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Application of ARIMA in Mean-Variance Portfolio Optimization
- 1 Shanghai Jiao Tong University
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Abstract
The stock market often carries investment risks, and portfolio investment can to some extent reduce investment risk, helping investors to achieve certain goal in the financial market. In this paper, stock data from March 15th, 2022, to March 20th, 2023, is collected, and the ARIMA prediction model is ap-plied in the mean-variance framework for constructing optimized portfolios. The results are summarized as follows. First, the data passed the white noise test and was used to conduct ARIMA prediction. The residual sequence of the prediction results is stable, and the model performance is good. Then, the minimum-variance model and the maximum Sharpe ratio model are imple-mented according to the predicted data. Ping An Insurance has the largest weight in the minimum variance model, and Baosteel has the largest weight in the maximum Sharpe ratio model. Overall, the result in this paper provides insightful point for financial investors.
Keywords
ARIMA, PingAn insurance, baosteel, portfolio
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Cite this article
Yang,W. (2023). Application of ARIMA in Mean-Variance Portfolio Optimization. Advances in Economics, Management and Political Sciences,36,11-16.
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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Volume title: Proceedings of the 7th International Conference on Economic Management and Green Development
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