Report NEP-CMP-2025-08-25

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:

• Adam Darmanin & Vince Vella, 2025. "Language Model Guided Reinforcement Learning in Quantitative Trading," Papers 2508.02366, arXiv.org.
• Caio de Souza Barbosa Costa & Anna Helena Reali Costa, 2025. "Comparing Normalization Methods for Portfolio Optimization with Reinforcement Learning," Papers 2508.03910, arXiv.org.
• Wv{e}i Zh=ang, 2025. "Neural Network-Based Algorithmic Trading Systems: Multi-Timeframe Analysis and High-Frequency Execution in Cryptocurrency Markets," Papers 2508.02356, arXiv.org.
• Longfei Lu, 2025. "Technical Indicator Networks (TINs): An Interpretable Neural Architecture Modernizing Classic al Technical Analysis for Adaptive Algorithmic Trading," Papers 2507.20202, arXiv.org.
• Maciej Wysocki & Pawe{l} Sakowski, 2025. "Investment Portfolio Optimization Based on Modern Portfolio Theory and Deep Learning Models," Papers 2508.14999, arXiv.org.
• Orr Shahar & Stefan Lessmann & Daniel Traian Pele, 2025. "Causality analysis of electricity market liberalization on electricity price using novel Machine Learning methods," Papers 2507.12331, arXiv.org.
• Hess, Dieter & Simon, Frederik & Weibels, Sebastian, 2025. "Interpretable machine learning for earnings forecasts: Leveraging high-dimensional financial statement data," CFR Working Papers 25-06, University of Cologne, Centre for Financial Research (CFR).
• Yu Shi & Zongliang Fu & Shuo Chen & Bohan Zhao & Wei Xu & Changshui Zhang & Jian Li, 2025. "Kronos: A Foundation Model for the Language of Financial Markets," Papers 2508.02739, arXiv.org.
• Imad Talhartit & Sanae Ait Jillali & Mounime El Kabbouri, 2025. "Enhancing Stock Price Forecasting with LSTM Networks: A Comparative Study of Classic and PSO-Optimized Models on S&P 500 Stocks," Post-Print hal-05177777, HAL.
• Tomu Hirata & Undral Byambadalai & Tatsushi Oka & Shota Yasui & Shingo Uto, 2025. "Efficient and Scalable Estimation of Distributional Treatment Effects with Multi-Task Neural Networks," Papers 2507.07738, arXiv.org.
• Akash Deep & Chris Monico & W. Brent Lindquist & Svetlozar T. Rachev & Frank J. Fabozzi, 2025. "Binary Tree Option Pricing Under Market Microstructure Effects: A Random Forest Approach," Papers 2507.16701, arXiv.org.
• Craig S Wright, 2025. "Epistemic Scarcity: The Economics of Unresolvable Unknowns," Papers 2507.01483, arXiv.org.
• Del Frari, Elisa & Aassve, Arnstein & Melegaro, Alessia, 2025. "Demographic Changes and Fiscal Sustainability of the Italian Pension System: An Agent-Based Modelling Approach," OSF Preprints g2xqt_v1, Center for Open Science.
• Ivan Letteri, 2025. "A Framework for Predictive Directional Trading Based on Volatility and Causal Inference," Papers 2507.09347, arXiv.org.
• Facundo Arga~naraz & Juan Carlos Escanciano, 2025. "Debiased Machine Learning for Unobserved Heterogeneity: High-Dimensional Panels and Measurement Error Models," Papers 2507.13788, arXiv.org.
• Joshua Aslett & Thomas Cantens & François Chastel & Emmanuel A Crown & Stuart Hamilton, 2025. "Generative Artificial Intelligence for Compliance Risk Analysis: Applications in Tax and Customs Administration," IMF Technical Notes and Manuals 2025/013, International Monetary Fund.
• Davide Veronelli & Francesca Cibrario & Emanuele Dri & Valeria Zaffaroni & Giacomo Ranieri & Davide Corbelletto & Bartolomeo Montrucchio, 2025. "Implementing Credit Risk Analysis with Quantum Singular Value Transformation," Papers 2507.19206, arXiv.org.
• Anastasis Kratsios & Ariel Neufeld & Philipp Schmocker, 2025. "Generative Neural Operators of Log-Complexity Can Simultaneously Solve Infinitely Many Convex Programs," Papers 2508.14995, arXiv.org.
• Jakub Karnowski & Przemys{l}aw Szufel, 2025. "Ukrainian-style oligarchic economies: how concentrated power undermines value added in production chains," Papers 2508.02949, arXiv.org, revised Aug 2025.
• Thomas Hazenberg & Yao Ma & Seyed Sahand Mohammadi Ziabari & Marijn van Rijswijk, 2025. "Multi-Agent Reinforcement Learning for Dynamic Pricing in Supply Chains: Benchmarking Strategic Agent Behaviours under Realistically Simulated Market Conditions," Papers 2507.02698, arXiv.org.
• Easton, Peter & Kapons, Martin & Monahan, S. & Schütt, Harm & Weisbrod, Eric H., 2024. "Forecasting earnings using k-nearest neighbor classification," Other publications TiSEM 47b3dffb-5015-44a5-8519-f, Tilburg University, School of Economics and Management.
• Item repec:arx:papers:2506.00099 is not listed on IDEAS anymore