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Report NEP-FOR-2022-04-11
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:
- Hauber, Philipp, 2021, "How useful is external information from professional forecasters? Conditional forecasts in large factor models," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 251469.
- Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2022, "Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data," Working Papers, University of Pretoria, Department of Economics, number 202217, Mar.
- Easaw, Joshy & Golinelli, Roberto & Heravi, Saeed, 2022, "Professionals Forecasting Inflation: The Role of Inattentiveness and Uncertainty," Cardiff Economics Working Papers, Cardiff University, Cardiff Business School, Economics Section, number E2022/7, Mar.
- Youssef Ulgazi & Paul Vertier, 2022, "Forecasting Inflation in France: an Update of MAPI," Working papers, Banque de France, number 869.
- Michael V. Klibanov & Aleksander A. Shananin & Kirill V. Golubnichiy & Sergey M. Kravchenko, 2022, "Forecasting Stock Options Prices via the Solution of an Ill-Posed Problem for the Black-Scholes Equation," Papers, arXiv.org, number 2202.07174, Feb, revised Feb 2022.
- Wheatcroft, Edward, 2021, "Evaluating probabilistic forecasts of football matches: the case against the ranked probability score," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 111494, Dec.
- Hauber, Philipp, 2022, "Real-time nowcasting with sparse factor models," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 251551.
- Jeyhun Mikayilov & Ryan Alyamani & Abdulelah Darandary & Muhammad Javid & Fakhri Hasanov & Saleh T. AlTurki & Rey B. Arnaiz, 2022, "Modeling and Forecasting Industrial Electricity Demand for Saudi Arabia: Uncovering Regional Characteristics," Discussion Papers, King Abdullah Petroleum Studies and Research Center, number ks--2021-dp19, Jan, DOI: 10.30573/KS--2021-DP19.