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Report NEP-FOR-2022-03-14
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:
- Fabio Calonaci & George Kapetanios & Simon Price, 2022, "Stock Returns Predictability with Unstable Predictors," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2022-04, Jan.
- Ogulcan E. Orsel & Sasha S. Yamada, 2022, "Comparative Study of Machine Learning Models for Stock Price Prediction," Papers, arXiv.org, number 2202.03156, Jan.
- Pincheira, Pablo & Hardy, Nicolas, 2022, "Correlation Based Tests of Predictability," MPRA Paper, University Library of Munich, Germany, number 112014, Feb.
- Udenio, Maximiliano & Vatamidou, Eleni & Fransoo, Jan C., 2023, "Exponential smoothing forecasts: Taming the Bullwhip Effect when demand is seasonal," Other publications TiSEM, Tilburg University, School of Economics and Management, number 8fca6329-83b9-4a49-a2aa-e.