Report NEP-CMP-2023-10-02

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stan 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:

• Patrick Rehill & Nicholas Biddle, 2023. "Fairness Implications of Heterogeneous Treatment Effect Estimation with Machine Learning Methods in Policy-making," Papers 2309.00805, arXiv.org.
• Mingyu Lee & Myeongjin Shin & Junseo Lee & Kabgyun Jeong, 2023. "Mutual Information Maximizing Quantum Generative Adversarial Network and Its Applications in Finance," Papers 2309.01363, arXiv.org.
• Andrii Babii & Eric Ghysels & Jonas Striaukas, 2023. "Econometrics of Machine Learning Methods in Economic Forecasting," Papers 2308.10993, arXiv.org.
• Eugene Kharitonov & Oksana Zakharchuk & Lin Mei, 2023. "Long-term Effects of Temperature Variations on Economic Growth: A Machine Learning Approach," Papers 2308.06265, arXiv.org.
• van den Berg, Gerard J. & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023. "Predicting Re-Employment: Machine Learning versus Assessments by Unemployed Workers and by Their Caseworkers," IZA Discussion Papers 16426, Institute of Labor Economics (IZA).
• Morande, Swapnil & Arshi, Tahseen & Gul, Kanwal & Amini, Mitra, 2023. "Harnessing the Power of Artificial Intelligence to Forecast Startup Success: An Empirical Evaluation of the SECURE AI Model," SocArXiv p3gyb, Center for Open Science.
• Kapil Panda, 2023. "Analysis of Optimal Portfolio Management Using Hierarchical Clustering," Papers 2308.11202, arXiv.org.
• Timothy DeLise, 2023. "Deep Semi-Supervised Anomaly Detection for Finding Fraud in the Futures Market," Papers 2309.00088, arXiv.org.
• Damien Challet & Vincent Ragel, 2023. "Recurrent Neural Networks with more flexible memory: better predictions than rough volatility," Papers 2308.08550, arXiv.org.
• Song Wei & Andrea Coletta & Svitlana Vyetrenko & Tucker Balch, 2023. "INTAGS: Interactive Agent-Guided Simulation," Papers 2309.01784, arXiv.org, revised Nov 2023.
• Brunori, Paolo & Hufe, Paul & Mahler, Daniel, 2023. "The roots of inequality: estimating inequality of opportunity from regression trees and forests," LSE Research Online Documents on Economics 118220, London School of Economics and Political Science, LSE Library.
• Ali Asgarov, 2023. "Predicting Financial Market Trends using Time Series Analysis and Natural Language Processing," Papers 2309.00136, arXiv.org.
• Lefteris Loukas & Ilias Stogiannidis & Prodromos Malakasiotis & Stavros Vassos, 2023. "Breaking the Bank with ChatGPT: Few-Shot Text Classification for Finance," Papers 2308.14634, arXiv.org.