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Report NEP-CMP-2024-02-26
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:
- Mestiri, Sami, 2023, "How to use machine learning in finance," MPRA Paper, University Library of Munich, Germany, number 120045, Oct.
- d’Aspremont, Alexandre & Arous, Simon Ben & Bricongne, Jean-Charles & Lietti, Benjamin & Meunier, Baptiste, 2024, "Satellites turn “concrete”: tracking cement with satellite data and neural networks," Working Paper Series, European Central Bank, number 2900, Jan.
- Tanmay Ghosh & Nithin Nagaraj, 2024, "Evaluating the Determinants of Mode Choice Using Statistical and Machine Learning Techniques in the Indian Megacity of Bengaluru," Papers, arXiv.org, number 2401.13977, Jan.
- Andrew Ye & James Xu & Vidyut Veedgav & Yi Wang & Yifan Yu & Daniel Yan & Ryan Chen & Vipin Chaudhary & Shuai Xu, 2024, "Learning the Market: Sentiment-Based Ensemble Trading Agents," Papers, arXiv.org, number 2402.01441, Feb, revised Nov 2024.
- Valentina Aparicio & Daniel Gordon & Sebastian G. Huayamares & Yuhuai Luo, 2024, "BioFinBERT: Finetuning Large Language Models (LLMs) to Analyze Sentiment of Press Releases and Financial Text Around Inflection Points of Biotech Stocks," Papers, arXiv.org, number 2401.11011, Jan.
- Bryan T. Kelly & Boris Kuznetsov & Semyon Malamud & Teng Andrea Xu, 2023, "Large (and Deep) Factor Models," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 23-121, Dec.
- F. Bolivar & M. A. Duran & A. Lozano-Vivas, 2024, "Bank Business Models, Size, and Profitability," Papers, arXiv.org, number 2401.12323, Jan.
- Shubham Singh & Mayur Bhat, 2024, "Transformer-based approach for Ethereum Price Prediction Using Crosscurrency correlation and Sentiment Analysis," Papers, arXiv.org, number 2401.08077, Jan.
- Nora Bearth & Michael Lechner, 2024, "Causal Machine Learning for Moderation Effects," Papers, arXiv.org, number 2401.08290, Jan, revised Jan 2025.
- O. Didkovskyi & N. Jean & G. Le Pera & C. Nordio, 2024, "Cross-Domain Behavioral Credit Modeling: transferability from private to central data," Papers, arXiv.org, number 2401.09778, Jan.
- Henri Arno & Klaas Mulier & Joke Baeck & Thomas Demeester, 2024, "From Numbers to Words: Multi-Modal Bankruptcy Prediction Using the ECL Dataset," Papers, arXiv.org, number 2401.12652, Jan.
- Busch, Malte & Duwe, Daniel, 2023, "Artificial intelligence in innovation processes. A study using the example of an innvation research institute," EconStor Research Reports, ZBW - Leibniz Information Centre for Economics, number 281981, DOI: 10.24406/publica-2314.
- Mathieu Chevrier & Brice Corgnet & Eric Guerci & Julie Rosaz, 2024, "Algorithm Credulity: Human and Algorithmic Advice in Prediction Experiments," GREDEG Working Papers, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France, number 2024-03, Feb, revised Dec 2024.
- João A. Bastos, 2023, "Conformal prediction of option prices," Working Papers REM, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa, number 2023/0304, Dec.
- Marie Obidzinski & Yves Oytana, 2024, "Artificial intelligence, inattention and liability rules," Working Papers, CRESE, number 2024-08, Feb.
- Anubha Goel & Damir Filipović & Puneet Pasricha, 2024, "Sparse Portfolio Selection via Topological Data Analysis based Clustering," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-07, Jan.
- Gmyrek, Pawel, & Lutz, Christoph, & Newlands, Gemma,, 2024, "A Technological Construction of Society comparing GPT-4 and human respondents for occupational evaluation in the UK," ILO Working Papers, International Labour Organization, number 995347793502676, DOI: 10.54394/UQOQ5153.
- Hannes Wallimann & Silvio Sticher, 2024, "How to Use Data Science in Economics -- a Classroom Game Based on Cartel Detection," Papers, arXiv.org, number 2401.14757, Jan.
- Lars Ericson & Xuejun Zhu & Xusi Han & Rao Fu & Shuang Li & Steve Guo & Ping Hu, 2024, "Deep Generative Modeling for Financial Time Series with Application in VaR: A Comparative Review," Papers, arXiv.org, number 2401.10370, Jan.