Report NEP-CMP-2025-06-16

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stanley Miles issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-CMP

The following items were announced in this report:

• 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.
• Starobinsky, Mark, 2025, "Ontology-Enhanced AI: Redefining Trust and Adaptability in Artificial Intelligence," OSF Preprints, Center for Open Science, number fh4ue_v1, May, DOI: 10.31219/osf.io/fh4ue_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.
• Dominik Stempie'n & Janusz Gajda, 2025, "Comparative analysis of financial data differentiation techniques using LSTM neural network," Papers, arXiv.org, number 2505.19243, 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.
• 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.
• 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.
• Hariom Tatsat & Ariye Shater, 2025, "Beyond the Black Box: Interpretability of LLMs in Finance," Papers, arXiv.org, number 2505.24650, May.
• 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.
• 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.
• Jasper Rou, 2025, "Error Analysis of Deep PDE Solvers for Option Pricing," Papers, arXiv.org, number 2505.05121, May.
• Chung I Lu & Julian Sester & Aijia Zhang, 2025, "Distributionally Robust Deep Q-Learning," Papers, arXiv.org, number 2505.19058, May.
• Erfan Loghmani, 2025, "Aligning Language Models with Observational Data: Opportunities and Risks from a Causal Perspective," Papers, arXiv.org, number 2506.00152, May.
• 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.
• Shanyu Han & Yang Liu & Xiang Yu, 2025, "Risk-sensitive Reinforcement Learning Based on Convex Scoring Functions," Papers, arXiv.org, number 2505.04553, May, revised May 2025.
• 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.
• Olivier Toubia & George Z. Gui & Tianyi Peng & Daniel J. Merlau & Ang Li & Haozhe Chen, 2025, "Twin-2K-500: A dataset for building digital twins of over 2,000 people based on their answers to over 500 questions," Papers, arXiv.org, number 2505.17479, May.
• Schraml, Christopher, 2025, "Automated Video Analytics in Marketing Research: A Systematic Literature Review and a Novel Multimodal Large Language Model Method," OSF Preprints, Center for Open Science, number 63nbc_v1, May, DOI: 10.31219/osf.io/63nbc_v1.
• Joshua S. Gans, 2025, "Capability Inversion: The Turing Test Meets Information Design," NBER Working Papers, National Bureau of Economic Research, Inc, number 33893, Jun.
• Perin, Augusto O. & Castro, Hélder U. & Filho, Euclério B. O. & Martins, Joberto S. B. Prof. Dr., 2024, "Smart City in Contemporary Times with Internet of Things and Artificial Intelligence," SocArXiv, Center for Open Science, number r36yg_v1, Dec, DOI: 10.31219/osf.io/r36yg_v1.
• 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.
• Jianhao Lin & Lexuan Sun & Yixin Yan, 2025, "Simulating Macroeconomic Expectations using LLM Agents," Papers, arXiv.org, number 2505.17648, May, revised Nov 2025.
• Daniel F. Villarraga & Ricardo A. Daziano, 2025, "Bayesian Deep Learning for Discrete Choice," Papers, arXiv.org, number 2505.18077, May, revised Dec 2025.
• Jean-Paul Daemen & Silvia Leoni, 2025, "Simulating Tertiary Educational Decision Dynamics: An Agent-Based Model for the Netherlands," Papers, arXiv.org, number 2505.01142, May.
• Kristoffer Andersson & Alessandro Gnoatto & Camilo Andr'es Garc'ia Trillos, 2025, "A deep solver for backward stochastic Volterra integral equations," Papers, arXiv.org, number 2505.18297, May, revised Oct 2025.
• Shanyan Lai, 2025, "Multilayer Perceptron Neural Network Models in Asset Pricing: An Empirical Study on Large-Cap US Stocks," Papers, arXiv.org, number 2505.01921, May, revised May 2025.
• Alberto Cabezas & Carlotta Montorsi, 2025, "Life Sequence Transformer: Generative Modelling of Socio-Economic Trajectories from Administrative Data," Papers, arXiv.org, number 2506.01874, Jun, 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.
• Pascal Michaillat, 2025, "Recession Detection Using Classifiers on the Anticipation-Precision Frontier," Papers, arXiv.org, number 2506.09664, Jun, revised Dec 2025.

Report NEP-CMP-2025-06-16

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stanley Miles issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-CMP

The following items were announced in this report: