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Published on 9 December 2024
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Zhang,Y. (2024). Application of Intelligent Portfolio Management System in Financial Field: Comprehensive Analysis Based on Accounting and Financial Knowledge. Advances in Economics, Management and Political Sciences,125,62-66.
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Application of Intelligent Portfolio Management System in Financial Field: Comprehensive Analysis Based on Accounting and Financial Knowledge

Yuxi Zhang *,1,
  • 1 Accounting major in Business School, XJTLU, Suzhou, 215021, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2754-1169/2024.17784

Abstract

In the current digital financial environment, portfolio management is highly valued, but traditional approaches face challenges. This study aims to explore the application of intelligent portfolio management systems in the financial field and design the system through accounting and financial knowledge to improve the efficiency of decision-making. Comprehensive research methods were adopted to collect financial and market data, and tools such as machine learning and data mining were used for in-depth analysis. Finally, an intelligent portfolio management system was designed and constructed, and its application effect was verified through empirical research. The research objects are financial market participants, and the data comes from the real market. This study chooses JPMorgan Chase and BlackRock as the research objects. These two well-known financial institutions have rich experience and resources in portfolio management, which will provide in-depth case analysis and data support for this study. The results show that the intelligent system can improve the decision-making efficiency, and put forward the technical challenges and countermeasures to promote the further development of the system.

Keywords

Intelligent Portfolio Management, Financial Decision-Making Efficiency, Machine Learning in Finance, Data Mining in Financial Markets, Empirical Research on Financial Institutions

[1]. Cooper, R., Edgett, S. and Kleinschmidt, E. (2001) ‘Portfolio management for new product development: Results of an industry practices study’, R&D Management, 31(4), pp. 361–380. doi:10.1111/1467-9310.00225.

[2]. Singh, P. (2020) ‘Intelligent Portfolio Management via NLP analysis of Financial 10-K Statements’, International Journal of Artificial Intelligence & Applications, 11(6), pp. 13–25. doi:10.5121/ijaia.2020.11602.

[3]. Sardianos, C. et al. (2020) ‘The emergence of explainability of intelligent systems: Delivering explainable and personalized recommendations for energy efficiency’, International Journal of Intelligent Systems, 36(2), pp. 656–680. doi:10.1002/int.22314.

[4]. Ploder, C. et al. (2022) ‘Agile portfolio management for hybrid projects: How to combine traditional and agile projects in a project portfolio’, Knowledge Management in Organisations, pp. 221–232. doi: 10.1007/978-3-031-07920-7_17.

[5]. Statman, S. (2011) ‘The failure of traditional portfolio management for long-only and hedge fund portfolios (mean-variance; normal distributions, Black Litterman)’, SSRN Electronic Journal [Preprint]. doi:10.2139/ssrn.1964386.

[6]. Curry, E. (2019) ‘Enabling intelligent systems, applications, and analytics for smart environments using real-time linked dataspaces’, Real-time Linked Dataspaces, pp. 229–236. doi:10.1007/978-3-030-29665-0_14.

[7]. Štrimaitis, R., Ramanauskaitė, S. and Stefanovič, P. (2023) ‘Analysis of Automated Forecasting Model POSSIBILITIES FOR COMPANY Financial Accounting Data’, 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) [Preprint]. doi:10.1109/iceccme57830.2023.10253327.

[8]. Sarker, I.H. (2021) ‘Machine learning: Algorithms, real-world applications and Research Directions’, SN Computer Science, 2(3). doi:10.1007/s42979-021-00592-x.

[9]. Agarwal, S. (2013) ‘Data Mining: Data Mining Concepts and Techniques’, 2013 International Conference on Machine Intelligence and Research Advancement [Preprint]. doi:10.1109/icmira.2013.45.

[10]. Zhang, N. (2023) ‘JPMorgan Chase Supply Chain Finance Business Development Strategy Study’, Advances in Economics, Management and Political Sciences, 37(1), pp. 112–117. doi:10.54254/2754-1169/37/20231849.

[11]. Blackrock (2024) Blackrock Model Portfolios, BlackRock. Available at: https://www.blackrock.com/us/financial-professionals/investment-strategies/model-portfolios (Accessed: 17 July 2024).

[12]. Aldoseri, A., Al-Khalifa, K.N. and Hamouda, A.M. (2023) ‘Re-thinking data strategy and integration for Artificial Intelligence: Concepts, opportunities, and challenges’, Applied Sciences, 13(12), p. 7082. doi:10.3390/app13127082.

[13]. Ryder, N.L., Geiman, J.A. and Weckman, E.J. (2021) ‘Hierarchical temporal memory continuous learning algorithms for fire state determination’, Fire Technology, 57(6), pp. 2905–2928. doi:10.1007/s10694-020-01055-0.

[14]. Haddadian, H., Baky Haskuee, M. and Zomorodian, G. (2022) ‘A hybrid artificial intelligence approach to portfolio management’, Iranian Journal of Finance, 6(1), pp. 1–27. doi:10.30699/ijf.2021.287131.1237.

Cite this article

Zhang,Y. (2024). Application of Intelligent Portfolio Management System in Financial Field: Comprehensive Analysis Based on Accounting and Financial Knowledge. Advances in Economics, Management and Political Sciences,125,62-66.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 8th International Conference on Economic Management and Green Development

Conference website: https://2024.icemgd.org/
ISBN:978-1-83558-755-3(Print) / 978-1-83558-756-0(Online)
Conference date: 26 September 2024
Editor:Lukáš Vartiak
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.125
ISSN:2754-1169(Print) / 2754-1177(Online)

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