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Copula-Based Models for Financial Time Series

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  • Andrew J. Patton

Abstract

This paper presents an overview of the literature on applications of copulas in the modelling of financial time series. Copulas have been used both in multivariate time series analysis, where they are used to characterise the (conditional) cross-sectional dependence between individual time series, and in univariate time series analysis, where they are used to characterise the dependence between a sequence of observations of a scalar time series process. The paper includes a broad, brief, review of the many applications of copulas in finance and economics.

Suggested Citation

  • Andrew J. Patton, 2008. "Copula-Based Models for Financial Time Series," Economics Series Working Papers 2008fe21, University of Oxford, Department of Economics.
  • Handle: RePEc:oxf:wpaper:2008fe21
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    Cited by:

    1. Pál Rakonczai & László Márkus & András Zempléni, 2012. "Autocopulas: Investigating the Interdependence Structure of Stationary Time Series," Methodology and Computing in Applied Probability, Springer, vol. 14(1), pages 149-167, March.
    2. Brendan K. Beare, 2010. "Copulas and Temporal Dependence," Econometrica, Econometric Society, vol. 78(1), pages 395-410, January.
    3. Vandna Jowaheer & Nafeessah Z. B. Ameerudden, 2012. "Modelling the Dependence Structure of MUR/USD and MUR/INR Exchange Rates using Copula," International Journal of Economics and Financial Issues, Econjournals, vol. 2(1), pages 27-32.
    4. Xiaohong Chen & Wei Biao Wu Wu & Yanping Yi, 2009. "Efficient estimation of copula-based semiparametric Markov models," CeMMAP working papers CWP06/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Documents de travail du Centre d'Economie de la Sorbonne 10040, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    6. Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2010. "Out-of-sample comparison of copula specifications in multivariate density forecasts," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1596-1609, September.
    7. Christoffersen, Peter & Langlois, Hugues, 2013. "The Joint Dynamics of Equity Market Factors," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(5), pages 1371-1404, October.
    8. Yongmin Chen & Michael H. Riordan, 2008. "Price‐increasing competition," RAND Journal of Economics, RAND Corporation, vol. 39(4), pages 1042-1058, December.
    9. Zhang, Dalu, 2014. "Vine copulas and applications to the European Union sovereign debt analysis," International Review of Financial Analysis, Elsevier, vol. 36(C), pages 46-56.
    10. Cathy Ning & Dinghai Xu & Tony Wirjanto, 2009. "Modeling Asymmetric Volatility Clusters Using Copulas and High Frequency Data," Working Papers 006, Ryerson University, Department of Economics.
    11. Cathy Q. Ning & Loran Chollete, 2009. "The Dependence Structure of Macroeconomic Variables in the US," Working Papers 005, Ryerson University, Department of Economics.
    12. Ning, Cathy & Xu, Dinghai & Wirjanto, Tony S., 2015. "Is volatility clustering of asset returns asymmetric?," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 62-76.
    13. Chollete, Loran & Pena, Victor de la & Lu, Ching-Chih, 2009. "International Diversification: A Copula Approach," UiS Working Papers in Economics and Finance 2009/27, University of Stavanger.
    14. Pierre-André Maugis & Dominique Guegan, 2010. "Note on new prospects on vines," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00471362, HAL.
    15. Romera, Rosario & Molanes, Elisa M., 2008. "Copulas in finance and insurance," DES - Working Papers. Statistics and Econometrics. WS ws086321, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Leonidas Tsiaras, 2010. "Dynamic Models of Exchange Rate Dependence Using Option Prices and Historical Returns," CREATES Research Papers 2010-35, Department of Economics and Business Economics, Aarhus University.
    17. Shenqiu Zhang & Ivan Paya & David Peel, 2009. "Linkages between Shanghai and Hong Kong stock indices," Applied Financial Economics, Taylor & Francis Journals, vol. 19(23), pages 1847-1857.
    18. Chollete, Loran & de la Pena , Victor & Lu, Ching-Chih, 2009. "International Diversification: An Extreme Value Approach," UiS Working Papers in Economics and Finance 2009/26, University of Stavanger.
    19. Lin, Feng & Peng, Liang & Xie, Jiehua & Yang, Jingping, 2018. "Stochastic distortion and its transformed copula," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 148-166.
    20. Yongmin Chen & Michael H. Riordan, 2013. "Profitability Of Product Bundling," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(1), pages 35-57, February.
    21. Bukre Yildirim Kulekci & Gulden Poyraz & Ismail Gur & Ozan Evkaya, 2023. "Dependence Analysis of the ISE100 Banking Sector Using Vine Copula," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 73(73-1), pages 55-81, June.

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