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Analysis of dependencies in low frequency financial data sets

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  • Ardia, David

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.

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File URL: http://mpra.ub.uni-muenchen.de/12682/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 12682.

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Date of creation: 2003
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Handle: RePEc:pra:mprapa:12682

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Related research

Keywords: dependencies; low-frequency; monthly; copula; GARCH;

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  1. Michel Dacorogna & Höskuldur Ari Hauksson & Thomas Domenig & Ulrich Müller & Gennady Samorodnitsky, 2001. "Multivariate extremes, aggregation and risk estimation," CeNDEF Workshop Papers, January 2001 P2, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  2. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
  3. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-617, December.
  4. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  5. Bouye, Eric & Durlleman, Valdo & Nikeghbali, Ashkan & Riboulet, Gaël & Roncalli, Thierry, 2000. "Copulas for finance," MPRA Paper 37359, University Library of Munich, Germany.
  6. Peter Blum & Michel Dacorogna & Lars Jaeger, 2003. "Performance and Risk Measurement Challenges For Hedge Funds: Empirical Considerations," Risk and Insurance 0311001, EconWPA.
  7. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
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