Report NEP-CMP-2025-02-24

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stan 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:

• Zhouyu Shen & Dacheng Xiu, 2025. "Can Machines Learn Weak Signals?," NBER Working Papers 33421, National Bureau of Economic Research, Inc.
• Yoontae Hwang & Yaxuan Kong & Stefan Zohren & Yongjae Lee, 2025. "Decision-informed Neural Networks with Large Language Model Integration for Portfolio Optimization," Papers 2502.00828, arXiv.org.
• Di Zhang, 2025. "Efficient Triangular Arbitrage Detection via Graph Neural Networks," Papers 2502.03194, arXiv.org.
• Fernando Perez-Cruz & Hyun Song Shin, 2025. "Putting AI agents through their paces on general tasks," BIS Working Papers 1245, Bank for International Settlements.
• Kubitza, Dennis Oliver & Weßling, Katarina, 2025. "Whole Lotta Training - Studying School-to-Training Transitions by Training Artificial Neural Networks," EconStor Preprints 310974, ZBW - Leibniz Information Centre for Economics.
• Pataranutaporn, Pat & Powdthavee, Nattavudh & Maes, Pattie, 2025. "Can AI Solve the Peer Review Crisis? A Large-Scale Experiment on LLM's Performance and Biases in Evaluating Economics Papers," IZA Discussion Papers 17659, Institute of Labor Economics (IZA).
• Ramaharo, Franck Maminirina & Rasolofomanana, Gerzhino H, 2023. "Nowcasting Madagascar's real GDP using machine learning algorithms," AfricArxiv vpuac_v1, Center for Open Science.
• Joshua Rosaler & Luca Candelori & Vahagn Kirakosyan & Kharen Musaelian & Ryan Samson & Martin T. Wells & Dhagash Mehta & Stefano Pasquali, 2025. "Supervised Similarity for High-Yield Corporate Bonds with Quantum Cognition Machine Learning," Papers 2502.01495, arXiv.org.
• Marco Bardoscia & Adrian Carro & Marc Hinterschweiger & Mauro Napoletano & Lilit Popoyan & Andrea Roventini & Arzu Uluc, 2024. "The impact of prudential regulations on the UK housing market and economy: insights from an agent-based model," Working Papers 2502, Banco de España.
• Matthew Caron & Oliver Müller & Johannes Kriebel, 2025. "Detecting and Mitigating Shortcut Learning Bias in Machine Learning: A Pathway to More Generalizable ML-based (IS) Research," Working Papers Dissertations 129, Paderborn University, Faculty of Business Administration and Economics.
• Daniil Karzanov & Rub'en Garz'on & Mikhail Terekhov & Caglar Gulcehre & Thomas Raffinot & Marcin Detyniecki, 2025. "Regret-Optimized Portfolio Enhancement through Deep Reinforcement Learning and Future Looking Rewards," Papers 2502.02619, arXiv.org.
• George Fatouros & Kostas Metaxas & John Soldatos & Manos Karathanassis, 2025. "MarketSenseAI 2.0: Enhancing Stock Analysis through LLM Agents," Papers 2502.00415, arXiv.org.
• Chowdhury, Koushik, 2023. "Towards a Deep Learning approach to regularise discourse of collaborative learner," Thesis Commons hjk4b_v1, Center for Open Science.
• Alnajjar, Khalid & Hämäläinen, Mika, 2024. "MLPESTEL: The New Era of Forecasting Change in the Operational Environment of Businesses Using LLMs," Thesis Commons qz8hk_v1, Center for Open Science.
• Felix Drinkall & Janet B. Pierrehumbert & Stefan Zohren, 2025. "When Dimensionality Hurts: The Role of LLM Embedding Compression for Noisy Regression Tasks," Papers 2502.02199, arXiv.org.
• Chen Ziyi & Gu Jia-wen, 2025. "Exploratory Utility Maximization Problem with Tsallis Entropy," Papers 2502.01269, arXiv.org.
• Iuliia Alekseenko & Dmitry Dagaev & Sofia Paklina & Petr Parshakov, 2025. "Strategizing with AI: Insights from a Beauty Contest Experiment," Papers 2502.03158, arXiv.org.
• Lionel Fontagné & Francesca Micocci & Armando Rungi, 2025. "The heterogeneous impact of the EU-Canada agreement with causal machine learning," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-04913313, HAL.
• Robin Jarry & Marc Chaumont & Laure Berti-Equille & Gérard Subsol, 2024. "Predicting Socio-economic Indicator Variations with Satellite Image Time Series and Transformer," Post-Print lirmm-04895134, HAL.
• de Avila, Rogerio, 2024. "Utilizing Big Administrative Data in Evaluation Research: Integrating Causal Modeling, Program Theory, and Machine Learning," Thesis Commons z7der_v1, Center for Open Science.
• Li-Chun Huang, 2024. "NEAT Algorithm-based Stock Trading Strategy with Multiple Technical Indicators Resonance," Papers 2501.14736, arXiv.org.
• Victor Chernozhukov & Mert Demirer & Esther Duflo & Iv'an Fern'andez-Val, 2025. "Comment on "Sequential validation of treatment heterogeneity" and "Comment on generic machine learning inference on heterogeneous treatment effects in randomized experiments"," Papers 2502.01548, arXiv.org, revised Feb 2025.
• Ying, Xiangji & Vorland, Colby J. & Qureshi, Riaz & Brown, Andrew William & Kilicoglu, Halil & Saldanha, Ian & DeVito, Nicholas J & Mayo-Wilson, Evan, 2024. "GPT's Performance in Identifying Outcome Changes on ClinicalTrials.gov," MetaArXiv npvwr_v1, Center for Open Science.