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Report NEP-FOR-2022-07-18
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:
- Elie Bouri & Rangan Gupta & Luca Rossini, 2022, "The Role of the Monthly ENSO in Forecasting the Daily Baltic Dry Index," Working Papers, University of Pretoria, Department of Economics, number 202229, Jun.
- Paulo M.M. Rodrigues & Robert Hill, 2022, "Forgetting Approaches to Improve Forecasting," Working Papers, Banco de Portugal, Economics and Research Department, number w202208.
- Jiazi Chen & Zhiwu Hong & Linlin Niu, 2022, "Forecasting Interest Rates with Shifting Endpoints: The Role of the Demographic Age Structure," Working Papers, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University, number 2022-06-25, Jun.
- Afees A. Salisu & Riza Demirer & Rangan Gupta, 2022, "Policy Uncertainty and Stock Market Volatility Revisited: The Predictive Role of Signal Quality," Working Papers, University of Pretoria, Department of Economics, number 202232, Jun.
- David Gabauer & Rangan Gupta & Sayar Karmakar & Joshua Nielsen, 2022, "Stock Market Bubbles and the Forecastability of Gold Returns (and Volatility)," Working Papers, University of Pretoria, Department of Economics, number 202228, Jun.
- Ryan Zischke & Gael M. Martin & David T. Frazier & D. S. Poskitt, 2022, "The Impact of Sampling Variability on Estimated Combinations of Distributional Forecasts," Papers, arXiv.org, number 2206.02376, Jun.
- Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022, ""Density forecasts of inflation using Gaussian process regression models"," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202210, Jul, revised Jul 2022.
- Luis Gruber & Gregor Kastner, 2022, "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers, arXiv.org, number 2206.04902, Jun, revised Feb 2025.
- Benjamin Avanzi & Yanfeng Li & Bernard Wong & Alan Xian, 2022, "Ensemble distributional forecasting for insurance loss reserving," Papers, arXiv.org, number 2206.08541, Jun, revised Jun 2024.
- María Alejandra Hernández-Montes & Ramón Hernández-Ortega & Jonathan Alexander Muñoz-Martínez, 2022, "Aporte de las expectativas de empresarios al pronóstico de las variables macroeconómicas," Borradores de Economia, Banco de la Republica de Colombia, number 1202, Jun, DOI: 10.32468/be.1202.
- Samarasinghe, Tharanga, 2022, "Impact analysis of GDP related variables on economic growth of Sri Lanka," MPRA Paper, University Library of Munich, Germany, number 113149, May.
- Christopher Bockel-Rickermann, 2022, "Predicting Day-Ahead Stock Returns using Search Engine Query Volumes: An Application of Gradient Boosted Decision Trees to the S&P 100," Papers, arXiv.org, number 2205.15853, May, revised Jun 2022.
- Christian Gourieroux & Joann Jasiak, 2022, "Nonlinear Fore(Back)casting and Innovation Filtering for Causal-Noncausal VAR Models," Papers, arXiv.org, number 2205.09922, May, revised Jul 2025.
- Koen W. de Bock & Arno de Caigny, 2021, "Spline-rule ensemble classifiers with structured sparsity regularization for interpretable customer churn modeling," Post-Print, HAL, number hal-03391564, Nov, DOI: 10.1016/j.dss.2021.113523.