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Report NEP-BIG-2025-06-16
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:
- Antonicelli, Margareth & Drago, Carlo & Costantiello, Alberto & Leogrande, Angelo, 2025, "Analyzing Income Inequalities across Italian regions: Instrumental Variable Panel Data, K-Means Clustering and Machine Learning Algorithms," OSF Preprints, Center for Open Science, number tk87m_v1, Jun, DOI: 10.31219/osf.io/tk87m_v1.
- Md. Yeasin Rahat & Rajan Das Gupta & Nur Raisa Rahman & Sudipto Roy Pritom & Samiur Rahman Shakir & Md Imrul Hasan Showmick & Md. Jakir Hossen, 2025, "Advancing Exchange Rate Forecasting: Leveraging Machine Learning and AI for Enhanced Accuracy in Global Financial Markets," Papers, arXiv.org, number 2506.09851, Jun, revised Mar 2026.
- Dominik Stempie'n & Robert 'Slepaczuk, 2025, "Hybrid Models for Financial Forecasting: Combining Econometric, Machine Learning, and Deep Learning Models," Papers, arXiv.org, number 2505.19617, May.
- Dominik Stempie'n & Janusz Gajda, 2025, "Comparative analysis of financial data differentiation techniques using LSTM neural network," Papers, arXiv.org, number 2505.19243, May.
- Syoiti Ninomiya & Yuming Ma, 2025, "A new architecture of high-order deep neural networks that learn martingales," Papers, arXiv.org, number 2505.03789, May, revised Jun 2025.
- Maximilian Andres & Lisa Bruttel, 2025, "Communication and collusion in oligopoly experiments: A meta-study using machine learning," CEPA Discussion Papers, Center for Economic Policy Analysis, number 88, Jun, DOI: 10.25932/publishup-68013.
- Drago, Carlo & Costantiello, Alberto & Savorgnan, Marco & Leogrande, Angelo, 2025, "Driving AI Adoption in the EU: A Quantitative Analysis of Macroeconomic Influences," MPRA Paper, University Library of Munich, Germany, number 124973, Jun.
- Jiahao Yang & Ran Fang & Ming Zhang & Jun Zhou, 2025, "An Efficient deep learning model to Predict Stock Price Movement Based on Limit Order Book," Papers, arXiv.org, number 2505.22678, May.
- Pierre Brugi`ere & Gabriel Turinici, 2025, "Model-Free Deep Hedging with Transaction Costs and Light Data Requirements," Papers, arXiv.org, number 2505.22836, May.
- Queiroz, Rafael L. & Martins, Joberto S. B. Prof. Dr., 2024, "Low-Code Strategy with Machine Learning for the Healthcare Area: Assessing the Correlation of Occupational Activity with the Incidence of Cancer in Brazil," SocArXiv, Center for Open Science, number 9wsqn_v1, Oct, DOI: 10.31219/osf.io/9wsqn_v1.
- Geyue Sun & Xiao Liu & Tomas Williams & Roberto Samaniego, 2025, "Learning to Regulate: A New Event-Level Dataset of Capital Control Measures," Papers, arXiv.org, number 2505.23025, May.
- Lucien Chaffa & Martin Trépanier & Thierry Warin, 2025, "Beyond PPML: Exploring Machine Learning Alternatives for Gravity Model Estimation in International Trade," CIRANO Working Papers, CIRANO, number 2025s-14, May.
- Chung I Lu & Julian Sester & Aijia Zhang, 2025, "Distributionally Robust Deep Q-Learning," Papers, arXiv.org, number 2505.19058, May.
- Jasper Rou, 2025, "Error Analysis of Deep PDE Solvers for Option Pricing," Papers, arXiv.org, number 2505.05121, May.
- Kizilirmak, Jasmin M. & Peter, Frauke, 2025, "What influences the time to reach a tenured university professorship? Insights from machine-learning," SocArXiv, Center for Open Science, number khfgj_v1, May, DOI: 10.31219/osf.io/khfgj_v1.
- Agam Shah & Siddhant Sukhani & Huzaifa Pardawala & Saketh Budideti & Riya Bhadani & Rudra Gopal & Siddhartha Somani & Rutwik Routu & Michael Galarnyk & Soungmin Lee & Arnav Hiray & Akshar Ravichandran, 2025, "Words That Unite The World: A Unified Framework for Deciphering Central Bank Communications Globally," Papers, arXiv.org, number 2505.17048, May, revised Nov 2025.
- Francesco Morri & H'el`ene Le Cadre & Pierre Gruet & Luce Brotcorne, 2025, "Game Theory and Multi-Agent Reinforcement Learning for Zonal Ancillary Markets," Papers, arXiv.org, number 2505.03288, May, revised Nov 2025.
- Jiaxiang Chen & Mingxi Zou & Zhuo Wang & Qifan Wang & Dongning Sun & Chi Zhang & Zenglin Xu, 2025, "FinHEAR: Human Expertise and Adaptive Risk-Aware Temporal Reasoning for Financial Decision-Making," Papers, arXiv.org, number 2506.09080, Jun, revised Oct 2025.
- Lijie Ding & Egang Lu & Kin Cheung, 2025, "Fast Derivative Valuation from Volatility Surfaces using Machine Learning," Papers, arXiv.org, number 2505.22957, May.
- Zikun Ye & Hema Yoganarasimhan, 2025, "Fair Document Valuation in LLM Summaries via Shapley Values," Papers, arXiv.org, number 2505.23842, May, revised Jan 2026.
- Stephen J. Lee & Cailinn Drouin, 2025, "Forecasting Residential Heating and Electricity Demand with Scalable, High-Resolution, Open-Source Models," Papers, arXiv.org, number 2505.22873, May.
- Hinrichs, Nicolás & Hartwigsen, Gesa & Guzman, Noah, 2025, "Detecting Phase Transitions in EEG Hyperscanning Networks Using Geometric Markers," OSF Preprints, Center for Open Science, number abx8u_v1, Jun, DOI: 10.31219/osf.io/abx8u_v1.
- Daniel F. Villarraga & Ricardo A. Daziano, 2025, "Bayesian Deep Learning for Discrete Choice," Papers, arXiv.org, number 2505.18077, May, revised Dec 2025.