Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India

Research Article

Assessment of Risk Management Capability and Effectiveness of Intelligent Algorithms in Energy Finance

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  • @INPROCEEDINGS{10.4108/eai.17-11-2023.2342789,
        author={Di  Ma and Jingrui  Qin},
        title={Assessment of Risk Management Capability and Effectiveness of Intelligent Algorithms in Energy Finance},
        proceedings={Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India},
        publisher={EAI},
        proceedings_a={ICSETPSD},
        year={2024},
        month={1},
        keywords={energy finance intelligent algorithm risk management capability risk management effectiveness},
        doi={10.4108/eai.17-11-2023.2342789}
    }
    
  • Di Ma
    Jingrui Qin
    Year: 2024
    Assessment of Risk Management Capability and Effectiveness of Intelligent Algorithms in Energy Finance
    ICSETPSD
    EAI
    DOI: 10.4108/eai.17-11-2023.2342789
Di Ma1, Jingrui Qin2,*
  • 1: Energy Finance, Intelligent Algorithm, Risk Management Capability, Risk Management Effectiveness
  • 2: Shandong Technology and Business University, Yantai, Shandong, 264000, China
*Contact email: mailtoqjr@126.com

Abstract

With the rapid development of the energy internet and renewable energy, the application of intelligent algorithms in energy finance is more and more promising. How to evaluate the risk management ability and effect of intelligent algorithms when it is widely used in the field of energy finance has become an urgent problem to be solved. This paper combs the status quo and problems of intelligent algorithms in the field of energy finance, and puts forward some suggestions to improve the level of energy finance service in China. Experimental results show that the Risk-return ratio of risk management in intelligent algorithm can reach up to 330%.