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Report NEP-CMP-2024-10-14
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:
- Jinyang Li, 2024, "A Deep Reinforcement Learning Framework For Financial Portfolio Management," Papers, arXiv.org, number 2409.08426, Sep.
- Zian Wang & Xinyi Lu, 2024, "COMEX Copper Futures Volatility Forecasting: Econometric Models and Deep Learning," Papers, arXiv.org, number 2409.08356, Sep.
- Rademacher, Philip, 2024, "Forecasting recessions in Germany with machine learning," DICE Discussion Papers, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE), number 416.
- Daniele Ballinari & Nora Bearth, 2024, "Improving the Finite Sample Estimation of Average Treatment Effects using Double/Debiased Machine Learning with Propensity Score Calibration," Papers, arXiv.org, number 2409.04874, Sep, revised Jan 2025.
- Sario, Azhar ul Haque, 2024, "Advanced Financial Modeling for Stock Price Prediction: A Quantitative Methods," OSF Preprints, Center for Open Science, number pk7w3, Sep, DOI: 10.31219/osf.io/pk7w3.
- Mukherjee, Krishnendu, 2024, "Machine Learning Methods for Surge Rate Prediction: A Case Study of Yassir," MPRA Paper, University Library of Munich, Germany, number 122151, Sep.
- Jingru Jia & Zehua Yuan, 2024, "An Experimental Study of Competitive Market Behavior Through LLMs," Papers, arXiv.org, number 2409.08357, Sep, revised Oct 2024.
- Shengkun Wang & Taoran Ji & Linhan Wang & Yanshen Sun & Shang-Ching Liu & Amit Kumar & Chang-Tien Lu, 2024, "StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction," Papers, arXiv.org, number 2409.08281, Aug.
- Ziyan Cui & Ning Li & Huaikang Zhou, 2024, "Can Large Language Models Replace Human Subjects? A Large-Scale Replication of Scenario-Based Experiments in Psychology and Management," Papers, arXiv.org, number 2409.00128, Aug, revised Jun 2025.
- Leonardo Gambacorta & Han Qiu & Shuo Shan & Daniel M Rees, 2024, "Generative AI and labour productivity: a field experiment on coding," BIS Working Papers, Bank for International Settlements, number 1208, Sep.
- Bohren, Noah & Hakimov, Rustamdjan & Lalive, Rafael, 2024, "Creative and Strategic Capabilities of Generative AI: Evidence from Large-Scale Experiments," IZA Discussion Papers, Institute of Labor Economics (IZA), number 17302, Sep.
- Peng Zhu & Yuante Li & Yifan Hu & Qinyuan Liu & Dawei Cheng & Yuqi Liang, 2024, "LSR-IGRU: Stock Trend Prediction Based on Long Short-Term Relationships and Improved GRU," Papers, arXiv.org, number 2409.08282, Aug, revised May 2025.
- Mohit Apte & Yashodhara Haribhakta, 2024, "Advancing Financial Forecasting: A Comparative Analysis of Neural Forecasting Models N-HiTS and N-BEATS," Papers, arXiv.org, number 2409.00480, Aug, revised Sep 2024.
- Junjie Li & Yang Liu & Weiqing Liu & Shikai Fang & Lewen Wang & Chang Xu & Jiang Bian, 2024, "MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model," Papers, arXiv.org, number 2409.07486, Sep, revised Mar 2025.
- Nasser Bouchareb, 2023, "The Role of Artificial Intelligence in Improving Hotels Property Management Systems," Post-Print, HAL, number hal-04680595, Dec.
- Sandy Chen & Leqi Zeng & Abhinav Raghunathan & Flora Huang & Terrence C. Kim, 2024, "MoA is All You Need: Building LLM Research Team using Mixture of Agents," Papers, arXiv.org, number 2409.07487, Sep, revised Sep 2024.
- Jianguo Sun & Yifan Jia & Yanbin Wang & Yiwei Liu & Zhang Sheng & Ye Tian, 2024, "Ethereum Fraud Detection via Joint Transaction Language Model and Graph Representation Learning," Papers, arXiv.org, number 2409.07494, Sep, revised Feb 2025.
- Loic Mar'echal & Nathan Monnet, 2024, "Disentangling the sources of cyber risk premia," Papers, arXiv.org, number 2409.08728, Sep.
- Shuochen Bi & Yufan Lian & Ziyue Wang, 2024, "Research and Design of a Financial Intelligent Risk Control Platform Based on Big Data Analysis and Deep Machine Learning," Papers, arXiv.org, number 2409.10331, Sep.