Printed from https://ideas.repec.org/n/nep-big/2025-03-24.html
Report NEP-BIG-2025-03-24
This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-BIG
The following items were announced in this report:
- Daksh Dave & Gauransh Sawhney & Vikhyat Chauhan, 2025, "Multi-Agent Stock Prediction Systems: Machine Learning Models, Simulations, and Real-Time Trading Strategies," Papers, arXiv.org, number 2502.15853, Feb.
- Furkan Karadac{s} & Bahaeddin Eravc{i} & Ahmet Murat Ozbayou{g}lu, 2025, "Multimodal Stock Price Prediction," Papers, arXiv.org, number 2502.05186, Jan.
- Item repec:osf:osfxxx:sxmq2_v1 is not listed on IDEAS anymore
- Zhipeng Liu & Peibo Duan & Mingyang Geng & Bin Zhang, 2025, "A Distillation-based Future-aware Graph Neural Network for Stock Trend Prediction," Papers, arXiv.org, number 2502.10776, Feb.
- Item repec:osf:osfxxx:gmrk7_v1 is not listed on IDEAS anymore
- Yan Zhang & Lin Chen & Yixiang Tian, 2025, "A Method for Evaluating the Interpretability of Machine Learning Models in Predicting Bond Default Risk Based on LIME and SHAP," Papers, arXiv.org, number 2502.19615, Feb.
- Meet Satishbhai Sonani & Atta Badii & Armin Moin, 2025, "Stock Price Prediction Using a Hybrid LSTM-GNN Model: Integrating Time-Series and Graph-Based Analysis," Papers, arXiv.org, number 2502.15813, Feb.
- Lei Zhao & Lin Cai, 2025, "Robust and Efficient Deep Hedging via Linearized Objective Neural Network," Papers, arXiv.org, number 2502.17757, Feb.
- Guojun Xiong & Zhiyang Deng & Keyi Wang & Yupeng Cao & Haohang Li & Yangyang Yu & Xueqing Peng & Mingquan Lin & Kaleb E Smith & Xiao-Yang Liu & Jimin Huang & Sophia Ananiadou & Qianqian Xie, 2025, "FLAG-Trader: Fusion LLM-Agent with Gradient-based Reinforcement Learning for Financial Trading," Papers, arXiv.org, number 2502.11433, Feb, revised Feb 2025.
- Remi Genet, 2025, "Recurrent Neural Networks for Dynamic VWAP Execution: Adaptive Trading Strategies with Temporal Kolmogorov-Arnold Networks," Papers, arXiv.org, number 2502.18177, Feb.
- Zichuan Guo & Mihai Cucuringu & Alexander Y. Shestopaloff, 2025, "Generalized Factor Neural Network Model for High-dimensional Regression," Papers, arXiv.org, number 2502.11310, Feb, revised Mar 2025.
- Item repec:osf:osfxxx:emgpv_v1 is not listed on IDEAS anymore
- Ankur Sinha & Chaitanya Agarwal & Pekka Malo, 2025, "FinBloom: Knowledge Grounding Large Language Model with Real-time Financial Data," Papers, arXiv.org, number 2502.18471, Feb, revised Feb 2026.
- Lei Zhao & Lin Cai & Wu-Sheng Lu, 2025, "Adaptive Nesterov Accelerated Distributional Deep Hedging for Efficient Volatility Risk Management," Papers, arXiv.org, number 2502.17777, Feb.
- Luiz Tavares & Jose Mazzon & Francisco Paletta & Fabio Barros, 2025, "Bankruptcy analysis using images and convolutional neural networks (CNN)," Papers, arXiv.org, number 2502.15726, Jan.
- Sihan Tu & Zhaoxing Gao, 2025, "A Supervised Screening and Regularized Factor-Based Method for Time Series Forecasting," Papers, arXiv.org, number 2502.15275, Feb.
- Enoch H. Kang & Hema Yoganarasimhan & Lalit Jain, 2025, "An Empirical Risk Minimization Approach for Offline Inverse RL and Dynamic Discrete Choice Model," Papers, arXiv.org, number 2502.14131, Feb, revised Jan 2026.
- Ricardo Masini & Marcelo Medeiros, 2025, "Balancing Flexibility and Interpretability: A Conditional Linear Model Estimation via Random Forest," Papers, arXiv.org, number 2502.13438, Feb.
- Luca Lalor & Anatoliy Swishchuk, 2025, "Event-Based Limit Order Book Simulation under a Neural Hawkes Process: Application in Market-Making," Papers, arXiv.org, number 2502.17417, Feb.
- Budría, Santiago & Fermé, Eduardo & Freitas, Diogo Nuno, 2025, "Toward Proactive Policy Design: Identifying 'To-Be' Energy-Poor Households Using Shap for Early Intervention," IZA Discussion Papers, IZA Network @ LISER, number 17669, Feb.
- Jian Chen & Guohao Tang & Guofu Zhou & Wu Zhu, 2025, "ChatGPT and Deepseek: Can They Predict the Stock Market and Macroeconomy?," Papers, arXiv.org, number 2502.10008, Feb.
- Muffert, Johanna & Winkler, Erwin, 2025, "Using Machine Learning to Understand the Heterogeneous Earnings Effects of Exports," IZA Discussion Papers, IZA Network @ LISER, number 17667, Feb.
- Item repec:osf:osfxxx:zxf5y_v1 is not listed on IDEAS anymore
- Item repec:osf:osfxxx:rjpxs_v1 is not listed on IDEAS anymore
- Yuzhi Hao & Danyang Xie, 2025, "A Multi-LLM-Agent-Based Framework for Economic and Public Policy Analysis," Papers, arXiv.org, number 2502.16879, Feb.
- Shunxin Yao, 2025, "Economic Causal Inference Based on DML Framework: Python Implementation of Binary and Continuous Treatment Variables," Papers, arXiv.org, number 2502.19898, Feb.
- Zheli Xiong, 2025, "Ensemble RL through Classifier Models: Enhancing Risk-Return Trade-offs in Trading Strategies," Papers, arXiv.org, number 2502.17518, Feb.
- Guanyuan Yu & Qing Li & Yu Zhao & Jun Wang & YiJun Chen & Shaolei Chen, 2025, "Utilizing Effective Dynamic Graph Learning to Shield Financial Stability from Risk Propagation," Papers, arXiv.org, number 2502.13979, Feb.
- Felix Drinkall & Stefan Zohren & Michael McMahon & Janet B. Pierrehumbert, 2025, "Stories that (are) Move(d by) Markets: A Causal Exploration of Market Shocks and Semantic Shifts across Different Partisan Groups," Papers, arXiv.org, number 2502.14497, Feb.
- Jibang Wu & Chenghao Yang & Yi Wu & Simon Mahns & Chaoqi Wang & Hao Zhu & Fei Fang & Haifeng Xu, 2025, "AI Realtor: Towards Grounded Persuasive Language Generation for Automated Copywriting," Papers, arXiv.org, number 2502.16810, Feb, revised Oct 2025.
- Xiangyu Li & Yawen Zeng & Xiaofen Xing & Jin Xu & Xiangmin Xu, 2025, "HedgeAgents: A Balanced-aware Multi-agent Financial Trading System," Papers, arXiv.org, number 2502.13165, Feb.