Report NEP-FOR-2026-06-08

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:

• Hilde C. Bjornland & Nicolas Hardy & Dimitris Korobilis, 2026, "Forecasting Oil Prices Across the Distribution: A Quantile VAR Approach," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2026-39, May.
• Nam Ho-Nguyen & Hossein Alipour & Anastasios Panagiotelis & George Athanasopoulos, 2026, "Optimal Forecast Reconciliation for Quantiles," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 4/26.
• Théo Metz & Carolina Ulloa-Suárez & Oscar M. Valencia, 2026, "Does oversight pay off?Independent fiscal institutions and forecast accuracy," Working Papers of BETA, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg, number 2026-14.
• Brooke Hathhorn & Laura E. Jackson & Michael T. Owyang, 2026, "Does Uncertainty Really Predict Recessions?," Working Papers, Federal Reserve Bank of St. Louis, number 2026-010, May, DOI: 10.20955/wp.2026.010.
• Thomas K. Kloster & Fred Espen Benth, 2026, "Forecasting of volatility and risk premia in electricity markets," Papers, arXiv.org, number 2606.05991, Jun.
• Tanisa Tawichsri & Suppawong Tuarob & Nuwat Nookhwun & Chinjuta Sangasaeng, 2026, "News-Based Inflation Expectations: LLM-Assisted Measurement and Forecasting," PIER Discussion Papers, Puey Ungphakorn Institute for Economic Research, number 252, May.
• Labastidas, Esteban, 2026, "A Hybrid Early-Warning System for Inflation in an Emerging Market: Combining Econometric Models, an Agent-Based Decomposition with Heterogeneous Expectations, a Large Language Model, and a Multi-Output Agent Architecture," MPRA Paper, University Library of Munich, Germany, number 128779, Apr.
• Jayesh Chaudhary, 2026, "Multi-Scale Markov Switching GARCH," Papers, arXiv.org, number 2606.06190, Jun.
• Rylan Wade, 2026, "Do Better Volatility Forecasts Lead to Better Portfolios? Evidence from Graph Neural Networks," Papers, arXiv.org, number 2605.19278, May, revised May 2026.
• Eric Engstrom, 2026, "Anchored to the Dot Plot: Central Bank Projections and Interest Rate Expectations," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2026-026, May, DOI: 10.17016/FEDS.2026.026.
• Nobuyuki Hanaki & Bolin Mao & Tiffany Tsz Kwan Tse & Wenxin Zhou, 2024, "Overvaluing Algorithmic Advice: Evidence from a Stock Price Forecasting Experiment," ISER Discussion Paper, Institute of Social and Economic Research, The University of Osaka, number 1268rr, Dec, revised May 2026.
• Sai Ma, 2026, "Attention Allocation and Belief Distortions," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.), number 1438, Apr, DOI: 10.17016/IFDP.2026.1438.
• Mamiko Yamashita, 2026, "Pricing Kernel Monotonicity and the Conservativeness of Risk-Neutral Forecasts," OSIPP Discussion Paper, Osaka School of International Public Policy, Osaka University, number 26E008, May.