The Role of Artificial Intelligence in Optimizing Portfolio Management: A Literature Review
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-67444-0_12
Reference30 articles.
1. Arisena, A., et al.: Portfolio return using Black-Litterman single view model with ARMA-GARCH and Treynor Black model. J. Phys: Conf. Ser. 974(1), 012023 (2018). https://doi.org/10.1088/1742-6596/974/1/012023
2. Barua, R., Sharma, A.K.: Using fear, Greed and machine learning for optimizing global portfolios: a Black-Litterman approach. Financ. Res. Lett. 58, 104515 (2023). https://doi.org/10.1016/j.frl.2023.104515
3. Black, F., Litterman, R.: Global portfolio optimization. Financ. Analysts J. 48(5), 28–43 (1992). https://doi.org/10.2469/faj.v48.n5.28
4. Chan, M.-C., et al.: Artificial intelligence in portfolio management. In: Yin, H., et al. (eds.) Intelligent Data Engineering and Automated Learning — IDEAL 2002, vol. 2412, pp. 403–409. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45675-9_60
5. Chanel, C., et al.: Conférence Nationale d’Intelligence Artificielle Année (2019)
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