Report NEP-FOR-2026-07-27

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:

• Andrea Carriero & Davide Pettenuzzo & Shubhranshu Shekhar, 2026, "MACROCAST: A Vintage-Consistent Time Series Foundation Model for Real-Time Macroeconomic Forecasting," Papers, arXiv.org, number 2606.28670, Jun.
• Chi, Ta-Chung & Fan, Ting-Han & Ghigliazza, Raffaele & Giannone, Domenico & Wang, Zixuan (Kevin), 2025, "Macroeconomic Forecasting and Machine Learning," CEPR Discussion Papers, Centre for Economic Policy Research, number 20727, Oct.
• Conrad, Christian & Enders, Zeno & Müller, Gernot, 2025, "Inflation Forecast Targeting Revisited," CEPR Discussion Papers, Centre for Economic Policy Research, number 20467, Jul.
• Gorodnichenko, Yuriy & Vasudevan, Vittal, 2025, "Macroeconomic Expectations in a War," CEPR Discussion Papers, Centre for Economic Policy Research, number 20462, Jul.
• Hyung Joo Kim & Dong Hwan Oh, 2026, "Capturing Heterogeneity: Machine Learning Approaches to Implied Volatility Forecasting," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2026-049, Jul, DOI: 10.17016/FEDS.2026.049.
• Alessio Brini, 2026, "Forecasting Realized Volatility with Time Series Foundation Models: A Comparison with Econometric Benchmarks," Papers, arXiv.org, number 2607.05291, Jul.
• Marcellino, Massimiliano & Pfarrhofer, Michael, 2025, "Nonparametric Mixed Frequency Monitoring Macro-at-Risk," CEPR Discussion Papers, Centre for Economic Policy Research, number 20442, Jul.
• Veni Arakelia & Guglielmo Maria Caporale & Mirto M. Gasparinatou & Menelaos Karanasos, 2026, "Machine Learning and Liquidity Dynamics in European Stock Markets," CESifo Working Paper Series, CESifo, number 12829.
• Yizhou & Kuang, 2026, "Revision Risk in Real-Time Macroeconomic Forecasting," Papers, arXiv.org, number 2607.05882, Jul, revised Jul 2026.
• Elisabeth Grewenig & Klaus Gründler & Philipp Lergetporer & Niklas Potrafke & Katharina Werner & Helen Zeidler, 2026, "Expertise and Prediction Accuracy," Munich Papers in Political Economy, Munich School of Politics and Public Policy and the School of Management at the Technical University of Munich, number 47, Feb.
• Yu Peng & Matloob Khushi & Josiah Poon, 2026, "CryptoGAT: Are Time Series Models Effective for Cryptocurrency Forecasting?," Papers, arXiv.org, number 2606.27670, Jun.
• Han Feng & Difang Huang & Jue Wang & Zhengjun Zhang, 2026, "When and Why Na\"ive Diversification Works: A Simple Diagnostic Strategy," Papers, arXiv.org, number 2607.11054, Jul.
• Giovanni Angelini, 2026, "The Shape of Macroeconomic Beliefs," Papers, arXiv.org, number 2606.30040, Jun.
• Leiva-Leon, Danilo & Sheremirov, Slavik & Tang, Jenny & ZakrajÅ¡ek, Egon, 2025, "Inflation Factors," CEPR Discussion Papers, Centre for Economic Policy Research, number 20574, Aug.
• Aldasoro, Inaki & Hördahl, Peter & Schrimpf, Andreas & Zhu, Sonya, 2025, "Predicting Financial Market Stress with Machine Learning," CEPR Discussion Papers, Centre for Economic Policy Research, number 20439, Jul.
• Sichao He & Yansong Zhang, 2026, "Heads, Not Backbones: Output Heads Dominate Architectures on Fat-Tailed Returns," Papers, arXiv.org, number 2606.30037, Jun.
• Dina M Hamed, 2026, "Leveraging Non-traditional Data for Macroeconomic Nowcasting: The Case of Morocco," IMF Working Papers, International Monetary Fund, number 2026/108, Jun.
• Xinxiang Guo & Yingkai Li & Yifen Mu, 2026, "Robust Aggregation of Calibrated Forecasts," Papers, arXiv.org, number 2606.31020, Jun.
• Junjie Guo, 2026, "Learning Predictive Ambiguity Sets for Decision-Focused Distributionally Robust Optimization," Papers, arXiv.org, number 2607.09820, Jul.
• Miguel Acosta & Yeji Sung, 2026, "Recency Effects in Perceived Uncertainty," Working Paper Series, Federal Reserve Bank of San Francisco, number 2026-12, Jul, DOI: 10.24148/wp2026-12.
• Aquilina, Matteo & Araujo, Douglas & Gelos, Gaston & Park, Taejin & Perez-Cruz, Fernando, 2025, "Harnessing Artificial Intelligence for Monitoring Financial Markets," CEPR Discussion Papers, Centre for Economic Policy Research, number 20768, Oct.
• Haji Mohamad Zubir, Ahmad Shauqi bin & Mohd Nasir, Muhammad Luqman bin, 2026, "Where Volume Belongs in a Tail Risk Model: Extreme Quantile Forecasts, Subordination, and Market Depth," MPRA Paper, University Library of Munich, Germany, number 130162, Jul.
• Malliaropulos, Dimitris & Passari, Evgenia & Petroulakis, Filippos, 2025, "Unpacking Commodity Price Fluctuations: Reading the News to Understand Inflation," CEPR Discussion Papers, Centre for Economic Policy Research, number 20404, Jul.