References in zbMATH (referenced in 33 articles )

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  1. Zhang, Kong-Sheng; Zhao, Yan-Yong: Modeling dynamic dependence between crude oil and natural gas return rates: a time-varying geometric copula approach (2021)
  2. Guilherme Bodin, Raphael Saavedra, Cristiano Fernandes, Alexandre Street: ScoreDrivenModels.jl: a Julia Package for Generalized Autoregressive Score Models (2020) arXiv
  3. Jiménez, Inés; Mora-Valencia, Andrés; Perote, Javier: Risk quantification and validation for Bitcoin (2020)
  4. Köchling, Gerrit; Schmidtke, Philipp; Posch, Peter N.: Volatility forecasting accuracy for Bitcoin (2020)
  5. Birr, Stefan; Kley, Tobias; Volgushev, Stanislav: Model assessment for time series dynamics using copula spectral densities: a graphical tool (2019)
  6. David Ardia; Keven Bluteau; Kris Boudt; Leopoldo Catania; Denis-Alexandre Trottier: Markov-Switching GARCH Models in R: The MSGARCH Package (2019) not zbMATH
  7. David Ardia; Kris Boudt; Leopoldo Catania: Generalized Autoregressive Score Models in R: The GAS Package (2019) not zbMATH
  8. Figá-Talamanca, Gianna; Patacca, Marco: Does market attention affect bitcoin returns and volatility? (2019)
  9. Li, Han; Tang, Qihe: Analyzing mortality bond indexes via hierarchical forecast reconciliation (2019)
  10. Müller, Dominik; Czado, Claudia: Dependence modelling in ultra high dimensions with vine copulas and the graphical lasso (2019)
  11. Ramasubramanian, Karthik; Singh, Abhishek: Machine learning using R. With time series and industry-based use cases in R (2019)
  12. Arbenz, Philipp; Cambou, Mathieu; Hofert, Marius; Lemieux, Christiane; Taniguchi, Yoshihiro: Importance sampling and stratification for copula models (2018)
  13. Bee, Marco; Dickson, Maria Michela; Santi, Flavio: Likelihood-based risk estimation for variance-gamma models (2018)
  14. Erhardt, Robert; Engler, David: An extension of spatial dependence models for estimating short-term temperature portfolio risk (2018)
  15. Hofert, Marius; Kojadinovic, Ivan; Mächler, Martin; Yan, Jun: Elements of copula modeling with R (2018)
  16. Iacus, Stefano M.; Yoshida, Nakahiro: Simulation and inference for stochastic processes with YUIMA. A comprehensive R framework for SDEs and other stochastic processes (2018)
  17. Philipp Otto: spGARCH: An R-Package for Spatial and Spatiotemporal ARCH models (2018) arXiv
  18. Punzo, Antonio; Bagnato, Luca; Maruotti, Antonello: Compound unimodal distributions for insurance losses (2018)
  19. Yoshiba, Toshinao: Maximum likelihood estimation of skew-(t) copulas with its applications to stock returns (2018)
  20. Bollmann, Laslo; Scherer, Matthias: Modeling influenza-like illness activity in the United States (2017)

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