Implementation of Artificial Intelligence in Investment Decision-making in the Chinese A-share Market
DOI:
https://doi.org/10.5281/zenodo.10940590References:
29Keywords:
Artificial Intelligence (AI), Investment Decision-making, Financial Services, A-share MarketAbstract
Financial services are crucial in people's lives, and the development of Artificial Intelligence (AI) technology has brought about new forms of financial services with great potential and prospects. Particularly in risk control and investment decision-making, AI technology not only improves efficiency and saves costs but also mitigates risks and uncertainties caused by subjective factors. This article first introduces several typical securities investment theories in the market, comparing them from aspects such as analysis methods and trading strategies, and analyzes the securities market. Then, the article introduces the popular machine learning technologies in AI and their applications, especially in the investment field. Utilizing mature machine learning methods, the article conducts securities investment analysis based on the trading data and key financial information of listed companies, establishes models for experimentation, and discusses the results. The results indicate that applying AI technology to predict and analyze stock markets is scientifically feasible. Finally, the article summarizes the entire content, proposes suggestions adapted to local investment based on the current situation of the A-share market, and looks forward to the future.
References
Xu, J., Wu, B., Huang, J., Gong, Y., Zhang, Y., & Liu, B. (2024). Practical Applications of Advanced Cloud Services and Generative AI Systems in Medical Image Analysis. arXiv preprint arXiv:2403.17549.
Huang, Zengyi, et al. "Research on Generative Artificial Intelligence for Virtual Financial Robo-Advisor." Academic Journal of Science and Technology 10.1 (2024): 74-80.
Huang, Zengyi, et al. "Application of Machine Learning-Based K-Means Clustering for Financial Fraud Detection." Academic Journal of Science and Technology 10.1 (2024): 33-39.
Che, C., Lin, Q., Zhao, X., Huang, J., & Yu, L. (2023, September). Enhancing Multimodal Understanding with CLIP-Based Image-to-Text Transformation. In Proceedings of the 2023 6th International Conference on Big Data Technologies (pp. 414-418).
Xu, Z., Gong, Y., Zhou, Y., Bao, Q., & Qian, W. (2024). Enhancing Kubernetes Automated Scheduling with Deep Learning and Reinforcement Techniques for Large-Scale Cloud Computing Optimization. arXiv preprint arXiv:2403.07905.
Gong, Y., Huang, J., Liu, B., Xu, J., Wu, B., & Zhang, Y. (2024). Dynamic Resource Allocation for Virtual Machine Migration Optimization using Machine Learning. arXiv preprint arXiv:2403.13619.
Zhang, Y., Liu, B., Gong, Y., Huang, J., Xu, J., & Wan, W. (2024). Application of Machine Learning Optimization in Cloud Computing Resource Scheduling and Management. arXiv preprint arXiv:2402.17216.Wang, Yong, et al. "Construction and application of artificial intelligence crowdsourcing map based on multi-track GPS data." arXiv preprint arXiv:2402.15796 (2024).
Xu, X., Xu, Z., Ling, Z., Jin, Z., & Du, S. (2024). Comprehensive Implementation of TextCNN for Enhanced Collaboration between Natural Language Processing and System Recommendation. arXiv preprint arXiv:2403.09718.
Song, B., Xu, Y., & Wu, Y. (2024). ViTCN: Vision Transformer Contrastive Network For Reasoning. arXiv preprint arXiv:2403.09962.
Wang, Yixu, et al. "Exploring New Frontiers of Deep Learning in Legal Practice: A Case Study of Large Language Models." International Journal of Computer Science and Information Technology 1.1 (2023): 131-138.
Zhou, Yanlin, et al. "Utilizing AI-Enhanced Multi-Omics Integration for Predictive Modeling of Disease Susceptibility in Functional Phenotypes." Journal of Theory and Practice of Engineering Science 4.02 (2024): 45-51.
Xiang, Yafei, et al. "Integrating AI for Enhanced Exploration of Video Recommendation Algorithm via Improved Collaborative Filtering." Journal of Theory and Practice of Engineering Science 4.02 (2024): 83-90.
Ji, Huan, et al. "Utilizing Machine Learning for Precise Audience Targeting in Data Science and Targeted Advertising." Academic Journal of Science and Technology 9.2 (2024): 215-220.
Chen, Y., Wang, S., Lin, L., Cui, Z., & Zong, Y. (2024). Computer Vision and Deep Learning Transforming Image Recognition and Beyond. International Journal of Computer Science and Information Technology, 2(1), 45-51.
Qian, Wenpin, et al. "Clinical Medical Detection and Diagnosis Technology Based on the AlexNet Network Model." Academic Journal of Science and Technology 9.2 (2024): 207-211.
Zeng, Q., Sun, W., Xu, J., Wan, W., & Pan, L. (2024). Machine Learning-Based Medical Imaging Detection and Diagnostic Assistance. International Journal of Computer Science and Information Technology, 2(1), 36-44.
Wang, H., Bao, Q., Shui, Z., Li, L., & Ji, H. (2024). A Novel Approach to Credit Card Security with Generative Adversarial Networks and Security Assessment.
Wu, Jiang, et al. "Case Study of Next-Generation Artificial Intelligence in Medical Image Diagnosis Based on Cloud Computing." Journal of Theory and Practice of Engineering Science 4.02 (2024): 66-73.
Zhu, Mingwei, et al. "Enhancing Collaborative Machine Learning for Security and Privacy in Federated Learning." Journal of Theory and Practice of Engineering Science 4.02 (2024): 74-82.
Yang, Le, et al. "Research and Application of Visual Object Recognition System Based on Deep Learning and Neural Morphological Computation." International Journal of Computer Science and Information Technology 2.1 (2024): 10-17.
Su, G., Wang, J., Xu, X., Wang, Y., & Wang, C. (2024). The Utilization of Homomorphic Encryption Technology Grounded on Artificial Intelligence for Privacy Preservation. International Journal of Computer Science and Information Technology, 2(1), 52-58.
Li, X., Zong, Y., Yu, L., Li, L., & Wang, C. (2024, February). OPTIMIZING USER EXPERIENCE DESIGN AND PROJECT MANAGEMENT PRACTICES IN THE CONTEXT OF ARTIFICIAL INTELLIGENCE INNOVATION. In The 8th International scientific and practical conference “Priority areas of research in the scientific activity of teachers”(February 27–March 01, 2024) Zagreb, Croatia. International Science Group. 2024. 298 p. (p. 214).
K. Xu, X. Wang, Z. Hu and Z. Zhang, "3D Face Recognition Based on Twin Neural Network Combining Deep Map and Texture," 2019 IEEE 19th International Conference on Communication Technology (ICCT), Xi'an, China, 2019, pp. 1665-1668, doi: 10.1109/ICCT46805.2019.8947113.
Shi, Peng, Yulin Cui, Kangming Xu, Mingmei Zhang, and Lianhong Ding. 2019. "Data Consistency Theory and Case Study for Scientific Big Data" Information 10, no. 4: 137. https://doi.org/10.3390/info10040137.
Yu, D., Xie, Y., An, W., Li, Z., & Yao, Y. (2023, December). Joint Coordinate Regression and Association For Multi-Person Pose Estimation, A Pure Neural Network Approach. In Proceedings of the 5th ACM International Conference on Multimedia in Asia (pp. 1-8).
Zhenghua Hu, Xianmei Wang, Kangming Xu, and Pu Dong. 2020. Real-time Target Tracking Based on PCANet-CSK Algorithm. In Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence (CSAI '19). Association for Computing Machinery, New York, NY, USA, 343–346. https://doi.org/10.1145/3374587.3374607.
Medication Recommendation System Based on Natural Language Processing for Patient Emotion Analysis. (2024). Academic Journal of Science and Technology, 10(1), 62-68. https://doi.org/10.54097/v160aa61
Li, X., Zheng, H., Chen, J., Zong, Y., & Yu, L. (2024). User Interaction Interface Design and Innovation Based on Artificial Intelligence Technology. Journal of Theory and Practice of Engineering Science, 4(03), 1-8.
Song, T., Li, X., Wang, B., & Han, L. (2024). Research on Intelligent Application Design Based on Artificial Intelligence and Adaptive Interface.

Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Copyright reserved by the author.

This work is licensed under a Creative Commons Attribution 4.0 International License.