Report NEP-CMP-2024-02-12

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:

• Brahmana, Rayenda Khresna, 2022. "Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?," MPRA Paper 119598, University Library of Munich, Germany.
• Vetter, Oliver A. & Sturm, Timo & Fecho, Mariska & Buxmann, Peter, 2023. "Machine Learning Developments as Stimuli for Organizational Learning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 142034, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "Model Averaging and Double Machine Learning," Papers 2401.01645, arXiv.org, revised Sep 2024.
• Yue Chen & Xingyi Andrew & Salintip Supasanya, 2024. "CRISIS ALERT:Forecasting Stock Market Crisis Events Using Machine Learning Methods," Papers 2401.06172, arXiv.org.
• Emmanuil H. Georgoulis & Antonis Papapantoleon & Costas Smaragdakis, 2024. "A deep implicit-explicit minimizing movement method for option pricing in jump-diffusion models," Papers 2401.06740, arXiv.org.
• Vetter, Oliver A. & Pumplun, Luisa & Koppe, Timo, 2023. "An Ambidextrous Perspective on Machine Learning Development and Operation: The Nexus of Organizational Structure, Tensions, and Tactics," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 142032, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Simons, Martin & Roloff, Malte & Liebe, Andrea & Lundborg, Martin, 2023. "Künstliche Intelligenz mit AutoML, Low-Code und No-Code: Eine Markterhebung von Software-Tools," WIK Discussion Papers 501, WIK Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH.
• Otero, Fernando & Managó, Bianca Bietti, 2024. "Aprendizaje Basado en Problemas: Estimación Óptima para evaluar una técnica de inversión basada en Monte Carlo," OSF Preprints xhztv, Center for Open Science.
• Paolo Pellizzari, 2024. "Learning Whether to Be Informed in an Agent-Based Evolutionary Market Model," Working Papers 2024: 03, Department of Economics, University of Venice "Ca' Foscari".
• Ali Mehrban & Pegah Ahadian, 2024. "An adaptive network-based approach for advanced forecasting of cryptocurrency values," Papers 2401.05441, arXiv.org, revised Feb 2024.
• Dar'io Blanco-Fern'andez & Stephan Leitner & Alexandra Rausch, 2024. "Interactions between dynamic team composition and coordination: An agent-based modeling approach," Papers 2401.05832, arXiv.org.
• Frank Xing, 2024. "Designing Heterogeneous LLM Agents for Financial Sentiment Analysis," Papers 2401.05799, arXiv.org.
• Alexander Leodolter & Aleksander Rutkowski, 2022. "The Fiscal and Distributional Effects of Removing Mortgage Interest Tax Relief in EU Member States," European Economy - Economic Briefs 072, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
• Amina Badreddine & Hadjira Larbi Cherif, 2023. "ChatGPT in Academic Research: Demonstrating Limitations through Real Practical Examples," Post-Print hal-04379581, HAL.
• Vetter, Oliver A. & Efremov, Alexander, 2023. "A User-Centric Approach to Explainable AI in Corporate Performance Management," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 142030, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Sara Slamić Tarade, 2023. "Discovering the Significance of Sports Footwear Brands through Text Analysis ," GATR Journals jmmr326, Global Academy of Training and Research (GATR) Enterprise.
• Baptiste Lefort & Eric Benhamou & Jean-Jacques Ohana & David Saltiel & Beatrice Guez & Damien Challet, 2024. "Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps?," Papers 2401.05447, arXiv.org.