Report NEP-CMP-2025-01-27

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:

• Weizhe Ren & Yichen Qin & Yang Li, 2024. "Alpha Mining and Enhancing via Warm Start Genetic Programming for Quantitative Investment," Papers 2412.00896, arXiv.org.
• Mengming Michael Dong & Theophanis C. Stratopoulos & Victor Xiaoqi Wang, 2024. "A Scoping Review of ChatGPT Research in Accounting and Finance," Papers 2412.05731, arXiv.org.
• Zhuohuan Hu & Richard Yu & Zizhou Zhang & Haoran Zheng & Qianying Liu & Yining Zhou, 2024. "Developing Cryptocurrency Trading Strategy Based on Autoencoder-CNN-GANs Algorithms," Papers 2412.18202, arXiv.org, revised Feb 2025.
• Dongwoo Lee & Gavin Kader, 2024. "The Emergence of Strategic Reasoning of Large Language Models," Papers 2412.13013, arXiv.org, revised Feb 2025.
• Tommaso Di Francesco & Daniel Torren Peraire, 2024. "(Mis)information diffusion and the financial market," Papers 2412.16269, arXiv.org.
• Jiajun Gu & Zichen Yang & Xintong Lin & Sixun Chen & YuTing Lu, 2024. "AI-Enhanced Factor Analysis for Predicting S&P 500 Stock Dynamics," Papers 2412.12438, arXiv.org.
• Hortense Fong & George Gui, 2024. "Modeling Story Expectations to Understand Engagement: A Generative Framework Using LLMs," Papers 2412.15239, arXiv.org.
• Pengbin Feng & Yankaiqi Li & Yijiashun Qi & Xiaojun Guo & Zhenghao Lin, 2024. "Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXt," Papers 2412.17314, arXiv.org.
• Zong Ke & Jingyu Xu & Zizhou Zhang & Yu Cheng & Wenjun Wu, 2024. "A Consolidated Volatility Prediction with Back Propagation Neural Network and Genetic Algorithm," Papers 2412.07223, arXiv.org, revised Feb 2025.
• Akash Deep & Chris Monico & Abootaleb Shirvani & Svetlozar Rachev & Frank J. Fabozzi, 2024. "Assessing the Impact of Technical Indicators on Machine Learning Models for Stock Price Prediction," Papers 2412.15448, arXiv.org.
• Gang Huang & Xiaohua Zhou & Qingyang Song, 2024. "Dynamic Optimization of Portfolio Allocation Using Deep Reinforcement Learning," Papers 2412.18563, arXiv.org, revised Jan 2025.
• Fengpei Li & Haoxian Chen & Jiahe Lin & Arkin Gupta & Xiaowei Tan & Gang Xu & Yuriy Nevmyvaka & Agostino Capponi & Henry Lam, 2024. "Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variate," Papers 2412.11257, arXiv.org.
• Item repec:hal:journl:hal-04839757 is not listed on IDEAS anymore

• Anton Korinek, 2024. "Generative AI for Economic Research: LLMs Learn to Collaborate and Reason," NBER Working Papers 33198, National Bureau of Economic Research, Inc.
• Jens Ludwig & Sendhil Mullainathan & Ashesh Rambachan, 2024. "Large Language Models: An Applied Econometric Framework," Papers 2412.07031, arXiv.org, revised Jan 2025.
• Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2024. "Machine Learning the Macroeconomic Effects of Financial Shocks," Papers 2412.07649, arXiv.org.
• Yuxin Fan & Zhuohuan Hu & Lei Fu & Yu Cheng & Liyang Wang & Yuxiang Wang, 2024. "Research on Optimizing Real-Time Data Processing in High-Frequency Trading Algorithms using Machine Learning," Papers 2412.01062, arXiv.org.
• Qilong Wu & Xiaoneng Xiang & Hejia Huang & Xuan Wang & Yeo Wei Jie & Ranjan Satapathy & Ricardo Shirota Filho & Bharadwaj Veeravalli, 2024. "SusGen-GPT: A Data-Centric LLM for Financial NLP and Sustainability Report Generation," Papers 2412.10906, arXiv.org.
• Jianhua Yao & Yuxin Dong & Jiajing Wang & Bingxing Wang & Hongye Zheng & Honglin Qin, 2024. "Stock Type Prediction Model Based on Hierarchical Graph Neural Network," Papers 2412.06862, arXiv.org.
• Tarek Alexander Hassan & Stephan Hollander & Aakash Kalyani & Laurence van Lent & Markus Schwedeler & Ahmed Tahoun, 2024. "Economic Surveillance using Corporate Text," NBER Working Papers 33158, National Bureau of Economic Research, Inc.
• Pengjie Zhou & Haoyu Wei & Huiming Zhang, 2024. "Selective Reviews of Bandit Problems in AI via a Statistical View," Papers 2412.02251, arXiv.org.
• Yuhan Wang & Zhen Xu & Yue Yao & Jinsong Liu & Jiating Lin, 2024. "Leveraging Convolutional Neural Network-Transformer Synergy for Predictive Modeling in Risk-Based Applications," Papers 2412.18222, arXiv.org.
• Vidhi Agrawal & Eesha Khalid & Tianyu Tan & Doris Xu, 2024. "Hunting Tomorrow's Leaders: Using Machine Learning to Forecast S&P 500 Additions & Removal," Papers 2412.12539, arXiv.org.
• Andrew Holmes & Matt Jensen & Sarah Coffland & Hidemi Mitani Shen & Logan Sizemore & Seth Bassetti & Brenna Nieva & Claudia Tebaldi & Abigail Snyder & Brian Hutchinson, 2024. "Emulating the Global Change Analysis Model with Deep Learning," Papers 2412.08850, arXiv.org.
• Shasha Yu & Qinchen Zhang & Yuwei Zhao, 2024. "S&P 500 Trend Prediction," Papers 2412.11462, arXiv.org.
• Sebastien Valeyre & Sofiane Aboura, 2024. "LLMs for Time Series: an Application for Single Stocks and Statistical Arbitrage," Papers 2412.09394, arXiv.org.
• Vincent Lee Wai Seng & Shariff Abu Bakar Sarip Abidinsa, 2024. "Machine learning for anomaly detection in money services business outlets using data by geolocation," IFC Working Papers 23, Bank for International Settlements.
• Yixuan Liang & Yuncong Liu & Boyu Zhang & Christina Dan Wang & Hongyang Yang, 2024. "FinGPT: Enhancing Sentiment-Based Stock Movement Prediction with Dissemination-Aware and Context-Enriched LLMs," Papers 2412.10823, arXiv.org.
• Eduardo Abi Jaber, 2024. "Simulation of square-root processes made simple: applications to the Heston model," Papers 2412.11264, arXiv.org.
• Item repec:hal:journl:hal-04799408 is not listed on IDEAS anymore

• Gero Junike & Hauke Stier, 2024. "Enhancing Fourier pricing with machine learning," Papers 2412.05070, arXiv.org.
• Zong Ke & Yuchen Yin, 2024. "Tail Risk Alert Based on Conditional Autoregressive VaR by Regression Quantiles and Machine Learning Algorithms," Papers 2412.06193, arXiv.org.
• Edward Li & Zhiyuan Tu & Dexin Zhou, 2024. "The Promise and Peril of Generative AI: Evidence from GPT-4 as Sell-Side Analysts," Papers 2412.01069, arXiv.org.
• Kirill Safonov, 2024. "Neural Network Approach to Demand Estimation and Dynamic Pricing in Retail," Papers 2412.00920, arXiv.org, revised Dec 2024.
• Thomas Krause & Steffen Otterbach & Johannes Singer, 2024. "Delving into Youth Perspectives on In-game Gambling-like Elements: A Proof-of-Concept Study Utilising Large Language Models for Analysing User-Generated Text Data," Papers 2412.09345, arXiv.org.
• Haohang Li & Yupeng Cao & Yangyang Yu & Shashidhar Reddy Javaji & Zhiyang Deng & Yueru He & Yuechen Jiang & Zining Zhu & Koduvayur Subbalakshmi & Guojun Xiong & Jimin Huang & Lingfei Qian & Xueqing Pe, 2024. "INVESTORBENCH: A Benchmark for Financial Decision-Making Tasks with LLM-based Agent," Papers 2412.18174, arXiv.org.
• Item repec:hal:journl:hal-04790290 is not listed on IDEAS anymore

• Bhaskarjit Sarmah & Mingshu Li & Jingrao Lyu & Sebastian Frank & Nathalia Castellanos & Stefano Pasquali & Dhagash Mehta, 2024. "How to Choose a Threshold for an Evaluation Metric for Large Language Models," Papers 2412.12148, arXiv.org.
• Igor L. R. Azevedo & Toyotaro Suzumura, 2024. "From Votes to Volatility Predicting the Stock Market on Election Day," Papers 2412.11192, arXiv.org.
• Jiti Gao & Fei Liu & Bin Peng & Yanrong Yang, 2024. "Localized Neural Network Modelling of Time Series: A Case Study on US Monetary Policy," Monash Econometrics and Business Statistics Working Papers 14/24, Monash University, Department of Econometrics and Business Statistics.
• Item repec:hal:journl:hal-04208686 is not listed on IDEAS anymore

• Item repec:hal:journl:hal-04779953 is not listed on IDEAS anymore

• You Wu & Mengfang Sun & Hongye Zheng & Jinxin Hu & Yingbin Liang & Zhenghao Lin, 2024. "Integrative Analysis of Financial Market Sentiment Using CNN and GRU for Risk Prediction and Alert Systems," Papers 2412.10199, arXiv.org.
• Siqiao Zhao & Dan Wang & Raphael Douady, 2024. "PolyModel for Hedge Funds' Portfolio Construction Using Machine Learning," Papers 2412.11019, arXiv.org.
• Nick Huntington-Klein & Eleanor J. Murray, 2024. "Do LLMs Act as Repositories of Causal Knowledge?," Papers 2412.10635, arXiv.org.
• Sumit Nawathe & Ravi Panguluri & James Zhang & Sashwat Venkatesh, 2024. "Multimodal Deep Reinforcement Learning for Portfolio Optimization," Papers 2412.17293, arXiv.org.
• Olamilekan Shobayo & Sidikat Adeyemi-Longe & Olusogo Popoola & Bayode Ogunleye, 2024. "Innovative Sentiment Analysis and Prediction of Stock Price Using FinBERT, GPT-4 and Logistic Regression: A Data-Driven Approach," Papers 2412.06837, arXiv.org.
• Amine M. Aboussalah & Xuanze Li & Cheng Chi & Raj Patel, 2024. "The AI Black-Scholes: Finance-Informed Neural Network," Papers 2412.12213, arXiv.org.
• Marco Pangallo & R. Maria del Rio-Chanona, 2024. "Data-Driven Economic Agent-Based Models," Papers 2412.16591, arXiv.org.
• Van-Duc Le, 2024. "Auto-Generating Earnings Report Analysis via a Financial-Augmented LLM," Papers 2412.08179, arXiv.org.
• Julian Junyan Wang & Victor Xiaoqi Wang, 2024. "Leveraging Large Language Models to Democratize Access to Costly Financial Datasets for Academic Research," Papers 2412.02065, arXiv.org.
• Philippe Goulet Coulombe & Maximilian Goebel & Karin Klieber, 2024. "Dual Interpretation of Machine Learning Forecasts," Papers 2412.13076, arXiv.org.
• Bhaskarjit Sarmah & Kriti Dutta & Anna Grigoryan & Sachin Tiwari & Stefano Pasquali & Dhagash Mehta, 2024. "A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation," Papers 2412.15298, arXiv.org.