Dow Jones size and sector-indices," International Economics, Elsevier, vol. 151(C), pages 100-112.
    9. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    10. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    11. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
    12. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    13. Bariviera, Aurelio F. & Font-Ferrer, Alejandro & Sorrosal-Forradellas, M. Teresa & Rosso, Osvaldo A., 2019. "An information theory perspective on the informational efficiency of gold price," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    14. Zhong, Meirui & Zhang, Rui & Ren, Xiaohang, 2023. "The time-varying effects of liquidity and market efficiency of the European Union carbon market: Evidence from the TVP-SVAR-SV approach," Energy Economics, Elsevier, vol. 123(C).
    15. Aye, Goodness C. & Gil-Alana, Luis A. & Gupta, Rangan & Wohar, Mark E., 2017. "The efficiency of the art market: Evidence from variance ratio tests, linear and nonlinear fractional integration approaches," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 283-294.
    16. Corsetti, Giancarlo & Lafarguette, Romain & Mehl, Arnaud, 2019. "Fast trading and the virtue of entropy: evidence from the foreign exchange market," Working Paper Series 2300, European Central Bank.
    17. repec:grz:wpsses:2020-04 is not listed on IDEAS
    18. Charles, Amélie & Darné, Olivier, 2009. "The efficiency of the crude oil markets: Evidence from variance ratio tests," Energy Policy, Elsevier, vol. 37(11), pages 4267-4272, November.
    19. Kim, Jae H. & Shamsuddin, Abul, 2008. "Are Asian stock markets efficient? Evidence from new multiple variance ratio tests," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 518-532, June.
    20. Kim Oosterlinck & Jeremy Simon, 2015. "Financial Repression and Bond Market Efficiency: the Case of Italy during World War II," Working Papers CEB 15-001, ULB -- Universite Libre de Bruxelles.
    21. Chun, Rodney M., 2000. "Compensation vouchers and equity markets: Evidence from Hungary," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1155-1178, July.

    More about this item

    Keywords

    Efficient market hypothesis (EMH); CDS; Permutation entropy;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:ecolet:v:161:y:2017:i:c:p:5-9. 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/ecolet .

    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.