Report NEP-CMP-2025-03-17

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:

• Mostapha Benhenda, 2025. "FinRL-DeepSeek: LLM-Infused Risk-Sensitive Reinforcement Learning for Trading Agents," Papers 2502.07393, arXiv.org.
• Tianzuo Hu, 2025. "Financial fraud detection system based on improved random forest and gradient boosting machine (GBM)," Papers 2502.15822, arXiv.org.
• Alicia Vidler & Toby Walsh, 2025. "Shifting Power: Leveraging LLMs to Simulate Human Aversion in ABMs of Bilateral Financial Exchanges, A bond market study," Papers 2503.00320, arXiv.org, revised Mar 2025.
• Rath Minati & Date Hema, 2025. "Quantum Powered Credit Risk Assessment: A Novel Approach using hybrid Quantum-Classical Deep Neural Network for Row-Type Dependent Predictive Analysis," Papers 2502.07806, arXiv.org.
• Yanhao & Wei & Zhenling Jiang, 2025. "Estimating Parameters of Structural Models Using Neural Networks," Papers 2502.04945, arXiv.org.
• Jaskaran Singh Walia & Aarush Sinha & Srinitish Srinivasan & Srihari Unnikrishnan, 2025. "Predicting Liquidity-Aware Bond Yields using Causal GANs and Deep Reinforcement Learning with LLM Evaluation," Papers 2502.17011, arXiv.org.
• Yuan Liao & Xinjie Ma & Andreas Neuhierl & Linda Schilling, 2025. "The Uncertainty of Machine Learning Predictions in Asset Pricing," Papers 2503.00549, arXiv.org.
• Pierre Beaucoral, 2025. "Cracking the Code: Enhancing Development finance understanding with artificial intelligence," Papers 2502.09495, arXiv.org.
• Eric Hitz & Mingmin Feng & Radu Tanase & Ren'e Algesheimer & Manuel S. Mariani, 2025. "The amplifier effect of artificial agents in social contagion," Papers 2502.21037, arXiv.org, revised Mar 2025.
• Pedro Reis & Ana Paula Serra & Jo~ao Gama, 2025. "The Role of Deep Learning in Financial Asset Management: A Systematic Review," Papers 2503.01591, arXiv.org.
• Yung, Vincent & Colyvas, Jeannette, 2023. "Munging the Ghosts in the Machine: Coded Bias and the Craft of Wrangling Archival Data," SocArXiv 2dve6_v1, Center for Open Science.
• Moustapha Pemy & Na Zhang, 2025. "Minimal Shortfall Strategies for Liquidation of a Basket of Stocks using Reinforcement Learning," Papers 2502.07868, arXiv.org.
• Merfeld,Joshua David & Newhouse,David Locke, 2023. "Improving Estimates of Mean Welfare and Uncertainty in Developing Countries," Policy Research Working Paper Series 10348, The World Bank.
• Gerion Spielberger & Florian M. Artinger & Jochen Reb & Rudolf Kerschreiter, 2025. "Retrieval Augmented Generation for Topic Modeling in Organizational Research: An Introduction with Empirical Demonstration," Papers 2502.20963, arXiv.org, revised Mar 2025.
• Tianmi Ma & Jiawei Du & Wenxin Huang & Wenjie Wang & Liang Xie & Xian Zhong & Joey Tianyi Zhou, 2025. "LLM Knows Geometry Better than Algebra: Numerical Understanding of LLM-Based Agents in A Trading Arena," Papers 2502.17967, arXiv.org.
• Lett, Elle & La Cava, William, 2023. "Translating Intersectionality to Fair Machine Learning in Health Sciences," SocArXiv gu7yh_v1, Center for Open Science.
• Morande, Swapnil & Arshi, Tahseen & Gul, Kanwal & Amini, Mitra, 2023. "Harnessing the Power of Artificial Intelligence to Forecast Startup Success: An Empirical Evaluation of the SECURE AI Model," SocArXiv p3gyb_v1, Center for Open Science.
• Zhu, Jin & Wan, Runzhe & Qi, Zhengling & Luo, Shikai & Shi, Chengchun, 2024. "Robust offline reinforcement learning with heavy-tailed rewards," LSE Research Online Documents on Economics 122740, London School of Economics and Political Science, LSE Library.
• Verhagen, Mark D., 2023. "Using machine learning to study effect heterogeneity in large-scale policy interventions: The Dutch decentralisation of the Social Domain," SocArXiv qzm7y_v1, Center for Open Science.
• Daniel Brunstein & Georges Casamatta & Sauveur Giannoni, 2025. "Using machine learning to estimate the heterogeneous impact of Airbnb on house prices: Evidence from Corsica," Post-Print hal-04934630, HAL.
• Iman Modarressi & Jann Spiess & Amar Venugopal, 2025. "Causal Inference on Outcomes Learned from Text," Papers 2503.00725, arXiv.org.
• Dirk Bergemann & Alessandro Bonatti & Alex Smolin, 2025. "The Economics of Large Language Models: Token Allocation, Fine-Tuning, and Optimal Pricing," Papers 2502.07736, arXiv.org.
• Songrun He & Linying Lv & Asaf Manela & Jimmy Wu, 2025. "Chronologically Consistent Large Language Models," Papers 2502.21206, arXiv.org, revised Mar 2025.
• Ruoyu Guo & Haochen Qiu, 2025. "Pursuing Top Growth with Novel Loss Function," Papers 2502.17493, arXiv.org.
• Hamid Moradi-Kamali & Mohammad-Hossein Rajabi-Ghozlou & Mahdi Ghazavi & Ali Soltani & Amirreza Sattarzadeh & Reza Entezari-Maleki, 2025. "Market-Derived Financial Sentiment Analysis: Context-Aware Language Models for Crypto Forecasting," Papers 2502.14897, arXiv.org, revised Mar 2025.
• Tanay Panat & Rohitash Chandra, 2025. "Global Ease of Living Index: a machine learning framework for longitudinal analysis of major economies," Papers 2502.06866, arXiv.org, revised Feb 2025.
• Shang Liu & Hanzhao Wang & Zhongyao Ma & Xiaocheng Li, 2025. "How Humans Help LLMs: Assessing and Incentivizing Human Preference Annotators," Papers 2502.06387, arXiv.org.
• Leonardo Berti & Gjergji Kasneci, 2025. "TLOB: A Novel Transformer Model with Dual Attention for Stock Price Trend Prediction with Limit Order Book Data," Papers 2502.15757, arXiv.org, revised Feb 2025.
• Arandjelović, Ognjen, 2023. "A Case for `Killer Robots': Why in the Long Run Martial AI May Be Good for Peace," SocArXiv 9kja8_v1, Center for Open Science.
• Mahony,Christopher Brian & Manning,Matthew & Wong,Gabriel, 2023. "Weighting Justice Reform Costs and Benefits Using Machine Learning and Modern Data Science," Policy Research Working Paper Series 10449, The World Bank.
• Hsin-Min Lu & Yu-Tai Chien & Huan-Hsun Yen & Yen-Hsiu Chen, 2025. "Utilizing Pre-trained and Large Language Models for 10-K Items Segmentation," Papers 2502.08875, arXiv.org.
• Montoya Munoz,Kelly Yelitza & Olivieri,Sergio Daniel & Silveira Braga,Cicero Augusto, 2023. "Considering Labor Informality in Forecasting Poverty and Inequality: A Microsimulation Modelfor Latin American and Caribbean Countries," Policy Research Working Paper Series 10497, The World Bank.