Report NEP-BIG-2025-10-20

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé 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:

• Yun Lin & Jiawei Lou & Jinghe Zhang, 2025. "From Headlines to Holdings: Deep Learning for Smarter Portfolio Decisions," Papers 2509.24144, arXiv.org.
• Saeid Mashhadi & Amirhossein Saghezchi & Vesal Ghassemzadeh Kashani, 2025. "Interpretable Machine Learning for Predicting Startup Funding, Patenting, and Exits," Papers 2510.09465, arXiv.org.
• Yun Zhao & Harry Zheng, 2025. "Neural Network Convergence for Variational Inequalities," Papers 2509.26535, arXiv.org, revised Oct 2025.
• Marlon Azinovic-Yang & Jan v{Z}emliv{c}ka, 2025. "Deep Learning in the Sequence Space," Papers 2509.13623, arXiv.org.
• Zheng Cao & Xingran Shao & Yuheng Yan & Helyette Geman, 2025. "Identifying and Quantifying Financial Bubbles with the Hyped Log-Periodic Power Law Model," Papers 2510.10878, arXiv.org.
• Mingqian Guan & Komei Fujita & Naoya Sueishi & Shota Yasui, 2025. "Denoised IPW-Lasso for Heterogeneous Treatment Effect Estimation in Randomized Experiments," Papers 2510.10527, arXiv.org.
• Marcos Delprato, 2025. "Determinants of Latin American students academic resilience-Insights based on PISA 2022 using an explainable machine learning approach," Papers 2509.24830, arXiv.org.
• Zofia Bracha & Pawe{l} Sakowski & Jakub Micha'nk'ow, 2025. "Application of Deep Reinforcement Learning to At-the-Money S&P 500 Options Hedging," Papers 2510.09247, arXiv.org.
• Ta-Chung Chi & Ting-Han Fan & Raffaele M. Ghigliazza & Domenico Giannone & Zixuan & Wang, 2025. "Macroeconomic Forecasting and Machine Learning," Papers 2510.11008, arXiv.org.
• Yilie Huang, 2025. "Continuous-Time Reinforcement Learning for Asset-Liability Management," Papers 2509.23280, arXiv.org.
• Mehmet Caner Qingliang Fan, 2025. "A Practitioner's Guide to AI+ML in Portfolio Investing," Papers 2509.25456, arXiv.org.
• Ross Koval & Nicholas Andrews & Xifeng Yan, 2025. "Multimodal Language Models with Modality-Specific Experts for Financial Forecasting from Interleaved Sequences of Text and Time Series," Papers 2509.19628, arXiv.org.
• Haochuan & Wang, 2025. "Forecasting Liquidity Withdraw with Machine Learning Models," Papers 2509.22985, arXiv.org.
• Philipp Bach & Victor Chernozhukov & Carlos Cinelli & Lin Jia & Sven Klaassen & Nils Skotara & Martin Spindler, 2025. "Sensitivity Analysis for Causal ML: A Use Case at Booking.com," Papers 2510.09109, arXiv.org.
• Mohammad Hassan Shakil & Arne Johan Pollestad & Khine Kyaw & Ziaul Haque Munim, 2025. "Board Gender Diversity and Carbon Emissions Performance: Insights from Panel Regressions, Machine Learning and Explainable AI," Papers 2510.00244, arXiv.org.
• Taejin Park & Fernando Perez-Cruz & Hyun Song Shin, 2025. "Mapping the space of central bankers' ideas," BIS Working Papers 1299, Bank for International Settlements.
• Ahad Yaqoob & Syed M. Abdullah, 2025. "Predictive Performance of LSTM Networks on Sectoral Stocks in an Emerging Market: A Case Study of the Pakistan Stock Exchange," Papers 2509.14401, arXiv.org.
• Shanjukta Nath & Jiwon Hong & Jae Ho Chang & Keith Warren & Subhadeep Paul, 2025. "Recidivism and Peer Influence with LLM Text Embeddings in Low Security Correctional Facilities," Papers 2509.20634, arXiv.org, revised Jan 2026.
• George Gui & Seungwoo Kim, 2025. "Leveraging LLMs to Improve Experimental Design: A Generative Stratification Approach," Papers 2509.25709, arXiv.org.
• Yuntao Wu & Ege Mert Akin & Charles Martineau & Vincent Gr'egoire & Andreas Veneris, 2025. "Extracting the Structure of Press Releases for Predicting Earnings Announcement Returns," Papers 2509.24254, arXiv.org, revised Oct 2025.
• Dimitrios Anastasiou & Apostolos G. Katsafados & Steven Ongena & Christos Tzomakas, 2025. "Beyond Words: Fed Chairs' Voice Sentiments and US Bank Stock Price Crash Risk," Swiss Finance Institute Research Paper Series 25-72, Swiss Finance Institute.