Report NEP-FOR-2021-04-26

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.

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Other reports in NEP-FOR

The following items were announced in this report:

• Paranhos, Livia, 2021. "Predicting Inflation with Neural Networks," The Warwick Economics Research Paper Series (TWERPS) 1344, University of Warwick, Department of Economics.
• Jiawen Luo & Riza Demirer & Rangan Gupta & Qiang Ji, 2021. "Forecasting Oil and Gold Volatilities with Sentiment Indicators Under Structural Breaks," Working Papers 202130, University of Pretoria, Department of Economics.
• Oscar Claveria & Enric Monte & Salvador Torra, 2021. "“Nowcasting and forecasting GDP growth with machine-learning sentiment indicators”," AQR Working Papers 202101, University of Barcelona, Regional Quantitative Analysis Group, revised Feb 2021.
• Kin G. Olivares & Cristian Challu & Grzegorz Marcjasz & Rafal Weron & Artur Dubrawski, 2021. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," WORking papers in Management Science (WORMS) WORMS/21/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Denis Shibitov & Mariam Mamedli, 2021. "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series wps70, Bank of Russia.
• Hoffmann, Linwood & Bond, Jennifer K. & Matias, Mariana, 2021. "Merits of an Aggregate Futures Price Forecasting Model for the All Wheat U.S. Season-Average Farm Price," USDA Miscellaneous 310518, United States Department of Agriculture.
• Sonja Tilly & Giacomo Livan, 2021. "Macroeconomic forecasting with statistically validated knowledge graphs," Papers 2104.10457, arXiv.org.