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Report NEP-FOR-2019-02-25
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:
- Pinto, Jeronymo Marcondes & Marçal, Emerson Fernandes, 2019, "Cross-validation based forecasting method: a machine learning approach," Textos para discussão, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil), number 498, Feb.
- Huang, Xiaobei & Li, Xi & Tse, Senyo & Tucker, Jennifer Wu, 2018, "The effects of a mixed approach toward management earnings forecasts: evidence from China," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 87113, Mar.
- Item repec:spo:wpmain:info:hdl:2441/6o4qdck7489u7pqc068eeuqsnq is not listed on IDEAS anymore
- Bauwens, Luc & Xu, Yongdeng, 2019, "DCC and DECO-HEAVY: a multivariate GARCH model based on realized variances and correlations," Cardiff Economics Working Papers, Cardiff University, Cardiff Business School, Economics Section, number E2019/5, Feb, revised Aug 2021.
- Sentana, Enrique & Fiorentini, Gabriele, 2019, "New testing approaches for mean-variance predictability," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13426, Jan.
- Nikolaos Passalis & Anastasios Tefas & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019, "Deep Adaptive Input Normalization for Time Series Forecasting," Papers, arXiv.org, number 1902.07892, Feb, revised Sep 2019.
- Vassilis Polimenis & Ioannis Neokosmidis, 2019, "Non-Stationary Dividend-Price Ratios," Papers, arXiv.org, number 1902.06053, Feb.