Report NEP-BIG-2026-01-26

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.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-BIG

The following items were announced in this report:

• Chike, Onyedikachi Emmanuel & Badruddoza, Syed & Lyford, Conrad, 2025, "Vaping Vs. Smoking: The Links To Arthritis And Overall Health Using Double Machine Learning," 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO, Agricultural and Applied Economics Association, number 360934, DOI: 10.22004/ag.econ.360934.
• Schmidt, Lorenz & Ritter, Matthias & Mußhoff, Oliver & Odening, Martin, 2025, "Can Machine Learning Improve the Design of Set-Aside Auctions?," 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO, Agricultural and Applied Economics Association, number 360670, DOI: 10.22004/ag.econ.360670.
• Chawla, Parth & Taylor, J. Edward, 2025, "Predicting Mexico-to-US Migration with Machine Learning for Counterfactual Analysis," 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO, Agricultural and Applied Economics Association, number 361223, DOI: 10.22004/ag.econ.361223.
• Benjamin Avanzi & Matthew Lambrianidis & Greg Taylor & Bernard Wong, 2025, "On the use of case estimate and transactional payment data in neural networks for individual loss reserving," Papers, arXiv.org, number 2601.05274, Dec.
• Muriuki, James & Lawani, Abdelaziz, 2025, "Regional Disparities and Determinants of SNAP Store Retention in the U.S.: A Survival Analysis and Machine Learning Approach," 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO, Agricultural and Applied Economics Association, number 360881, DOI: 10.22004/ag.econ.360881.
• Kim Ristolainen, 2026, "Quantifying Minsky Cycles," Discussion Papers, Aboa Centre for Economics, number 173, Jan.
• Chang Liu, 2025, "Unveiling Hedge Funds: Topic Modeling and Sentiment Correlation with Fund Performance," Papers, arXiv.org, number 2512.06620, Dec.
• Zhimin Chen & Bryan T. Kelly & Semyon Malamud, 2025, "Limits To (Machine) Learning," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 25-106, Dec.
• Pablo Hidalgo & Julio E. Sandubete & Agust'in Garc'ia-Garc'ia, 2025, "Explainable Prediction of Economic Time Series Using IMFs and Neural Networks," Papers, arXiv.org, number 2512.12499, Dec.
• Kirchner, Ella & Benami, Elinor & Cecil, Michael & Becker-Reshef, Inbal & Wagner, Josef & Sahajpal, Ritvik, 2025, "Targeting Field Data Collection for Effective Agricultural Monitoring and Disaster Relief with Earth Observation and Machine Learning," 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO, Agricultural and Applied Economics Association, number 361023, DOI: 10.22004/ag.econ.361023.
• Adler, Brian & Brown, Anne, 2026, "Predicting St. Louis Housing Prices with Machine Learning on Market and Assessor Data," SocArXiv, Center for Open Science, number s9v4u_v1, Jan, DOI: 10.31219/osf.io/s9v4u_v1.
• Agust'in M. de los Riscos & Julio E. Sandubete & Diego Carmona-Fern'andez & Le'on Bele~na, 2025, "Empirical Mode Decomposition and Graph Transformation of the MSCI World Index: A Multiscale Topological Analysis for Graph Neural Network Modeling," Papers, arXiv.org, number 2512.12526, Dec.
• Cen, Huang & Wanying, Liao & He, Leng & Sheetal, Abhishek, 2026, "Replication Study on “Machine Learning from a ‘Universe’ of Signals: The Role of Feature Engineering” (Li et al., 2025)," SocArXiv, Center for Open Science, number 3fh8x_v2, Jan, DOI: 10.31219/osf.io/3fh8x_v2.
• Jaisal Patel & Yunzhe Chen & Kaiwen He & Keyi Wang & David Li & Kairong Xiao & Xiao-Yang Liu, 2025, "Reasoning Models Ace the CFA Exams," Papers, arXiv.org, number 2512.08270, Dec.
• Sayed Akif Hussain & Chen Qiu-shi & Syed Amer Hussain & Syed Atif Hussain & Asma Komal & Muhammad Imran Khalid, 2026, "Improving Financial Forecasting with a Synergistic LLM-Transformer Architecture: A Hybrid Approach to Stock Price Prediction," Papers, arXiv.org, number 2601.02878, Jan.
• Zhiming Lian, 2026, "Instruction Finetuning LLaMA-3-8B Model Using LoRA for Financial Named Entity Recognition," Papers, arXiv.org, number 2601.10043, Jan.
• Kedidi, Islem & Araujo, Hamilton & Randriamarolo, Marie Rose, 2025, "Impact of milk price volatility on French dairy farm profitability: A data-driven approach combining econometric modeling and machine learning," 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO, Agricultural and Applied Economics Association, number 360682, DOI: 10.22004/ag.econ.360682.
• Ahmed Khwaja & Sonal Srivastava, 2026, "Reinforcement Learning Based Computationally Efficient Conditional Choice Simulation Estimation of Dynamic Discrete Choice Models," Papers, arXiv.org, number 2601.02069, Jan.
• Rainer Michael Rilke & Dirk Sliwka, 2026, "When Algorithms Rate Performance: Do Large Language Models Replicate Human Evaluation Biases?," ECONtribute Discussion Papers Series, University of Bonn and University of Cologne, Germany, number 384, Jan.
• Nikoleta Anesti & Edward Hill & Andreas Joseph, 2025, "Inflation Attitudes of Large Language Models," Papers, arXiv.org, number 2512.14306, Dec.
• Jakob Bjelac & Victor Chernozhukov & Phil-Adrian Klotz & Jannis Kueck & Theresa M. A. Schmitz, 2026, "Automatic debiased machine learning and sensitivity analysis for sample selection models," Papers, arXiv.org, number 2601.08643, Jan.
• Giovanni Ballarin & Lyudmila Grigoryeva & Yui Ching Li, 2025, "From Many Models, One: Macroeconomic Forecasting with Reservoir Ensembles," Papers, arXiv.org, number 2512.13642, Dec, revised Jan 2026.
• Kieran Wood & Stephen J. Roberts & Stefan Zohren, 2026, "DeePM: Regime-Robust Deep Learning for Systematic Macro Portfolio Management," Papers, arXiv.org, number 2601.05975, Jan.
• Carrera Gonzalo, 2025, "Modelos de Nowcasting para el pronóstico de la actividad económica mensual argentina," Asociación Argentina de Economía Política: Working Papers, Asociación Argentina de Economía Política, number 4784, Dec.
• Gabriel Saco, 2025, "Ill-Conditioned Orthogonal Scores in Double Machine Learning," Papers, arXiv.org, number 2512.07083, Dec, revised Jan 2026.
• Gongao Zhang & Haijiang Zeng & Lu Jiang, 2026, "Uni-FinLLM: A Unified Multimodal Large Language Model with Modular Task Heads for Micro-Level Stock Prediction and Macro-Level Systemic Risk Assessment," Papers, arXiv.org, number 2601.02677, Jan.
• Efstratios Manolakis & Christian Bongiorno & Rosario Nunzio Mantegna, 2026, "Physics-Informed Singular-Value Learning for Cross-Covariances Forecasting in Financial Markets," Papers, arXiv.org, number 2601.07687, Jan, revised Jan 2026.
• Sahaj Raj Malla & Shreeyash Kayastha & Rumi Suwal & Harish Chandra Bhandari & Rajendra Adhikari, 2026, "XGBoost Forecasting of NEPSE Index Log Returns with Walk Forward Validation," Papers, arXiv.org, number 2601.08896, Jan.
• Pawe{l} Niszczota & Cassandra Grutzner, 2026, "Antisocial behavior towards large language model users: experimental evidence," Papers, arXiv.org, number 2601.09772, Jan.

Report NEP-BIG-2026-01-26

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.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-BIG

The following items were announced in this report: