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COPAR—multivariate time series modeling using the copula autoregressive model

Citations

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Cited by:

  1. Dominique Guegan & Giovanni de Luca & Giorgia Rivieccio, 2017. "Three-stage estimation method for non-linear multiple time-series," Post-Print halshs-01439860, HAL.
  2. Guilherme Armando Almeida Pereira & Álvaro Veiga, 2019. "Periodic Copula Autoregressive Model Designed to Multivariate Streamflow Time Series Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(10), pages 3417-3431, August.
  3. Eugen Ivanov & Aleksey Min & Franz Ramsauer, 2017. "Copula-Based Factor Models for Multivariate Asset Returns," Econometrics, MDPI, vol. 5(2), pages 1-24, May.
  4. Martin Bladt & Alexander J. McNeil, 2020. "Time series copula models using d-vines and v-transforms," Papers 2006.11088, arXiv.org, revised Jul 2021.
  5. 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).
  6. Woraphon Yamaka & Rangan Gupta & Sukrit Thongkairat & Paravee Maneejuk, 2023. "Structural and predictive analyses with a mixed copula‐based vector autoregression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 223-239, March.
  7. Rivieccio, Giorgia & De Luca, Giovanni, 2016. "Copula function approaches for the analysis of serial and cross dependence in stock returns," Finance Research Letters, Elsevier, vol. 17(C), pages 55-61.
  8. Bladt Martin & McNeil Alexander J., 2022. "Time series with infinite-order partial copula dependence," Dependence Modeling, De Gruyter, vol. 10(1), pages 87-107, January.
  9. Arisara Romyen & Jianxu Liu & Songsak Sriboonchitta & Parinya Cherdchom & Paratta Prommee, 2019. "Assessing Regional Economic Performance in the Southern Thailand Special Economic Zone Using a Vine-COPAR Model," Economies, MDPI, vol. 7(2), pages 1-10, April.
  10. Dominique Guegan & Giovanni De Luca & Giorgia Rivieccio, 2017. "Three-stage estimation method for non-linear multiple time-series," Documents de travail du Centre d'Economie de la Sorbonne 17001, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  11. Luca, Giovanni De & Guégan, Dominique & Rivieccio, Giorgia, 2019. "Assessing tail risk for nonlinear dependence of MSCI sector indices: A copula three-stage approach," Finance Research Letters, Elsevier, vol. 30(C), pages 327-333.
  12. Jean-David Fermanian, 2017. "Recent Developments in Copula Models," Econometrics, MDPI, vol. 5(3), pages 1-3, July.
  13. Kjersti Aas, 2016. "Pair-Copula Constructions for Financial Applications: A Review," Econometrics, MDPI, vol. 4(4), pages 1-15, October.
  14. Nagler, Thomas & Krüger, Daniel & Min, Aleksey, 2022. "Stationary vine copula models for multivariate time series," Journal of Econometrics, Elsevier, vol. 227(2), pages 305-324.
  15. Ruben Loaiza-Maya & Michael Stanley Smith, 2017. "Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series," Papers 1712.09150, arXiv.org, revised Jul 2018.
  16. Michael Stanley Smith, 2021. "Implicit Copulas: An Overview," Papers 2109.04718, arXiv.org.
  17. Ramírez, Andres Felipe & Valencia, Carlos Felipe & Cabrales, Sergio & Ramírez, Carlos G., 2021. "Simulation of photo-voltaic power generation using copula autoregressive models for solar irradiance and air temperature time series," Renewable Energy, Elsevier, vol. 175(C), pages 44-67.
  18. Dominique Guegan & Giovanni de Luca & Giorgia Rivieccio, 2017. "Three-stage estimation method for non-linear multiple time-series," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01439860, HAL.
  19. 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.
  20. Monica Defend & Aleksey Min & Lorenzo Portelli & Franz Ramsauer & Francesco Sandrini & Rudi Zagst, 2021. "Quantifying Drivers of Forecasted Returns Using Approximate Dynamic Factor Models for Mixed-Frequency Panel Data," Forecasting, MDPI, vol. 3(1), pages 1-35, February.
  21. Rubén Loaiza‐Maya & Michael S. Smith & Worapree Maneesoonthorn, 2018. "Time series copulas for heteroskedastic data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 332-354, April.
  22. Jang, Hyuna & Kim, Jong-Min & Noh, Hohsuk, 2022. "Vine copula Granger causality in mean," Economic Modelling, Elsevier, vol. 109(C).
  23. Martin Bladt & Alexander J. McNeil, 2021. "Time series models with infinite-order partial copula dependence," Papers 2107.00960, arXiv.org.
  24. Smith, Michael Stanley, 2023. "Implicit Copulas: An Overview," Econometrics and Statistics, Elsevier, vol. 28(C), pages 81-104.
  25. Saeide Sefidi & Mojtaba Ganjali & Taban Baghfalaki, 2022. "Analysis of ordinal and continuous longitudinal responses using pair copula construction," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 255-280, August.
  26. Bladt, Martin & McNeil, Alexander J., 2022. "Time series copula models using d-vines and v-transforms," Econometrics and Statistics, Elsevier, vol. 24(C), pages 27-48.
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