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Report NEP-BIG-2024-02-12
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:
- Brahmana, Rayenda Khresna, 2022, "Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?," MPRA Paper, University Library of Munich, Germany, number 119598, Dec.
- Yue Chen & Xingyi Andrew & Salintip Supasanya, 2024, "CRISIS ALERT:Forecasting Stock Market Crisis Events Using Machine Learning Methods," Papers, arXiv.org, number 2401.06172, Jan.
- Shun Liu & Kexin Wu & Chufeng Jiang & Bin Huang & Danqing Ma, 2023, "Financial Time-Series Forecasting: Towards Synergizing Performance And Interpretability Within a Hybrid Machine Learning Approach," Papers, arXiv.org, number 2401.00534, Dec.
- Vetter, Oliver A. & Sturm, Timo & Fecho, Mariska & Buxmann, Peter, 2023, "Machine Learning Developments as Stimuli for Organizational Learning," 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 142034, Dec.
- Emmanuil H. Georgoulis & Antonis Papapantoleon & Costas Smaragdakis, 2024, "A deep implicit-explicit minimizing movement method for option pricing in jump-diffusion models," Papers, arXiv.org, number 2401.06740, Jan, revised Mar 2025.
- Drin, Svitlana, 2024, "Forecast model of the price of a product with a cold start," Working Papers, Örebro University, School of Business, number 2024:2, Jan.
- Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024, "Model Averaging and Double Machine Learning," Papers, arXiv.org, number 2401.01645, Jan, revised Sep 2024.
- Sara Slamić Tarade, 2023, "Discovering the Significance of Sports Footwear Brands through Text Analysis ," GATR Journals, Global Academy of Training and Research (GATR) Enterprise, number jmmr326, Dec, DOI: https://doi.org/10.35609/jmmr.2023..
- Zinuo You & Pengju Zhang & Jin Zheng & John Cartlidge, 2024, "Multi-relational Graph Diffusion Neural Network with Parallel Retention for Stock Trends Classification," Papers, arXiv.org, number 2401.05430, Jan.
- Alessio Brini & Giacomo Toscano, 2024, "SpotV2Net: Multivariate Intraday Spot Volatility Forecasting via Vol-of-Vol-Informed Graph Attention Networks," Papers, arXiv.org, number 2401.06249, Jan, revised Jan 2025.
- Haiyan Hao & Yan Wang, 2024, "A Deep Learning Representation of Spatial Interaction Model for Resilient Spatial Planning of Community Business Clusters," Papers, arXiv.org, number 2401.04849, Jan.
- Frank Xing, 2024, "Designing Heterogeneous LLM Agents for Financial Sentiment Analysis," Papers, arXiv.org, number 2401.05799, Jan.
- Khalil Liouane, 2024, "Follow The Money: Exploring the Key Factors Influencing Investment in African Startups," Papers, arXiv.org, number 2401.05760, Jan.
- Gal Amedi, 2023, "The Determinants of the Transit Accessibility Premium," Bank of Israel Working Papers, Bank of Israel, number 2023.12, Jun.
- Rametta, Jack T. & Fuller, Sam, 2024, "The Balance Permutation Test: A Machine Learning Replacement for Balance Tables," OSF Preprints, Center for Open Science, number xcwt9, Jan, DOI: 10.31219/osf.io/xcwt9.
- Ali Mehrban & Pegah Ahadian, 2024, "An adaptive network-based approach for advanced forecasting of cryptocurrency values," Papers, arXiv.org, number 2401.05441, Jan, revised Feb 2024.
- Baptiste Lefort & Eric Benhamou & Jean-Jacques Ohana & David Saltiel & Beatrice Guez & Damien Challet, 2024, "Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps?," Papers, arXiv.org, number 2401.05447, Jan.