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Report NEP-FOR-2022-10-24
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.
Other reports in NEP-FOR
The following items were announced in this report:
- Robert Lehmann & Sascha Möhrle, 2022. "Forecasting Regional Industrial Production with High-Frequency Electricity Consumption Data," CESifo Working Paper Series 9917, CESifo.
- Dangxing Chen & Weicheng Ye, 2022. "Monotonic Neural Additive Models: Pursuing Regulated Machine Learning Models for Credit Scoring," Papers 2209.10070, arXiv.org.
- Ruochen Xiao & Yingying Feng & Lei Yan & Yihan Ma, 2022. "Predict stock prices with ARIMA and LSTM," Papers 2209.02407, arXiv.org.
- Dangxing Chen & Weicheng Ye & Jiahui Ye, 2022. "Interpretable Selective Learning in Credit Risk," Papers 2209.10127, arXiv.org.
- Soohan Kim & Seok-Bae Yun & Hyeong-Ohk Bae & Muhyun Lee & Youngjoon Hong, 2022. "Physics-Informed Convolutional Transformer for Predicting Volatility Surface," Papers 2209.10771, arXiv.org, revised Nov 2023.