IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v52y2011i3p709-731.html
   My bibliography  Save this article

Comparing point and interval estimates in the bivariate t-copula model with application to financial data

Author

Listed:
  • Rada Dakovic
  • Claudia Czado

Abstract

No abstract is available for this item.

Suggested Citation

  • Rada Dakovic & Claudia Czado, 2011. "Comparing point and interval estimates in the bivariate t-copula model with application to financial data," Statistical Papers, Springer, vol. 52(3), pages 709-731, August.
    • Handle: RePEc:spr:stpapr:v:52:y:2011:i:3:p:709-731
    DOI: 10.1007/s00362-009-0279-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00362-009-0279-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00362-009-0279-8?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. 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. Luciana Dalla Valle, 2012. "Erratum to: Bayesian Copulae Distributions, with Application to Operational Risk Management," Methodology and Computing in Applied Probability, Springer, vol. 14(4), pages 1121-1121, December.
    3. Luciana Dalla Valle, 2009. "Bayesian Copulae Distributions, with Application to Operational Risk Management," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 95-115, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. O. Chatrabgoun & G. Parham & R. Chinipardaz, 2017. "A Legendre multiwavelets approach to copula density estimation," Statistical Papers, Springer, vol. 58(3), pages 673-690, September.

    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. Philipp Arbenz, 2013. "Bayesian Copulae Distributions, with Application to Operational Risk Management—Some Comments," Methodology and Computing in Applied Probability, Springer, vol. 15(1), pages 105-108, March.
    2. Pavel V. Shevchenko, 2009. "Implementing Loss Distribution Approach for Operational Risk," Papers 0904.1805, arXiv.org, revised Jul 2009.
    3. Juan Wu & Xue Wang & Stephen G. Walker, 2014. "Bayesian Nonparametric Inference for a Multivariate Copula Function," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 747-763, September.
    4. Muhammad Aslam, 2024. "Bayes Estimator Under Neutrosophic Statistics: A Robust Approach for Handling Uncertainty and Imprecise Data," Methodology and Computing in Applied Probability, Springer, vol. 26(4), pages 1-18, December.
    5. Luca Regis, 2011. "A Bayesian copula model for stochastic claims reserving," Carlo Alberto Notebooks 227, Collegio Carlo Alberto.
    6. Pavel V. Shevchenko, 2010. "Implementing loss distribution approach for operational risk," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(3), pages 277-307, May.
    7. Shumin Ma & Zhiri Yuan & Qi Wu & Yiyan Huang & Xixu Hu & Cheuk Hang Leung & Dongdong Wang & Zhixiang Huang, 2023. "Deep into The Domain Shift: Transfer Learning through Dependence Regularization," Papers 2305.19499, arXiv.org.
    8. Dean Fantazzini, 2008. "Econometric Analysis of Financial Data in Risk Management (continuation). Section III: Managing Operational Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 11(3), pages 87-122.
    9. Tahani S. Alotaibi & Luciana Dalla Valle & Matthew J. Craven, 2022. "The Worst Case GARCH-Copula CVaR Approach for Portfolio Optimisation: Evidence from Financial Markets," JRFM, MDPI, vol. 15(10), pages 1-14, October.
    10. Mohamed Habachi & Saâd Benbachir, 2020. "The Bayesian Approach to Capital Allocation at Operational Risk: A Combination of Statistical Data and Expert Opinion," IJFS, MDPI, vol. 8(1), pages 1-25, February.
    11. DAVID E. ALLEN & MICHAEL McALEER & ROBERT J. POWELL & ABHAY K. SINGH, 2018. "Non-Parametric Multiple Change Point Analysis Of The Global Financial Crisis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-23, June.
    12. Rand Kwong Yew Low, 2018. "Vine copulas: modelling systemic risk and enhancing higher‐moment portfolio optimisation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 423-463, November.
    13. F. Durante & A. Gatto & F. Ravazzolo, 2024. "Understanding relationships with the Aggregate Zonal Imbalance using copulas," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(2), pages 513-554, April.
    14. Roger M. Cooke & Harry Joe & Bo Chang, 2020. "Vine copula regression for observational studies," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(2), pages 141-167, June.
    15. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    16. Yao, Yinhong & Chen, Xiuwen & Chen, Zhensong, 2025. "Portfolio tail risk forecasting for international financial assets: A GARCH-MIDAS-R-Vine copula model," The North American Journal of Economics and Finance, Elsevier, vol. 77(C).
    17. Li, Feng & Kang, Yanfei, 2018. "Improving forecasting performance using covariate-dependent copula models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 456-476.
    18. 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.
    19. Portier, François & Segers, Johan, 2018. "On the weak convergence of the empirical conditional copula under a simplifying assumption," Journal of Multivariate Analysis, Elsevier, vol. 166(C), pages 160-181.
    20. Reboredo, Juan C. & Ugolini, Andrea, 2015. "A vine-copula conditional value-at-risk approach to systemic sovereign debt risk for the financial sector," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 98-123.

    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:spr:stpapr:v:52:y:2011:i:3:p:709-731. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.