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Report NEP-FOR-2021-07-12
This is the archive for NEP-FOR, a report on new working papers in the area of Forecasting. Rob J Hyndman issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-FOR
The following items were announced in this report:
- Shafiullah Qureshi & Ba Chu & Fanny S. Demers, 2021, "Forecasting Canadian GDP Growth with Machine Learning," Carleton Economic Papers, Carleton University, Department of Economics, number 21-05, May.
- Szymon Lis & Marcin Chlebus, 2021, "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-11.
- Knut Are Aastveit & Jamie Cross & Herman K. Djik, 2021, "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School, number No 03/2021, Jun.
- Malick Fall & Waël Louhichi & Jean-Laurent Viviani, 2021, "Forecasting the intra-day effective bid ask spread by combining density forecasts," Post-Print, HAL, number hal-03257268, Oct, DOI: 10.1080/00036846.2021.1929821.
- Bent Jesper Christensen & Mads Markvart Kjær & Bezirgen Veliyev, 2021, "The incremental information in the yield curve about future interest rate risk," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2021-11, Jul.