Report NEP-CMP-2024-05-06
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.Subscribe to this report: email, RSS, or Mastodon.
Other reports in NEP-CMP
The following items were announced in this report:
- Hoang Hiep Nguyen & Jean-Laurent Viviani & Sami Ben Jabeur, 2023. "Bankruptcy prediction using machine learning and Shapley additive explanations," Post-Print hal-04223161, HAL.
- Javier Mancilla & Andr'e Sequeira & Tomas Tagliani & Francisco Llaneza & Claudio Beiza, 2024. "Empowering Credit Scoring Systems with Quantum-Enhanced Machine Learning," Papers 2404.00015, arXiv.org, revised Apr 2024.
- Jai Pal, 2024. "Long Short-Term Memory Pattern Recognition in Currency Trading," Papers 2403.18839, arXiv.org.
- Eva Lutkebohmert & Julian Sester, 2024. "Measuring Name Concentrations through Deep Learning," Papers 2403.16525, arXiv.org, revised Nov 2024.
- Denis Levchenko & Efstratios Rappos & Shabnam Ataee & Biagio Nigro & Stephan Robert-Nicoud, 2024. "Chain-structured neural architecture search for financial time series forecasting," Papers 2403.14695, arXiv.org, revised Dec 2024.
- Silvia Garc'ia-M'endez & Francisco de Arriba-P'erez & Ana Barros-Vila & Francisco J. Gonz'alez-Casta~no, 2024. "Detection of Temporality at Discourse Level on Financial News by Combining Natural Language Processing and Machine Learning," Papers 2404.01337, arXiv.org.
- Enmin Zhu & Jerome Yen, 2024. "BERTopic-Driven Stock Market Predictions: Unraveling Sentiment Insights," Papers 2404.02053, arXiv.org, revised Apr 2024.
- Gyungbae Park, 2024. "Debiased Machine Learning when Nuisance Parameters Appear in Indicator Functions," Papers 2403.15934, arXiv.org.
- Masanori Hirano, 2024. "Construction of a Japanese Financial Benchmark for Large Language Models," Papers 2403.15062, arXiv.org.
- Michele Costola & Bertrand Maillet & Zhining Yuan & Xiang Zhang, 2024. "Mean-Variance Efficient Large Portfolios : A Simple Machine Learning Heuristic Technique based on the Two-Fund Separation Theorem," Post-Print hal-04514343, HAL.
- Bartosz Bieganowski & Robert Slepaczuk, 2024. "Supervised Autoencoder MLP for Financial Time Series Forecasting," Papers 2404.01866, arXiv.org, revised Jun 2024.
- Nolan Alexander & William Scherer, 2024. "Using Machine Learning to Forecast Market Direction with Efficient Frontier Coefficients," Papers 2404.00825, arXiv.org.
- Lei Bill Wang & Om Prakash Bedant & Zhenbang Jiao & Haoran Wang, 2024. "From Friendship Networks to Classroom Dynamics: Leveraging Neural Networks, Instrumental Variable and Genetic Algorithms for Optimal Educational Outcomes," Papers 2404.02497, arXiv.org, revised Aug 2024.
- Stijn De Backer & Luis E. C. Rocha & Jan Ryckebusch & Koen Schoors, 2024. "On the potential of quantum walks for modeling financial return distributions," Papers 2403.19502, arXiv.org, revised Dec 2024.
- Francesco Catalano & Laura Nasello & Daniel Guterding, 2024. "Quantum computing approach to realistic ESG-friendly stock portfolios," Papers 2404.02582, arXiv.org.