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 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:

• 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 tk87m_v1, Center for Open Science.
• 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 2506.09851, arXiv.org.
• Dominik Stempie'n & Robert 'Slepaczuk, 2025. "Hybrid Models for Financial Forecasting: Combining Econometric, Machine Learning, and Deep Learning Models," Papers 2505.19617, arXiv.org.
• Dominik Stempie'n & Janusz Gajda, 2025. "Comparative analysis of financial data differentiation techniques using LSTM neural network," Papers 2505.19243, arXiv.org.
• Syoiti Ninomiya & Yuming Ma, 2025. "A new architecture of high-order deep neural networks that learn martingales," Papers 2505.03789, arXiv.org, revised Jun 2025.
• Maximilian Andres & Lisa Bruttel, 2025. "Communication and collusion in oligopoly experiments: A meta-study using machine learning," CEPA Discussion Papers 88, Center for Economic Policy Analysis.
• Drago, Carlo & Costantiello, Alberto & Savorgnan, Marco & Leogrande, Angelo, 2025. "Driving AI Adoption in the EU: A Quantitative Analysis of Macroeconomic Influences," MPRA Paper 124973, University Library of Munich, Germany.
• 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 2505.22678, arXiv.org.
• Pierre Brugi`ere & Gabriel Turinici, 2025. "Model-Free Deep Hedging with Transaction Costs and Light Data Requirements," Papers 2505.22836, arXiv.org.
• 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 9wsqn_v1, Center for Open Science.
• Geyue Sun & Xiao Liu & Tomas Williams & Roberto Samaniego, 2025. "Learning to Regulate: A New Event-Level Dataset of Capital Control Measures," Papers 2505.23025, arXiv.org.
• Lucien Chaffa & Martin Trépanier & Thierry Warin, 2025. "Beyond PPML: Exploring Machine Learning Alternatives for Gravity Model Estimation in International Trade," CIRANO Working Papers 2025s-14, CIRANO.
• Chung I Lu & Julian Sester & Aijia Zhang, 2025. "Distributionally Robust Deep Q-Learning," Papers 2505.19058, arXiv.org.
• Jasper Rou, 2025. "Error Analysis of Deep PDE Solvers for Option Pricing," Papers 2505.05121, arXiv.org.
• Kizilirmak, Jasmin M. & Peter, Frauke, 2025. "What influences the time to reach a tenured university professorship? Insights from machine-learning," SocArXiv khfgj_v1, Center for Open Science.
• Agam Shah & Siddhant Sukhani & Huzaifa Pardawala & Saketh Budideti & Riya Bhadani & Rudra Gopal & Siddhartha Somani & Michael Galarnyk & Soungmin Lee & Arnav Hiray & Akshar Ravichandran & Eric Kim & P, 2025. "Words That Unite The World: A Unified Framework for Deciphering Central Bank Communications Globally," Papers 2505.17048, arXiv.org.
• Francesco Morri & H'el`ene Le Cadre & Pierre Gruet & Luce Brotcorne, 2025. "Nonconvex Game and Multi Agent Reinforcement Learning for Zonal Ancillary Markets," Papers 2505.03288, arXiv.org, revised Jun 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 2506.09080, arXiv.org.
• Lijie Ding & Egang Lu & Kin Cheung, 2025. "Fast Derivative Valuation from Volatility Surfaces using Machine Learning," Papers 2505.22957, arXiv.org.
• Zikun Ye & Hema Yoganarasimhan, 2025. "Document Valuation in LLM Summaries: A Cluster Shapley Approach," Papers 2505.23842, arXiv.org.
• Stephen J. Lee & Cailinn Drouin, 2025. "Forecasting Residential Heating and Electricity Demand with Scalable, High-Resolution, Open-Source Models," Papers 2505.22873, arXiv.org.
• Hinrichs, Nicolás & Hartwigsen, Gesa & Guzman, Noah, 2025. "Detecting Phase Transitions in EEG Hyperscanning Networks Using Geometric Markers," OSF Preprints abx8u_v1, Center for Open Science.
• Daniel F. Villarraga & Ricardo A. Daziano, 2025. "Bayesian Deep Learning for Discrete Choice," Papers 2505.18077, arXiv.org.