Printed from https://ideas.repec.org/n/nep-for/2026-04-13.html
Report NEP-FOR-2026-04-13
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:
- Abdelfatah, Omar Sharafeldin Mohamed, 2026, "Machine Learning Approaches for Improving Demand Forecasting Accuracy in Retail Supply Chains," SocArXiv, Center for Open Science, number 4z9be_v1, Apr, DOI: 10.31219/osf.io/4z9be_v1.
- Abhinav Das & Stephan Schlüter & Lorenz Schneider, 2026, "Regime-aware conditional neural processes with multi-criteria decision support for operational electricity price forecasting," Post-Print, HAL, number hal-05562231, May, DOI: 10.1016/j.eneco.2026.109233.
- Alexandre Alouadi & Gr'egoire Loeper & C'elian Marsala & Othmane Mazhar & Huy^en Pham, 2026, "SBBTS: A Unified Schr\"odinger-Bass Framework for Synthetic Financial Time Series," Papers, arXiv.org, number 2604.07159, Apr.
- Zheqi Fan & Meng Melody Wang & Yifan Ye, 2026, "On options-driven realized volatility forecasting: Information gains via rough volatility model," Papers, arXiv.org, number 2604.02743, Apr, revised Apr 2026.
- Christopher Gerling & Hanqiu Peng & Ying Chen & Stefan Lessmann, 2026, "Transfer Learning for Loan Recovery Prediction under Distribution Shifts with Heterogeneous Feature Spaces," Papers, arXiv.org, number 2604.02832, Apr, revised Apr 2026.
- Tashreef Muhammad & Tahsin Ahmed & Meherun Farzana & Md. Mahmudul Hasan & Abrar Eyasir & Md. Emon Khan & Mahafuzul Islam Shawon & Ferdous Mondol & Mahmudul Hasan & Muhammad Ibrahim, 2026, "A Benchmark of Classical and Deep Learning Models for Agricultural Commodity Price Forecasting on A Novel Bangladeshi Market Price Dataset," Papers, arXiv.org, number 2604.06227, Mar.
- Zhenyu Gao & Wenxi Jiang & Yutong Yan, 2026, "Debiasing LLMs by Fine-tuning," Papers, arXiv.org, number 2604.02921, Apr, revised May 2026.
- Mykola Babiak & Jozef Barunik & Josef Kurka, 2026, "Skewness Dispersion and Stock Market Returns," Papers, arXiv.org, number 2604.07870, Apr.
- Mostapha Benhenda, 2026, "YC Bench: a Live Benchmark for Forecasting Startup Outperformance in Y Combinator Batches," Papers, arXiv.org, number 2604.02378, Apr, revised Apr 2026.
- Kazim, Zeeshan, 2026, "Intraday Decision Support for Traders: Explainable CNN-Based Directional Price Forecasting from Candlestick Chart Images," SocArXiv, Center for Open Science, number btnz8_v1, Mar, DOI: 10.31219/osf.io/btnz8_v1.
- Jaden Zhang & Gardenia Liu & Oliver Johansson & Hileamlak Yitayew & Kamryn Ohly & Grace Li, 2026, "Prediction Arena: Benchmarking AI Models on Real-World Prediction Markets," Papers, arXiv.org, number 2604.07355, Mar.
- Nolan Alexander & William Scherer, 2026, "Forecasting Tangency Portfolios and Investing in the Minimum Euclidean Distance Portfolio to Maximize Out-of-Sample Sharpe Ratios," Papers, arXiv.org, number 2604.03948, Apr.
- Daichi Hiraki & Siddhartha Chib & Yasuhiro Omori, 2026, "Dynamic Factor Stochastic Volatility-in-Mean VAR for Large Macroeconomic Panels," Papers, arXiv.org, number 2604.04529, Apr.
- Mr. Sam Ouliaris & Ms. Celine Rochon, 2026, "Solving the Canonical Quarterly Projection Model Using EViews," IMF Technical Notes and Manuals, International Monetary Fund, number 2026/003, Apr.