Analysis of Dependencies in Low Frequency Financial Data Sets
Posted: 15 Apr 2004 Last revised: 14 Dec 2015
Date Written: January 11, 2003
This empirical study proposes a dependency analysis of monthly financial time series. We use the overlapping technique and non-parametric correlation in order to increase both accuracy and consistency. Copulas are used to test extreme co-movements between financial securities. Our results indicate that even in a low-frequency framework, the common practice of assuming independence over time should be taken with caution due to the presence of GARCH effects. In addition, extreme co-movements are observed across securities, especially for interest rates.
Keywords: Dependencies, low-frequency, monthly, copula, GARCH
JEL Classification: C10, C13, C14, C50, G22
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