IDEAS home Printed from https://ideas.repec.org/r/pra/mprapa/67702.html
   My bibliography  Save this item

Functional generalized autoregressive conditional heteroskedasticity

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Shaher Al-Gounmeein Remal & Ismail Mohd Tahir, 2021. "Modelling and forecasting monthly Brent crude oil prices: a long memory and volatility approach," Statistics in Transition New Series, Statistics Poland, vol. 22(1), pages 29-54, March.
  2. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2020. "Forecasting value at risk with intra-day return curves," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1023-1038.
  3. Han Lin Shang & Yang Yang, 2021. "Forecasting Australian subnational age-specific mortality rates," Journal of Population Research, Springer, vol. 38(1), pages 1-24, March.
  4. Gregory Rice & Tony Wirjanto & Yuqian Zhao, 2020. "Tests for conditional heteroscedasticity of functional data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(6), pages 733-758, November.
  5. Horváth, Lajos & Liu, Zhenya & Rice, Gregory & Wang, Shixuan, 2020. "A functional time series analysis of forward curves derived from commodity futures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 646-665.
  6. Horváth, Lajos & Rice, Gregory & Zhao, Yuqian, 2022. "Change point analysis of covariance functions: A weighted cumulative sum approach," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
  7. Gregory Rice & Han Lin Shang, 2017. "A Plug-in Bandwidth Selection Procedure for Long-Run Covariance Estimation with Stationary Functional Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(4), pages 591-609, July.
  8. Baye Matar Kandji, 2023. "On the growth rate of superadditive processes and the stability of functional GARCH models," Working Papers 2023-07, Center for Research in Economics and Statistics.
  9. Rodney V. Fonseca & Aluísio Pinheiro, 2020. "Wavelet estimation of the dimensionality of curve time series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(5), pages 1175-1204, October.
  10. Mihyun Kim & Piotr Kokoszka & Gregory Rice, 2024. "Projection-based white noise and goodness-of-fit tests for functional time series," Statistical Inference for Stochastic Processes, Springer, vol. 27(3), pages 693-724, October.
  11. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2023. "Exploring volatility of crude oil intraday return curves: A functional GARCH-X model," Journal of Commodity Markets, Elsevier, vol. 32(C).
  12. Rostyslav Bodnar & Taras Bodnar & Wolfgang Schmid, 2023. "Sequential monitoring of high‐dimensional time series," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(3), pages 962-992, September.
  13. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2021. "Exploring volatility of crude oil intra-day return curves: a functional GARCH-X Model," MPRA Paper 109231, University Library of Munich, Germany.
  14. Cerovecki, Clément & Francq, Christian & Hörmann, Siegfried & Zakoïan, Jean-Michel, 2019. "Functional GARCH models: The quasi-likelihood approach and its applications," Journal of Econometrics, Elsevier, vol. 209(2), pages 353-375.
  15. Characiejus, Vaidotas & Rice, Gregory, 2020. "A general white noise test based on kernel lag-window estimates of the spectral density operator," Econometrics and Statistics, Elsevier, vol. 13(C), pages 175-196.
  16. Bo Hu & Joon Y. Park & Junhui Qian, 2025. "Analysis of Distributional Dynamics for Repeated Cross-Sectional and Intra-Period Observations," Papers 2505.15763, arXiv.org.
  17. B. Cooper Boniece & Lajos Horv'ath & Lorenzo Trapani, 2023. "On changepoint detection in functional data using empirical energy distance," Papers 2310.04853, arXiv.org.
  18. Wang, Bin & Qian, Yixin & Yu, Enping, 2025. "Bayesian analysis for functional coefficient conditional autoregressive range model with applications," Economic Modelling, Elsevier, vol. 144(C).
  19. Gao, Yuan & Shang, Han Lin & Yang, Yanrong, 2019. "High-dimensional functional time series forecasting: An application to age-specific mortality rates," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 232-243.
  20. Zdeněk Hlávka & Marie Hušková & Simos G. Meintanis, 2021. "Testing serial independence with functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 603-629, September.
  21. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2019. "Tests for conditional heteroscedasticity with functional data and goodness-of-fit tests for FGARCH models," MPRA Paper 93048, University Library of Munich, Germany.
  22. Phillip A. Jang & David S. Matteson, 2023. "Spatial correlation in weather forecast accuracy: a functional time series approach," Computational Statistics, Springer, vol. 38(3), pages 1215-1229, September.
  23. Guochang Wang & Zengyao Wen & Shanming Jia & Shanshan Liang, 2024. "Supervised dimension reduction for functional time series," Statistical Papers, Springer, vol. 65(7), pages 4057-4077, September.
  24. Joann Jasiak & Cheng Zhong, 2025. "Intraday Functional PCA Forecasting of Cryptocurrency Returns," Papers 2505.20508, arXiv.org.
  25. Marc Hallin & Gilles Nisol & Shahin Tavakoli, 2023. "Factor models for high‐dimensional functional time series I: Representation results," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(5-6), pages 578-600, September.
  26. Xin Huang & Han Lin Shang & Tak Kuen Siu, 2025. "An IID Test for Functional Time Series with Applications to High-Frequency VIX Index Data," Risks, MDPI, vol. 13(2), pages 1-25, January.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.