Report NEP-CMP-2023-05-15

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:

• Gutierrez-Lythgoe, Antonio, 2023. "Movilidad urbana sostenible: Predicción de demanda con Inteligencia Artificial [Sustainable Urban Mobility: Demand Prediction with Artificial Intelligence]," MPRA Paper 117103, University Library of Munich, Germany.
• Gutierrez-Lythgoe, Antonio, 2023. "Teletrabajo en Twitter: Análisis mediante Deep Learning [Teleworking on Twitter: Analysis using Deep Learning]," MPRA Paper 117101, University Library of Munich, Germany.
• Krist'of N'emeth & D'aniel Hadh'azi, 2023. "GDP nowcasting with artificial neural networks: How much does long-term memory matter?," Papers 2304.05805, arXiv.org, revised Feb 2024.
• Soumyadip Sarkar, 2023. "Quantitative Trading using Deep Q Learning," Papers 2304.06037, arXiv.org.
• Fantazzini, Dean, 2023. "Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models," MPRA Paper 117141, University Library of Munich, Germany.
• Daniel Oeltz & Jan Hamaekers & Kay F. Pilz, 2023. "Parameterized Neural Networks for Finance," Papers 2304.08883, arXiv.org.
• Malte Jahn, 2023. "Artificial neural networks and time series of counts: A class of nonlinear INGARCH models," Papers 2304.01025, arXiv.org.
• Artem Lensky & Mingyu Hao, 2023. "Learning to Predict Short-Term Volatility with Order Flow Image Representation," Papers 2304.02472, arXiv.org, revised Mar 2024.
• Mark-Oliver Wolf & Tom Ewen & Ivica Turkalj, 2023. "Quantum Architecture Search for Quantum Monte Carlo Integration via Conditional Parameterized Circuits with Application to Finance," Papers 2304.08793, arXiv.org, revised Sep 2023.
• Mahsa Tavakoli & Rohitash Chandra & Fengrui Tian & Cristi'an Bravo, 2023. "Multi-Modal Deep Learning for Credit Rating Prediction Using Text and Numerical Data Streams," Papers 2304.10740, arXiv.org, revised Nov 2024.
• Angun, Ebru & Kleijnen, Jack, 2023. "Constrained optimization in Random Simulation : Efficient Global Optimization and Karush-Kuhn-Tucker Conditions (Revision of CentER DP 2022-022)," Discussion Paper 2023-010, Tilburg University, Center for Economic Research.
• Frédéric Marty, 2022. "Artificial Intelligence: Opportunities and Managerial Challenges," GREDEG Working Papers 2022-23, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
• Sebastian Jaimungal & Yuri F. Saporito & Max O. Souza & Yuri Thamsten, 2023. "Optimal Trading in Automatic Market Makers with Deep Learning," Papers 2304.02180, arXiv.org.
• Frédéric Marty, 2022. "From Economic Evidence to Algorithmic Evidence: Artificial Intelligence and Blockchain: An Application to Anti-competitive Agreements," GREDEG Working Papers 2022-32, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
• Oleg V. Pavlov & Jason M. Sardell, 2023. "Economic Origins of the Sicilian Mafia: A Simulation Feedback Model," Papers 2304.07975, arXiv.org.
• Lucrezia Fanti & Marcelo C. Pereira & Maria Enrica Virgillito, 2023. "A North-South agent based model of segmented labour markets. The role of education and trade asymmetries," LEM Papers Series 2023/17, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
• Pacchiano, Aldo & Wulsin, Drausin & Barton, Robert A. & Voloch, Luis, 2023. "Neural Design for Genetic Perturbation Experiments," Research Papers 4087, Stanford University, Graduate School of Business.
• Purnomo, Andronius, 2023. "Riview Literatur Dengan Menggunakan ChatGPT," OSF Preprints fhr52, Center for Open Science.
• Pinski, Marc & Adam, Martin & Benlian, Alexander, 2023. "AI Knowledge: Improving AI Delegation through Human Enablement," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 137544, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Byrne, David & Goodhead, Robert & McMahon, Michael & Parle, Conor, 2023. "Measuring the Temporal Dimension of Text: An Application to Policymaker Speeches," Research Technical Papers 2/RT/23, Central Bank of Ireland.
• Alfredo B. Roisenzvit, 2023. "From Euclidean Distance to Spatial Classification: Unraveling the Technology behind GPT Models," CEMA Working Papers: Serie Documentos de Trabajo. 853, Universidad del CEMA.
• Angun, Ebru & Kleijnen, Jack, 2023. "Constrained optimization in Random Simulation : Efficient Global Optimization and Karush-Kuhn-Tucker Conditions (Revision of CentER DP 2022-022)," Other publications TiSEM ae1ec947-12e1-4bf7-89fb-7, Tilburg University, School of Economics and Management.
• Alejandro Lopez-Lira & Yuehua Tang, 2023. "Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models," Papers 2304.07619, arXiv.org, revised Sep 2024.
• Muriel Dal Pont Legrand & Martina Cioni & Eugenio Petrovich & Alberto Baccini, 2022. "Is There Cross-fertilization in Macroeconomics? A Quantitative Exploration of the Interactions between DSGE and Macro Agent-Based Models," GREDEG Working Papers 2022-25, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
• Nabil Kahale, 2023. "Simulating Gaussian vectors via randomized dimension reduction and PCA," Papers 2304.07377, arXiv.org.
• Justin Diamond & Ben Garcia, 2023. "Egyptian Ratscrew: Discovering Dominant Strategies with Computational Game Theory," Papers 2304.01007, arXiv.org.
• Carlos Mendez & Ayush Patnaik, 2023. "Exploring economic activity from outer space: A Python notebook for processing and analyzing satellite nighttime lights," Working Papers 21, xKDR.