Report NEP-CMP-2024-05-13

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.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-CMP

The following items were announced in this report:

• Dat Mai, 2024, "StockGPT: A GenAI Model for Stock Prediction and Trading," Papers, arXiv.org, number 2404.05101, Apr, revised Oct 2024.
• Sara Fish & Yannai A. Gonczarowski & Ran I. Shorrer, 2024, "Algorithmic Collusion by Large Language Models," Papers, arXiv.org, number 2404.00806, Mar, revised Sep 2025.
• Sendhil Mullainathan & Ashesh Rambachan, 2024, "From Predictive Algorithms to Automatic Generation of Anomalies," Papers, arXiv.org, number 2404.10111, Apr, revised Sep 2025.
• Yupeng Cao & Zhi Chen & Prashant Kumar & Qingyun Pei & Yangyang Yu & Haohang Li & Fabrizio Dimino & Lorenzo Ausiello & K. P. Subbalakshmi & Papa Momar Ndiaye, 2024, "RiskLabs: Predicting Financial Risk Using Large Language Model based on Multimodal and Multi-Sources Data," Papers, arXiv.org, number 2404.07452, Apr, revised May 2025.
• Van Pham & Scott Cunningham, 2024, "Can Base ChatGPT be Used for Forecasting without Additional Optimization?," Papers, arXiv.org, number 2404.07396, Apr, revised Jul 2024.
• Kirtac, Kemal & Germano, Guido, 2024, "Sentiment trading with large language models," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 122592, Apr.
• Kapil Panda, 2023, "Artificial Intelligence-based Analysis of Change in Public Finance between US and International Markets," Papers, arXiv.org, number 2403.18823, Dec.
• Armand Mihai Cismaru, 2024, "DeepTraderX: Challenging Conventional Trading Strategies with Deep Learning in Multi-Threaded Market Simulations," Papers, arXiv.org, number 2403.18831, Feb.
• Andre Guettler & Mahvish Naeem & Lars Norden & Bernardus F Nazar Van Doornik, 2024, "Pre-publication revisions of bank financial statements: a novel way to monitor banks?," BIS Working Papers, Bank for International Settlements, number 1177, Mar.
• Artem Kraevskiy & Artem Prokhorov & Evgeniy Sokolovskiy, 2024, "An early warning system for emerging markets," Papers, arXiv.org, number 2404.03319, Apr, revised May 2025.
• Giambattista Albora & Matteo Straccamore & Andrea Zaccaria, 2024, "Machine learning-based similarity measure to forecast M&A from patent data," Papers, arXiv.org, number 2404.07179, Apr.
• Marco Bardoscia & Adrian Carro & Marc Hinterschweiger & Mauro Napoletano & Lilit Popoyan & Andrea Roventini & Arzu Uluc, 2024, "The impact of prudential regulations on the UK housing market and economy: insights from an agent-based model," Bank of England working papers, Bank of England, number 1066, Mar.
• Iñaki Aldasoro & Sebastian Doerr & Leonardo Gambacorta & Daniel Rees, 2024, "The impact of artificial intelligence on output and inflation," BIS Working Papers, Bank for International Settlements, number 1179, Apr.
• Nouhaila Innan & Alberto Marchisio & Mohamed Bennai & Muhammad Shafique, 2024, "QFNN-FFD: Quantum Federated Neural Network for Financial Fraud Detection," Papers, arXiv.org, number 2404.02595, Apr, revised Jul 2025.
• Thorsten Hens & Trine Nordlie, 2024, "How good are LLMs in risk profiling?," KIER Working Papers, Kyoto University, Institute of Economic Research, number 1103, Apr.
• Knoth, Nils & Decker, Marie & Laupichler, Matthias Carl & Pinski, Marc & Buchholtz, Nils & Bata, Katharina & Schultz, Ben, 2024, "Developing a Holistic AI Literacy Assessment Matrix - Bridging Generic, Domain-Specific, and Ethical Competencies," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 144414, Apr.
• Irene Aldridge, 2024, "Fast TTC Computation," Papers, arXiv.org, number 2403.15111, Mar.
• Siting Estee Lu, 2024, "Strategic Interactions between Large Language Models-based Agents in Beauty Contests," Papers, arXiv.org, number 2404.08492, Apr, revised Oct 2024.
• Scott Wentland & Gary Cornwall & Jeremy G. Moulton, 2023, "For What It's Worth: Measuring Land Value in the Era of Big Data and Machine Learning," BEA Papers, Bureau of Economic Analysis, number 0115, Jun.
• Lorenc Kapllani & Long Teng, 2024, "A backward differential deep learning-based algorithm for solving high-dimensional nonlinear backward stochastic differential equations," Papers, arXiv.org, number 2404.08456, Apr.
• Buda Baji'c & Sr{dj}an Mili'cevi'c & Aleksandar Anti'c & Slobodan Markovi'c & Nemanja Tomi'c, 2024, "Neural Network Modeling for Forecasting Tourism Demand in Stopi\'{c}a Cave: A Serbian Cave Tourism Study," Papers, arXiv.org, number 2404.04974, Apr.
• Paola Tubaro, 2024, "Algorithms, inequalities, and the 'humans-in-the-loop'
  [Algorithmes, inégalités, et les « humains dans la boucle »]," Post-Print, HAL, number hal-04533266, Mar.

Report NEP-CMP-2024-05-13

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.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-CMP

The following items were announced in this report: