IDEAS home Printed from https://ideas.repec.org/r/hal/journl/halshs-00180865.html
   My bibliography  Save this item

Empirical Estimation of Tail Dependence Using Copulas. Application to Asian Markets

Citations

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


Cited by:

  1. Yali Dou & Haiyan Liu & Georgios Aivaliotis, 2019. "Dynamic Dependence Modeling in financial time series," Papers 1908.05130, arXiv.org.
  2. D. Guegan & J. Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 421-430.
  3. Dominique Guegan, 2008. "Non-stationarity and meta-distribution," Post-Print halshs-00270708, HAL.
  4. Dominique Guegan, 2011. "Contagion Between the Financial Sphere and the Real Economy. Parametric and non Parametric Tools: A Comparison," PSE-Ecole d'économie de Paris (Postprint) halshs-00185373, HAL.
  5. Fousekis, Panos, 2017. "Price co-movement and the hedger's value-at-risk in the futures markets for coffee," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 0(Issue 1), January.
  6. Dominique Guegan, 2007. "Global and local stationary modelling in finance: theory and empirical evidence," Post-Print halshs-00187875, HAL.
  7. Dominique Guegan, 2010. "Value at Risk Computation in a Non-Stationary Setting," Post-Print halshs-00511995, HAL.
  8. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 113-149.
  9. Cyril Caillault, Dominique Guégan, 2009. "Forecasting VaR and Expected Shortfall Using Dynamical Systems: A Risk Management Strategy," Frontiers in Finance and Economics, SKEMA Business School, vol. 6(1), pages 26-50, April.
  10. Trottini, Mario & Muralidhar, Krish & Sarathy, Rathindra, 2011. "Maintaining tail dependence in data shuffling using t copula," Statistics & Probability Letters, Elsevier, vol. 81(3), pages 420-428, March.
  11. Dominique Guegan & Jing Zhang, 2006. "Change analysis of dynamic copula for measuring dependence in multivariate financial data," Post-Print halshs-00189141, HAL.
  12. Dominique Guégan, 2009. "A Meta-Distribution for Non-Stationary Samples," CREATES Research Papers 2009-24, Department of Economics and Business Economics, Aarhus University.
  13. Dominique Guegan & Jing Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," Post-Print halshs-00368334, HAL.
  14. Bedendo, Mascia & Campolongo, Francesca & Joossens, Elisabeth & Saita, Francesco, 2010. "Pricing multiasset equity options: How relevant is the dependence function?," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 788-801, April.
  15. Carlos Díaz-Caro & Jorge Onrubia, 2019. "How Did the ‘Dualization’ of the Spanish Income Tax Affect Horizontal Equity? Assessing its Impact Using Copula Functions," Hacienda Pública Española / Review of Public Economics, IEF, vol. 231(4), pages 81-124, December.
  16. repec:mth:ijafr8:v:9:y:2019:i:1:p:414-431 is not listed on IDEAS
  17. Dominique Guegan, 2011. "Contagion Between the Financial Sphere and the Real Economy. Parametric and non Parametric Tools: A Comparison," Post-Print halshs-00185373, HAL.
  18. Herrera, R. & Eichler, S., 2011. "Extreme dependence with asymmetric thresholds: Evidence for the European Monetary Union," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2916-2930, November.
  19. Sheng Fang & Paul Egan, 2021. "Tail dependence between oil prices and China's A‐shares: Evidence from firm‐level data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1469-1487, January.
  20. César Garcia-Gomez & Ana Pérez & Mercedes Prieto-Alaiz, 2022. "The evolution of poverty in the EU-28: a further look based on multivariate tail dependence," Working Papers 605, ECINEQ, Society for the Study of Economic Inequality.
  21. Aloui, Riadh & Aïssa, Mohamed Safouane Ben & Nguyen, Duc Khuong, 2011. "Global financial crisis, extreme interdependences, and contagion effects: The role of economic structure?," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 130-141, January.
  22. Fousekis, Panos & Grigoriadis, Vasilis, 2017. "Price co-movement and the crack spread in the US futures markets," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 57-71.
  23. Garcia, René & Tsafack, Georges, 2011. "Dependence structure and extreme comovements in international equity and bond markets," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1954-1970, August.
  24. Nikoloulopoulos, Aristidis K. & Joe, Harry & Li, Haijun, 2012. "Vine copulas with asymmetric tail dependence and applications to financial return data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3659-3673.
  25. Dominique Guegan & Jing Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," PSE-Ecole d'économie de Paris (Postprint) halshs-00368334, HAL.
  26. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," PSE-Ecole d'économie de Paris (Postprint) halshs-00375765, HAL.
  27. Bing-Yue Liu & Qiang Ji & Ying Fan, 2017. "A new time-varying optimal copula model identifying the dependence across markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 437-453, March.
  28. Matthieu Garcin & Maxime L. D. Nicolas, 2021. "Nonparametric estimator of the tail dependence coefficient: balancing bias and variance," Papers 2111.11128, arXiv.org, revised Jul 2023.
  29. Cubillos-Rocha, Juan S. & Gomez-Gonzalez, Jose E. & Melo-Velandia, Luis F., 2019. "Detecting exchange rate contagion using copula functions," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 13-22.
  30. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 113-149.
  31. Dominique Guegan, 2010. "Value at Risk Computation in a Non-Stationary Setting," PSE-Ecole d'économie de Paris (Postprint) halshs-00511995, HAL.
  32. Arismendi-Zambrano, Juan & Belitsky, Vladimir & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2022. "The implications of dependence, tail dependence, and bounds’ measures for counterparty credit risk pricing," Journal of Financial Stability, Elsevier, vol. 58(C).
  33. Qing Xu & Xiao-Ming Li, 2009. "Estimation of dynamic asymmetric tail dependences: an empirical study on Asian developed futures markets," Applied Financial Economics, Taylor & Francis Journals, vol. 19(4), pages 273-290.
  34. Gijbels Irène & Matterne Margot, 2021. "Study of partial and average conditional Kendall’s tau," Dependence Modeling, De Gruyter, vol. 9(1), pages 82-120, January.
  35. Dominique Guegan, 2007. "La persistance dans les marchés financiers," Post-Print halshs-00179269, HAL.
  36. Prayer M. Rikhotso & Beatrice D. Simo-Kengne, 2022. "Dependence Structures between Sovereign Credit Default Swaps and Global Risk Factors in BRICS Countries," JRFM, MDPI, vol. 15(3), pages 1-22, February.
  37. Yuri Salazar Flores & Adán Díaz-Hernández, 2021. "Counterdiagonal/nonpositive tail dependence in Vine copula constructions: application to portfolio management," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 375-407, June.
  38. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," Post-Print halshs-00375765, HAL.
  39. 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).
  40. Bücher, Axel & Jäschke, Stefan & Wied, Dominik, 2015. "Nonparametric tests for constant tail dependence with an application to energy and finance," Journal of Econometrics, Elsevier, vol. 187(1), pages 154-168.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.