Report NEP-FOR-2020-06-08

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:

• Manuel M. F. Martins & Fabio Verona, 2020. "Forecasting Inflation with the New Keynesian Phillips Curve: Frequency Matters," CEF.UP Working Papers 2001, Universidade do Porto, Faculdade de Economia do Porto.
• Marcelo Madeiros & Gabriel Vasconcelos & Álvaro Veiga & Eduardo Zilberman, 2019. "Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods," Working Papers Central Bank of Chile 834, Central Bank of Chile.
• Kristof Decock & Koenraad Debackere & Anne Mieke Vandamme & Bart Van Looy, 2020. "Scenario-driven forecasting: Modeling peaks and paths. Insights from the COVID-19 Pandemic in Belgium," Working Papers of Department of Management, Strategy and Innovation, Leuven 655122, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
• Sadek, Bassel A & Martin, Elliot W & Shaheen, Susan A, 2020. "Forecasting Truck Parking Using Fourier Transformations," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0gm743bg, Institute of Transportation Studies, UC Berkeley.
• Sylvia Kaufmann, 2020. "Covid-19 outbreak and beyond: The information content of registered short-time workers for GDP now- and forecasting," Working Papers 20.03, Swiss National Bank, Study Center Gerzensee.
• Jens Kley-Holsteg & Florian Ziel, 2020. "Probabilistic Multi-Step-Ahead Short-Term Water Demand Forecasting with Lasso," Papers 2005.04522, arXiv.org.
• Fabrizio Cipollini & Giampiero Gallo & Alessandro Palandri, 2020. "A Dynamic Conditional Approach to Portfolio Weights Forecasting," Econometrics Working Papers Archive 2020_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
• Tong Fang & Tae-Hwy Lee & Zhi Su, 2020. "Predicting the Long-term Stock Market Volatility: A GARCH-MIDAS Model with Variable Selection," Working Papers 202009, University of California at Riverside, Department of Economics.
• Giuseppe Storti & Chao Wang, 2020. "Nonparametric Expected Shortfall Forecasting Incorporating Weighted Quantiles," Papers 2005.04868, arXiv.org, revised Mar 2021.
• Camila Figueroa & Michael Pedersen, 2019. "Extracting Information of the Economic Activity from Business and Consumer Surveys in an Emerging Economy (Chile)," Working Papers Central Bank of Chile 832, Central Bank of Chile.