Report NEP-CMP-2026-03-30

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:

• Yicai Xing, 2026, "AI-Driven Multi-Agent Simulation of Stratified Polyamory Systems: A Computational Framework for Optimizing Social Reproductive Efficiency," Papers, arXiv.org, number 2603.20678, Mar.
• Oleksandr Castello & Marco Corazza, 2026, "Machine Learning techniques for synthetic data generation in Energy and Financial Markets," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2026: 11.
• Hui Gong, 2026, "AI Agents in Financial Markets: Architecture, Applications, and Systemic Implications," Papers, arXiv.org, number 2603.13942, Mar, revised Apr 2026.
• Hanyong Cho & Jang Ho Kim, 2026, "Constructing a Portfolio Optimization Benchmark Framework for Evaluating Large Language Models," Papers, arXiv.org, number 2603.09301, Mar.
• Takayuki Sakuma, 2026, "Differential Machine Learning for 0DTE Options with Stochastic Volatility and Jumps," Papers, arXiv.org, number 2603.07600, Mar, revised Apr 2026.
• Pei-Jun Liao & Hung-Shin Lee & Yao-Fei Cheng & Li-Wei Chen & Hung-yi Lee & Hsin-Min Wang, 2026, "Generalized Stock Price Prediction for Multiple Stocks Combined with News Fusion," Papers, arXiv.org, number 2603.19286, Mar.
• Hanyong Cho & Geumil Bae & Jang Ho Kim, 2026, "Investor risk profiles of large language models," Papers, arXiv.org, number 2603.09303, Mar.
• Haochen Luo & Zhengzhao Lai & Junjie Xu & Yifan Li & Tang Pok Hin & Yuan Zhang & Chen Liu, 2026, "From Natural Language to Executable Option Strategies via Large Language Models," Papers, arXiv.org, number 2603.16434, Mar.
• Keonvin Park, 2026, "Joint Return and Risk Modeling with Deep Neural Networks for Portfolio Construction," Papers, arXiv.org, number 2603.19288, Mar.
• Chung-Hoo Poon & James Kwok & Calvin Chow & Jang-Hyeon Choi, 2026, "LineMVGNN: Anti-Money Laundering with Line-Graph-Assisted Multi-View Graph Neural Networks," Papers, arXiv.org, number 2603.23584, Mar.
• Takashi Kameyama & Masahiro Kato & Yasuko Hio & Yasushi Takano & Naoto Minakawa, 2026, "Causality Elicitation from Large Language Models," Papers, arXiv.org, number 2603.04276, Mar.
• Minxuan Hu & Ziheng Chen & Jiayu Yi & Wenxi Sun, 2026, "Autonomous AI Agents for Option Hedging: Enhancing Financial Stability through Shortfall Aware Reinforcement Learning," Papers, arXiv.org, number 2603.06587, Feb.
• Mohammad Al Ridhawi & Mahtab Haj Ali & Hussein Al Osman, 2026, "Adaptive Regime-Aware Stock Price Prediction Using Autoencoder-Gated Dual Node Transformers with Reinforcement Learning Control," Papers, arXiv.org, number 2603.19136, Mar, revised Apr 2026.
• Stephan Ludwig & Peter J. Danaher & Xiaohao Yang, 2026, "A Neural Topic Method Using a Large-Language-Model-in-the-Loop for Business Research," Papers, arXiv.org, number 2603.03623, Mar.
• Pranjal Rawat, 2026, "A Survey of Reinforcement Learning For Economics," Papers, arXiv.org, number 2603.08956, Mar, revised Mar 2026.
• Yogesh Agrawal & Aniruddha Dutta & Md Mahadi Hasan & Santu Karmaker & Aritra Dutta, 2026, "FinTradeBench: A Financial Reasoning Benchmark for LLMs," Papers, arXiv.org, number 2603.19225, Mar, revised Mar 2026.
• Rahul D Ray, 2026, "ARTEMIS: A Neuro Symbolic Framework for Economically Constrained Market Dynamics," Papers, arXiv.org, number 2603.18107, Mar.
• Wei Wei & Jin Zheng & Zining Wang, 2026, "LR-Robot: A Unified Supervised Intelligent Framework for Real-Time Systematic Literature Reviews with Large Language Models," Papers, arXiv.org, number 2603.17723, Mar.
• Takanobu Mizuta & Isao Yagi, 2026, "Is an investor stolen their profits by mimic investors? Investigated by an agent-based model," Papers, arXiv.org, number 2603.03671, Mar.
• Yicai Xing, 2026, "AI Token Futures Market: Commoditization of Compute and Derivatives Contract Design," Papers, arXiv.org, number 2603.21690, Mar.
• Federico Vittorio Cortesi & Giuseppe Iannone & Giulia Crippa & Tomaso Poggio & Pierfrancesco Beneventano, 2026, "Same Error, Different Function: The Optimizer as an Implicit Prior in Financial Time Series," Papers, arXiv.org, number 2603.02620, Mar.
• Kevin Mott, 2026, "Feynman-Kac Derivatives Pricing on the Full Forward Curve," Papers, arXiv.org, number 2603.12375, Mar.
• Chang Chen & Duy-Minh Dang, 2026, "Convergence of Neural Network Policies for Risk--Reward Optimization," Papers, arXiv.org, number 2603.06563, Mar.
• Khem Raj Bhatt & Krishna Sharma, 2026, "Algorithmic Compliance and Regulatory Loss in Digital Assets," Papers, arXiv.org, number 2603.04328, Mar.
• Shogo Fukui, 2026, "Enhancing the Accuracy of Regional Input-Output Table Estimation: A Deep Learning Approach," Papers, arXiv.org, number 2603.13823, Mar.
• Reiner Martin & Piroska Nagy Mohacsi & Tatiana Evdokimova & Jan Klacso & Olga Ponomarenko, 2026, "Central Bank Communication on Financial Stability – A Shadowed Sibling? The Tale of Central Europe," Working and Discussion Papers, Research Department, National Bank of Slovakia, number WP 5/2026, Mar.
• Anna Baiardi & Paul S. Clarke & Andrea A. Naghi & Annalivia Polselli, 2026, "Double Machine Learning for Static Panel Data with Instrumental Variables: New Method and Applications," Papers, arXiv.org, number 2603.20464, Mar.
• Anders G Fr{o}seth, 2026, "Spectral Portfolio Theory: From SGD Weight Matrices to Wealth Dynamics," Papers, arXiv.org, number 2603.09006, Mar, revised Apr 2026.
• Enoch Hyunwook Kang, 2026, "Reasonably reasoning AI agents can avoid game-theoretic failures in zero-shot, provably," Papers, arXiv.org, number 2603.18563, Mar.
• Grzeskiewicz, M., 2026, "Neural Demand Estimation with Habit Formation and Rationality Constraints," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2613, Mar.
• Mohammad Mosaffa & Omid Rafieian, 2026, "The Privacy-Utility Trade-Off of Location Tracking in Ad Personalization," Papers, arXiv.org, number 2603.12374, Mar.
• Ziqin Gong & Ning Li & Huaikang Zhou, 2026, "Machines acquire scientific taste from institutional traces," Papers, arXiv.org, number 2603.16659, Mar.
• Daria Dzyabura & Renana Peres & Irina Linevich, 2025, "Color Analytics for Data-Driven Brand Communications," Working Papers, New Economic School (NES), number w0292, Dec.
• Mahesh Kumar & Bhaskarjit Sarmah & Stefano Pasquali, 2026, "FinReflectKG -- HalluBench: GraphRAG Hallucination Benchmark for Financial Question Answering Systems," Papers, arXiv.org, number 2603.20252, Mar.
• Adjemian, Stéphane & Juillard, Michel & Karamé, Fréderic & Mutschler, Willi & Pfeifer, Johannes & Ratto, Marco & Rion, Normann & Villemot, Sébastien, 2026, "Dynare: Reference Manual, Version 7," Dynare Working Papers, CEPREMAP, number 87, Mar.
• Martin Jaraiz, 2026, "Macroeconomic Forecasting from Input-Output Tables Alone: A Darwinian Agent-Based Approach with FIGARO Data," Papers, arXiv.org, number 2603.12412, Mar, revised Mar 2026.
• Abraham Itzhak Weinberg, 2026, "Quantum-Assisted Optimal Rebalancing with Uncorrelated Asset Selection for Algorithmic Trading Walk-Forward QUBO Scheduling via QAOA," Papers, arXiv.org, number 2603.16904, Mar.

Report NEP-CMP-2026-03-30

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: