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. 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:

• Jinyang Li, 2024. "A Deep Reinforcement Learning Framework For Financial Portfolio Management," Papers 2409.08426, arXiv.org.
• Zian Wang & Xinyi Lu, 2024. "COMEX Copper Futures Volatility Forecasting: Econometric Models and Deep Learning," Papers 2409.08356, arXiv.org.
• Rademacher, Philip, 2024. "Forecasting recessions in Germany with machine learning," DICE Discussion Papers 416, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
• Daniele Ballinari & Nora Bearth, 2024. "Improving the Finite Sample Performance of Double/Debiased Machine Learning with Propensity Score Calibration," Papers 2409.04874, arXiv.org.
• Sario, Azhar ul Haque, 2024. "Advanced Financial Modeling for Stock Price Prediction: A Quantitative Methods," OSF Preprints pk7w3, Center for Open Science.
• Mukherjee, Krishnendu, 2024. "Machine Learning Methods for Surge Rate Prediction: A Case Study of Yassir," MPRA Paper 122151, University Library of Munich, Germany.
• Jingru Jia & Zehua Yuan, 2024. "An Experimental Study of Competitive Market Behavior Through LLMs," Papers 2409.08357, arXiv.org, 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 2409.08281, arXiv.org.
• Ziyan Cui & Ning Li & Huaikang Zhou, 2024. "Can AI Replace Human Subjects? A Large-Scale Replication of Psychological Experiments with LLMs," Papers 2409.00128, arXiv.org, revised Sep 2024.
• Leonardo Gambacorta & Han Qiu & Shuo Shan & Daniel M Rees, 2024. "Generative AI and labour productivity: a field experiment on coding," BIS Working Papers 1208, Bank for International Settlements.
• Bohren, Noah & Hakimov, Rustamdjan & Lalive, Rafael, 2024. "Creative and Strategic Capabilities of Generative AI: Evidence from Large-Scale Experiments," IZA Discussion Papers 17302, Institute of Labor Economics (IZA).
• 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 2409.08282, arXiv.org, revised Sep 2024.
• Mohit Apte & Yashodhara Haribhakta, 2024. "Advancing Financial Forecasting: A Comparative Analysis of Neural Forecasting Models N-HiTS and N-BEATS," Papers 2409.00480, arXiv.org, 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 2409.07486, arXiv.org.
• Item repec:hal:journl:hal-04680595 is not listed on IDEAS anymore

• 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 2409.07487, arXiv.org, revised Sep 2024.
• Yifan Jia & Yanbin Wang & Jianguo Sun & Yiwei Liu & Zhang Sheng & Ye Tian, 2024. "Ethereum Fraud Detection via Joint Transaction Language Model and Graph Representation Learning," Papers 2409.07494, arXiv.org.
• Loic Mar'echal & Nathan Monnet, 2024. "Disentangling the sources of cyber risk premia," Papers 2409.08728, arXiv.org.
• 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 2409.10331, arXiv.org.