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Report NEP-CMP-2026-04-20
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:
- Avidit Acharya & Jens Hainmueller & Yiqing Xu, 2026, "Learning Preferences from Conjoint Data: A Structural Deep Learning Approach," Papers, arXiv.org, number 2604.10845, Apr.
- Wei Wei & Jin Zheng & Zining Wang & Weibin Feng, 2026, "LR-Robot: An Human-in-the-Loop LLM Framework for Systematic Literature Reviews with Applications in Financial Research," Papers, arXiv.org, number 2604.14793, Apr.
- Shuze Daniel Liu & Claire Chen & Jiabao Sean Xiao & Lei Lei & Yuheng Zhang & Yisong Yue & David Simchi-Levi, 2026, "Instructing LLMs to Negotiate using Reinforcement Learning with Verifiable Rewards," Papers, arXiv.org, number 2604.09855, Apr.
- Onur Polat & Rangan Gupta & Dhanashree Somani & Sayar Karmakar, 2026, "Machine Learning Forecasting of U.S. Stock Market Volatility: The Role of Stock and Oil Bubbles," Working Papers, University of Pretoria, Department of Economics, number 202611, Apr.
- Cory Baird & Jonathan Benchimol & Wook Sohn & Vira Vyshnevska & Iegor Vyshnevskyi, 2026, "The Monetary Policy Statement Database: An LLM Application to Global Financial Conditions," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2026-25, Apr.
- Xiang Ao & Jingxuan Zhang & Xinyu Zhao, 2026, "Dynamic Forecasting and Temporal Feature Evolution of Stock Repurchases in Listed Companies Using Attention-Based Deep Temporal Networks," Papers, arXiv.org, number 2604.09650, Mar.
- Pu Cheng & Juncheng Liu & Yunshen Long, 2026, "PolyBench: Benchmarking LLM Forecasting and Trading Capabilities on Live Prediction Market Data," Papers, arXiv.org, number 2604.14199, Apr.
- Kun Liu & Liqun Chen, 2026, "OOM-RL: Out-of-Money Reinforcement Learning Market-Driven Alignment for LLM-Based Multi-Agent Systems," Papers, arXiv.org, number 2604.11477, Apr.
- Bin Ramli, Muhammad Sukri, 2026, "Pattern Recognition of Critical Mineral Copper in Global Trade Data," SocArXiv, Center for Open Science, number v53nw_v1, Mar, DOI: 10.31219/osf.io/v53nw_v1.
- Gotherwal, Deepesh & Ranjan, Pritam & Lekivetz, Ryan, 2026, "Comprehensive Review of Various Verification and Validation Techniques for Business Simulation Models," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 339750.
- J'er^ome Lelong & V'eronique Maume-Deschamps & William Thevenot, 2026, "Multi periods mean-DCVaR optimization: a Recursive Neural Network resolution," Papers, arXiv.org, number 2604.14439, Apr.
- Ecenur Oguz & Robert L. Bray, 2026, "Training Neural Networks Embedded in Dynamic Discrete Choice Models," Papers, arXiv.org, number 2604.09736, Apr.
- Mansur M. Arief, 2026, "Deepbullwhip: An Open-Source Simulation and Benchmarking for Multi-Echelon Bullwhip Analyses," Papers, arXiv.org, number 2604.13478, Apr.