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Report NEP-BIG-2024-07-29
This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-BIG
The following items were announced in this report:
- Sang-Ha Yoon, 2024, "Developing an International Macroeconomic Forecasting Model Based on Big Data," World Economy Brief, Korea Institute for International Economic Policy, number 24-18, Jun.
- Yanqing Yang & Xingcheng Xu & Jinfeng Ge & Yan Xu, 2024, "Machine Learning for Economic Forecasting: An Application to China's GDP Growth," Papers, arXiv.org, number 2407.03595, Jul.
- Sarra Ben Yahia & Jose Angel Garcia Sanchez & Rania Hentati Kaffel, 2024, "Impact of Sentiment analysis on Energy Sector Stock Prices : A FinBERT Approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers), HAL, number hal-04629569, Jun.
- Yuhui Jin, 2024, "GraphCNNpred: A stock market indices prediction using a Graph based deep learning system," Papers, arXiv.org, number 2407.03760, Jul, revised Jul 2024.
- Item repec:ags:aaea22:343836 is not listed on IDEAS anymore
- Item repec:ags:aaea22:343727 is not listed on IDEAS anymore
- Item repec:ags:aaea22:344016 is not listed on IDEAS anymore
- Raeid Saqur, 2024, "What Teaches Robots to Walk, Teaches Them to Trade too -- Regime Adaptive Execution using Informed Data and LLMs," Papers, arXiv.org, number 2406.15508, Jun.
- Zexing Xu & Linjun Zhang & Sitan Yang & Rasoul Etesami & Hanghang Tong & Huan Zhang & Jiawei Han, 2024, "F-FOMAML: GNN-Enhanced Meta-Learning for Peak Period Demand Forecasting with Proxy Data," Papers, arXiv.org, number 2406.16221, Jun.
- Bogdan Oancea, 2024, "Big data in economics," Papers, arXiv.org, number 2406.11913, Jun.
- Felderer, Barbara & Repke, Lydia & Weber, Wiebke & Schweisthal, jonas & Bothmann, Ludwig, 2024, "Predicting the Validity and Reliability of Survey Questions," OSF Preprints, Center for Open Science, number hkngd, Jun, DOI: 10.31219/osf.io/hkngd.
- Zuzanna Kostecka & Robert 'Slepaczuk, 2024, "Improving Realized LGD Approximation: A Novel Framework with XGBoost for Handling Missing Cash-Flow Data," Papers, arXiv.org, number 2406.17308, Jun.
- Adam Korniejczuk & Robert 'Slepaczuk, 2024, "Statistical arbitrage in multi-pair trading strategy based on graph clustering algorithms in US equities market," Papers, arXiv.org, number 2406.10695, Jun.
- Susan Athey & Herman Brunborg & Tianyu Du & Ayush Kanodia & Keyon Vafa, 2024, "LABOR-LLM: Language-Based Occupational Representations with Large Language Models," Papers, arXiv.org, number 2406.17972, Jun, revised Jan 2026.
- Khudri, Md Mohsan & Hussey, Andrew, 2024, "Breastfeeding and Child Development Outcomes across Early Childhood and Adolescence: Doubly Robust Estimation with Machine Learning," IZA Discussion Papers, IZA Network @ LISER, number 17080, Jun.
- Brevin Franklin & Emily Silcock & Abhishek Arora & Tom Bryan & Melissa Dell, 2024, "News Deja Vu: Connecting Past and Present with Semantic Search," Papers, arXiv.org, number 2406.15593, Jun, revised Dec 2024.
- Item repec:ags:aaea22:343814 is not listed on IDEAS anymore
- Orson Mengara, 2024, "Trading Devil: Robust backdoor attack via Stochastic investment models and Bayesian approach," Papers, arXiv.org, number 2406.10719, Jun, revised Apr 2025.
- Alexander Quispe & Rodrigo Grijalba, 2024, "Impact of the Availability of ChatGPT on Software Development: A Synthetic Difference in Differences Estimation using GitHub Data," Papers, arXiv.org, number 2406.11046, Jun.
- Feng Xu & Yan Yin & Xinyu Zhang & Tianyuan Liu & Shengyi Jiang & Zongzhang Zhang, 2024, "$\text{Alpha}^2$: Discovering Logical Formulaic Alphas using Deep Reinforcement Learning," Papers, arXiv.org, number 2406.16505, Jun, revised Jun 2024.
- Abhishek Arora & Emily Silcock & Leander Heldring & Melissa Dell, 2024, "Contrastive Entity Coreference and Disambiguation for Historical Texts," Papers, arXiv.org, number 2406.15576, Jun.