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Report NEP-BIG-2025-10-13
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:
- Georgy Milyushkov, 2025, "Can Machine Learning Algorithms Outperform Traditional Models for Option Pricing?," Papers, arXiv.org, number 2510.01446, Oct.
- Nicolas Salvad'e & Tim Hillel, 2025, "Functional effects models: Accounting for preference heterogeneity in panel data with machine learning," Papers, arXiv.org, number 2509.18047, Sep.
- Lokesh Antony Kadiyala & Amir Mirzaeinia, 2025, "Mamba Outpaces Reformer in Stock Prediction with Sentiments from Top Ten LLMs," Papers, arXiv.org, number 2510.01203, Sep.
- Jonathan Proctor & Tamma Carleton & Trinetta Chong & Taryn Fransen & Simon Greenhill & Jessica Katz & Hikari Murayama & Luke Sherman & Jeanette Tseng & Hannah Druckenmiller & Solomon Hsiang, 2025, "What Can Satellite Imagery and Machine Learning Measure?," NBER Working Papers, National Bureau of Economic Research, Inc, number 34315, Oct.
- Yanran Wu & Xinlei Zhang & Quanyi Xu & Qianxin Yang & Chao Zhang, 2025, "Predicting Credit Spreads and Ratings with Machine Learning: The Role of Non-Financial Data," Papers, arXiv.org, number 2509.19042, Sep.
- Byeungchun Kwon & Taejin Park & Phurichai Rungcharoenkitkul & Frank Smets, 2025, "Parsing the pulse: decomposing macroeconomic sentiment with LLMs," BIS Working Papers, Bank for International Settlements, number 1294, Oct.
- Kairan Hong & Jinling Gan & Qiushi Tian & Yanglinxuan Guo & Rui Guo & Runnan Li, 2025, "Multi-Agent Analysis of Off-Exchange Public Information for Cryptocurrency Market Trend Prediction," Papers, arXiv.org, number 2510.08268, Oct.
- Albert Di Wang & Ye Du, 2025, "Minimizing the Value-at-Risk of Loan Portfolio via Deep Neural Networks," Papers, arXiv.org, number 2510.07444, Oct.
- Marcos Delprato, 2025, "Cognitive and non-cognitive efficiency gaps between private and public schools in the Latin America region-a hybrid DEA and machine learning approach based on PISA 2022," Papers, arXiv.org, number 2509.25353, Sep, revised Mar 2026.
- Antonios Stamatogiannakis & Arsham Ghodsinia & Sepehr Etminanrad & Dilney Gonc{c}alves & David Santos, 2025, "How human is the machine? Evidence from 66,000 Conversations with Large Language Models," Papers, arXiv.org, number 2510.07321, Aug.
- Remi Genet & Hugo Inzirillo, 2025, "LEMs: A Primer On Large Execution Models," Papers, arXiv.org, number 2509.25211, Sep.
- Ziv Ben-Zion & Zohar Elyoseph & Tobias Spiller & Teddy Lazebnik, 2025, "Inducing State Anxiety in LLM Agents Reproduces Human-Like Biases in Consumer Decision-Making," Papers, arXiv.org, number 2510.06222, Aug.
- Alba, Charles, 2025, "Understanding sentiments and discourse surrounding the Make America Healthy Again (#MAHA) movement on social media with pre-trained language models," SocArXiv, Center for Open Science, number 2gsxq_v1, Oct, DOI: 10.31219/osf.io/2gsxq_v1.
- Jaeho Choi & Jaewon Kim & Seyoung Chung & Chae-shick Chung & Yoonsoo Lee, 2025, "Does FOMC Tone Really Matter? Statistical Evidence from Spectral Graph Network Analysis," Papers, arXiv.org, number 2510.02705, Oct.
- Avinash Kumar Singh & Bhaskarjit Sarmah & Stefano Pasquali, 2025, "FINCH: Financial Intelligence using Natural language for Contextualized SQL Handling," Papers, arXiv.org, number 2510.01887, Oct.
- Aadi Singhi, 2025, "An Adaptive Multi Agent Bitcoin Trading System," Papers, arXiv.org, number 2510.08068, Oct, revised Nov 2025.
- Anne Lundgaard Hansen & Seung Jung Lee, 2025, "Financial Stability Implications of Generative AI: Taming the Animal Spirits," Papers, arXiv.org, number 2510.01451, Oct.
- Sid Ghatak & Arman Khaledian & Navid Parvini & Nariman Khaledian, 2025, "Increase Alpha: Performance and Risk of an AI-Driven Trading Framework," Papers, arXiv.org, number 2509.16707, Sep, revised Oct 2025.
- Patrick J.F. Groenen & Michael Greenacre, 2025, "Interpretable Kernels," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1915, Sep.