Report NEP-BIG-2024-04-01

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:

• John D. Huber & Laura Mayoral, 2024, "Economic Development in Pixels: The Limitations of Nightlights and New Spatially Disaggregated Measures of Consumption and Poverty," Working Papers, Barcelona School of Economics, number 1433, Mar.
• Victor Chernozhukov & Christian Hansen & Nathan Kallus & Martin Spindler & Vasilis Syrgkanis, 2024, "Applied Causal Inference Powered by ML and AI," Papers, arXiv.org, number 2403.02467, Mar.
• Ziyuan Ma & Conor Ryan & Jim Buckley & Muslim Chochlov, 2024, "Do Weibo platform experts perform better at predicting stock market?," Papers, arXiv.org, number 2403.00772, Feb.
• Pierre Brugiere & Gabriel Turinici, 2024, "Transformer for Times Series: an Application to the S&P500," Papers, arXiv.org, number 2403.02523, Mar.
• Hanshuang Tong & Jun Li & Ning Wu & Ming Gong & Dongmei Zhang & Qi Zhang, 2024, "Ploutos: Towards interpretable stock movement prediction with financial large language model," Papers, arXiv.org, number 2403.00782, Feb.
• Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024, "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers, DNB, number 806, Mar.
• Carlos Giraldo & Iader Giraldo & Jose E. Gomez-Gonzalez & Jorge M. Uribe, 2024, "High Frequency Monitoring of Credit Creation: A New Tool for Central Banks in Emerging Market Economies," Documentos de trabajo, FLAR, number 21077, Mar.
• Bryan Kelly & Boris Kuznetsov & Semyon Malamud & Teng Andrea Xu & Yuan Zhang, 2024, "Large and Deep Factor Models," Papers, arXiv.org, number 2402.06635, Jan, revised Feb 2026.
• Qishuo Cheng & Le Yang & Jiajian Zheng & Miao Tian & Duan Xin, 2024, "Optimizing Portfolio Management and Risk Assessment in Digital Assets Using Deep Learning for Predictive Analysis," Papers, arXiv.org, number 2402.15994, Feb.
• Vikranth Lokeshwar Dhandapani & Shashi Jain, 2024, "Neural Networks for Portfolio-Level Risk Management: Portfolio Compression, Static Hedging, Counterparty Credit Risk Exposures and Impact on Capital Requirement," Papers, arXiv.org, number 2402.17941, Feb.
• Daniele Ballinari, 2024, "Calibrating doubly-robust estimators with unbalanced treatment assignment," Papers, arXiv.org, number 2403.01585, Mar, revised Jun 2024.
• Pengfei Zhao & Haoren Zhu & Wilfred Siu Hung NG & Dik Lun Lee, 2024, "From GARCH to Neural Network for Volatility Forecast," Papers, arXiv.org, number 2402.06642, Jan.
• Meilian ZHANG & Ting YIN & Emiko USUI & Takashi OSHIO & Yi ZHANG, 2024, "Unraveling the Determinants of Overemployment and Underemployment among Older Workers in Japan: A machine learning approach," Discussion papers, Research Institute of Economy, Trade and Industry (RIETI), number 24034, Mar.
• Wentao Zhang & Lingxuan Zhao & Haochong Xia & Shuo Sun & Jiaze Sun & Molei Qin & Xinyi Li & Yuqing Zhao & Yilei Zhao & Xinyu Cai & Longtao Zheng & Xinrun Wang & Bo An, 2024, "A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist," Papers, arXiv.org, number 2402.18485, Feb, revised Jun 2024.
• Ruoyu Sun & Angelos Stefanidis & Zhengyong Jiang & Jionglong Su, 2024, "Combining Transformer based Deep Reinforcement Learning with Black-Litterman Model for Portfolio Optimization," Papers, arXiv.org, number 2402.16609, Feb.
• Antonis Papapantoleon & Jasper Rou, 2024, "A time-stepping deep gradient flow method for option pricing in (rough) diffusion models," Papers, arXiv.org, number 2403.00746, Mar, revised Apr 2025.
• Adele Ravagnani & Fabrizio Lillo & Paola Deriu & Piero Mazzarisi & Francesca Medda & Antonio Russo, 2024, "Dimensionality reduction techniques to support insider trading detection," Papers, arXiv.org, number 2403.00707, Mar, revised May 2024.
• Yilun Wang & Shengjie Guo, 2024, "RVRAE: A Dynamic Factor Model Based on Variational Recurrent Autoencoder for Stock Returns Prediction," Papers, arXiv.org, number 2403.02500, Mar.
• Yiyan Huang & Cheuk Hang Leung & Siyi Wang & Yijun Li & Qi Wu, 2024, "Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators," Papers, arXiv.org, number 2402.18392, Feb, revised Oct 2024.
• Jiajian Zheng & Duan Xin & Qishuo Cheng & Miao Tian & Le Yang, 2024, "The Random Forest Model for Analyzing and Forecasting the US Stock Market in the Context of Smart Finance," Papers, arXiv.org, number 2402.17194, Feb.
• Sylvain Barthélémy & Virginie Gautier & Fabien Rondeau, 2024, "Early warning system for currency crises using long short‐term memory and gated recurrent unit neural networks," Post-Print, HAL, number hal-04470367, DOI: 10.1002/for.3069.
• Vikranth Lokeshwar Dhandapani & Shashi Jain, 2024, "Optimizing Neural Networks for Bermudan Option Pricing: Convergence Acceleration, Future Exposure Evaluation and Interpolation in Counterparty Credit Risk," Papers, arXiv.org, number 2402.15936, Feb.
• Chu Myaet Thwal & Ye Lin Tun & Kitae Kim & Seong-Bae Park & Choong Seon Hong, 2024, "Transformers with Attentive Federated Aggregation for Time Series Stock Forecasting," Papers, arXiv.org, number 2402.06638, Jan.
• Mi Zhou & Vibhanshu Abhishek & Timothy Derdenger & Jaymo Kim & Kannan Srinivasan, 2024, "Bias in Generative AI," Papers, arXiv.org, number 2403.02726, Mar.
• Yuhao Fu & Nobuyuki Hanaki, 2024, "Do people rely on ChatGPT more than their peers to detect deepfake news?," ISER Discussion Paper, Institute of Social and Economic Research, The University of Osaka, number 1233, Mar.
• Martin Berka, & Yiran Mao, 2023, "Social media sentiment and house prices: Evidence from 35 Chinese cities," Discussion Papers, School of Economics and Finance, Massey University, New Zealand, number 2301.
• Vasilii Chsherbakov & Ilia Karpov, 2024, "Regional inflation analysis using social network data," Papers, arXiv.org, number 2403.00774, Feb, revised Mar 2024.
• Wessel Vermeulen & Fernanda Gutierrez Amaros, 2024, "How well do online job postings match national sources in European countries?: Benchmarking Lightcast data against statistical and labour agency sources across regions, sectors and occupation," OECD Local Economic and Employment Development (LEED) Papers, OECD Publishing, number 2024/02, Mar, DOI: 10.1787/e1026d81-en.
• Andres Garc√≠a-Suaza & Daniela Varela, 2024, "Nightlight, landcover and buildings: understanding intracity socioeconomic differences," Documentos de Trabajo, Universidad del Rosario, number 21025, Feb.

Report NEP-BIG-2024-04-01

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: