Report NEP-BIG-2026-01-12

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.

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Other reports in NEP-BIG

The following items were announced in this report:

• Safiye Turgay & Serkan Erdou{g}an & v{Z}eljko Stevi'c & Orhan Emre Elma & Tevfik Eren & Zhiyuan Wang & Mahmut Baydac{s}, 2025, "Risk-Aware Financial Forecasting Enhanced by Machine Learning and Intuitionistic Fuzzy Multi-Criteria Decision-Making," Papers, arXiv.org, number 2512.17936, Dec.
• Liying Zhang & Ying Gao, 2025, "An Efficient Machine Learning Framework for Option Pricing via Fourier Transform," Papers, arXiv.org, number 2512.16115, Dec, revised Dec 2025.
• Jiawei Du & Yi Hong, 2025, "Ultimate Forward Rate Prediction and its Application to Bond Yield Forecasting: A Machine Learning Perspective," Papers, arXiv.org, number 2601.00011, Dec.
• Abraham Itzhak Weinberg, 2025, "Hybrid Quantum-Classical Ensemble Learning for S\&P 500 Directional Prediction," Papers, arXiv.org, number 2512.15738, Dec.
• Yan Liu & Ye Luo & Zigan Wang & Xiaowei Zhang, 2026, "Uncertainty-Adjusted Sorting for Asset Pricing with Machine Learning," Papers, arXiv.org, number 2601.00593, Jan.
• Annalivia Polselli, 2025, "xtdml: Double Machine Learning Estimation to Static Panel Data Models with Fixed Effects in R," Papers, arXiv.org, number 2512.15965, Dec.
• Zhenyu Gao & Wenxi Jiang & Yutong Yan, 2025, "A Test of Lookahead Bias in LLM Forecasts," Papers, arXiv.org, number 2512.23847, Dec.
• Calil, Yuri Clements Daglia, 2024, "Cattle Prices Under Arid Conditions: Hedonic and Neural Network Approach," 2024 Annual Meeting, July 28-30, New Orleans, LA, Agricultural and Applied Economics Association, number 343928, DOI: 10.22004/ag.econ.343928.
• Yuhan Hou & Tianji Rao & Jeremy Tan & Adler Viton & Xiyue Zhang & David Ye & Abhishek Kodi & Sanjana Dulam & Aditya Paul & Yikai Feng, 2025, "FedSight AI: Multi-Agent System Architecture for Federal Funds Target Rate Prediction," Papers, arXiv.org, number 2512.15728, Dec.
• Alina Voronina & Oleksandr Romanko & Ruiwen Cao & Roy H. Kwon & Rafael Mendoza-Arriaga, 2025, "Generative AI-enhanced Sector-based Investment Portfolio Construction," Papers, arXiv.org, number 2512.24526, Dec.
• Filippo Gusella & Eugenio Vicario, 2025, "Generative Agents and Expectations: Do LLMs Align with Heterogeneous Agent Models?," Working Papers - Economics, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, number wp2025_18.rdf.
• Zihan Zhang & Lianyan Fu & Dehui Wang, 2026, "Difference-in-Differences using Double Negative Controls and Graph Neural Networks for Unmeasured Network Confounding," Papers, arXiv.org, number 2601.00603, Jan.
• Sergio Alvarez-Telena & Marta Diez-Fernandez, 2025, "Advances in Agentic AI: Back to the Future," Papers, arXiv.org, number 2512.24856, Dec.
• Tim J. Boonen & Xinyue Fan & Zixiao Quan, 2025, "Fairness-Aware Insurance Pricing: A Multi-Objective Optimization Approach," Papers, arXiv.org, number 2512.24747, Dec.
• Jianping Mei & Michael Moses & Jan Waelty & Yucheng Yang, 2025, "Deep Learning for Art Market Valuation," Papers, arXiv.org, number 2512.23078, Dec.
• Linuk Perera, 2025, "Quantitative Financial Modeling for Sri Lankan Markets: Approach Combining NLP, Clustering and Time-Series Forecasting," Papers, arXiv.org, number 2512.20216, Dec.