Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China

Research Article

Portfolio Investment Analysis Based on Markowitz Mean-variance Model with a Realistic Fund Dataset

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  • @INPROCEEDINGS{10.4108/eai.18-11-2022.2326894,
        author={Xi  Chen and Shiqi  Fang and Zixin  Shen},
        title={Portfolio Investment Analysis Based on Markowitz Mean-variance Model with a Realistic Fund Dataset},
        proceedings={Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China},
        publisher={EAI},
        proceedings_a={ICEMME},
        year={2023},
        month={2},
        keywords={portfolio management; markowitz mean-variance model; stock market; sharpe ratio; efficient frontier},
        doi={10.4108/eai.18-11-2022.2326894}
    }
    
  • Xi Chen
    Shiqi Fang
    Zixin Shen
    Year: 2023
    Portfolio Investment Analysis Based on Markowitz Mean-variance Model with a Realistic Fund Dataset
    ICEMME
    EAI
    DOI: 10.4108/eai.18-11-2022.2326894
Xi Chen1,*, Shiqi Fang2, Zixin Shen3
  • 1: Department of Statistics, University of Toronto
  • 2: Desautels Faculty of Management, McGill University
  • 3: Department of Mathematics, University College
*Contact email: cynthiacxi.chen@mail.utoronto.ca

Abstract

As the financial market is getting increasingly complicated, many investors have confronted the quandary between the investment target and their ability of risk tolerance. To provide investors with insights on portfolio management, this paper is dedicated to boost the return and avoid the risks to the maximum level simultaneously. With 9 separate assets selected, the portfolio which features lower variance, higher expected return, and higher Sharpe Ratio is expected. Throughout the research, normal distribution and independent and identically distributed tests test helped us initially understand the data. With the help of the demonstration of the efficient frontier, we found the best fit portfolios. Corresponding portfolio suggestions have been given, and limitations have also been discussed.