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. Stanley 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, arXiv.org, number 2311.10723, Sep, 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, arXiv.org, number 2311.10799, Nov.
• 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, arXiv.org, number 2311.11913, Nov, 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, number hal-04263512, Jan, DOI: 10.4018/JGIM.323059.
• 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, arXiv.org, number 2311.07211, Nov, revised Apr 2024.
• Ixandra Achitouv & Dragos Gorduza & Antoine Jacquier, 2023, "Natural Language Processing for Financial Regulation," Papers, arXiv.org, number 2311.08533, Nov.
• Jiahao Chen & Xiaofei Li, 2023, "Analysis of frequent trading effects of various machine learning models," Papers, arXiv.org, number 2311.10719, Sep.
• Moritz Scherrmann & Ralf Elsas, 2023, "Earnings Prediction Using Recurrent Neural Networks," Papers, arXiv.org, number 2311.10756, Nov.
• Nicolas Cofre & Magdalena Mosionek-Schweda, 2023, "A simulated electronic market with speculative behaviour and bubble formation," Papers, arXiv.org, number 2311.12247, Nov.
• 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, University of Zurich, Department of Business Administration (IBW), number 0209, Nov.
• Alexej Brauer, 2023, "Enhancing Actuarial Non-Life Pricing Models via Transformers," Papers, arXiv.org, number 2311.07597, Nov, revised Jun 2024.
• David E. Bloom & Klaus Prettner & Jamel Saadaoui & Mario Veruete, 2023, "Artificial intelligence and the skill premium," Papers, arXiv.org, number 2311.09255, Nov.
• Kaichen Zhang & Zixuan Yuan & Hui Xiong, 2023, "The Impact of Generative Artificial Intelligence on Market Equilibrium: Evidence from a Natural Experiment," Papers, arXiv.org, number 2311.07071, Nov, 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, arXiv.org, number 2311.10801, Nov, 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, Center for Research in Economics and Statistics, number 2023-09, Aug.
• 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, World Institute for Development Economic Research (UNU-WIDER), number wp-2023-139.
• 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, London School of Economics and Political Science, LSE Library, number 120649, Oct.
• 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, arXiv.org, number 2311.06292, Nov.
• Gang Hu, 2023, "Advancing Algorithmic Trading: A Multi-Technique Enhancement of Deep Q-Network Models," Papers, arXiv.org, number 2311.05743, Nov.
• 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, arXiv.org, number 2311.07513, Nov.
• Moritz Scherrmann, 2023, "Multi-Label Topic Model for Financial Textual Data," Papers, arXiv.org, number 2311.07598, Nov.
• Ricardo Cuervo, 2023, "Predictive AI for SME and Large Enterprise Financial Performance Management," Papers, arXiv.org, number 2311.05840, Sep.
• Soumyadip Sarkar, 2023, "Harnessing Deep Q-Learning for Enhanced Statistical Arbitrage in High-Frequency Trading: A Comprehensive Exploration," Papers, arXiv.org, number 2311.10718, Sep.