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Vine copulas with asymmetric tail dependence and applications to financial return data

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Cited by:

  1. 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.
  2. 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.
  3. Dalla Valle, Luciana & De Giuli, Maria Elena & Tarantola, Claudia & Manelli, Claudio, 2016. "Default probability estimation via pair copula constructions," European Journal of Operational Research, Elsevier, vol. 249(1), pages 298-311.
  4. Reboredo, Juan C. & Ugolini, Andrea, 2018. "The impact of energy prices on clean energy stock prices. A multivariate quantile dependence approach," Energy Economics, Elsevier, vol. 76(C), pages 136-152.
  5. Stöber, Jakob & Czado, Claudia, 2014. "Regime switches in the dependence structure of multidimensional financial data," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 672-686.
  6. Arreola Hernandez, Jose, 2014. "Are oil and gas stocks from the Australian market riskier than coal and uranium stocks? Dependence risk analysis and portfolio optimization," Energy Economics, Elsevier, vol. 45(C), pages 528-536.
  7. Brechmann, Eike Christian & Schepsmeier, Ulf, 2013. "Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i03).
  8. Pavel Krupskii & Harry Joe, 2015. "Tail-weighted measures of dependence," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 614-629, March.
  9. 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.
  10. Marbac, Matthieu & Sedki, Mohammed, 2017. "A family of block-wise one-factor distributions for modeling high-dimensional binary data," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 130-145.
  11. Li, Wei-Zhen & Zhai, Jin-Rui & Jiang, Zhi-Qiang & Wang, Gang-Jin & Zhou, Wei-Xing, 2022. "Predicting tail events in a RIA-EVT-Copula framework," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
  12. Laih, Yih-Wenn, 2014. "Measuring rank correlation coefficients between financial time series: A GARCH-copula based sequence alignment algorithm," European Journal of Operational Research, Elsevier, vol. 232(2), pages 375-382.
  13. 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.
  14. Mangold, Benedikt, 2017. "New concepts of symmetry for copulas," FAU Discussion Papers in Economics 06/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2017.
  15. Wahbeeah Mohti & Andreia Dionísio & Paulo Ferreira & Isabel Vieira, 2019. "Contagion of the Subprime Financial Crisis on Frontier Stock Markets: A Copula Analysis," Economies, MDPI, vol. 7(1), pages 1-14, February.
  16. Chao Xu & Jinchuan Ke & Xiaojun Zhao & Xiaofang Zhao, 2020. "Multiscale Quantile Correlation Coefficient: Measuring Tail Dependence of Financial Time Series," Sustainability, MDPI, vol. 12(12), pages 1-24, June.
  17. Atil, Ahmed & Bradford, Marc & Elmarzougui, Abdelaziz & Lahiani, Amine, 2016. "Conditional dependence of US and EU sovereign CDS: A time-varying copula-based estimation," Finance Research Letters, Elsevier, vol. 19(C), pages 42-53.
  18. Mensi, Walid & Hammoudeh, Shawkat & Reboredo, Juan C. & Nguyen, Duc Khuong, 2015. "Are Sharia stocks, gold and U.S. Treasury hedges and/or safe havens for the oil-based GCC markets?," Emerging Markets Review, Elsevier, vol. 24(C), pages 101-121.
  19. Hua, Lei & Joe, Harry, 2014. "Strength of tail dependence based on conditional tail expectation," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 143-159.
  20. Giuseppe Arbia & Riccardo Bramante & Silvia Facchinetti, 2020. "Least Quartic Regression Criterion to Evaluate Systematic Risk in the Presence of Co-Skewness and Co-Kurtosis," Risks, MDPI, vol. 8(3), pages 1-14, September.
  21. A. Ford Ramsey & Barry K. Goodwin, 2019. "Value-at-Risk and Models of Dependence in the U.S. Federal Crop Insurance Program," JRFM, MDPI, vol. 12(2), pages 1-21, April.
  22. Pavel Krupskii, 2017. "Copula-based measures of reflection and permutation asymmetry and statistical tests," Statistical Papers, Springer, vol. 58(4), pages 1165-1187, December.
  23. Alqaralleh, Huthaifa & Canepa, Alessandra & Zanetti Chini, Emilio, 2020. "COVID-19 Pandemic and Stock Market Contagion: A Wavelet-Copula GARCH Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202012, University of Turin.
  24. Weiß, Gregor N.F. & Scheffer, Marcus, 2015. "Mixture pair-copula-constructions," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 175-191.
  25. Ojea Ferreiro, Javier, 2020. "Disentangling the role of the exchange rate in oil-related scenarios for the European stock market," Energy Economics, Elsevier, vol. 89(C).
  26. 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.
  27. Kreuzer, Alexander & Czado, Claudia, 2021. "Bayesian inference for a single factor copula stochastic volatility model using Hamiltonian Monte Carlo," Econometrics and Statistics, Elsevier, vol. 19(C), pages 130-150.
  28. Müller, Alfred & Reuber, Matthias, 2023. "A copula-based time series model for global horizontal irradiation," International Journal of Forecasting, Elsevier, vol. 39(2), pages 869-883.
  29. Ming-Chu Chiang & I-Chun Tsai, 2016. "Ripple effect and contagious effect in the US regional housing markets," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 55-82, January.
  30. Alqaralleh, Huthaifa & Canepa, Alessandra & Chini, Zanetti, 2021. "Financial Contagion During the Covid-19 Pandemic: A Wavelet-Copula-GARCH Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202110, University of Turin.
  31. Ming-Chu Chiang & I-Chun Tsai, 2016. "Ripple effect and contagious effect in the US regional housing markets," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 55-82, January.
  32. Siburg, Karl Friedrich & Stoimenov, Pavel & Weiß, Gregor N.F., 2015. "Forecasting portfolio-Value-at-Risk with nonparametric lower tail dependence estimates," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 129-140.
  33. Dißmann, 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.
  34. Reboredo, Juan C. & Ugolini, Andrea, 2015. "Downside/upside price spillovers between precious metals: A vine copula approach," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 84-102.
  35. Brechmann, Eike C. & Joe, Harry, 2015. "Truncation of vine copulas using fit indices," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 19-33.
  36. Dingshi Tian & Zongwu Cai & Ying Fang, 2018. "Econometric Modeling of Risk Measures: A Selective Review of the Recent Literature," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201807, University of Kansas, Department of Economics, revised Oct 2018.
  37. Ojea-Ferreiro, Javier & Reboredo, Juan C., 2022. "Exchange rates and the global transmission of equity market shocks," Economic Modelling, Elsevier, vol. 114(C).
  38. Wu, Fei & Xiao, Xuanqi & Zhou, Xinyu & Zhang, Dayong & Ji, Qiang, 2022. "Complex risk contagions among large international energy firms: A multi-layer network analysis," Energy Economics, Elsevier, vol. 114(C).
  39. Tófoli Paula V. & Ziegelmann Flávio A. & Candido Osvaldo & Valls Pereira Pedro L., 2019. "Dynamic D-Vine Copula Model with Applications to Value-at-Risk (VaR)," Journal of Time Series Econometrics, De Gruyter, vol. 11(2), pages 1-34, July.
  40. Hua, Lei & Joe, Harry, 2012. "Tail comonotonicity: Properties, constructions, and asymptotic additivity of risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 492-503.
  41. Marcela de Marillac Carvalho & Luiz Otávio de Oliveira Pala & Gabriel Rodrigo Gomes Pessanha & Thelma Sáfadi, 2021. "Asymmetric dependence of intraday frequency components in the Brazilian stock market," SN Business & Economics, Springer, vol. 1(6), pages 1-18, June.
  42. Arisara Romyen & Chukiat Chaiboonsri & Satawat Wannapan & Songsak Sriboonchitta, 2019. "Multi-Process-Based Maximum Entropy Bootstrapping Estimator: Application for Net Foreign Direct Investment in ASEAN," Economies, MDPI, vol. 7(3), pages 1-13, July.
  43. J. Rosco & Harry Joe, 2013. "Measures of tail asymmetry for bivariate copulas," Statistical Papers, Springer, vol. 54(3), pages 709-726, August.
  44. Sayed H. Kadhem & Aristidis K. Nikoloulopoulos, 2023. "Bi-factor and Second-Order Copula Models for Item Response Data," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 132-157, March.
  45. Yuri Salazar & Wing Ng, 2015. "Nonparametric estimation of general multivariate tail dependence and applications to financial time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 121-158, March.
  46. Zhou, Wei & Chen, Yan & Chen, Jin, 2022. "Risk spread in multiple energy markets: Extreme volatility spillover network analysis before and during the COVID-19 pandemic," Energy, Elsevier, vol. 256(C).
  47. Durante, Fabrizio & Fernández Sánchez, Juan & Sempi, Carlo, 2013. "Multivariate patchwork copulas: A unified approach with applications to partial comonotonicity," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 897-905.
  48. Krupskii, Pavel & Genton, Marc G., 2019. "A copula model for non-Gaussian multivariate spatial data," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 264-277.
  49. Arrieta-Prieto, Mario & Schell, Kristen R., 2022. "Spatio-temporal probabilistic forecasting of wind power for multiple farms: A copula-based hybrid model," International Journal of Forecasting, Elsevier, vol. 38(1), pages 300-320.
  50. Shogo Kato & Toshinao Yoshiba & Shinto Eguchi, 2022. "Copula-based measures of asymmetry between the lower and upper tail probabilities," Statistical Papers, Springer, vol. 63(6), pages 1907-1929, December.
  51. Paravee Maneejuk & Woraphon Yamaka, 2021. "The Role of Economic Contagion in the Inward Investment of Emerging Economies: The Dynamic Conditional Copula Approach," Mathematics, MDPI, vol. 9(20), pages 1-23, October.
  52. Shahzad, Syed Jawad Hussain & Arreola-Hernandez, Jose & Bekiros, Stelios & Shahbaz, Muhammad & Kayani, Ghulam Mujtaba, 2018. "A systemic risk analysis of Islamic equity markets using vine copula and delta CoVaR modeling," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 104-127.
  53. Timm Bönke & Astrid Harnack-Eber & Holger Lüthen, 2024. "The Broken Elevator: Declining Absolute Mobility of Living Standards in Germany," Discussion Papers of DIW Berlin 2068, DIW Berlin, German Institute for Economic Research.
  54. Krupskii, Pavel & Joe, Harry, 2013. "Factor copula models for multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 85-101.
  55. Brechmann Eike Christain & Czado Claudia, 2013. "Risk management with high-dimensional vine copulas: An analysis of the Euro Stoxx 50," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 307-342, December.
  56. Sayed H. Kadhem & Aristidis K. Nikoloulopoulos, 2023. "Factor Tree Copula Models for Item Response Data," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 776-802, September.
  57. Aristidis K. Nikoloulopoulos, 2022. "An one‐factor copula mixed model for joint meta‐analysis of multiple diagnostic tests," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1398-1423, July.
  58. Tan, Sook-Rei & Li, Changtai & Yeap, Xiu Wei, 2022. "A time-varying copula approach for constructing a daily financial systemic stress index," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
  59. Ko, Vinnie & Hjort, Nils Lid, 2019. "Model robust inference with two-stage maximum likelihood estimation for copulas," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 362-381.
  60. Giuseppe Orlando & Michele Bufalo, 2021. "Empirical Evidences on the Interconnectedness between Sampling and Asset Returns’ Distributions," Risks, MDPI, vol. 9(5), pages 1-35, May.
  61. Jondeau, Eric, 2016. "Asymmetry in tail dependence in equity portfolios," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 351-368.
  62. Han, Xuyuan & Liu, Zhenya & Wang, Shixuan, 2022. "An R-vine copula analysis of non-ferrous metal futures with application in Value-at-Risk forecasting," Journal of Commodity Markets, Elsevier, vol. 25(C).
  63. Joel Hinaunye Eita & Charles Raoul Tchuinkam Djemo, 2022. "Quantifying Foreign Exchange Risk in the Selected Listed Sectors of the Johannesburg Stock Exchange: An SV-EVT Pairwise Copula Approach," IJFS, MDPI, vol. 10(2), pages 1-29, April.
  64. Amjad, Muhammad & Akbar, Muhammad & Ullah, Hamd, 2022. "A copula-based approach for creating an index of micronutrient intakes at household level in Pakistan," Economics & Human Biology, Elsevier, vol. 46(C).
  65. Ji-Eun Choi & Dong Wan Shin, 2022. "Quantile correlation coefficient: a new tail dependence measure," Statistical Papers, Springer, vol. 63(4), pages 1075-1104, August.
  66. Jianxu Liu & Mengjiao Wang & Songsak Sriboonchitta, 2019. "Examining the Interdependence between the Exchange Rates of China and ASEAN Countries: A Canonical Vine Copula Approach," Sustainability, MDPI, vol. 11(19), pages 1-20, October.
  67. Zhikai Peng & Jinchuan Ke, 2022. "Spillover Effect of the Interaction between Fintech and the Real Economy Based on Tail Risk Dependent Structure Analysis," Sustainability, MDPI, vol. 14(13), pages 1-22, June.
  68. Carlson, Mari K. & Rezitis, Anthony N., 2018. "Integration of the EU broiler meat markets – Application of Regular Vine Copulas," 2018 Annual Meeting, August 5-7, Washington, D.C. 273864, Agricultural and Applied Economics Association.
  69. Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019. "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, vol. 78(C), pages 143-164.
  70. Aristidis K. Nikoloulopoulos & Peter G. Moffatt, 2019. "Coupling Couples With Copulas: Analysis Of Assortative Matching On Risk Attitude," Economic Inquiry, Western Economic Association International, vol. 57(1), pages 654-666, January.
  71. Han, Yingwei & Li, Ping & Xia, Yong, 2017. "Dynamic robust portfolio selection with copulas," Finance Research Letters, Elsevier, vol. 21(C), pages 190-200.
  72. Grundke, Peter & Polle, Simone, 2012. "Crisis and risk dependencies," European Journal of Operational Research, Elsevier, vol. 223(2), pages 518-528.
  73. Wattanawongwan, Suttisak & Mues, Christophe & Okhrati, Ramin & Choudhry, Taufiq & So, Mee Chi, 2023. "Modelling credit card exposure at default using vine copula quantile regression," European Journal of Operational Research, Elsevier, vol. 311(1), pages 387-399.
  74. Acar, Elif F. & Czado, Claudia & Lysy, Martin, 2019. "Flexible dynamic vine copula models for multivariate time series data," Econometrics and Statistics, Elsevier, vol. 12(C), pages 181-197.
  75. Juwon Seo, 2018. "Randomization Tests for Equality in Dependence Structure," Papers 1811.02105, arXiv.org.
  76. 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.
  77. Spanhel, Fabian & Kurz, Malte S., 2016. "The partial copula: Properties and associated dependence measures," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 76-83.
  78. Simon Fritzsch & Maike Timphus & Gregor Weiss, 2021. "Marginals Versus Copulas: Which Account For More Model Risk In Multivariate Risk Forecasting?," Papers 2109.10946, arXiv.org.
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