Abstract
This study investigates whether nonlinear relationship resulted from mutual regime switching mechanism exists in the European CDS’s markets during crisis. Multivariate Markov Switching Autoregressive Model that captures the switching mechanism is used. We analyzed the daily CDS spreads of Ireland, Italy, Portugal and Spain those most affected in European Debt Crisis. The data used in this study, belongs to the time period including 2010 and 2014 (1241 observations). The model have got three different regimes as depression, moderate growth and expansion. The results of the tests indicate that (1) CDS markets are governed by a long run relation, (2) volatility have an importance role in determining the regimes, (3) the shocks that applied to Italy and Spain are more effective than others, (4) Portugal is the more affected country between all, (5) the biggest response to the shocks are in the third regime.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Apergis N, Ajmi AN (2015) Systemic sovereign risk and asset prices: evidence from the CDS market, stressed European economies and nonlinear causality tests. Financ Uver 65(2):127
Balcilar M, Ozdemir ZA (2013) Asymmetric and time‐varying causality between inflation and inflation uncertainty in G‐7 countries. Scot J Polit Econ 60(1):1–42
Calice G, Mio R, Štěrba F, Vašíček B (2015) Short-term determinants of the idiosyncratic sovereign risk premium: a regime-dependent analysis for European credit default swaps. J Empir Financ 33:174–189
Caporin M (2013) Equity and CDS sector indices: dynamic models and risk hedging. N Am J Econ Financ 25:261–275
Chan KC, Marsden A (2014) Macro risk factors of credit default swap indices in a regime-switching framework. J Int Financ Mark Inst Money 29(C):285–308
Chan KC, Fung HG, Zhang G (2009) On the relationship between Asian credit default swap and equity markets. J Asia Case Stud 4(1):3–12
Chang JR, Hung MW, Tsai FT (2012) Cross-market hedging strategies for credit default swaps under a Markov regime-switching framework. J Fixed Income 22(2):44
Cornett MM, Mehran H, Pan K, Phan M, Wei CJ (2014) CDS and equity market reactions to stock issuances in the US financial industry: evidence from the 2002–13 period. FRB of New York Staff Report (697)
Coudert V, Gex M (2010) Disrupted links between credit default swaps, bonds and equities during the GM and Ford crisis in 2005. Appl Financ Econ 20(23):1769–1792
Dong Y, Yuen KC, Wu C (2014) A multivariate regime-switching mean reverting process and its application to the valuation of credit risk. Stoch Anal Appl 32(4):687–710
Ersan İ, Günay S (2009) Kredi Risk Göstergesi Olarak Kredi Temerrüt Swapları (CDSs) ve Kapatma Davasının Türkiye Riski Üzerine Etkilerine Dair Bir Uygulama. Bankacılar Dergisi 71:3–22
Guidolin M. Modelling, estimating and forecasting financial data under regime (Markov) switching. Lecture 7, Department of Finance, Bocconi University. http://didattica.unibocconi.it/mypage/dwload.php?nomefile=Lecture_7_-_Markov_Switching_Models20130520235704.pdf. Accessed 30 Mar 2016
Gun M, Kutlu M, Karamustafa O (2016) The effects of Gezi Park protests on Turkey’s Credit Default Swaps (CDS). J Bus Res Turk 8(1):556–575
Guo B, Newton D (2013) Regime-dependent liquidity determinants of credit default swap spread changes. J Financ Res 36(2):279–298
Hamilton JD (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57(2):357–384
Huang AY, Hu WC (2012) Regime switching dynamics in credit default swaps: evidence from smooth transition autoregressive model. Phys Stat Mech Appl 391(4):1497–1508
Hull JC (2012) Options, futures and other derivatives. Pearson Education, London
Kapadia N, Pu X (2012) Limited arbitrage between equity and credit markets. J Financ Econ 105(3):542–564
Krolzig HM (1998) Econometric modelling of Markov-switching vector autoregressions using MSVAR for Ox
Krolzig HM (2000) Predicting Markov-switching vector autoregressive processes. Nuffield College
Liang X, Wang G, Li H (2014) Pricing credit default swaps with bilateral counterparty risk in a reduced form model with Markov regime switching. Appl Math Comput 230:290–302
Qian Z, Luo Q (2016) Regime-dependent determinants of China’s sovereign credit default swap spread. Emerg Market Finance Trade 52(1):10–21
Realdon M (2008) Credit default swap rates and stock prices. Appl Financ Econ Lett 4(4):241–248
Yenice S, Hazar A (2015) A study for the interaction between risk premiums and stock exchange in developing countries. J Econ Finan Acc 2(2):135–151
Zhang G (2009) Informational efficiency of credit default swap and stock markets: the impact of adverse credit events. Int Rev Bank Acc Financ 1:1–15
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Koy, A. (2017). International Credit Default Swaps Market During European Crisis: A Markov Switching Approach. In: Hacioğlu, Ü., Dinçer, H. (eds) Global Financial Crisis and Its Ramifications on Capital Markets. Contributions to Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-47021-4_30
Download citation
DOI: https://doi.org/10.1007/978-3-319-47021-4_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-47020-7
Online ISBN: 978-3-319-47021-4
eBook Packages: Economics and FinanceEconomics and Finance (R0)