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Report NEP-CMP-2024-05-20
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:
- Masanori Hirano, 2024, "Experimental Analysis of Deep Hedging Using Artificial Market Simulations for Underlying Asset Simulators," Papers, arXiv.org, number 2404.09462, Apr.
- Böcking, Lars & Michaelis, Anne & Schäfermeier, Bastian & Baier, André & Kühl, Niklas & Körner, Marc-Fabian & Nolting, Lars, 2024, "Generative Artificial Intelligence in the energy sector," Bayreuth Reports on Information Systems Management, University of Bayreuth, Chair of Information Systems Management, number 71, DOI: 10.15495/EPub_UBT_00007674.
- Francisco de Arriba-P'erez & Silvia Garc'ia-M'endez & Jos'e A. Regueiro-Janeiro & Francisco J. Gonz'alez-Casta~no, 2024, "Detection of financial opportunities in micro-blogging data with a stacked classification system," Papers, arXiv.org, number 2404.07224, Mar.
- Masanori Hirano & Kentaro Imajo, 2024, "Construction of Domain-specified Japanese Large Language Model for Finance through Continual Pre-training," Papers, arXiv.org, number 2404.10555, Apr.
- Pawanesh Pawanesh & Charu Sharma & Niteesh Sahni, 2024, "Exploiting the geometry of heterogeneous networks: A case study of the Indian stock market," Papers, arXiv.org, number 2404.04710, Apr, revised Jan 2025.
- Mark Setterfield & George Wheaton, 2024, "Animal spirits and the Goodwin pattern," Working Papers, New School for Social Research, Department of Economics, number 2407, May.
- Alicia Vidler, 2024, "Recommender Systems in Financial Trading: Using machine-based conviction analysis in an explainable AI investment framework," Papers, arXiv.org, number 2404.11080, Apr.
- Thiago C. Silva & Paulo V. B. Wilhelm & Diego R. Amancio, 2024, "Machine learning and economic forecasting: the role of international trade networks," Papers, arXiv.org, number 2404.08712, Apr.
- Chen, Yudong & Chen, Yining, 2024, "Yudong Chen and Yining Chen's contribution to the discussion of ‘the discussion meeting on probabilistic and statistical aspects of machine learning’," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 121252, Apr.
- Gavioli-Akilagun, Shakeel, 2024, "Shakeel Gavioli-Akilagun's contribution to the discussion of the discussion meeting on probabilistic and statistical aspects of machine learning," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 121251, Apr.
- Daube, Carl Heinz & Krivenkov, Vladislav, 2024, "Generative AI Tools zur Prognose von Leitzins-Entscheidungen: eine Fallstudie am Beispiel der Leitzinsentscheidungen der Federal Reserve," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 293992.
- Nisarg Patel & Harmit Shah & Kishan Mewada, 2023, "Enhancing Financial Data Visualization for Investment Decision-Making," Papers, arXiv.org, number 2403.18822, Dec.
- Spurthi Setty & Harsh Thakkar & Alyssa Lee & Eden Chung & Natan Vidra, 2024, "Improving Retrieval for RAG based Question Answering Models on Financial Documents," Papers, arXiv.org, number 2404.07221, Mar, revised Jul 2024.
- Yanwei Jia, 2024, "Continuous-time Risk-sensitive Reinforcement Learning via Quadratic Variation Penalty," Papers, arXiv.org, number 2404.12598, Apr.
- Benjamin S. Manning & Kehang Zhu & John J. Horton, 2024, "Automated Social Science: Language Models as Scientist and Subjects," Papers, arXiv.org, number 2404.11794, Apr, revised Apr 2024.
- Lee, Wang-Sheng & Tran, Trang My, 2024, "Emissions from Military Training: Evidence from Australia," IZA Discussion Papers, Institute of Labor Economics (IZA), number 16889, Mar.
- Haotian Chen & Xinjie Shen & Zeqi Ye & Wenjun Feng & Haoxue Wang & Xiao Yang & Xu Yang & Weiqing Liu & Jiang Bian, 2024, "Towards Data-Centric Automatic R&D," Papers, arXiv.org, number 2404.11276, Apr, revised Jul 2024.
- Rei Iwafuchi & Yasumasa Matsuda, 2024, "Deep learning for multivariate volatility forecasting in high-dimensional financial time series," DSSR Discussion Papers, Graduate School of Economics and Management, Tohoku University, number 141, May.
- Marie Hogan & Aakash Kalyani, 2024, "AI and Productivity Growth: Evidence from Historical Developments in Other Technologies," On the Economy, Federal Reserve Bank of St. Louis, number 98109, Apr.
- R. Michael Alvarez & Jacob Morrier, 2024, "Measuring the Quality of Answers in Political Q&As with Large Language Models," Papers, arXiv.org, number 2404.08816, Apr, revised Feb 2025.