Report NEP-CMP-2024-04-01

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.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-CMP

The following items were announced in this report:

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• Daniele Ballinari, 2024, "Calibrating doubly-robust estimators with unbalanced treatment assignment," Papers, arXiv.org, number 2403.01585, Mar, revised Jun 2024.
• 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.
• 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.
• 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.
• Pierre Brugiere & Gabriel Turinici, 2024, "Transformer for Times Series: an Application to the S&P500," Papers, arXiv.org, number 2403.02523, Mar.
• Andrei Iakovlev & Annie Liang, 2024, "The Value of Context: Human versus Black Box Evaluators," Papers, arXiv.org, number 2402.11157, Feb, revised Jun 2024.
• Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024, "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers, DNB, number 806, Mar.
• 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.
• 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.
• 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.
• 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.
• 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.
• Zhuangwei Shi, 2024, "MambaStock: Selective state space model for stock prediction," Papers, arXiv.org, number 2402.18959, Feb.
• Mourelatos, Evangelos & Zervas, Panagiotis & Lagios, Dimitris & Tzimas, Giannis, 2024, "Can AI Bridge the Gender Gap in Competitiveness?," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1404.
• 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.
• Deepeka Garg & Benjamin Patrick Evans & Leo Ardon & Annapoorani Lakshmi Narayanan & Jared Vann & Udari Madhushani & Makada Henry-Nickie & Sumitra Ganesh, 2024, "A Heterogeneous Agent Model of Mortgage Servicing: An Income-based Relief Analysis," Papers, arXiv.org, number 2402.17932, Feb, revised Feb 2024.
• Reinking, Ernst & Becker, Marco, 2024, "Large language models and proprietary data - More accurate query results thanks to efficient data management and improved technical processes," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 285307.
• Lijia Ma & Xingchen Xu & Yong Tan, 2024, "Crafting Knowledge: Exploring the Creative Mechanisms of Chat-Based Search Engines," Papers, arXiv.org, number 2402.19421, Feb.
• Alexander Cuntz & Carsten Fink & Hansueli Stamm, 2024, "Artificial Intelligence and Intellectual Property : An Economic Perspective," WIPO Economic Research Working Papers, World Intellectual Property Organization - Economics and Statistics Division, number 77, Mar.
• Emiliano Alvarez & Volker Grimm, 2024, "The added value of using the ODD Protocol for agent-based modeling in Economics: go for it!," Working Papers, Red Nacional de Investigadores en Economía (RedNIE), number 307, Mar.
• Mi Zhou & Vibhanshu Abhishek & Timothy Derdenger & Jaymo Kim & Kannan Srinivasan, 2024, "Bias in Generative AI," Papers, arXiv.org, number 2403.02726, Mar.
• Nozomu Kobayashi & Yoshiyuki Suimon & Koichi Miyamoto, 2024, "Time series generation for option pricing on quantum computers using tensor network," Papers, arXiv.org, number 2402.17148, Feb.
• S. Alex Yang & Angela Huyue Zhang, 2024, "Generative AI and Copyright: A Dynamic Perspective," Papers, arXiv.org, number 2402.17801, Feb, revised Dec 2025.
• Konark Jain & Nick Firoozye & Jonathan Kochems & Philip Treleaven, 2024, "Limit Order Book Simulations: A Review," Papers, arXiv.org, number 2402.17359, Feb, revised Mar 2024.

Report NEP-CMP-2024-04-01

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.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-CMP

The following items were announced in this report: