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Stock market volatility spillovers: Evidence for Latin America

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  • Gamba-Santamaria, Santiago
  • Gomez-Gonzalez, Jose Eduardo
  • Hurtado-Guarin, Jorge Luis
  • Melo-Velandia, Luis Fernando

Abstract

We extend the framework of Diebold and Yilmaz (2009b) and Diebold and Yilmaz (2012) and construct volatility spillover indexes using a DCC-GARCH framework to model the multivariate relationships of volatility among assets. We compute spillover indexes directly from the series of asset returns and recognize the time-variant nature of the covariance matrix. Our approach allows for a better understanding of the movements of financial returns within a framework of volatility spillovers. We apply our method to stock market indexes of the United States and four Latin American countries. Our results show that Brazil is a net volatility transmitter for most of the sample period, while Chile, Colombia and Mexico are net receivers. The total spillover index is substantially higher between 2008Q3 and 2012Q2, and shock transmission from the United States to Latin America substantially increased around the Lehman Brothers’ episode.

Suggested Citation

  • Gamba-Santamaria, Santiago & Gomez-Gonzalez, Jose Eduardo & Hurtado-Guarin, Jorge Luis & Melo-Velandia, Luis Fernando, 2017. "Stock market volatility spillovers: Evidence for Latin America," Finance Research Letters, Elsevier, vol. 20(C), pages 207-216.
    • Handle: RePEc:eee:finlet:v:20:y:2017:i:c:p:207-216
    DOI: 10.1016/j.frl.2016.10.001
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    More about this item

    Keywords

    Volatility spillovers; DCC-GARCH model; Stock market linkages; Financial crisis;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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