Can CDS indexes signal future turmoils in the stock market? A Markov switching perspective

  • Rosella CastellanoEmail author
  • Luisa Scaccia
Original Paper


Single-name Credit Default Swaps (CDS) are considered the main providers of direct information related with a reference entity’s creditworthiness and, for this reason, they have often been the core of news on the current financial crisis. The academic research has focused mainly on the capacity of CDS in anticipating agencies’ official rating changes and—in this respect—on their superior signalling power, compared to bond and stock markets. The aim of this work is, instead, to investigate the ability of fluctuations in CDS indexes in anticipating the occurrence of stock market crises. Our goal is to show that CDS indexes may provide investors and institutions with early warning signals of financial distresses in the stock market. We make use of a Markov switching model with states characterized by increasing levels of volatility and compare the times in which the first switch in a high volatility state occurs, respectively, in CDS and stock market index quotes. The data set consists of daily closing quotes for 5 years CDS and stock market index prices, covering the time period from 2004 to 2010. In order to capture possible geographic differences in CDS index capacity of foreseeing stock market distresses, data referring to two different regions, Europe and United States, are analyzed.


Credit default swaps Markov switching model Financial crisis Bayesian hierarchical modeling 

Mathematics Subject Classification (2000)

60J05 62F15 62M05 62P05 


  1. Alexander C, Kaeck A (2008) Regime dependent determinants of credit default swap spreads. J Banking Financ 32:1008–1021CrossRefGoogle Scholar
  2. Ammer J, Clinton N (2004) Good news in no news? The impact of credit rating changes on the pricing of asset-backed securities, Federal Reserve Board, International Finance Discussion Paper 809Google Scholar
  3. Besag J, Green PJ, Higdon D, Mengersen K (1995) Bayesian computation and stochastic systems (with discussion). Stat Sci 10:3–66CrossRefGoogle Scholar
  4. Blanco R, Brennan S, Marsh IW (2005) An empirical analysis of the dynamic relation between investment-grade bonds and credit default swaps. J Financ 60:2255–2281CrossRefGoogle Scholar
  5. Castellano R, Scaccia L (2010) A Markov switching re-evaluation of event-study methodology. In: Lechevallier Y, Saporta G (eds) COMPSTAT’2010—19th international conference on computational statistics. Physica-Verlag, Heidelberg, pp 429–436Google Scholar
  6. Castellano R, D’Ecclesia RL (2011) Credit default swaps and rating announcements. J Financ Decis Mak 7:3–19Google Scholar
  7. Castellano R, Scaccia L (2012) Cds and rating announcements: changing signaling during the crisis? RMS 6:239–264CrossRefGoogle Scholar
  8. Castellano R, Giacometti R (2012) Credit default swaps: implied ratings versus official ones. 4OR-Q J Oper Res 10:163–180CrossRefGoogle Scholar
  9. Castellano R, D’Ecclesia RL (2012) Cds volatility: the key signal of credit quality. Ann Oper Res (forthcoming)Google Scholar
  10. Chan-Lau JA, Kim YS (2004) Equity prices, credit default swaps, and bond spreads in emerging markets. IMF working Paper WP/04/27Google Scholar
  11. Coudert V, Gex M (2010) Credit default swap and bond markets: which leads the other? Financ Stab Rev 14:161–167Google Scholar
  12. Dionne G, Gauthier G, Hammami K, Maurice M (2010) Default risk in corporate yield spreads. Financ Manag 39:707–731CrossRefGoogle Scholar
  13. Duffie D (1999) Credit swap valuation. Financ Anal J 55:73–87CrossRefGoogle Scholar
  14. Frühwirth-Schnatter S (2004) Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques. Econ J 7:143–167CrossRefGoogle Scholar
  15. Houweling P, Vorst T (2005) Pricing default swaps: empirical evidence. J Int Money Financ 24:1200–1225CrossRefGoogle Scholar
  16. Hull JC, White A (2000) Valuing credit default swaps I: no counterparty default risk. J Deriv 8:29–40CrossRefGoogle Scholar
  17. Hull JC, Predescu M, White A (2004) The relationship between credit default swap spreads, bond yields and credit rating announcements. J Banking Financ 28:2789–2811CrossRefGoogle Scholar
  18. Jarrow RA, Turnbull S (1995) Pricing derivatives on financial securities subject to credit risk. J Financ 50:53–85CrossRefGoogle Scholar
  19. Kaminsky G, Reinhart CM (1996) The twin crises: the causes of banking and balance of payments problems. Am Econ Rev 89:473–500CrossRefGoogle Scholar
  20. Kou J, Varotto S (2008) Timeliness of spread implied ratings. Eur Financ Manag 14:503–527CrossRefGoogle Scholar
  21. Longstaff FA, Mithal S, Neis E (2005) Corporate yield spreads: default risk or liquidity? New evidence from the credit-default swap market. J Financ 60:2213–2253CrossRefGoogle Scholar
  22. Meng XL, Wong WH (1996) Simulating ratios of normalizing constants via a simple identity: a theoretical exploration. Stat Sin 6:831–860Google Scholar
  23. Merton RC (1974) On the pricing of corporate debt: The risk structure of interest rates. J Financ 29:449–470Google Scholar
  24. Micu M, Remolona E, Wooldridge P (2006) The price impact of rating announcements: which announcement matter? BIS working paper 207Google Scholar
  25. Mishkin FS, White EN (2002) US stock market crashes and their aftermath: Implications for monetary policy. NBER working paper 8992Google Scholar
  26. Norden L, Weber M (2004) Informational efficiency of credit default swap and stock markets: the impact of credit rating announcements. J Banking Financ 28:2813–2843CrossRefGoogle Scholar
  27. Reinhart CM, Rogoff KS (2008) Is the 2007 US subprime crisis so different? An international historical comparison. Am Econ Rev 98:339–344Google Scholar
  28. Reisen H (2008) The fallout from the global credit crisis: Contagion—emerging markets under stress. In: Felton A, Reinhart CM (eds) The first global financial crisis of the 21st Century. VoxEU.orgGoogle Scholar
  29. Richardson S, Green PJ (1997) On bayesian analysis of mixtures with an unknown number of components (with discussion). J R Stat Soc B 59:731–792CrossRefGoogle Scholar
  30. Robert CP, Celeux G, Diebolt J (1993) Bayesian estimation of hidden Markov chains: a stochastic implementation. Stat Probab Lett 16:77–83CrossRefGoogle Scholar
  31. Scott SL (2002) Bayesian methods for hidden Markov models: recursive computing in the 21st century. J Am Stat Assoc 97:337–351Google Scholar
  32. Tierney L (1994) Markov chains for exploring posterior distributions. Ann Stat 22:1701–1764CrossRefGoogle Scholar
  33. Zhu H (2006) An empirical comparison of credit spreads between the bond market and the credit default swap market. J Financ Serv Res 29:211–235CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Dipartimento di Economia e DirittoUniversità di MacerataMacerataItaly

Personalised recommendations