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Report NEP-FOR-2022-04-18
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:
- Pesaran, M. H. & Pick, A. & Timmermann, A., 2022, "Forecasting with panel data: estimation uncertainty versus parameter heterogeneity," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2219, Mar.
- Daniel Hopp, 2022, "Performance of long short-term memory artificial neural networks in nowcasting during the COVID-19 crisis," Papers, arXiv.org, number 2203.11872, Mar.
- Yuxuan Huang & Luiz Fernando Capretz & Danny Ho, 2022, "Machine Learning for Stock Prediction Based on Fundamental Analysis," Papers, arXiv.org, number 2202.05702, Jan.