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Volatility Transmission in Overlapping Trading Zones

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  • Andreas Masuhr

Abstract

Previous volatility spillover models (Engle et al. 1990, Clements et al. 2015) use artificially non overlapping trading zones to identify sources of volatility transmission between these zones. The problem of non overlapping zones is overcome using a copula GARCH approach that allows for multiple overlaps between zones incorporating vine copulas to flexibly model the dependence structure and to meet stylized facts of return data. Stationarity conditions are examined and identifications problems concerning previous work, as well, are pointed out. To handle the relatively large parameter space, the model is estimated by Bayesian methods using a differential evolution MCMC (Braak 2006) approach. Simulation studies are carried out in order to ensure robustness against copula or error term misspecification and in order to analyze the identification problem.

Suggested Citation

  • Andreas Masuhr, 2017. "Volatility Transmission in Overlapping Trading Zones," CQE Working Papers 6717, Center for Quantitative Economics (CQE), University of Muenster.
  • Handle: RePEc:cqe:wpaper:6717
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    File URL: https://www.wiwi.uni-muenster.de/cqe/sites/cqe/files/CQE_Paper/cqe_wp_67_2017.pdf
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    References listed on IDEAS

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    1. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    2. Lee, Tae-Hwy & Long, Xiangdong, 2009. "Copula-based multivariate GARCH model with uncorrelated dependent errors," Journal of Econometrics, Elsevier, vol. 150(2), pages 207-218, June.
    3. Cornelia Savu & Mark Trede, 2010. "Hierarchies of Archimedean copulas," Quantitative Finance, Taylor & Francis Journals, vol. 10(3), pages 295-304.
    4. DiƟmann, J. & Brechmann, E.C. & Czado, C. & Kurowicka, D., 2013. "Selecting and estimating regular vine copulae and application to financial returns," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 52-69.
    5. Richard J Rogalski & Joseph D Vinso, 1978. "Empirical Properties of Foreign Exchange Rates," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 9(2), pages 69-79, June.
    6. Engle, Robert F & Ito, Takatoshi & Lin, Wen-Ling, 1990. "Meteor Showers or Heat Waves? Heteroskedastic Intra-daily Volatility in the Foreign Exchange Market," Econometrica, Econometric Society, vol. 58(3), pages 525-542, May.
    7. Boothe, Paul & Glassman, Debra, 1987. "The statistical distribution of exchange rates: Empirical evidence and economic implications," Journal of International Economics, Elsevier, vol. 22(3-4), pages 297-319, May.
    8. Clements, A.E. & Hurn, A.S. & Volkov, V.V., 2015. "Volatility transmission in global financial markets," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 3-18.
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