Report NEP-CMP-2026-02-02

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stanley Miles issued this report. It is usually issued weekly.

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Other reports in NEP-CMP

The following items were announced in this report:

• Ficura, Milan & Ibragimov, Rustam & Janda, Karel, 2025, "Artificial Intelligence–Based Forecasting of Oil Prices: Evidence from Neural Network Models," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 335571.
• James Rice, 2026, "Stochastic Deep Learning: A Probabilistic Framework for Modeling Uncertainty in Structured Temporal Data," Papers, arXiv.org, number 2601.05227, Jan.
• Vincent Gurgul & Ying Chen & Stefan Lessmann, 2026, "Variational Quantum Circuit-Based Reinforcement Learning for Dynamic Portfolio Optimization," Papers, arXiv.org, number 2601.18811, Jan, revised Jan 2026.
• Alexander Eliseev & Sergei Seleznev, 2026, "Fake Date Tests: Can We Trust In-sample Accuracy of LLMs in Macroeconomic Forecasting?," Papers, arXiv.org, number 2601.07992, Jan.
• Ac-Pangan, Walter & Hendricks, Nathan P., 2025, "In-Season US Corn Acreage Forecasting Using Machine Learning," 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO, Agricultural and Applied Economics Association, number 360869, DOI: 10.22004/ag.econ.360869.
• Mohammed Alruqimi & Luca Di Persio, 2025, "Integrating LSTM Networks with Neural Levy Processes for Financial Forecasting," Papers, arXiv.org, number 2512.07860, Nov.
• Varun Narayan Kannan Pillai & Akshay Ajith & Sumesh K J, 2026, "Generating Alpha: A Hybrid AI-Driven Trading System Integrating Technical Analysis, Machine Learning and Financial Sentiment for Regime-Adaptive Equity Strategies," Papers, arXiv.org, number 2601.19504, Jan.
• Hui Chen & Yuhan Cheng & Yanchu Liu & Ke Tang, 2026, "Teaching Economics to the Machines," NBER Working Papers, National Bureau of Economic Research, Inc, number 34713, Jan.
• Bohan Liang & Zijian Chen & Qi Jia & Kaiwei Zhang & Kaiyuan Ji & Guangtao Zhai, 2025, "PriceSeer: Evaluating Large Language Models in Real-Time Stock Prediction," Papers, arXiv.org, number 2601.06088, Dec.
• Mostapha Benhenda, 2026, "Look-Ahead-Bench: a Standardized Benchmark of Look-ahead Bias in Point-in-Time LLMs for Finance," Papers, arXiv.org, number 2601.13770, Jan.
• Rui Sun & Yifan Sun & Sheng Xu & Li Zhao & Jing Li & Daxin Jiang & Cheng Hua & Zuo Bai, 2026, "Trade-R1: Bridging Verifiable Rewards to Stochastic Environments via Process-Level Reasoning Verification," Papers, arXiv.org, number 2601.03948, Jan, revised Jan 2026.
• Liu He, 2026, "Incorporating Cognitive Biases into Reinforcement Learning for Financial Decision-Making," Papers, arXiv.org, number 2601.08247, Jan.
• Mohammadhossien Rashidi, 2025, "Can Large Language Models Improve Venture Capital Exit Timing After IPO?," Papers, arXiv.org, number 2601.00810, Dec.
• Haochong Xia & Simin Li & Ruixiao Xu & Zhixia Zhang & Hongxiang Wang & Zhiqian Liu & Teng Yao Long & Molei Qin & Chuqiao Zong & Bo An, 2026, "Bayesian Robust Financial Trading with Adversarial Synthetic Market Data," Papers, arXiv.org, number 2601.17008, Jan.
• Sungwoo Kang, 2026, "The Limits of Complexity: Why Feature Engineering Beats Deep Learning in Investor Flow Prediction," Papers, arXiv.org, number 2601.07131, Jan.
• Jinjun Liu & Ming-Yen Cheng, 2026, "Forecasting the U.S. Treasury Yield Curve: A Distributionally Robust Machine Learning Approach," Papers, arXiv.org, number 2601.04608, Jan.
• Jack Fanshawe & Rumi Masih & Alexander Cameron, 2026, "Forecasting Equity Correlations with Hybrid Transformer Graph Neural Network," Papers, arXiv.org, number 2601.04602, Jan.
• Brandon Luo & Jim Skufca, 2026, "Enhancing Portfolio Optimization with Deep Learning Insights," Papers, arXiv.org, number 2601.07942, Jan.
• Masahiro Kato, 2026, "Riesz Representer Fitting under Bregman Divergence: A Unified Framework for Debiased Machine Learning," Papers, arXiv.org, number 2601.07752, Jan, revised Jan 2026.
• Sunil K Sapra, 2025, "Nonlinear Regression Modeling via Machine Learning Techniques with Applications in Business and Economics," RAIS Conference Proceedings 2022-2025, Research Association for Interdisciplinary Studies, number 0594, Nov.
• Bridget Smart & Ebba Mark & Anne Bastian & Josefina Waugh, 2026, "Manipulation in Prediction Markets: An Agent-based Modeling Experiment," Papers, arXiv.org, number 2601.20452, Jan.
• Beier, Gregory Caldwell, 2026, "Superharddata: Liability-Grounded Information as Training Substrate for Aligned Artificial Intelligence," LawArchive, Center for Open Science, number yhc6t_v1, Jan, DOI: 10.31219/osf.io/yhc6t_v1.
• Masoud Soleimani, 2025, "LLM-Generated Counterfactual Stress Scenarios for Portfolio Risk Simulation via Hybrid Prompt-RAG Pipeline," Papers, arXiv.org, number 2512.07867, Nov.