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.

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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 498, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
• 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 87113, London School of Economics and Political Science, LSE Library.
• 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 E2019/5, Cardiff University, Cardiff Business School, Economics Section, revised Aug 2021.
• Sentana, Enrique & Fiorentini, Gabriele, 2019. "New testing approaches for mean-variance predictability," CEPR Discussion Papers 13426, C.E.P.R. Discussion Papers.
• Nikolaos Passalis & Anastasios Tefas & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Deep Adaptive Input Normalization for Time Series Forecasting," Papers 1902.07892, arXiv.org, revised Sep 2019.
• Vassilis Polimenis & Ioannis Neokosmidis, 2019. "Non-Stationary Dividend-Price Ratios," Papers 1902.06053, arXiv.org.