Extracting the sovereigns´ CDS market hierarchy: a correlation-filtering approach
AbstractSince correlation may be interpreted as a measure of the influence across time-series, it may be conveniently mapped into a distance and into a weighted adjacency matrix. Based on such matrix, network theory has attempted to filter out the noise in correlation matrices by extracting the dominant hierarchy (i.e. the strongest linear-dependence signals) within time-series. The aim of this brief paper is to find the current hierarchy in the sovereigns´ CDS market after the structural shift caused by the failure of Lehman Brothers. Thus, based on two different correlation-into-distance mapping techniques and a minimal spanning tree-based correlation-filtering methodology on 36 sovereign CDS spread time-series, the target is to identify which sovereigns are providing the strongest -less noisy- and most informative signals. The resulting sovereigns´ CDS market hierarchy agrees with prior findings of Gilmore et al. (2010) regarding sovereigns´ bonds market, such as the importance of geographical clustering and the idiosyncratic nature of Japan and United States. Additionally, results (i) confirm that a small set of common factors affect the entire system; (ii) identify the relevance of credit rating clustering; (iii) identify Russia, Turkey and Brazil as regional benchmarks; (iv) suggest that lower-medium grade rated sovereigns are the most influential, but also the most prone to contagion; and (v) suggest the existence of a Latin American common factor". "
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Bibliographic InfoPaper provided by BANCO DE LA REPÚBLICA in its series BORRADORES DE ECONOMIA with number 010749.
Date of creation: 22 May 2013
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correlation; minimal spanning tree; correlation-filtering; sovereign; credit default swap;
Other versions of this item:
- Carlos Eduardo León Rincón & Karen Julieth Leiton & Jhonatan Perez Villalobos, 2013. "Extracting the sovereigns’ CDS market hierarchy: a correlation-filtering approach," Borradores de Economia 766, Banco de la Republica de Colombia.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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- Carlos León & Karen Leiton & Alejandro Reveiz, 2012.
"Investment Horizon Dependent CAPM: Adjusting beta for long-term dependence,"
BORRADORES DE ECONOMIA
009909, BANCO DE LA REPÚBLICA.
- Carlos León & Karen Leiton & Alejandro Reveiz, 2012. "Investment horizon dependent CAPM: Adjusting beta for long-term dependence," Borradores de Economia 730, Banco de la Republica de Colombia.
- Coudert, V. & Gex, M., 2010. "Credit default swap and bond markets: which leads the other?," Financial Stability Review, Banque de France, issue 14, pages 161-167, July.
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