Printed from https://ideas.repec.org/n/nep-for/2017-05-21.html
Report NEP-FOR-2017-05-21
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:
- Karol Szafranek, 2017, "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers, Narodowy Bank Polski, number 262.
- Gilles Mourre & Caterina Astarita & Anamaria Maftei, 2016, "Measuring the Uncertainty in Predicting Public Revenue," European Economy - Discussion Papers, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission, number 039, Dec.
- Asai, M. & McAleer, M.J., 2017, "Forecasting the Volatility of Nikkei 225 Futures," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number TI 2017-017/III, Jan.
- Item repec:imf:imfwpa:17/108 is not listed on IDEAS anymore
- Daisuke MIYAKAWA & Yuhei MIYAUCHI & Christian PEREZ, 2017, "Forecasting Firm Performance with Machine Learning: Evidence from Japanese firm-level data," Discussion papers, Research Institute of Economy, Trade and Industry (RIETI), number 17068, May.