IDEAS home Printed from https://ideas.repec.org/a/taf/emetrv/v31y2012i6p654-687.html
   My bibliography  Save this article

A Survey on Time-Varying Copulas: Specification, Simulations, and Application

Author

Listed:
  • Hans Manner
  • Olga Reznikova

Abstract

The aim of this article is to bring together different specifications for copula models with time-varying dependence structure. Copula models are widely used in financial econometrics and risk management. They are considered to be a competitive alternative to the Gaussian dependence structure. The dynamic structure of the dependence between the data can be modeled by allowing either the copula function or the dependence parameter to be time-varying. First, we give a brief description of eight different models, among which there are fully parametric, semiparametric, and adaptive methods. The purpose of this study is to compare the applicability of each particular model in different cases. We conduct a simulation study to show the performance for model selection, to compare the model fit for different setups and to study the ability of the models to estimate the (latent) time-varying dependence parameter. Finally, we provide an illustration by applying the competing models on the same financial dataset and compare their performance by means of Value-at-Risk.

Suggested Citation

  • Hans Manner & Olga Reznikova, 2012. "A Survey on Time-Varying Copulas: Specification, Simulations, and Application," Econometric Reviews, Taylor & Francis Journals, vol. 31(6), pages 654-687, November.
    • Handle: RePEc:taf:emetrv:v:31:y:2012:i:6:p:654-687
    DOI: 10.1080/07474938.2011.608042
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07474938.2011.608042
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/07474938.2011.608042?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Drew Creal & Siem Jan Koopman & André Lucas, 2008. "A General Framework for Observation Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 08-108/4, Tinbergen Institute.
    2. Markwat, T.D. & Kole, H.J.W.G. & van Dijk, D.J.C., 2009. "Time Variation in Asset Return Dependence: Strength or Structure?," ERIM Report Series Research in Management ERS-2009-052-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. HEINEN, Andréas & VALDESOGO, Alfonso, 2009. "Asymmetric CAPM dependence for large dimensions: the Canonical Vine Autoregressive Model," LIDAM Discussion Papers CORE 2009069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    2. Małgorzata Doman & Ryszard Doman, 2013. "Dynamic linkages between stock markets: the effects of crises and globalization," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 12(2), pages 87-112, August.
    3. Jammazi, Rania & Tiwari, Aviral Kr. & Ferrer, Román & Moya, Pablo, 2015. "Time-varying dependence between stock and government bond returns: International evidence with dynamic copulas," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 74-93.
    4. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," JRFM, MDPI, vol. 7(2), pages 1-30, June.
    5. Luca Riccetti, 2013. "A copula–GARCH model for macro asset allocation of a portfolio with commodities," Empirical Economics, Springer, vol. 44(3), pages 1315-1336, June.
    6. David E. Allen & Michael McAleer & Marcel Scharth, 2009. "Realized Volatility Risk," CARF F-Series CARF-F-197, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, revised Jan 2010.
    7. David Walsh-Jones & Daniel Jones & Christoph Reisinger, 2014. "Modelling of dependence in high-dimensional financial time series by cluster-derived canonical vines," Papers 1411.4970, arXiv.org.
    8. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    9. Weiß, Gregor N.F. & Scheffer, Marcus, 2015. "Mixture pair-copula-constructions," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 175-191.
    10. Koliai, Lyes, 2016. "Extreme risk modeling: An EVT–pair-copulas approach for financial stress tests," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 1-22.
    11. Karim, Sitara & Lucey, Brian M. & Naeem, Muhammad Abubakr & Vigne, Samuel A., 2023. "The dark side of Bitcoin: Do Emerging Asian Islamic markets help subdue the ethical risk?," Emerging Markets Review, Elsevier, vol. 54(C).
    12. Francq, Christian & Zakoian, Jean-Michel, 2023. "Local Asymptotic Normality Of General Conditionally Heteroskedastic And Score-Driven Time-Series Models," Econometric Theory, Cambridge University Press, vol. 39(5), pages 1067-1092, October.
    13. Neil Shephard, 2013. "Martingale unobserved component models," Economics Papers 2013-W01, Economics Group, Nuffield College, University of Oxford.
    14. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    15. Jose Arreola Hernandez & Shawkat Hammoudeh & Duc Khuong Nguyen & Mazin A. M. Al Janabi & Juan Carlos Reboredo, 2017. "Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach," Applied Economics, Taylor & Francis Journals, vol. 49(25), pages 2409-2427, May.
    16. Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2021. "Price Dividend Ratio and Long-Run Stock Returns: A Score-Driven State Space Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1054-1065, October.
    17. Gregor Weiß, 2013. "Copula-GARCH versus dynamic conditional correlation: an empirical study on VaR and ES forecasting accuracy," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 179-202, August.
    18. Aepli, Matthias D. & Frauendorfer, Karl & Fuess, Roland & Paraschiv, Florentina, 2015. "Multivariate Dynamic Copula Models: Parameter Estimation and Forecast Evaluation," Working Papers on Finance 1513, University of St. Gallen, School of Finance.
    19. Hobæk Haff, Ingrid & Aas, Kjersti & Frigessi, Arnoldo & Lacal, Virginia, 2016. "Structure learning in Bayesian Networks using regular vines," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 186-208.
    20. Giovanni Angelini & Giuseppe Cavaliere & Enzo D'Innocenzo & Luca De Angelis, 2022. "Time-Varying Poisson Autoregression," Papers 2207.11003, arXiv.org.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:emetrv:v:31:y:2012:i:6:p:654-687. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: http://www.tandfonline.com/LECR20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.