Periodic Copula Autoregressive Model Designed to Multivariate Streamflow Time Series Modelling
Author
Abstract
Suggested Citation
DOI: 10.1007/s11269-019-02308-6
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- 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.
- Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
- Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
- M. Reddy & Poulomi Ganguli, 2012. "Bivariate Flood Frequency Analysis of Upper Godavari River Flows Using Archimedean Copulas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(14), pages 3995-4018, November.
- Brendan K. Beare & Juwon Seo, 2015. "Vine Copula Specifications for Stationary Multivariate Markov Chains," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 228-246, March.
- Wenzhuo Wang & Zengchuan Dong & Wei Si & Yu Zhang & Wei Xu, 2018. "Two-Dimension Monthly River Flow Simulation Using Hierarchical Network-Copula Conditional Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(12), pages 3801-3820, September.
- Eike Christian Brechmann & Claudia Czado, 2015. "COPAR—multivariate time series modeling using the copula autoregressive model," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(4), pages 495-514, July.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Zhaoyi Xu & Yuqing Zeng & Yangrong Xue & Shenggang Yang, 2022. "Early Warning of Chinese Yuan’s Exchange Rate Fluctuation and Value at Risk Measure Using Neural Network Joint Optimization Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1293-1315, December.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Shokry Abdelaziz & Ahmed Mohamed Mahmoud Ahmed & Abdelhamid Mohamed Eltahan & Ahmed Medhat Ismail Abd Elhamid, 2023. "Long-Term Stochastic Modeling of Monthly Streamflow in River Nile," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
- Huawei Li & Guohe Huang & Yongping Li & Jie Sun & Pangpang Gao, 2021. "A C-Vine Copula-Based Quantile Regression Method for Streamflow Forecasting in Xiangxi River Basin, China," Sustainability, MDPI, vol. 13(9), pages 1-22, April.
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.- 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.
- Rub'en Loaiza-Maya & Michael S. Smith & Worapree Maneesoonthorn, 2017. "Time Series Copulas for Heteroskedastic Data," Papers 1701.07152, arXiv.org.
- Jang, Hyuna & Kim, Jong-Min & Noh, Hohsuk, 2022. "Vine copula Granger causality in mean," Economic Modelling, Elsevier, vol. 109(C).
- Eugen Ivanov & Aleksey Min & Franz Ramsauer, 2017. "Copula-Based Factor Models for Multivariate Asset Returns," Econometrics, MDPI, vol. 5(2), pages 1-24, May.
- 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.
- 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.
- Smith, Michael Stanley, 2023. "Implicit Copulas: An Overview," Econometrics and Statistics, Elsevier, vol. 28(C), pages 81-104.
- Martin Bladt & Alexander J. McNeil, 2020. "Time series copula models using d-vines and v-transforms," Papers 2006.11088, arXiv.org, revised Jul 2021.
- 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.
- 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.
- Martin Bladt & Alexander J. McNeil, 2021. "Time series models with infinite-order partial copula dependence," Papers 2107.00960, arXiv.org.
- 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.
- 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.
- Bukre Yildirim Kulekci & Gulden Poyraz & Ismail Gur & Ozan Evkaya, 2023. "Dependence Analysis of the ISE100 Banking Sector Using Vine Copula," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 73(73-1), pages 55-81, June.
- Michael Stanley Smith, 2021. "Implicit Copulas: An Overview," Papers 2109.04718, arXiv.org.
- Maziar Sahamkhadam, 2021. "Dynamic copula-based expectile portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 22(3), pages 209-223, May.
- Dominique Guegan & Pierre-André Maugis, 2010.
"An Econometric Study of Vine Copulas,"
Documents de travail du Centre d'Economie de la Sorbonne
10040, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
- Dominique Guegan & Pierre-André Maugis, 2011. "An econometric Study for Vine Copulas," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00645799, HAL.
- Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00492124, HAL.
- David Walsh-Jones & Daniel Jones & Christoph Reisinger, 2014. "Modelling of dependence in high-dimensional financial time series by cluster-derived canonical vines," Papers 1411.4970, arXiv.org.
- 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).
- Jinyu Zhang & Kang Gao & Yong Li & Qiaosen Zhang, 2022. "Maximum Likelihood Estimation Methods for Copula Models," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 99-124, June.
- 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.
More about this item
Keywords
Non-linear models; Stochastic streamflow simulation; Copula models for multivariate streamflow time series; Periodic multivariate copula model;All these keywords.
Statistics
Access and download statisticsCorrections
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:waterr:v:33:y:2019:i:10:d:10.1007_s11269-019-02308-6. 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.