Report NEP-CMP-2026-08-24

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.

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Other reports in NEP-CMP

The following items were announced in this report:

• Giorgos Iacovides & Wuyang Zhou & Danilo Mandic, 2026, "FinSMART: Financial Sentiment Analysis for Algorithmic Trading through Market-Aligned Reinforcement Learning," Papers, arXiv.org, number 2607.28127, Jul.
• Ash, Elliott & Hansen, Stephen & Muvdi, Yabra, 2024, "Large Language Models in Economics," CEPR Discussion Papers, Centre for Economic Policy Research, number 19479, Sep.
• Mukashov, Askar & Kim, Soonho & Fang, Peixun & Diao, Xinshen & Thurlow, James & Proctor, Joshua & Rennison, Alan, 2026, "An agentic AI assistant for country-level economic modeling: Methods, data, and expert evaluation," IFPRI discussion papers, International Food Policy Research Institute (IFPRI), number 2424, Jun.
• Qihui Chen & Ka Yan Cheng & Zheng Fang, 2026, "Debiased Machine Learning: Identification, Estimation, and Shape Constraints," Papers, arXiv.org, number 2607.24472, Jul, revised Jul 2026.
• Hauzenberger, Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2024, "Bayesian Neural Networks for Macroeconomic Analysis," CEPR Discussion Papers, Centre for Economic Policy Research, number 19381, Aug.
• Zane Shen & Xinli Xu & Guangyi Zhang & Jialong Chen & Jinsong Zhou & Cong Chen & Guibao Shen & Dongyu Yan & Luozhou Wang & Zhen Yang, 2026, "Can Large Language Models Execute Parent Orders?," Papers, arXiv.org, number 2607.28410, Jul.
• Guillaume Coqueret & Joan Llull & Florian Oswald & Christophe P'erignon & Christoph Scheuch & Lars Vilhuber, 2026, "Randomness in large language models: What researchers need to know (and report)," Papers, arXiv.org, number 2607.24372, Jul.
• Uehara, Masatoshi & Shi, Chengchun & Kallus, Nathan, 2026, "A review of off-policy evaluation in reinforcement learning," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 127940, Aug.
• Yuya Shimizu, 2026, "Econometrics with Pre-Trained Embeddings for Unstructured Data," Papers, arXiv.org, number 2607.17378, Jul.
• Travis L. Johnson & Jiannan Jiang & Soumyabrata Chaudhuri & Yihao Chen & Lauren Falvey & Donal O'Cofaigh, 2026, "Long-Horizon Forecasting of Complete Financial Statements with Forma," Papers, arXiv.org, number 2608.11327, Aug.
• Wu, Tianyi & Wang, Tengyao & Samworth, Richard J., 2026, "Deep learning with missing data," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 139005, Jul.
• Rametta, Jack T. & Fuller, Sam, 2026, "Are Random Forests Still ‘Good Enough’? Tabular Prior-Data Fitted Networks for Predictive and Causal Tasks," SocArXiv, Center for Open Science, number g29xc_v1, Jul, DOI: 10.31235/osf.io/g29xc_v1.
• Ebrahimi Kahou, Mahdi & Fernández-Villaverde, Jesús & Gomez Cardona, Sebastian & Perla, Jesse & Rosa, Jan, 2024, "Spooky Boundaries at a Distance: Inductive Bias, Dynamic Models, and Behavioral Macro," CEPR Discussion Papers, Centre for Economic Policy Research, number 19386, Aug.
• Keller, Wolfgang & Shiue, Carol & Yan, Sen, 2024, "Mining Chinese Historical Sources At Scale: A Machine Learning-Approach to Qing State Capacity," CEPR Discussion Papers, Centre for Economic Policy Research, number 19517, Sep.
• Arishi Orra & Himanshu Choudhary & Manoj Thakur, 2026, "Self-Supervised Auxiliary Task Discovery for Stable Reinforcement Learning in Stock Trading," Papers, arXiv.org, number 2608.15841, Aug.
• Hongyu Lin & Yulin Chen & Yuanrong Wang & Antonio Briola & Tomaso Aste, 2026, "Dependence-Informed Sparse Neural Architecture for Stock Return Prediction," Papers, arXiv.org, number 2608.14323, Aug.
• Esteban Sánchez-Gómez, 2026, "Machine Learning Methods for Multi-Horizon Inflation Forecasting: A Comparative Analysis for Costa Rica," Documentos de Trabajo, Banco Central de Costa Rica, number 2606, Aug.
• Christian Terwiesch & Lennart Meincke & Karan Girotra & Ethan Mollick & Gideon Nave & Karl T. Ulrich, 2026, "AI and Its Impact on Creativity and Diversity: An Empirical Study of LLM-Generated Product Ideas," Papers, arXiv.org, number 2607.27553, Jul, revised Jul 2026.
• Bohren, Noah & Hakimov, Rustamdjan & Lalive, Rafael, 2024, "Creative and Strategic Capabilities of Generative AI: Evidence from Large-Scale Experiments," CEPR Discussion Papers, Centre for Economic Policy Research, number 19507, Sep.
• Junyi Ye & Gargi Vijay Borde, 2026, "Regime-Gated Residual Mixture-of-Experts for Cross-Sectional Volatility Forecasting," Papers, arXiv.org, number 2608.12251, Aug.
• Bruno Bouchard & Lucas Gnecco Heredia & Ludovic Moreau & Kim-Anh Pham, 2026, "Optimal Control with Expectation Constraint in a Smooth Boundary Case," Papers, arXiv.org, number 2607.24114, Jul.
• Yijia Xiao & Rujun Han & Yanfei Chen & Zifeng Wang & Ke Jiang & Zhongying CuiZhu & Vishy Tirumalashetty & Wei Wang & Burak Gokturk & Tomas Pfister & Chen-Yu Lee, 2026, "FinanceHarness: Autonomous Financial Deep Research Framework," Papers, arXiv.org, number 2607.27853, Jul, revised Aug 2026.
• Kasun Dewage & Suranadi De Silva & Shankhadeep Mondal, 2026, "Hybrid Neural-Classical Correction for Frozen Time Series Foundation Models: A Comprehensive Ablation Study on High-Frequency Stock Prediction," Papers, arXiv.org, number 2608.08825, Aug.
• Howard Su & Huan-Hsin Tseng & Chi-Sheng Chen & Lance Bai, 2026, "Quantum Transformer BSDE Solver via Multi-Layer Fully-Connected Variational Quantum Circuits," Papers, arXiv.org, number 2607.25162, Jul.
• Christian Bongiorno & Efstratios Manolakis & Rosario Nunzio Mantegna, 2026, "Neural Network-Driven Volatility Drag Mitigation under Aggressive Leverage," Papers, arXiv.org, number 2607.23068, Jul.
• Mayer, Thierry & Rapoport, Hillel & Umana-Dajud, Camilo, 2024, "Free Trade Agreements and the Movement of Business People," CEPR Discussion Papers, Centre for Economic Policy Research, number 19463, Sep.
• Alireza Kargarzadeh & Nariman Khaledian & Navid Parvini & Arman Khaledian, 2026, "Large Language Model-Driven Small-Capitalization Trading: Integrating Financial News Sentiment, Macroeconomic Indicators, and Technical Signals," Papers, arXiv.org, number 2608.12283, Aug.
• Binzhi Chen & Annalivia Polselli & Paul S. Clarke, 2026, "Double Machine Learning with High-dimensional Interactive Fixed Effects," Papers, arXiv.org, number 2608.01137, Aug.
• Liexin Cheng & Xue Cheng & Shuaiqiang Liu & Cornelis W. Oosterlee, 2026, "RIDGE: An Autonomous Framework for Validation and Method Discovery in LLM-Generated Option Pricing," Papers, arXiv.org, number 2607.25199, Jul, revised Jul 2026.