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Report NEP-FOR-2019-08-26
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.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-FOR
The following items were announced in this report:
- Loermann, Julius & Maas, Benedikt, 2019, "Nowcasting US GDP with artificial neural networks," MPRA Paper, University Library of Munich, Germany, number 95459, May.
- Franses, Ph.H.B.F., 2019, "IMA(1,1) as a new benchmark for forecast evaluation," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number EI2019-28, Aug.
- Franses, Ph.H.B.F., 2019, "Professional Forecasters and January," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number EI2019-25, Jul.
- Daniel Borup & Erik Christian Montes Schütte, 2019, "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-13, Aug.
- Bucci, Andrea, 2019, "Realized Volatility Forecasting with Neural Networks," MPRA Paper, University Library of Munich, Germany, number 95443, Aug.
- Jonathan Benchimol & Makram El-Shagi, 2019, "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers, Bank of Israel, number 2019.08, Jul.
- Shen, Ze & Wan, Qing & Leatham, David J., , "Bitcoin Return Volatility Forecasting: A Comparative Study of GARCH Model and Machine Learning Model," 2019 Annual Meeting, July 21-23, Atlanta, Georgia, Agricultural and Applied Economics Association, number 290696, DOI: 10.22004/ag.econ.290696.
- Fokin, Nikita & Polbin, Andrey, 2019, "A Bivariate Forecasting Model For Russian GDP Under Structural Changes In Monetary Policy and Long-Term Growth," MPRA Paper, University Library of Munich, Germany, number 95306, Apr, revised Apr 2019.
- Fatima Zahra Azayite & Said Achchab, 2019, "A hybrid neural network model based on improved PSO and SA for bankruptcy prediction," Papers, arXiv.org, number 1907.12179, Jul.
- Zahra Saki & Lori Rothenberg & Marguerite Moor & Ivan Kandilov & A. Blanton Godfrey, 2019, "Forecasting U.S. Textile Comparative Advantage Using Autoregressive Integrated Moving Average Models and Time Series Outlier Analysis," Papers, arXiv.org, number 1908.04852, Aug.