Report NEP-BIG-2025-09-01

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.

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Other reports in NEP-BIG

The following items were announced in this report:

• David Imhof & Emanuel W Viklund & Martin Huber, 2025. "Catching Bid-rigging Cartels with Graph Attention Neural Networks," Papers 2507.12369, arXiv.org, revised Jul 2025.
• Jieyu Chen & Sebastian Lerch & Melanie Schienle & Tomasz Serafin & Rafal Weron, 2025. "Probabilistic intraday electricity price forecasting using generative machine learning," WORking papers in Management Science (WORMS) WORMS/25/05, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Daniele Ballinari & Jessica Maly, 2025. "FX sentiment analysis with large language models," Working Papers 2025-11, Swiss National Bank.
• Gambara, Matteo & Livieri, Giulia & Pallavicini, Andrea, 2025. "Machine-learning regression methods for American-style path-dependent contracts," LSE Research Online Documents on Economics 128600, London School of Economics and Political Science, LSE Library.
• Rehim Kılıç, 2025. "Linear and nonlinear econometric models against machine learning models: realized volatility prediction," Finance and Economics Discussion Series 2025-061, Board of Governors of the Federal Reserve System (U.S.).
• Jeremy Proz & Martin Huber, 2025. "Machine Learning for Detecting Collusion and Capacity Withholding in Wholesale Electricity Markets," Papers 2508.09885, arXiv.org.
• Chenghao Liu & Aniket Mahanti & Ranesh Naha & Guanghao Wang & Erwann Sbai, 2025. "Enhancing Cryptocurrency Sentiment Analysis with Multimodal Features," Papers 2508.15825, arXiv.org, revised Aug 2025.
• Arkadiusz Lipiecki & Kaja Bilinska & Nikolaos Kourentzes & Rafal Weron, 2025. "Stealing accuracy: Predicting day-ahead electricity prices with Temporal Hierarchy Forecasting (THieF)," WORking papers in Management Science (WORMS) WORMS/25/06, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
• Ivan Letteri, 2025. "A Comparative Analysis of Statistical and Machine Learning Models for Outlier Detection in Bitcoin Limit Order Books," Papers 2507.14960, arXiv.org.
• Yueyi Wang & Qiyao Wei, 2025. "Event-Aware Sentiment Factors from LLM-Augmented Financial Tweets: A Transparent Framework for Interpretable Quant Trading," Papers 2508.07408, arXiv.org.
• Askitas, Nikos, 2025. "The Behavioral Signature of GenAI in Scientific Communication," IZA Discussion Papers 18062, Institute of Labor Economics (IZA).
• Jinbo Cai & Wenze Li & Wenjie Wang, 2025. "Electricity Market Predictability: Virtues of Machine Learning and Links to the Macroeconomy," Papers 2507.07477, arXiv.org.
• Dixon Domfeh & Saeid Safarveisi, 2025. "CATNet: A geometric deep learning approach for CAT bond spread prediction in the primary market," Papers 2508.10208, arXiv.org.
• Guilherme V. Moura & Andr'e P. Santos & Hudson S. Torrent, 2025. "Variable selection for minimum-variance portfolios," Papers 2508.14986, arXiv.org.
• Vidya Sagar G & Shifat Ali & Siddhartha P. Chakrabarty, 2025. "Machine Learning Based Stress Testing Framework for Indian Financial Market Portfolios," Papers 2507.02011, arXiv.org.
• Tianjiao Zhao & Jingrao Lyu & Stokes Jones & Harrison Garber & Stefano Pasquali & Dhagash Mehta, 2025. "AlphaAgents: Large Language Model based Multi-Agents for Equity Portfolio Constructions," Papers 2508.11152, arXiv.org.
• Cathy Yi‐Hsuan Chen & Abraham Lioui & O. Scaillet, 2025. "Green Silence: Double Machine Learning Carbon Emissions Under Sample Selection Bias," Swiss Finance Institute Research Paper Series 25-66, Swiss Finance Institute.
• Igor Halperin, 2025. "Prompt-Response Semantic Divergence Metrics for Faithfulness Hallucination and Misalignment Detection in Large Language Models," Papers 2508.10192, arXiv.org.
• Yuqi Luan, 2025. "Deep Learning for Short Term Equity Trend Forecasting: A Behavior Driven Multi Factor Approach," Papers 2508.14656, arXiv.org.
• Diego Vallarino, 2025. "Adaptive Market Intelligence: A Mixture of Experts Framework for Volatility-Sensitive Stock Forecasting," Papers 2508.02686, arXiv.org.
• Ca' Zorzi, Michele & Manu, Ana-Simona & Lopardo, Gianluigi, 2025. "Verba volant, transcripta manent: what corporate earnings calls reveal about the AI stock rally," Working Paper Series 3093, European Central Bank.
• Aryan Varshney & Venkat Ram Reddy Ganuthula, 2025. "Signal or Noise? Evaluating Large Language Models in Resume Screening Across Contextual Variations and Human Expert Benchmarks," Papers 2507.08019, arXiv.org.
• Orhan Erdem & Ragavi Pobbathi Ashok, 2025. "Artificial Finance: How AI Thinks About Money," Papers 2507.10933, arXiv.org.
• Lapo Santarlasci & Armando Rungi & Antonio Zinilli, 2025. "Seeing Through Green: Text-Based Classification and the Firm's Returns from Green Patents," Papers 2507.02287, arXiv.org.
• Dimitrios Emmanoulopoulos & Ollie Olby & Justin Lyon & Namid R. Stillman, 2025. "To Trade or Not to Trade: An Agentic Approach to Estimating Market Risk Improves Trading Decisions," Papers 2507.08584, arXiv.org.
• Qizhao Chen, 2025. "Sentiment-Aware Mean-Variance Portfolio Optimization for Cryptocurrencies," Papers 2508.16378, arXiv.org.