Asymmetric volatility spillovers of financial markets: an application to Colombia

In this article we suggest how to quantify asymmetric volatility transmission between financial markets by transforming asset prices into cumulative positive and negative changes, while recognizing a time-varying covariance matrix. We compute the asymmetrical spillover indices for the Colombia’s sov...

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Autores:
Vargas Paez, Andrea Carolina
Tipo de recurso:
Fecha de publicación:
2019
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/69227
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/69227
http://bdigital.unal.edu.co/70810/
Palabra clave:
33 Economía / Economics
Asymmetric effects
Volatility transmission
Generalized IRF
Financial markets
Market linkages
Efectos asimétricos
Transmisión de volatilidad
Funciones de impulso-respuesta generalizadas
Mercados financieros
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:In this article we suggest how to quantify asymmetric volatility transmission between financial markets by transforming asset prices into cumulative positive and negative changes, while recognizing a time-varying covariance matrix. We compute the asymmetrical spillover indices for the Colombia’s sovereign bond, interbank overnight, foreign exchange, equity, and credit default swaps markets. The US stock market index was also included to avoid a possible omitted variable bias. Daily data for the period 2006-2016 was used. Our findings support the asymmetric connectedness among Colombia’s financialmarkets as spillovers in presence of adverse shocks are larger than the observed with positive innovations. CDS achieved the largest transmission levels of downside risk, whereas transmission from US stock market to the other markets was higher on average, especially in periods of financial turmoil. We compare the results with those obtained from the estimation of a multivariate asymmetric GARCH model for the total asset returns. An algorithm for robustness analysis is presented.