Report NEP-CMP-2023-12-18

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:

• Yinheng Li & Shaofei Wang & Han Ding & Hang Chen, 2023. "Large Language Models in Finance: A Survey," Papers 2311.10723, arXiv.org, revised Jul 2024.
• Minati Rath & Hema Date, 2023. "Adaptive Modelling Approach for Row-Type Dependent Predictive Analysis (RTDPA): A Framework for Designing Machine Learning Models for Credit Risk Analysis in Banking Sector," Papers 2311.10799, arXiv.org.
• Namid R. Stillman & Rory Baggott & Justin Lyon & Jianfei Zhang & Dingqiu Zhu & Tao Chen & Perukrishnen Vytelingum, 2023. "Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networks," Papers 2311.11913, arXiv.org, revised Nov 2023.
• Yazan Alnsour & Marina Johnson & Abdullah Albizri & Antoine Harfouche, 2023. "Predicting Patient Length of Stay Using Artificial Intelligence to Assist Healthcare Professionals in Resource Planning and Scheduling Decisions," Post-Print hal-04263512, HAL.
• Jirong Zhuang & Deng Ding & Weiguo Lu & Xuan Wu & Gangnan Yuan, 2023. "A Gaussian Process Based Method with Deep Kernel Learning for Pricing High-dimensional American Options," Papers 2311.07211, arXiv.org, revised Apr 2024.
• Ixandra Achitouv & Dragos Gorduza & Antoine Jacquier, 2023. "Natural Language Processing for Financial Regulation," Papers 2311.08533, arXiv.org.
• Jiahao Chen & Xiaofei Li, 2023. "Analysis of frequent trading effects of various machine learning models," Papers 2311.10719, arXiv.org.
• Moritz Scherrmann & Ralf Elsas, 2023. "Earnings Prediction Using Recurrent Neural Networks," Papers 2311.10756, arXiv.org.
• Nicolas Cofre & Magdalena Mosionek-Schweda, 2023. "A simulated electronic market with speculative behaviour and bubble formation," Papers 2311.12247, arXiv.org.
• Daniel Goller & Christian Gschwendt & Stefan C. Wolter, 2023. ""This time it's different" Generative Artificial Intelligence and Occupational Choice," Economics of Education Working Paper Series 0209, University of Zurich, Department of Business Administration (IBW).
• Alexej Brauer, 2023. "Enhancing Actuarial Non-Life Pricing Models via Transformers," Papers 2311.07597, arXiv.org, revised Jun 2024.
• David E. Bloom & Klaus Prettner & Jamel Saadaoui & Mario Veruete, 2023. "Artificial intelligence and the skill premium," Papers 2311.09255, arXiv.org.
• Kaichen Zhang & Zixuan Yuan & Hui Xiong, 2023. "The Impact of Generative Artificial Intelligence on Market Equilibrium: Evidence from a Natural Experiment," Papers 2311.07071, arXiv.org, revised Oct 2024.
• Wentao Zhang & Yilei Zhao & Shuo Sun & Jie Ying & Yonggang Xie & Zitao Song & Xinrun Wang & Bo An, 2023. "Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools," Papers 2311.10801, arXiv.org, revised Feb 2024.
• Gerard J. van den Berg & Max Kunaschk & Julia Lang & Gesine Stephan & Arne Uhlendorf, 2023. "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," Working Papers 2023-09, Center for Research in Economics and Statistics.
• Ada Jansen & Winile Ngobeni & Wynnona Steyn, 2023. "A reform option for pension fund contribution as tax expenditure in South Africa: A microsimulation model approach using tax administrative data," WIDER Working Paper Series wp-2023-139, World Institute for Development Economic Research (UNU-WIDER).
• Zhang, Wen & Shi, Jingwen & Wang, Xiaojun & Wynn, Henry, 2023. "AI-powered decision-making in facilitating insurance claim dispute resolution," LSE Research Online Documents on Economics 120649, London School of Economics and Political Science, LSE Library.
• Abel Sancarlos & Edgar Bahilo & Pablo Mozo & Lukas Norman & Obaid Ur Rehma & Mihails Anufrijevs, 2023. "Towards a data-driven debt collection strategy based on an advanced machine learning framework," Papers 2311.06292, arXiv.org.
• Gang Hu, 2023. "Advancing Algorithmic Trading: A Multi-Technique Enhancement of Deep Q-Network Models," Papers 2311.05743, arXiv.org.
• Branka Hadji Misheva & Joerg Osterrieder, 2023. "A Hypothesis on Good Practices for AI-based Systems for Financial Time Series Forecasting: Towards Domain-Driven XAI Methods," Papers 2311.07513, arXiv.org.
• Moritz Scherrmann, 2023. "Multi-Label Topic Model for Financial Textual Data," Papers 2311.07598, arXiv.org.
• Ricardo Cuervo, 2023. "Predictive AI for SME and Large Enterprise Financial Performance Management," Papers 2311.05840, arXiv.org.
• Soumyadip Sarkar, 2023. "Harnessing Deep Q-Learning for Enhanced Statistical Arbitrage in High-Frequency Trading: A Comprehensive Exploration," Papers 2311.10718, arXiv.org.