International Credit Default Swaps Market During European Crisis: A Markov Switching Approach

Ayben Koy ()
Additional contact information
Ayben Koy: Istanbul Commerce University

A chapter in Global Financial Crisis and Its Ramifications on Capital Markets, 2017, pp 431-443 from Springer

Abstract: 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.

Keywords: Credit Risk; Credit Default Swap; Regime Switching; Markov Switching; Credit Default Swap Spread (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (3)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:conchp:978-3-319-47021-4_30

Ordering information: This item can be ordered from
http://www.springer.com/9783319470214

DOI: 10.1007/978-3-319-47021-4_30

Access Statistics for this chapter

More chapters in Contributions to Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().