Report NEP-BIG-2025-09-15

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.

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Other reports in NEP-BIG

The following items were announced in this report:

• Fiona Xiao Jingyi & Lili Liu, 2025, "Can We Reliably Predict the Fed's Next Move? A Multi-Modal Approach to U.S. Monetary Policy Forecasting," Papers, arXiv.org, number 2506.22763, Jun.
• Gorjian, Mahshid, 2025, "Integrating Machine Learning and Hedonic Regression for Housing Price Prediction: A Systematic International Review of Model Performance and Interpretability," MPRA Paper, University Library of Munich, Germany, number 125676.
• Nicholas Gray & Finn Lattimore & Kate McLoughlin & Callan Windsor, 2025, "An AI-powered Tool for Central Bank Business Liaisons: Quantitative Indicators and On-demand Insights from Firms," Papers, arXiv.org, number 2506.18505, Jun.
• Yating Ru & Elizabeth Tennant & David Matteson & Christopher Barrett, 2025, "Spatial Heterogeneity in Machine Learning-Based Poverty Mapping: Where Do Models Underperform?," ADB Economics Working Paper Series, Asian Development Bank, number 798, Sep.
• Linh Nguyen & Marcel Boersma & Erman Acar, 2025, "Detecting Fraud in Financial Networks: A Semi-Supervised GNN Approach with Granger-Causal Explanations," Papers, arXiv.org, number 2507.01980, Jun.
• Paulo Andr'e Lima de Castro, 2025, "AlphaX: An AI-Based Value Investing Strategy for the Brazilian Stock Market," Papers, arXiv.org, number 2508.13429, Aug.
• Boris Kriuk & Logic Ng & Zarif Al Hossain, 2025, "DeepSupp: Attention-Driven Correlation Pattern Analysis for Dynamic Time Series Support and Resistance Levels Identification," Papers, arXiv.org, number 2507.01971, Jun.
• Jakub Micha'nk'ow, 2025, "Forecasting Probability Distributions of Financial Returns with Deep Neural Networks," Papers, arXiv.org, number 2508.18921, Aug, revised Aug 2025.
• Jonathan Garita-Garita & César Ulate-Sancho, 2025, "Forecasting Nominal Exchange Rate using Deep Neural Networks," Documentos de Trabajo, Banco Central de Costa Rica, number 2505, Jul.
• Ryan Samson & Adrian Banner & Luca Candelori & Sebastien Cottrell & Tiziana Di Matteo & Paul Duchnowski & Vahagn Kirakosyan & Jose Marques & Kharen Musaelian & Stefano Pasquali & Ryan Stever & Dario V, 2025, "Supervised Similarity for Firm Linkages," Papers, arXiv.org, number 2506.19856, Jun.
• Jonathan Benchimol & Sophia Kazinnik & Yossi Saadon, 2025, "Federal Reserve Communication and the COVID‐19 Pandemic," Post-Print, HAL, number hal-05203069, Sep, DOI: 10.1111/manc.12520.
• Ayato Kitadai & Yusuke Fukasawa & Nariaki Nishino, 2025, "Bias-Adjusted LLM Agents for Human-Like Decision-Making via Behavioral Economics," Papers, arXiv.org, number 2508.18600, Aug.
• Alper Deniz Karakas, 2025, "The Persistent Effects of Peru's Mining MITA: Double Machine Learning Approach," Papers, arXiv.org, number 2506.18947, Jun.
• Irina G. Tanashkina & Alexey S. Tanashkin & Alexander S. Maksimchuik & Anna Yu. Poshivailo, 2025, "Modern approaches to building interpretable models of the property market using machine learning on the base of mass cadastral valuation," Papers, arXiv.org, number 2506.15723, Jun, revised Jul 2025.
• Kai-Robin Lange & Tobias Schmidt & Matthias Reccius & Henrik Muller & Michael Roos & Carsten Jentsch, 2025, "Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models," Papers, arXiv.org, number 2506.20269, Jun.
• Sedigheh Mahdavi & Jiating & Chen & Pradeep Kumar Joshi & Lina Huertas Guativa & Upmanyu Singh, 2025, "Integrating Large Language Models in Financial Investments and Market Analysis: A Survey," Papers, arXiv.org, number 2507.01990, Jun.
• Ho Ming Lee & Katrien Antonio & Benjamin Avanzi & Lorenzo Marchi & Rui Zhou, 2025, "Machine Learning with Multitype Protected Attributes: Intersectional Fairness through Regularisation," Papers, arXiv.org, number 2509.08163, Sep, revised Oct 2025.
• Paloma Mar'in & Sergio Ardanza-Trevijano & Javier Sabio, 2025, "Causal Interventions in Bond Multi-Dealer-to-Client Platforms," Papers, arXiv.org, number 2506.18147, Jun, revised Oct 2025.
• Muhammad Bilal Zafar, 2025, "FinAI-BERT: A Transformer-Based Model for Sentence-Level Detection of AI Disclosures in Financial Reports," Papers, arXiv.org, number 2507.01991, Jun.
• Pesce, Simone & Errico, Marco & Pollio, Luigi, 2025, "Nonlinearities and heterogeneity in firms response to aggregate fluctuations: what can we learn from machine learning?," Working Paper Series, European Central Bank, number 3107, Sep.
• Shrenik Jadhav & Birva Sevak & Srijita Das & Akhtar Hussain & Wencong Su & Van-Hai Bui, 2025, "FairMarket-RL: LLM-Guided Fairness Shaping for Multi-Agent Reinforcement Learning in Peer-to-Peer Markets," Papers, arXiv.org, number 2506.22708, Jun.
• Alessio Brini & David A. Hsieh & Patrick Kuiper & Sean Moushegian & David Ye, 2025, "Empirical Models of the Time Evolution of SPX Option Prices," Papers, arXiv.org, number 2506.17511, Jun.
• Giorgos Demosthenous & Chryssis Georgiou & Eliada Polydorou, 2025, "From On-chain to Macro: Assessing the Importance of Data Source Diversity in Cryptocurrency Market Forecasting," Papers, arXiv.org, number 2506.21246, Jun.
• Yanlong Wang & Jian Xu & Fei Ma & Hongkang Zhang & Hang Yu & Tiantian Gao & Yu Wang & Haochen You & Shao-Lun Huang & Danny Dongning Sun & Xiao-Ping Zhang, 2025, "FinZero: Launching Multi-modal Financial Time Series Forecast with Large Reasoning Model," Papers, arXiv.org, number 2509.08742, Sep.
• Chi-Sheng Chen & Xinyu Zhang & Ya-Chuan Chen, 2025, "Quantum Reinforcement Learning Trading Agent for Sector Rotation in the Taiwan Stock Market," Papers, arXiv.org, number 2506.20930, Jun, revised Oct 2025.
• Sebastien Gallet & Julja Prodani, 2025, "Federated Modelling: A new framework and an application to system-wide stress testing," Occasional Studies, DNB, number 2503, Aug.
• Kerstin Bernoth, 2025, "Dovish Coos or Hawkish Screech? From Central Bank Talk to Economic Walk," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 2137.
• Umberto Collodel, 2025, "Interpreting the Interpreter: Can We Model post-ECB Conferences Volatility with LLM Agents?," Papers, arXiv.org, number 2508.13635, Aug, revised Oct 2025.
• Ziyao Wang & Svetlozar T Rachev, 2025, "Neural L\'evy SDE for State--Dependent Risk and Density Forecasting," Papers, arXiv.org, number 2509.01041, Aug.

Report NEP-BIG-2025-09-15

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: