Report NEP-CMP-2025-06-30

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:

• Timoth'ee Hornek Amir Sartipi & Igor Tchappi & Gilbert Fridgen, 2025, "Benchmarking Pre-Trained Time Series Models for Electricity Price Forecasting," Papers, arXiv.org, number 2506.08113, Jun, revised Aug 2025.
• Liexin Cheng & Xue Cheng & Shuaiqiang Liu, 2025, "Fast Learning in Quantitative Finance with Extreme Learning Machine," Papers, arXiv.org, number 2505.09551, May, revised May 2025.
• Francesco Cozzi & Marco Pangallo & Alan Perotti & Andr'e Panisson & Corrado Monti, 2025, "Learning Individual Behavior in Agent-Based Models with Graph Diffusion Networks," Papers, arXiv.org, number 2505.21426, May, revised Nov 2025.
• Sukru Selim Calik & Andac Akyuz & Zeynep Hilal Kilimci & Kerem Colak, 2025, "Explainable-AI powered stock price prediction using time series transformers: A Case Study on BIST100," Papers, arXiv.org, number 2506.06345, Jun.
• Mateusz Wilinski & Anubha Goel & Alexandros Iosifidis & Juho Kanniainen, 2025, "Classifying and Clustering Trading Agents," Papers, arXiv.org, number 2505.21662, May.
• Shu Wang & Zijun Yao & Shuhuai Zhang & Jianuo Gai & Tracy Xiao Liu & Songfa Zhong, 2025, "When Experimental Economics Meets Large Language Models: Evidence-based Tactics," Papers, arXiv.org, number 2505.21371, May, revised Jul 2025.
• Tobias Schmidt & Kai-Robin Lange & Matthias Reccius & Henrik Muller & Michael Roos & Carsten Jentsch, 2025, "Identifying economic narratives in large text corpora -- An integrated approach using Large Language Models," Papers, arXiv.org, number 2506.15041, Jun.
• R. Maria del Rio-Chanona & Marco Pangallo & Cars Hommes, 2025, "Can Generative AI agents behave like humans? Evidence from laboratory market experiments," Papers, arXiv.org, number 2505.07457, May.
• Zonghan Wu & Congyuan Zou & Junlin Wang & Chenhan Wang & Hangjing Yang & Yilei Shao, 2025, "Towards Competent AI for Fundamental Analysis in Finance: A Benchmark Dataset and Evaluation," Papers, arXiv.org, number 2506.07315, May, revised Nov 2025.
• Qirui Mi & Qipeng Yang & Zijun Fan & Wentian Fan & Heyang Ma & Chengdong Ma & Siyu Xia & Bo An & Jun Wang & Haifeng Zhang, 2025, "EconGym: A Scalable AI Testbed with Diverse Economic Tasks," Papers, arXiv.org, number 2506.12110, Jun.
• Fabio Gatti & Joel Huesler, 2025, "Text Analysis Methods for Historical Letters, The case of Michelangelo Buonarrotti," Working Papers, European Historical Economics Society (EHES), number 0279, Jun.
• Marcus Buckmann & Ed Hill, 2025, "Improving text classification: logistic regression makes small LLMs strong and explainable ‘tens-of-shot’ classifiers," Bank of England working papers, Bank of England, number 1127, May.
• Marcus Buckmann & Quynh Anh Nguyen & Edward Hill, 2025, "Revealing economic facts: LLMs know more than they say," Papers, arXiv.org, number 2505.08662, May, revised Dec 2025.
• Mihai Cucuringu & Kang Li & Chao Zhang, 2025, "Forecasting Intraday Volume in Equity Markets with Machine Learning," Papers, arXiv.org, number 2505.08180, May.
• Weixian Waylon Li & Hyeonjun Kim & Mihai Cucuringu & Tiejun Ma, 2025, "Can LLM-based Financial Investing Strategies Outperform the Market in Long Run?," Papers, arXiv.org, number 2505.07078, May, revised Feb 2026.
• Yang Qiang, 2025, "The impact of extracurricular education on socioeconomic mobility in Japan: an application of causal machine learning," Papers, arXiv.org, number 2506.07421, Jun.
• Robert Scriba & Yuying Li & Jingbo B Wang, 2025, "Monte-Carlo Option Pricing in Quantum Parallel," Papers, arXiv.org, number 2505.09459, May.
• Giuseppe Arbia & Luca Morandini & Vincenzo Nardelli, 2025, "Evaluating Large Language Model Capabilities in Assessing Spatial Econometrics Research," Papers, arXiv.org, number 2506.06377, Jun.
• Gabriel Nova & Stephane Hess & Sander van Cranenburgh, 2025, "Delphos: A reinforcement learning framework for assisting discrete choice model specification," Papers, arXiv.org, number 2506.06410, Jun, revised Jul 2025.
• Yu Li & Yuhan Wu & Shuhua Zhang, 2025, "The Exploratory Multi-Asset Mean-Variance Portfolio Selection using Reinforcement Learning," Papers, arXiv.org, number 2505.07537, May.
• Jesse Zhou & Geoffrey T. Wodtke, 2025, "Causal Mediation Analysis with Multiple Mediators: A Simulation Approach," Papers, arXiv.org, number 2506.14019, Jun.
• Item repec:fpr:gsspwp:158180 is not listed on IDEAS anymore

• Mindy L. Mallory & Rundong Peng & Meilin Ma & H. Holly Wang, 2025, "High-Dimensional Spatial-Plus-Vertical Price Relationships and Price Transmission: A Machine Learning Approach," Papers, arXiv.org, number 2506.13967, Jun.
• Stella C. Dong & James R. Finlay, 2025, "Dynamic Reinsurance Treaty Bidding via Multi-Agent Reinforcement Learning," Papers, arXiv.org, number 2506.13113, Jun.
• Fabian Muny, 2025, "Evaluating Program Sequences with Double Machine Learning: An Application to Labor Market Policies," Papers, arXiv.org, number 2506.11960, Jun.
• Muhammad Sukri Bin Ramli, 2025, "Intelligent Automation for FDI Facilitation: Optimizing Tariff Exemption Processes with OCR And Large Language Models," Papers, arXiv.org, number 2506.12093, Jun.
• Jan Hurt & Stefan Thurner & Peter Klimek, 2025, "An Agent-Based Extension to Sector-Wise Input-Output Recovery Models," Papers, arXiv.org, number 2505.10146, May.
• James Cussens & Julia Hatamyar & Vishalie Shah & Noemi Kreif, 2025, "Fast Learning of Optimal Policy Trees," Papers, arXiv.org, number 2506.15435, Jun.
• Ningzi Li & Shiyang Lai & James Evans, 2025, "Big Data and the Computational Social Science of Entrepreneurship and Innovation," Papers, arXiv.org, number 2505.08706, May.
• Xueying Ding & Aakriti Mittal & Achintya Gopal, 2025, "DELPHYNE: A Pre-Trained Model for General and Financial Time Series," Papers, arXiv.org, number 2506.06288, May.
• Thiago Christiano Silva & Kei Moriya & Mr. Romain M Veyrune, 2025, "From Text to Quantified Insights: A Large-Scale LLM Analysis of Central Bank Communication," IMF Working Papers, International Monetary Fund, number 2025/109, Jun.
• Magaletti, Nicola & Notarnicola, Valeria & Di Molfetta, Mauro & Mariani, Stefano & Leogrande, Angelo, 2025, "Logistics Performance and ESG Outcomes: An Empirical Exploration Using IV Panel Models and Machine Learning," MPRA Paper, University Library of Munich, Germany, number 124746, May.
• Qingkai Zhang & L. Jeff Hong & Houmin Yan, 2025, "Conditional Generative Modeling for Enhanced Credit Risk Management in Supply Chain Finance," Papers, arXiv.org, number 2506.15305, Jun, revised Dec 2025.
• Item repec:fpr:gsspwp:174327 is not listed on IDEAS anymore

• Falck-Zepeda, José B. & Zambrano, Patricia & Sanders, Arie & Trabanino, Carlos Rogelio, 2025, "Parametric and machine learning approaches to examine yield differences between control and treatment considering outliers and statistical biases: The case of insect resistant/herbicide tolerant (IR/HT) maize in Honduras," IFPRI discussion papers, International Food Policy Research Institute (IFPRI), number 2334, Apr.
• Glyn-Davies, Alex & Vadeboncoeur, Arnaud & Akyildiz, O. Deniz & Kazlauskaite, Ieva & Girolami, Mark, 2025, "A primer on variational inference for physics-informed deep generative modelling," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 128504, Jun.

Report NEP-CMP-2025-06-30

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: