Exploration of Portfolio Optimization Methods Based on Machine Learning
Journal: Modern Economics & Management Forum DOI: 10.32629/memf.v6i2.3950
Abstract
As the complexity of financial markets increases, traditional portfolio optimization methods face significant challenges. Machine learning, as an effective data analysis tool, has gained widespread application in portfolio optimization in recent years. This paper explores machine learning-based portfolio optimization methods, analyzing the application of supervised learning and reinforcement learning algorithms in asset allocation, and compares them with the traditional mean-variance approach. The results indicate that machine learning optimization can significantly improve expected returns while controlling risk. However, challenges such as data quality and model complexity still persist in practical applications. This paper also looks ahead to the future development directions of machine learning in portfolio optimization, including improving stability, real-time performance, and interpretability.
Keywords
portfolio optimization, machine learning, supervised learning, reinforcement learning
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[1] Botero S B ,Claudia María García Mazo, Arboleda F J M .Power generation mix in Colombia including wind power: Markowitz portfolio efficient frontier analysis with machine learning[J].Journal of Open Innovation: Technology, Market, and Complexity, 2024, 10(4).
[2] Al Janabi M A M .Insights into Liquidity Dynamics: Optimizing Asset Allocation and Portfolio Risk Management with Machine Learning Algorithms[M].Palgrave Macmillan, Cham,2024.
[3] Abensur E .Machine Learning for liquidity classification and its applications to portfolio selection[J].Brazilian Review of Finance / Revista Brasileira de Finanças, 2024, 22(2).
[4] Sak H , Huang T , Chng M T ,et al.Exploring the factor zoo with a machine-learning portfolio[J].International Review of Financial Analysis 2024.PB.23-33.
[5] Meng C , Chen C , Xu H ,et al.Asset Pricing and Portfolio Investment Management Using Machine Learning: Research Trend Analysis Using Scientometrics[J].Economics, 2024, 18(1):16961-16988.
[2] Al Janabi M A M .Insights into Liquidity Dynamics: Optimizing Asset Allocation and Portfolio Risk Management with Machine Learning Algorithms[M].Palgrave Macmillan, Cham,2024.
[3] Abensur E .Machine Learning for liquidity classification and its applications to portfolio selection[J].Brazilian Review of Finance / Revista Brasileira de Finanças, 2024, 22(2).
[4] Sak H , Huang T , Chng M T ,et al.Exploring the factor zoo with a machine-learning portfolio[J].International Review of Financial Analysis 2024.PB.23-33.
[5] Meng C , Chen C , Xu H ,et al.Asset Pricing and Portfolio Investment Management Using Machine Learning: Research Trend Analysis Using Scientometrics[J].Economics, 2024, 18(1):16961-16988.
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