IDEAS home Printed from https://ideas.repec.org/r/eee/econom/v201y2017i2p307-321.html
   My bibliography  Save this item

Generalized dynamic factor models and volatilities: estimation and forecasting

Citations

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


Cited by:

  1. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
  2. Carlos Trucíos & João H. G. Mazzeu & Marc Hallin & Luiz K. Hotta & Pedro L. Valls Pereira & Mauricio Zevallos, 2022. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 40-52, December.
  3. Valentina Aprigliano & Lorenzo Bencivelli, 2013. "Ita-coin: a new coincident indicator for the Italian economy," Temi di discussione (Economic working papers) 935, Bank of Italy, Economic Research and International Relations Area.
  4. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
  5. M. E. Bontempi & I. Mammi, 2012. "A strategy to reduce the count of moment conditions in panel data GMM," Working Papers wp843, Dipartimento Scienze Economiche, Universita' di Bologna.
  6. Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
  7. Andreou, Elena & Ghysels, Eric, 2021. "Predicting the VIX and the volatility risk premium: The role of short-run funding spreads Volatility Factors," Journal of Econometrics, Elsevier, vol. 220(2), pages 366-398.
  8. Trucíos, Carlos & Mazzeu, João H.G. & Hotta, Luiz K. & Valls Pereira, Pedro L. & Hallin, Marc, 2021. "Robustness and the general dynamic factor model with infinite-dimensional space: Identification, estimation, and forecasting," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1520-1534.
  9. Kumar, Sudarshan & Bansal, Avijit & Chakrabarti, Anindya S., 2019. "Ripples on financial networks," IIMA Working Papers WP 2019-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
  10. Jari Miettinen & Markus Matilainen & Klaus Nordhausen & Sara Taskinen, 2020. "Extracting Conditionally Heteroskedastic Components using Independent Component Analysis," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 293-311, March.
  11. Marc Hallin, 2022. "Manfred Deistler and the General Dynamic Factor Model Approach to the Analysis of High-Dimensional Time Series," Working Papers ECARES 2022-30, ULB -- Universite Libre de Bruxelles.
  12. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhang, Wei, 2020. "Research on China's financial systemic risk contagion under jump and heavy-tailed risk," International Review of Financial Analysis, Elsevier, vol. 72(C).
  13. Barigozzi, Matteo & Hallin, Marc, 2020. "Generalized dynamic factor models and volatilities: Consistency, rates, and prediction intervals," Journal of Econometrics, Elsevier, vol. 216(1), pages 4-34.
  14. Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
  15. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Working Papers ECARES ECARES 2015-34, ULB -- Universite Libre de Bruxelles.
  16. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
  17. Trucíos, Carlos & Hotta, Luiz K. & Valls Pereira, Pedro L., 2019. "On the robustness of the principal volatility components," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 201-219.
  18. Gaoke Liao & Peng Hou & Xiaoyan Shen & Khaldoon Albitar, 2021. "The impact of economic policy uncertainty on stock returns: The role of corporate environmental responsibility engagement," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4386-4392, July.
  19. Li, Y-N. & Chen, J. & Linton, O., 2021. "Estimation of Common Factors for Microstructure Noise and Efficient Price in a High-frequency Dual Factor Model," Cambridge Working Papers in Economics 2150, Faculty of Economics, University of Cambridge.
  20. Duc Thi Luu, 2022. "Portfolio Correlations in the Bank-Firm Credit Market of Japan," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 529-569, August.
  21. Xinyu Song, 2019. "Large Volatility Matrix Prediction with High-Frequency Data," Papers 1907.01196, arXiv.org, revised Sep 2019.
  22. Ma, Yan-Ran & Zhang, Dayong & Ji, Qiang & Pan, Jiaofeng, 2019. "Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?," Energy Economics, Elsevier, vol. 81(C), pages 536-544.
  23. Boudt, Kris & Cornilly, Dries & Verdonck, Tim, 2020. "Nearest comoment estimation with unobserved factors," Journal of Econometrics, Elsevier, vol. 217(2), pages 381-397.
  24. Xisong Jin & Francisco Nadal De Simone, 2012. "An Early-warning and Dynamic Forecasting Framework of Default Probabilities for the Macroprudential Policy Indicators Arsenal," BCL working papers 75, Central Bank of Luxembourg.
  25. Sudarshan Kumar & Tiziana Di Matteo & Anindya S. Chakrabarti, 2020. "Disentangling shock diffusion on complex networks: Identification through graph planarity," Papers 2001.01518, arXiv.org.
  26. Marc Hallin, 2022. "Manfred Deistler and the General-Dynamic-Factor-Model Approach to the Statistical Analysis of High-Dimensional Time Series," Econometrics, MDPI, vol. 10(4), pages 1-9, December.
  27. Tingting Lan & Liuguo Shao & Hua Zhang & Caijun Yuan, 2023. "The impact of pandemic on dynamic volatility spillover network of international stock markets," Empirical Economics, Springer, vol. 65(5), pages 2115-2144, November.
  28. Eklund, Jana & Kapetanios, George, 2008. "A review of forecasting techniques for large datasets," National Institute Economic Review, Cambridge University Press, vol. 203, pages 109-115, January.
  29. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.
  30. Krupskii, Pavel & Joe, Harry, 2020. "Flexible copula models with dynamic dependence and application to financial data," Econometrics and Statistics, Elsevier, vol. 16(C), pages 148-167.
  31. Lübbers, Johannes & Posch, Peter N., 2016. "Commodities' common factor: An empirical assessment of the markets' drivers," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 28-40.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.