Report NEP-CMP-2025-10-13

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:

• Fabio Bagarello & Francesco Gargano & Polina Khrennikova, 2025, "From Classical Rationality to Contextual Reasoning: Quantum Logic as a New Frontier for Human-Centric AI in Finance," Papers, arXiv.org, number 2510.05475, Oct.
• Georgy Milyushkov, 2025, "Can Machine Learning Algorithms Outperform Traditional Models for Option Pricing?," Papers, arXiv.org, number 2510.01446, Oct.
• Nicolas Salvad'e & Tim Hillel, 2025, "Functional effects models: Accounting for preference heterogeneity in panel data with machine learning," Papers, arXiv.org, number 2509.18047, Sep.
• Antonios Stamatogiannakis & Arsham Ghodsinia & Sepehr Etminanrad & Dilney Gonc{c}alves & David Santos, 2025, "How human is the machine? Evidence from 66,000 Conversations with Large Language Models," Papers, arXiv.org, number 2510.07321, Aug.
• Luis Enriquez Alvarez, 2025, "An Artificial Intelligence Value at Risk Approach: Metrics and Models," Papers, arXiv.org, number 2509.18394, Sep.
• Albert Di Wang & Ye Du, 2025, "Minimizing the Value-at-Risk of Loan Portfolio via Deep Neural Networks," Papers, arXiv.org, number 2510.07444, Oct.
• Evan Heus & Rick Bookstaber & Dhruv Sharma, 2025, "Exploring Network-Knowledge Graph Duality: A Case Study in Agentic Supply Chain Risk Analysis," Papers, arXiv.org, number 2510.01115, Oct, revised Dec 2025.
• Himanshu Choudhary & Arishi Orra & Manoj Thakur, 2025, "Diffusion-Augmented Reinforcement Learning for Robust Portfolio Optimization under Stress Scenarios," Papers, arXiv.org, number 2510.07099, Oct.
• Byeungchun Kwon & Taejin Park & Phurichai Rungcharoenkitkul & Frank Smets, 2025, "Parsing the pulse: decomposing macroeconomic sentiment with LLMs," BIS Working Papers, Bank for International Settlements, number 1294, Oct.
• So Kuroki & Yingtao Tian & Kou Misaki & Takashi Ikegami & Takuya Akiba & Yujin Tang, 2025, "Reimagining Agent-based Modeling with Large Language Model Agents via Shachi," Papers, arXiv.org, number 2509.21862, Sep, revised Oct 2025.
• Yu Liu & Wenwen Li & Yifan Dou & Guangnan Ye, 2025, "When Machines Meet Each Other: Network Effects and the Strategic Role of History in Multi-Agent AI," Papers, arXiv.org, number 2510.06903, Oct.
• Anne Lundgaard Hansen & Seung Jung Lee, 2025, "Financial Stability Implications of Generative AI: Taming the Animal Spirits," Papers, arXiv.org, number 2510.01451, Oct.
• Lokesh Antony Kadiyala & Amir Mirzaeinia, 2025, "Mamba Outpaces Reformer in Stock Prediction with Sentiments from Top Ten LLMs," Papers, arXiv.org, number 2510.01203, Sep.
• Mengyu Wang & Sotirios Sabanis & Miguel de Carvalho & Shay B. Cohen & Tiejun Ma, 2025, "One More Question is Enough, Expert Question Decomposition (EQD) Model for Domain Quantitative Reasoning," Papers, arXiv.org, number 2510.01526, Oct.
• Kairan Hong & Jinling Gan & Qiushi Tian & Yanglinxuan Guo & Rui Guo & Runnan Li, 2025, "Multi-Agent Analysis of Off-Exchange Public Information for Cryptocurrency Market Trend Prediction," Papers, arXiv.org, number 2510.08268, Oct.
• Binqi Chen & Hongjun Ding & Ning Shen & Jinsheng Huang & Taian Guo & Luchen Liu & Ming Zhang, 2025, "AlphaSAGE: Structure-Aware Alpha Mining via GFlowNets for Robust Exploration," Papers, arXiv.org, number 2509.25055, Sep, revised Sep 2025.
• Ziv Ben-Zion & Zohar Elyoseph & Tobias Spiller & Teddy Lazebnik, 2025, "Inducing State Anxiety in LLM Agents Reproduces Human-Like Biases in Consumer Decision-Making," Papers, arXiv.org, number 2510.06222, Aug.
• Remi Genet & Hugo Inzirillo, 2025, "LEMs: A Primer On Large Execution Models," Papers, arXiv.org, number 2509.25211, Sep.
• Fabrizio Dimino & Abhinav Arun & Bhaskarjit Sarmah & Stefano Pasquali, 2025, "FinReflectKG - EvalBench: Benchmarking Financial KG with Multi-Dimensional Evaluation," Papers, arXiv.org, number 2510.05710, Oct.
• Xinrui Ruan & Xinwei Ma & Yingfei Wang & Waverly Wei & Jingshen Wang, 2025, "Can language models boost the power of randomized experiments without statistical bias?," Papers, arXiv.org, number 2510.05545, Oct, revised Dec 2025.
• Axel Ciceri & Austin Cottrell & Joshua Freeland & Daniel Fry & Hirotoshi Hirai & Philip Intallura & Hwajung Kang & Chee-Kong Lee & Abhijit Mitra & Kentaro Ohno & Das Pemmaraju & Manuel Proissl & Brian, 2025, "Enhanced fill probability estimates in institutional algorithmic bond trading using statistical learning algorithms with quantum computers," Papers, arXiv.org, number 2509.17715, Sep.
• Yanran Wu & Xinlei Zhang & Quanyi Xu & Qianxin Yang & Chao Zhang, 2025, "Predicting Credit Spreads and Ratings with Machine Learning: The Role of Non-Financial Data," Papers, arXiv.org, number 2509.19042, Sep.
• Fabrizio Dimino & Krati Saxena & Bhaskarjit Sarmah & Stefano Pasquali, 2025, "Uncovering Representation Bias for Investment Decisions in Open-Source Large Language Models," Papers, arXiv.org, number 2510.05702, Oct, revised Nov 2025.
• Shuto Endo & Takanobu Mizuta & Isao Yagi, 2025, "Analysis of the Impact of an Execution Algorithm with an Order Book Imbalance Strategy on a Financial Market Using an Agent-based Simulation," Papers, arXiv.org, number 2509.16912, Sep.
• Aadi Singhi, 2025, "An Adaptive Multi Agent Bitcoin Trading System," Papers, arXiv.org, number 2510.08068, Oct, revised Nov 2025.
• Jonathan Proctor & Tamma Carleton & Trinetta Chong & Taryn Fransen & Simon Greenhill & Jessica Katz & Hikari Murayama & Luke Sherman & Jeanette Tseng & Hannah Druckenmiller & Solomon Hsiang, 2025, "What Can Satellite Imagery and Machine Learning Measure?," NBER Working Papers, National Bureau of Economic Research, Inc, number 34315, Oct.
• Miguel Alves Pereira, 2025, "Predictive economics: Rethinking economic methodology with machine learning," Papers, arXiv.org, number 2510.04726, Oct.
• Weilong Fu, 2025, "The New Quant: A Survey of Large Language Models in Financial Prediction and Trading," Papers, arXiv.org, number 2510.05533, Oct.
• Marcos Delprato, 2025, "Private and public school efficiency gaps in Latin America-A combined DEA and machine learning approach based on PISA 2022," Papers, arXiv.org, number 2509.25353, Sep.
• Sid Ghatak & Arman Khaledian & Navid Parvini & Nariman Khaledian, 2025, "Increase Alpha: Performance and Risk of an AI-Driven Trading Framework," Papers, arXiv.org, number 2509.16707, Sep, revised Oct 2025.
• Makoto Naito & Taiga Saito & Akihiko Takahashi & Kohta Takehara, 2025, "Asymptotic expansions as control variates for deep solvers to fully-coupled forward-backward stochastic differential equations "Forthcoming in PLOS ONE"," CARF F-Series, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, number CARF-F-600, Mar.
• Kevin Kamm, 2025, "Joint Stochastic Optimal Control and Stopping in Aquaculture: Finite-Difference and PINN-Based Approaches," Papers, arXiv.org, number 2510.02910, Oct.
• Bertie Vidgen & Abby Fennelly & Evan Pinnix & Julien Benchek & Daniyal Khan & Zach Richards & Austin Bridges & Calix Huang & Kanishka Sahu & Abhishek Kottamasu & Bo Ma & Ben Hunsberger & Isaac Robinso, 2025, "The AI Productivity Index (APEX)," Papers, arXiv.org, number 2509.25721, Sep, revised Dec 2025.
• Riccardo Zanardelli, 2025, "Navigating the safe harbor paradox in human-machine systems," Papers, arXiv.org, number 2509.14057, Sep, revised Jan 2026.
• Abdelhafid Khazzar & Yassine Sekaki & Yasser Lachhab & Said El-marzouki, 2025, "Artificial Intelligence in Port Logistics: A Bibliometric Analysis of Technological Integration and Research Dynamics," Papers, arXiv.org, number 2510.06556, Oct.
• Pierre Dumont & Lorenzo Nicoletti & Marc Petit & Damien-Pierre Sainflou, 2025, "Why Virtual Mileage Can Threaten Vehicle-to-Grid," Post-Print, HAL, number hal-05294002, Jun.
• James R. Markusen, 2025, "Incorporating Non-Unitary Income Elasticities, Choke Prices and Choke Incomes into Applied General-Equilibrium Models," NBER Working Papers, National Bureau of Economic Research, Inc, number 34314, Oct.
• Neugebauer, Claudia & Mattern, Marcel, 2025, "Progressiver Einkommensteuertarif und Ehegattenbesteuerung - Simulationsanalyse alternativer Besteuerungskonzepte," Schumpeter Discussion Papers, Universitätsbibliothek Wuppertal, University Library, number sdp25001, Sep.
• Antonio Cozzolino & Cristina Gualdani & Ivan Gufler & Niccolò Lomys & Lorenzo Magnolfi, 2025, "Robust Identification in Repeated Games: An Empirical Approach to Algorithmic Competition," Working Papers, NET Institute, number 25-04, Sep.
• Jinho Cha & Long Pham & Thi Le Hoa Vo & Jaeyoung Cho & Jaejin Lee, 2025, "Inverse Portfolio Optimization with Synthetic Investor Data: Recovering Risk Preferences under Uncertainty," Papers, arXiv.org, number 2510.06986, Oct, revised Oct 2025.
• Farah Abdoune & Rasmus Andersen & Ann-Louise Andersen & Catherine da Cunha, 2025, "Cost estimation in the context of Manufacturing-as-a-Service," Post-Print, HAL, number hal-05288523, Jun, DOI: 10.1016/j.ifacol.2025.09.207.
• Esteban García-Miralles & Maximilian Freier & Sara Riscado & Chrysa Leventi & Alberto Mazzon & Glenn Abela & Laura Lehtonen & Laura Boyd & Baiba BrusbÄ rde & Marion Cochard & David Cornille & Emanuel, 2025, "Fiscal Drag in Theory and in Practice: a European Perspective," Working Papers, DNB, number 844, Oct.
• Jinho Cha & Eunchan D. Cha & Emily Yoo & Hyoshin Song, 2025, "Modeling ROI in Chronic Disease Management, A Simulation-Based Framework Integrating Patient Adherence and Policy Timing," Papers, arXiv.org, number 2510.06379, Oct.
• Shawn Berry, 2025, "Traffic jams and driver behavior archetypes," Papers, arXiv.org, number 2510.04740, Oct.
• Jinho Cha & Youngchul Kim & Junyeol Ryu & Sangjun Park & Jeongho Kang & Hyeyoung Hwang, 2025, "Smart Contract-Enabled Procurement under Bounded Demand Variability: A Truncated Normal Approach," Papers, arXiv.org, number 2510.07801, Oct.

Report NEP-CMP-2025-10-13

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: