Relación dinámica entre los Credit Default Swaps y la deuda pública. Análisis en el contexto latinoamericano
Dynamic relationship between Credit Default Swaps and sovereign debt: analysis on the Latin-American context
Relação dinâmica entre Credit Default Swaps e a dívida pública. Análise no contexto latino-americano
DOI:
https://doi.org/10.15446/cuad.econ.v40n83.81997Palabras clave:
Credit Default Swaps, Correlación Condicional Dinámica, derivados de crédito, deuda soberana, riesgo de crédito (es)credit default swaps, correlação condicional dinâmica, derivados de crédito, dívida soberana, risco de crédito (pt)
Credit default swaps, credit derivatives, credit risk, dynamic conditional correlation, sovereign debt (en)
Se analiza cómo los Credit Default Swaps (CDS) están relacionados con el riesgo soberano en Brasil, Chile, Colombia y México, durante el período 2010-2019. Se estiman modelos de correlación condicional dinámica (DCC) y pruebas de causalidad de Granger. Se encuentra una tendencia general decreciente en las correlaciones de los últimos años de la muestra, lo cual puede ser explicado por una mejoría en la calificación de deuda soberana y una caída en riesgo de inversión en Colombia, Chile y Brasil. Además, los resultados empíricos evidencian que los CDS tienen influencia en el comportamiento de los bonos de deuda pública.
Credit Default Swaps (CDS) on public external debt can be used as a proxy for sovereign risk. This study analyzes how the behavior of the CDS is related to sovereign risk in the period 2010-2019 for Colombia, Chile, Brazil, and Mexico. Thus, the dynamic conditional correlation (DCC) model and the Granger causality test are used. It is found that there is a dynamic conditional correlation between these two instruments. Also, there is Granger causality given by the CDS for the bonds, that is, that the CDS has some influence on the bonds' behavior; presenting the bidirectional causality (the bonds have some influence of the CDS behavior), for Brazil, Chile, and Colombia. Besides, the DCC estimates shows a considerable variation in the correlations, where the general trend is decreasing, with negative correlations in the sample last years, which can be explained by an improvement in the rating and an investment risk fall in Colombia, Chile and Brazil, exhibiting Chile the lowest volatility due to its good rating and Mexico a stable volatility with conditional correlations close to 0%, reflecting a desired behavior of the price of the bonds.
Analisa-se como os Credit Default Swaps (CDS) se relacionam com o risco soberano no Brasil, Chile, Colômbia e México, durante o período 2010-2019. Modelos de correlação condicional dinâmica (DCC) e testes de causalidade de Granger são estimados. Observa-se uma tendência decrescente geral nas correlações dos últimos anos da amostra, que pode ser explicada por uma melhora no rating da dívida soberana e uma queda no risco de investimento na Colômbia, Chile e Brasil. Além disso, os resultados empíricos mostram que os CDS influenciam o comportamento dos títulos da dívida pública.
Referencias
Amstad, M., Remolona, E., & Shek, J. (2016). How do global investors differentiate between sovereign risks? The new normal versus the old. Journal of International Money and Finance, 66, 32-48. https://www.doi.org/10.1016/j.jimonfin.2015.12.006
Arbeláez, J. C., & Maya, C. (2008). Valoración de Credit Default Swaps (CDS). Una aproximación con el método Monte Carlo. Cuadernos de Administración, 21(36), 87-111.
Banco de la República. (2016, 18 de marzo). Circular reglamentaria externa DODM-144. Asunto 6. Operaciones de derivados. Bogotá: autor. https://bit.ly/37V8Yso
Bernardi, E., Falangi, F., & Romagnoli, S. (2015). A hierarchical copulabased world-wide valuation of sovereign risk. Insurance: Mathematics and Economics, 61, 155-169. https://www.doi.org/10.1016/j.insmatheco.2015.01.003
Chiang, T. C., Jeon, B. N., & Li, H. (2007). Dynamic correlation analysis of financial contagion: Evidence from Asian markets. Journal of International Money and Finance, 26(7), 1206-1228. https://www.doi.org/10.1016/j.jimonfin.2007.06.005
Claußen, A., Löhr, S., Rösch, D., & Scheule, H. (2015). Valuation of sytematic risk in the cross-section of credit default swap spreads. Quarterly Review of Economics and Finance, 64, 183-195. https://www.doi.org/10.1016/j.qref.2016.06.007
Diebold, F. X., & Li, C. (2006). Forecasting the term structure of government bond yields. Journal of Econometrics, 130(2), 337-364. https://www.doi.org/10.1016/j.jeconom.2005.03.005
Elliott, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4), 813-836. https://www.doi.org/10.2307/2171846
Engle, R. (2002). Dynamic conditional correlation. Journal of Business & Economic Statistics, 20(3), 339-350. https://www.doi.org/10.1198/073500102288618487
Gökgöz, I. H., Ugˇur, Ö., & Yolcu, Y. (2014). On the single name CDS price under structural modeling. Journal of Computational and Applied Mathematics, 259(Part B), 406-412. https://www.doi.org/10.1016/j.cam.2013.07.052
Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424-438. https://www.doi.org/10.2307/1912791
Guarin, A., Liu, X., & Ng, W. L. (2014). Recovering default risk from CDS spreads with a nonlinear filter. Journal of Economic Dynamics and Control, 38(1), 87-104. https://www.doi.org/10.1016/j.jedc.2013.09.006
Hassan, M. K., Ngene, G. M., & Yu, J. S. (2015). Credit default swaps and sovereign debt markets. Economic Systems, 39(2), 240-252. https://www.doi.org/10.1016/j.ecosys.2014.07.002
Houweling, P., & Vorst, T. (2005). Pricing default swaps: Empirical evidence. Journal of International Money and Finance, 24(8), 1200-1225. https://www.doi.org/10.1016/j.jimonfin.2005.08.009
Jacquier, E., & Jarrow, R. (2000). Bayesian analysis of contingent claim model error. Journal of Econometrics, 94(1), 145-180. https://www.doi.org/10.1016/S0304-4076(99)00020-2
Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics & Control, 12(2/3), 231-254. https://doi.org/10.1016/0165-1889(88)90041-3
Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica, 59(6), 1551-1580. https://www.doi.org/10.2307/2938278
Longstaff, F. A., Pan, J., Pedersen, L. H., & Singleton, K. J. (2011). How sovereign is sovereign credit risk? American Economic Journal: Macroeconomics, 3(2), 75-103. https://www.doi.org/10.1257/mac.3.2.75
Madan, D. B. (2014). Modeling and monitoring risk acceptability in markets: The case of the Credit Default Swap market. Journal of Banking and Finance, 47(1), 63-73. https://www.doi.org/10.1016/j.jbankfin.2014.05.024
Nelson, C. R., & Siegel, A. F. (1987). Parsimonious modeling of yield curves. Journal of Business, 60(4), 473-489. https://www.doi.org/10.1086/296409
Phillips, P. C., & Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75(2), 335-346. https://www.doi.org/10.1093/biomet/75.2.335
Ratner, M., & Chiu, C. C. (2013). Hedging stock sector risk with Credit Default Swaps. International Review of Financial Analysis, 30, 18-25. https://www.doi.org/10.1016/j.irfa.2013.05.001
Rubia, A., Sanchis, L., & Serrano, P. (2016). Market frictions and the pricing of sovereign credit default swaps. Journal of International Money and Finance, 60, 223-252. https://www.doi.org/10.1016/j.jimonfin.2015.04.006
Schwarcz, D., & Schwarcz, S. L. (2016). Regulating systemic risk in insurance. The University of Chicago Law Review, 81(4), 1569-1640.
Shaw, F., Murphy, F., & O’Brien, F. (2014). The forecasting efficiency of the dynamic Nelson Siegel model on Credit Default Swaps. Research in International Business and Finance, 30, 348-368. https://www.doi.org/10.1016/j.ribaf.2012.08.007
Vuillemey, G., & Peltonen, T. A. (2015). Disentangling the bond-CDS Nexus: A stress test model of the CDS market. Economic Modelling, 49, 32-45. https://www.doi.org/10.1016/j.econmod.2015.03.015
Cómo citar
APA
ACM
ACS
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver
Descargar cita
Licencia
Derechos de autor 2021 Cuadernos de EconomíaCuadernos de Economía a través de la División de Bibliotecas de la Universidad Nacional de Colombia promueve y garantiza el acceso abierto de todos sus contenidos. Los artículos publicados por la revista se encuentran disponibles globalmente con acceso abierto y licenciados bajo los términos de Creative Commons Atribución-No_Comercial-Sin_Derivadas 4.0 Internacional (CC BY-NC-ND 4.0), lo que implica lo siguiente:




