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Selecting and estimating regular vine copulae and application to financial returns

Citations

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Cited by:

  1. Yu, Lean & Zha, Rui & Stafylas, Dimitrios & He, Kaijian & Liu, Jia, 2020. "Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models," International Review of Financial Analysis, Elsevier, vol. 68(C).
  2. Saha, Kunal, 2018. "An investigation into the dependence structure of major cryptocurrencies," EconStor Preprints 181878, ZBW - Leibniz Information Centre for Economics.
  3. Eling, Martin & Jung, Kwangmin, 2018. "Copula approaches for modeling cross-sectional dependence of data breach losses," Insurance: Mathematics and Economics, Elsevier, vol. 82(C), pages 167-180.
  4. Fabrizio Durante & Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2022. "A Multivariate Dependence Analysis for Electricity Prices, Demand and Renewable Energy Sources," Papers 2201.01132, arXiv.org.
  5. Brida Juan Gabriel & Moreno Leonardo & Scaglione Miriam, 2024. "Modeling multivariate tourism expenditure using vine copula: empirical findings from of Fribourg-Switzerland," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(5), pages 4093-4116, October.
  6. Mejdoub, Hanène & Ben Arab, Mounira, 2018. "Impact of dependence modeling of non-life insurance risks on capital requirement: D-Vine Copula approach," Research in International Business and Finance, Elsevier, vol. 45(C), pages 208-218.
  7. Panagiotou Dimitrios & Stavrakoudis Athanassios, 2016. "Price Dependence between Different Beef Cuts and Quality Grades: A Copula Approach at the Retail Level for the U.S. Beef Industry," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 14(1), pages 121-131, May.
  8. 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.
  9. Alexandr Travkin, 2013. "Pair copula constructions in portfolio optimization ploblem," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 32(4), pages 110-133.
  10. 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).
  11. Yang, Haoran & Chen, Chen & Zhao, Wenjian & Lu, Xiang & Zhang, Pengtao & Xue, Jianghan, 2025. "A novel reliability method for assessing dam slope stability by incorporating intrinsic correlations of rockfill materials," Reliability Engineering and System Safety, Elsevier, vol. 259(C).
  12. Kim, Sojung & Weber, Stefan, 2022. "Simulation methods for robust risk assessment and the distorted mix approach," European Journal of Operational Research, Elsevier, vol. 298(1), pages 380-398.
  13. Muhammad Mar’i & Turgut Tursoy, 2021. "Exchange Rate Dependency Between Emerging Countries-Case of Black Sea Countries," Capital Markets Review, Malaysian Finance Association, vol. 29(2), pages 43-54.
  14. Wang, Peiwan & Zong, Lu, 2020. "Contagion effects and risk transmission channels in the housing, stock, interest rate and currency markets: An Empirical Study in China and the U.S," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
  15. Marco Geidosch & Matthias Fischer, 2016. "Application of Vine Copulas to Credit Portfolio Risk Modeling," JRFM, MDPI, vol. 9(2), pages 1-15, June.
  16. Wang, Mengjiao & Liu, Jianxu & Yang, Bing, 2024. "Does the strength of the US dollar affect the interdependence among currency exchange rates of RCEP and CPTPP countries?," Finance Research Letters, Elsevier, vol. 62(PA).
  17. Fredy Pokou & Jules Sadefo Kamdem & François Benhmad, 2024. "Empirical Performance of an ESG Assets Portfolio from US Market," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1569-1638, September.
  18. Himchan Jeong & Dipak Dey, 2020. "Application of a Vine Copula for Multi-Line Insurance Reserving," Risks, MDPI, vol. 8(4), pages 1-23, October.
  19. 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.
  20. M. Mesfioui & T. Bouezmarni & M. Belalia, 2023. "Copula-based link functions in binary regression models," Statistical Papers, Springer, vol. 64(2), pages 557-585, April.
  21. Yousaf Ali Khan, 2022. "Modeling Dependent Structure Among Micro-Economics Variables Through COPAR (1)-Model in Pakistan," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 257-279, March.
  22. Martin Magris, 2019. "A Vine-copula extension for the HAR model," Papers 1907.08522, arXiv.org.
  23. Maziar Sahamkhadam & Andreas Stephan, 2019. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for the financial crisis," Papers 1912.10328, arXiv.org.
  24. Huang, Wanling & Mollick, André Varella & Nguyen, Khoa Huu, 2016. "U.S. stock markets and the role of real interest rates," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 231-242.
  25. Weiß, Gregor N.F. & Scheffer, Marcus, 2015. "Mixture pair-copula-constructions," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 175-191.
  26. Zhu, Kailun & Kurowicka, Dorota & Nane, Gabriela F., 2021. "Simplified R-vine based forward regression," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
  27. 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.
  28. Hemei Li & Zhenya Liu & Shixuan Wang, 2022. "Vines climbing higher: Risk management for commodity futures markets using a regular vine copula approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2438-2457, April.
  29. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stober, 2016. "Regime switching vine copula models for global equity and volatility indices," Papers 1604.05598, arXiv.org.
  30. Chen, Kuan-Ju & Chen, Kuan-Heng, 2016. "Analysis of Energy and Agricultural Commodity Markets with the Policy Mandated: A Vine Copula-based ARMA-EGARCH Model," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236028, Agricultural and Applied Economics Association.
  31. 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.
  32. Kjersti Aas, 2016. "Pair-Copula Constructions for Financial Applications: A Review," Econometrics, MDPI, vol. 4(4), pages 1-15, October.
  33. 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).
  34. 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.
  35. Cyprian Omari & Peter Mwita & Anthony Waititu, 2019. "Conditional Dependence Modelling with Regular Vine Copulas," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(1), pages 1-5.
  36. 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.
  37. Panagiotelis, Anastasios & Czado, Claudia & Joe, Harry & Stöber, Jakob, 2017. "Model selection for discrete regular vine copulas," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 138-152.
  38. David Jobst & Annette Möller & Jürgen Groß, 2024. "Gradient‐Boosted Generalized Linear Models for Conditional Vine Copulas," Environmetrics, John Wiley & Sons, Ltd., vol. 35(8), December.
  39. Krupskii, Pavel & Joe, Harry, 2015. "Structured factor copula models: Theory, inference and computation," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 53-73.
  40. Brechmann, Eike C. & Joe, Harry, 2014. "Parsimonious parameterization of correlation matrices using truncated vines and factor analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 233-251.
  41. Nathaniel Tomasetti & Catherine Forbes & Anastasios Panagiotelis, 2019. "Updating Variational Bayes: Fast Sequential Posterior Inference," Monash Econometrics and Business Statistics Working Papers 13/19, Monash University, Department of Econometrics and Business Statistics.
  42. Jun Li & Yao Zhang & Emanuele Bevacqua & Jakob Zscheischler & Trevor F. Keenan & Xu Lian & Sha Zhou & Hongying Zhang & Mingzhu He & Shilong Piao, 2024. "Future increase in compound soil drought-heat extremes exacerbated by vegetation greening," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  43. Eling, Martin & Jung, Kwangmin, 2020. "Risk aggregation in non-life insurance: Standard models vs. internal models," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 183-198.
  44. Thitivadee Chaiyawat & Pannarat Guayjarernpanishk, 2025. "Enhancing Insurer Portfolio Resilience and Capital Efficiency with Green Bonds: A Framework Combining Dynamic R-Vine Copulas and Tail-Risk Modeling," Risks, MDPI, vol. 13(9), pages 1-34, August.
  45. Jean-David Fermanian & Benjamin Poignard & Panos Xidonas, 2025. "Model-based vs. agnostic methods for the prediction of time-varying covariance matrices," Annals of Operations Research, Springer, vol. 346(1), pages 511-548, March.
  46. E. Allevi & L. Boffino & M. E. Giuli & G. Oggioni, 2019. "Analysis of long-term natural gas contracts with vine copulas in optimization portfolio problems," Annals of Operations Research, Springer, vol. 274(1), pages 1-37, March.
  47. Müller, Dominik & Czado, Claudia, 2019. "Dependence modelling in ultra high dimensions with vine copulas and the Graphical Lasso," Computational Statistics & Data Analysis, Elsevier, vol. 137(C), pages 211-232.
  48. Çekin, Semih Emre & Pradhan, Ashis Kumar & Tiwari, Aviral Kumar & Gupta, Rangan, 2020. "Measuring co-dependencies of economic policy uncertainty in Latin American countries using vine copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 207-217.
  49. Tuoyuan Cheng & Kan Chen, 2023. "A General Framework for Portfolio Construction Based on Generative Models of Asset Returns," Papers 2312.03294, arXiv.org.
  50. Chebbi, Ali & Hedhli, Amel, 2022. "Revisiting the accuracy of standard VaR methods for risk assessment: Using the Copula–EVT multidimensional approach for stock markets in the MENA region," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 430-445.
  51. Sehee Kim & Yi Li & Donna Spiegelman, 2016. "A semiparametric copula method for Cox models with covariate measurement error," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(1), pages 1-16, January.
  52. Vahidin Jeleskovic & Claudio Latini & Zahid I. Younas & Mamdouh A. S. Al-Faryan, 2023. "Optimization of portfolios with cryptocurrencies: Markowitz and GARCH-Copula model approach," Papers 2401.00507, arXiv.org.
  53. Talbi, Marwa & Bedoui, Rihab & de Peretti, Christian & Belkacem, Lotfi, 2021. "Is the role of precious metals as precious as they are? A vine copula and BiVaR approaches," Resources Policy, Elsevier, vol. 73(C).
  54. Raza, Syed Ali & Sharif, Arshian & Anwar, Rija, 2025. "Optimizing portfolio performance with DeFi tokens: Insights from a dynamic R-vine copula-based mean-CVaR approach," Research in International Business and Finance, Elsevier, vol. 77(PB).
  55. Haffar, Adlane & Le Fur, Éric, 2022. "Time-varying dependence of Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 211-220.
  56. Kunlapath Sukcharoen & David Leatham, 2018. "Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula Method," International Journal of Energy Economics and Policy, Econjournals, vol. 8(5), pages 193-201.
  57. Mo, Guoli & Zhang, Weiguo & Tan, Chunzhi & Liu, Xing, 2022. "Predicting the portfolio risk of high-dimensional international stock indices with dynamic spatial dependence," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
  58. Guo, Rui & Shamsi, Mohammad Haris & Sharifi, Mohsen & Saelens, Dirk, 2025. "Exploring uncertainty in district heat demand through a probabilistic building characterization approach," Applied Energy, Elsevier, vol. 377(PA).
  59. Lado-Sestayo, Rubén & De Llano-Paz, Fernando & Vivel-Búa, Milagros & Martínez-Salgueiro, Andrea, 2023. "Commodity exposure in the eurozone: How EU energy security is conditioned by the Euro," Energy, Elsevier, vol. 277(C).
  60. Hanif, Waqas & Arreola Hernandez, Jose & Sadorsky, Perry & Yoon, Seong-Min, 2020. "Are the interdependence characteristics of the US and Canadian energy equity sectors nonlinear and asymmetric?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
  61. BenMim, Imen & BenSaïda, Ahmed, 2019. "Financial contagion across major stock markets: A study during crisis episodes," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 187-201.
  62. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.
  63. Stübinger, Johannes & Mangold, Benedikt & Krauss, Christopher, 2016. "Statistical arbitrage with vine copulas," FAU Discussion Papers in Economics 11/2016, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  64. Brechmann, Eike C. & Joe, Harry, 2015. "Truncation of vine copulas using fit indices," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 19-33.
  65. Benoumechiara Nazih & Bousquet Nicolas & Michel Bertrand & Saint-Pierre Philippe, 2020. "Detecting and modeling critical dependence structures between random inputs of computer models," Dependence Modeling, De Gruyter, vol. 8(1), pages 263-297, January.
  66. Benedikt Schamberger & Lutz F. Gruber & Claudia Czado, 2017. "Bayesian Inference for Latent Factor Copulas and Application to Financial Risk Forecasting," Econometrics, MDPI, vol. 5(2), pages 1-23, May.
  67. Bram Thijssen & Lodewyk F A Wessels, 2020. "Approximating multivariate posterior distribution functions from Monte Carlo samples for sequential Bayesian inference," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-25, March.
  68. Bartels, Mariana & Ziegelmann, Flavio A., 2016. "Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 66-79.
  69. Li, Yanting & Peng, Xinghao & Zhang, Yu, 2022. "Forecasting methods for wind power scenarios of multiple wind farms based on spatio-temporal dependency structure," Renewable Energy, Elsevier, vol. 201(P1), pages 950-960.
  70. Li, Xuan & Zhang, Wei, 2020. "Long-term assessment of a floating offshore wind turbine under environmental conditions with multivariate dependence structures," Renewable Energy, Elsevier, vol. 147(P1), pages 764-775.
  71. Jakob Stöber & Ulf Schepsmeier, 2013. "Estimating standard errors in regular vine copula models," Computational Statistics, Springer, vol. 28(6), pages 2679-2707, December.
  72. Mikhail Semenov & Daulet Smagulov, 2017. "Portfolio Risk Assessment using Copula Models," Papers 1707.03516, arXiv.org.
  73. Aloui, Riadh & Ben Aïssa, Mohamed Safouane, 2016. "Relationship between oil, stock prices and exchange rates: A vine copula based GARCH method," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 458-471.
  74. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stöber, 2017. "Regime Switching Vine Copula Models for Global Equity and Volatility Indices," Econometrics, MDPI, vol. 5(1), pages 1-38, January.
  75. Apergis, Nicholas & Gozgor, Giray & Lau, Chi Keung Marco & Wang, Shixuan, 2020. "Dependence structure in the Australian electricity markets: New evidence from regular vine copulae," Energy Economics, Elsevier, vol. 90(C).
  76. 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.
  77. GRIGORIADIS, Vasilis & EMMANOUILIDES, Christos & FOUSEKIS, Panos, . "The Integration Of Pigmeat Markets In The Eu. Evidence From A Regular Mixed Vine Copula," Review of Agricultural and Applied Economics (RAAE), Faculty of Economics and Management, Slovak Agricultural University in Nitra, vol. 19(01), pages 1-10.
  78. Mohd Sabri Ismail & Nurulkamal Masseran & Mohd Almie Alias & Sakhinah Abu Bakar, 2024. "Modeling Asymmetric Dependence Structure of Air Pollution Characteristics: A Vine Copula Approach," Mathematics, MDPI, vol. 12(4), pages 1-23, February.
  79. Sahin, Özge & Czado, Claudia, 2022. "Vine copula mixture models and clustering for non-Gaussian data," Econometrics and Statistics, Elsevier, vol. 22(C), pages 136-158.
  80. Anulekha Dhara & Bikramjit Das & Karthik Natarajan, 2021. "Worst-Case Expected Shortfall with Univariate and Bivariate Marginals," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 370-389, January.
  81. Maximilian Coblenz & Simon Holz & Hans‐Jörg Bauer & Oliver Grothe & Rainer Koch, 2020. "Modelling fuel injector spray characteristics in jet engines by using vine copulas," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 863-886, August.
  82. Andrej Stenšin & Daumantas Bloznelis, 2022. "Copulas and Portfolios in the Electric Vehicle Sector," JRFM, MDPI, vol. 15(3), pages 1-20, March.
  83. Genest Christian & Scherer Matthias, 2019. "The world of vines: An interview with Claudia Czado," Dependence Modeling, De Gruyter, vol. 7(1), pages 169-180, January.
  84. Fritzsch, Simon & Timphus, Maike & Weiß, Gregor, 2024. "Marginals versus copulas: Which account for more model risk in multivariate risk forecasting?," Journal of Banking & Finance, Elsevier, vol. 158(C).
  85. 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.
  86. Kiriliouk, Anna & Lee, Jeongjin & Segers, Johan, 2023. "X-Vine Models for Multivariate Extremes," LIDAM Discussion Papers ISBA 2023038, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  87. Ha Che-Ngoc & Thao Nguyen-Trang & Hieu Huynh-Van & Tai Vo-Van, 2024. "Improving Bayesian Classifier Using Vine Copula and Fuzzy Clustering Technique," Annals of Data Science, Springer, vol. 11(2), pages 709-732, April.
  88. Ahmed BenSaïda & Houda Litimi, 2021. "Financial contagion across G10 stock markets: A study during major crises," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4798-4821, July.
  89. 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.
  90. Zhu, Lingwei & Xu, Bin & Wang, Xinrong & Yue, Hao & Mo, Ran & Wang, Sen & Zhao, Zenghai & Lu, Peng, 2025. "Stochastic simulation framework for renewable power output: Integrating hybrid discrete-continuous distributions with vine copula function," Renewable Energy, Elsevier, vol. 251(C).
  91. Czado, Claudia & Ivanov, Eugen & Okhrin, Yarema, 2019. "Modelling temporal dependence of realized variances with vines," Econometrics and Statistics, Elsevier, vol. 12(C), pages 198-216.
  92. Chang, Bo & Joe, Harry, 2019. "Prediction based on conditional distributions of vine copulas," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 45-63.
  93. Zięba, Damian & Kokoszczyński, Ryszard & Śledziewska, Katarzyna, 2019. "Shock transmission in the cryptocurrency market. Is Bitcoin the most influential?," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 102-125.
  94. Steffen Grønneberg & Njål Foldnes, 2017. "Covariance Model Simulation Using Regular Vines," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 1035-1051, December.
  95. Kongsheng Zhang & Xiaorui Xu & Mingtao Zhao, 2025. "Risk Spillover Effect from Oil to Chinese New-Energy-Related Stock Markets: An R-vine Copula-Based CoVaR Approach," Mathematics, MDPI, vol. 13(12), pages 1-19, June.
  96. Barthel, Nicole & Geerdens, Candida & Killiches, Matthias & Janssen, Paul & Czado, Claudia, 2018. "Vine copula based likelihood estimation of dependence patterns in multivariate event time data," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 109-127.
  97. Ghufran Ahmad & Muhammad Suhail Rizwan & Dawood Ashraf, 2021. "Systemic risk and macroeconomic forecasting: A globally applicable copula‐based approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1420-1443, December.
  98. Jose Arreola Hernandez & Mazin A.M. Al Janabi, 2020. "Forecasting of dependence, market, and investment risks of a global index portfolio," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 512-532, April.
  99. Zhou, Rui & Ji, Min, 2021. "Modelling mortality dependence: An application of dynamic vine copula," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 241-255.
  100. Li, Xuan & Zhang, Wei, 2020. "Long-term fatigue damage assessment for a floating offshore wind turbine under realistic environmental conditions," Renewable Energy, Elsevier, vol. 159(C), pages 570-584.
  101. Wanling Huang & André Varella Mollick & Khoa Huu Nguyen, 2017. "Dynamic responses and tail-dependence among commodities, the US real interest rate and the dollar," Empirical Economics, Springer, vol. 53(3), pages 959-997, November.
  102. Jialing Han & Yu-Ning Li, 2025. "Approximate Factor Model with S-vine Copula Structure," Papers 2508.11619, arXiv.org.
  103. Ahmed BenSaïda, 2023. "The linkage between Bitcoin and foreign exchanges in developed and emerging markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
  104. Krishna, Attoti Bharath & Abhyankar, Abhijit R., 2023. "Time-coupled day-ahead wind power scenario generation: A combined regular vine copula and variance reduction method," Energy, Elsevier, vol. 265(C).
  105. Carlson, Mari K. & Rezitis, Anthony N., "undated". "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.
  106. Maziar Sahamkhadam & Andreas Stephan, 2023. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for global financial crises," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2139-2166, December.
  107. Weiping Zhang & MengMeng Zhang & Yu Chen, 2020. "A Copula-Based GLMM Model for Multivariate Longitudinal Data with Mixed-Types of Responses," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(2), pages 353-379, November.
  108. Md Erfanul Hoque & Elif F. Acar & Mahmoud Torabi, 2023. "A time‐heterogeneous D‐vine copula model for unbalanced and unequally spaced longitudinal data," Biometrics, The International Biometric Society, vol. 79(2), pages 734-746, June.
  109. Zhi, Bangdong & Wang, Xiaojun & Xu, Fangming, 2022. "Managing inventory financing in a volatile market: A novel data-driven copula model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
  110. Hui Hwang Goh & Gumeng Peng & Dongdong Zhang & Wei Dai & Tonni Agustiono Kurniawan & Kai Chen Goh & Chin Leei Cham, 2022. "A New Wind Speed Scenario Generation Method Based on Principal Component and R-Vine Copula Theories," Energies, MDPI, vol. 15(7), pages 1-21, April.
  111. Han, Yingwei & Li, Jie, 2022. "Should investors include green bonds in their portfolios? Evidence for the USA and Europe," International Review of Financial Analysis, Elsevier, vol. 80(C).
  112. Ozan Evkaya & İsmail Gür & Bükre Yıldırım Külekci & Gülden Poyraz, 2024. "Vine Copula Approach to Understand the Financial Dependence of the Istanbul Stock Exchange Index," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 2935-2980, November.
  113. Hua He & Shuhui Cai & Yan Zhou, 2025. "RETRACTED ARTICLE: Unraveling the Interplay of Knowledge and Innovation in the Global Financial System: A Vine Copula Analysis of Sino-US Financial Risk Contagion," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(1), pages 1049-1077, March.
  114. Steffen Nico & Dickhaus Thorsten, 2020. "Optimizing effective numbers of tests by vine copula modeling," Dependence Modeling, De Gruyter, vol. 8(1), pages 172-185, January.
  115. 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.
  116. Chu, Amanda M.Y. & Ip, Chun Yin & Lam, Benson S.Y. & So, Mike K.P., 2022. "Vine copula statistical disclosure control for mixed-type data," Computational Statistics & Data Analysis, Elsevier, vol. 176(C).
  117. Cao, Juan & Zhang, Zhao & Tao, Fulu & Chen, Yi & Luo, Xiangzhong & Xie, Jun, 2023. "Forecasting global crop yields based on El Nino Southern Oscillation early signals," Agricultural Systems, Elsevier, vol. 205(C).
  118. Su, Xiaoshan & Bai, Manying & Han, Yingwei, 2021. "Robust portfolio selection with regime switching and asymmetric dependence," Economic Modelling, Elsevier, vol. 99(C).
  119. Zhu, Kailun & Kurowicka, Dorota, 2022. "Regular vines with strongly chordal pattern of (conditional) independence," Computational Statistics & Data Analysis, Elsevier, vol. 172(C).
  120. Karoline Bax & Ozge Sahin & Claudia Czado & Sandra Paterlini, 2021. "ESG, Risk, and (Tail) Dependence," Papers 2105.07248, arXiv.org, revised Nov 2021.
  121. 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).
  122. Hofert, Marius & Prasad, Avinash & Zhu, Mu, 2022. "Multivariate time-series modeling with generative neural networks," Econometrics and Statistics, Elsevier, vol. 23(C), pages 147-164.
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