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Report NEP-CMP-2026-01-05
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.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-CMP
The following items were announced in this report:
- Zuoyou Jiang & Li Zhao & Rui Sun & Ruohan Sun & Zhongjian Li & Jing Li & Daxin Jiang & Zuo Bai & Cheng Hua, 2025, "Alpha-R1: Alpha Screening with LLM Reasoning via Reinforcement Learning," Papers, arXiv.org, number 2512.23515, Dec.
- Julia Ko'nczal & Micha{l} Balcerek & Krzysztof Burnecki, 2025, "Machine learning models for predicting catastrophe bond coupons using climate data," Papers, arXiv.org, number 2512.22660, Dec.
- Christophe D. Hounwanou & Yae Ulrich Gaba, 2025, "Deep Generative Models for Synthetic Financial Data: Applications to Portfolio and Risk Modeling," Papers, arXiv.org, number 2512.21798, Dec, revised Dec 2025.
- Muço, Arieda, 2025, "Measuring Corruption from Text Data," SocArXiv, Center for Open Science, number cftvk_v1, Dec, DOI: 10.31219/osf.io/cftvk_v1.
- Greta Polo & Yuan Gao Rollinson & Ms. Yevgeniya Korniyenko & Tongfang Yuan, 2025, "Nowcasting GCC GDP: A Machine Learning Solution for Enhanced Non-Oil GDP Prediction," IMF Working Papers, International Monetary Fund, number 2025/268, Dec.
- Jeffrey Allen & Max S. Hatfield, 2025, "Can LLMs Improve Sanctions Screening in the Financial System? Evidence from a Fuzzy Matching Assessment," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2025-092, Sep, DOI: 10.17016/FEDS.2025.092.
- M. Coronado-Vaca, 2025, "Multi-Objective Bayesian Optimization of Deep Reinforcement Learning for Environmental, Social, and Governance (ESG) Financial Portfolio Management," Papers, arXiv.org, number 2512.14992, Dec.
- Ferraz, Vinícius & Olah, Tamas & Sazedul, Ratin & Schmidt, Robert & Schwieren, Christiane, 2025, "When Artificial Minds Negotiate: Dark Personality and the Ultimatum Game in Large Language Models," Working Papers, University of Heidelberg, Department of Economics, number 0768, Dec.
- Bong-Gyu Jang & Younwoo Jeong & Changeun Kim, 2025, "Interpretable Deep Learning for Stock Returns: A Consensus-Bottleneck Asset Pricing Model," Papers, arXiv.org, number 2512.16251, Dec, revised Dec 2025.
- Nathan Kallus, 2025, "Semiparametric Preference Optimization: Your Language Model is Secretly a Single-Index Model," Papers, arXiv.org, number 2512.21917, Dec, revised Feb 2026.
- Daniel H. Karney & Don Fullerton & Kathy Baylis, 2025, "A Model of the Model: Unpacking CGE Results on Carbon Leakage," CESifo Working Paper Series, CESifo, number 12332.
- Frank Tian-Fang Ye & Xiaozi Gao, 2025, "Marriage Discourse on Chinese Social Media: An LLM-assisted Analysis," Papers, arXiv.org, number 2512.23609, Dec, revised Jan 2026.