Common volatility across Latin American foreign exchange markets
AbstractThis article uses high-frequency exchange rate data for a group of 13 Latin American countries in order to analyse volatility co-movements. Particular interest is posed on understanding the existence of a common volatility process during the 1995-2008 period. The analysis relies on bivariate common factor models. We test for second-order common features using the common autoregressive conditional heteroskedasticity-feature methodology developed by Engle and Kozicki (1993). Overall, the results of this article indicate that while most currencies display evidence of time-varying variance, the volatility movements in the Latin American foreign exchange markets seems to be mainly country specific. Common volatility processes seem to be present only for a few South American markets.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Financial Economics.
Volume (Year): 19 (2009)
Issue (Month): 15 ()
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Web page: http://www.tandfonline.com/RAFE20
Other versions of this item:
- Isabel Ruiz, 2007. "Common Volatility across Latin American Foreign Exchange Markets," Working Papers 0702, Sam Houston State University, Department of Economics and International Business.
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- Arturo Lorenzo-Valdés & Antonio Ruiz-Porras, 2012. "Los rendimientos cambiarios latinoamericanos y la (a)simetría de los shocks informacionales: un análisis econométrico," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 87-113, November.
- David McMillan & Isabel Ruiz & Alan Speight, 2010. "Correlations and spillovers among three euro rates: evidence using realised variance," The European Journal of Finance, Taylor & Francis Journals, vol. 16(8), pages 753-767.
- Hecq Alain & Laurent Sébastien & Palm Franz C., 2012. "On the Univariate Representation of BEKK Models with Common Factors," Research Memorandum 018, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
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