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Report NEP-FOR-2020-06-15
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:
- Item repec:wrk:wrkemf:33 is not listed on IDEAS anymore
- Yue Qiu & Tian Xie & Jun Yu, 2020, "Forecast combinations in machine learning," Economics and Statistics Working Papers, Singapore Management University, School of Economics, number 13-2020, May.
- Roberto Baviera & Giuseppe Messuti, 2020, "Daily Middle-Term Probabilistic Forecasting of Power Consumption in North-East England," Papers, arXiv.org, number 2005.13005, May, revised Oct 2020.
- Tim Janke & Florian Steinke, 2020, "Probabilistic multivariate electricity price forecasting using implicit generative ensemble post-processing," Papers, arXiv.org, number 2005.13417, May.
- Laurent Pauwels & Peter Radchenko & Andrey L. Vasnev, 2020, "High Moment Constraints for Predictive Density Combination," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2020-45, May, revised Jun 2023.
- Håvard Hungnes, 2020, "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers, Statistics Norway, Research Department, number 931, May.
- Marek Kwas & Alessia Paccagnini & Michal Rubaszek, 2020, "Common Factors and the Dynamics of Cereal Prices: A Forecasting Perspective," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2020-47, May.
- Michael Puglia & Adam Tucker, 2020, "Machine Learning, the Treasury Yield Curve and Recession Forecasting," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2020-038, May, DOI: 10.17016/FEDS.2020.038.
- Afees A. Salisu & Rangan Gupta & Elie Bouri & Qiang Ji, 2020, "The Role of Global Economic Conditions in Forecasting Gold Market Volatility: Evidence from a GARCH-MIDAS Approach," Working Papers, University of Pretoria, Department of Economics, number 202043, May.
- Nino Antulov-Fantulin & Tian Guo & Fabrizio Lillo, 2020, "Temporal mixture ensemble models for intraday volume forecasting in cryptocurrency exchange markets," Papers, arXiv.org, number 2005.09356, May, revised Dec 2020.
- Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2020, "Making text count: economic forecasting using newspaper text," Bank of England working papers, Bank of England, number 865, May.
- Rui Dong & Raymond Fisman & Yongxiang Wang & Nianhang Xu, 2019, "Air Pollution, Affect, and Forecasting Bias: Evidence from Chinese Financial Analysts," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series, Boston University - Department of Economics, number dp-345, Dec.
- Escribano, Álvaro & Wang, Dandan, 2020, "Forecasting gasoline prices with mixed random forest error correction models," UC3M Working papers. Economics, Universidad Carlos III de Madrid. Departamento de EconomÃa, number 30557, Jun.
- Xinyue Cui & Zhaoyu Xu & Yue Zhou, 2020, "Using Machine Learning to Forecast Future Earnings," Papers, arXiv.org, number 2005.13995, May.
- Item repec:spo:wpmain:info:hdl:2441/7t8isspkbs8hk8kol9kk9sjdl6 is not listed on IDEAS anymore
- Item repec:wrk:wrkemf:32 is not listed on IDEAS anymore
- Tobias Hartl, 2020, "Macroeconomic Forecasting with Fractional Factor Models," Papers, arXiv.org, number 2005.04897, May.
- Item repec:gla:glaewp:2019-07 is not listed on IDEAS anymore
- Neeti Mathur & Himanshu Mathur, 2020, "Application of GARCH Models For Volatility Modelling of Stock Market Returns: Evidences From BSE India," Proceedings of Business and Management Conferences, International Institute of Social and Economic Sciences, number 10112533, Feb.
- Kristof Decock & Michela Bergamini & Koenraad Debackere & Enrico Lupi & Anne Mieke Vandamme & Bart Van Looy, 2020, "Predicting when peaks will occur, ex ante. Insights from the COVID-19 Pandemic in Italy and Belgium," Working Papers of Department of Management, Strategy and Innovation, Leuven, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven, number 654760, May.