Analysis of dependencies in low frequency financial data sets

Ardia, David (2003): Analysis of dependencies in low frequency financial data sets.

Abstract

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: dependencies; low-frequency; monthly; copula; GARCH
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C50 - General; G - Financial Economics > G2 - Financial Institutions and Services > G22 - Insurance; Insurance Companies

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