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Report NEP-FOR-2022-12-19
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:
- Dorien Herremans & Kah Wee Low, 2022, "Forecasting Bitcoin volatility spikes from whale transactions and CryptoQuant data using Synthesizer Transformer models," Papers, arXiv.org, number 2211.08281, Oct.
- Simon Hirsch & Florian Ziel, 2022, "Simulation-based Forecasting for Intraday Power Markets: Modelling Fundamental Drivers for Location, Shape and Scale of the Price Distribution," Papers, arXiv.org, number 2211.13002, Nov.
- Petre, Konstantin & Varoutas, Dimitris, 2022, "On the application of Machine Learning in telecommunications forecasting: A comparison," 31st European Regional ITS Conference, Gothenburg 2022: Reining in Digital Platforms? Challenging monopolies, promoting competition and developing regulatory regimes, International Telecommunications Society (ITS), number 265665.
- Shayan Halder, 2022, "FinBERT-LSTM: Deep Learning based stock price prediction using News Sentiment Analysis," Papers, arXiv.org, number 2211.07392, Nov.