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作者:

Zheng, Xiaolong (Zheng, Xiaolong.) | Li, Jingyu (Li, Jingyu.) | Lu, Mengyao (Lu, Mengyao.) | Wang, Fei-Yue (Wang, Fei-Yue.)

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EI Scopus SCIE

摘要:

In the past few years, we have witnessed the rapid development and exponential growth of generative artificial intelligence (GAI) technologies including large language models (LLMs)-enabled ChatGPT and peripheral innovations. These technologies are designed to be humanlike intelligence and intuitive by providing direct access to systems using application programming interfaces (APIs). The GAI applications can fundamentally change economic and financial activities, through revolutionizing the ways that humans interact with machines and giving rise to new modes of production and behavior patterns. It is imperative to develop a new research paradigm that is more suitable than the currently dominating conventional research paradigms. This article presents the new paradigm for economic and financial research with GAI, covering the research objectives, scientific data, and models, and explores the underlying impact and perspective that bring to this field. We elaborate on the potential five scenarios including portfolio management, economic and financial prediction, extreme scenario analysis, policy analysis, and financial fraud detection. The new research paradigm with GAI proposed in this article can provide significant insights for a comprehensive understanding of innovation and transformation in this domain.

关键词:

Task analysis Economics Data models Behavioral sciences finance research paradigm Big Data reinforcement learning from human feedback (RLHF) generative artificial intelligence (GAI) Biological system modeling Analytical models

作者机构:

  • [ 1 ] [Zheng, Xiaolong]Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 101408, Peoples R China
  • [ 2 ] [Wang, Fei-Yue]Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 101408, Peoples R China
  • [ 3 ] [Zheng, Xiaolong]Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
  • [ 4 ] [Wang, Fei-Yue]Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
  • [ 5 ] [Zheng, Xiaolong]Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
  • [ 6 ] [Wang, Fei-Yue]Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
  • [ 7 ] [Li, Jingyu]Beijing Univ Technol, Sch Econ & Management, Beijing 100124, Peoples R China
  • [ 8 ] [Lu, Mengyao]Beijing Univ Technol, Sch Econ & Management, Beijing 100124, Peoples R China

通讯作者信息:

  • [Wang, Fei-Yue]Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 101408, Peoples R China;;[Li, Jingyu]Beijing Univ Technol, Sch Econ & Management, Beijing 100124, Peoples R China

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来源 :

IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS

ISSN: 2329-924X

年份: 2024

期: 3

卷: 11

页码: 3457-3467

5 . 0 0 0

JCR@2022

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SCOPUS被引频次: 10

ESI高被引论文在榜: 0 展开所有

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