Report NEP-FOR-2021-01-18

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.

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Other reports in NEP-FOR

The following items were announced in this report:

• Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2021. "Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility," Discussion paper series HIAS-E-104, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
• Crespo-Cuaresma, Jesus & Fortin, Ines & Hlouskova, Jaroslava & Obersteiner, Michael, 2021. "Regime-dependent commodity price dynamics: A predictive analysis," IHS Working Paper Series 28, Institute for Advanced Studies.
• Wei Li & Denis Mike Becker, 2021. "Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling," Papers 2101.05249, arXiv.org, revised Jul 2021.
• Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2020. "Smooth Robust Multi-Horizon Forecasts," Working Papers 2020-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• Christoph Schlembach & Sascha L. Schmidt & Dominik Schreyer & Linus Wunderlich, 2020. "Forecasting the Olympic medal distribution during a pandemic: a socio-economic machine learning model," Papers 2012.04378, arXiv.org, revised Jun 2021.
• Mueller, H. & Rauh, C., 2021. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2103, Faculty of Economics, University of Cambridge.
• Benjamin Carton & Nan Hu & Mr. Joannes Mongardini & Kei Moriya & Aneta Radzikowski, 2020. "Improving the Short-term Forecast of World Trade During the Covid-19 Pandemic Using Swift Data on Letters of Credit," IMF Working Papers 2020/247, International Monetary Fund.
• Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Working Paper Series 2510, European Central Bank.
• Kátay Gábor & Kerdelhué Lisa & Lequien Matthieu, 2020. "Semi-Structural VAR and Unobserved Components Models to Estimate Finance-Neutral Output Gap," Working papers 791, Banque de France.
• Cheng, Kent Jason Go, 2021. "Using Predictive Analytics for Public Policy: The Case for Lost Work due to the COVID-19," SocArXiv e5z73, Center for Open Science.