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<p>This study investigates the application of Multiple Criteria Decision Analysis (MCDA) methods for portfolio selection in the Vietnamese stock market using daily stock price data from the VN100 index spanning January 2015 to November 2023. Creating 150 criteria based on stock returns, volatility, and correlation, we employ five popular MCDA methods and four weighting methods to compare the performance of up to 500 portfolios. While MCDA methods may not effectively differentiate between stocks with higher and lower future returns, they consistently excel in selecting portfolios with superior risk-adjusted returns and lower drawdown compared to both the benchmark and the traditional Mean-Variance (MV) method. The PROMETHEE II (Preference Ranking Organization Method for Enrichment of Evaluations) method stands out as a robust performer, and the CRITIC (Criteria Importance Through Intercriteria Correlation) weighting method emerges as a reliable choice for constructing portfolios with favorable risk-adjusted returns. Moreover, the MCDA methods demonstrate potential computational efficiency over the tested MV implementation, enhancing their practicality. These findings highlight the practical utility of MCDA, particularly PROMETHEE II with CRITIC weighting, for navigating the complexities of portfolio optimization in dynamic emerging markets like Vietnam, offering a compelling alternative to traditional approaches.</p>

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Mcda strategies for portfolio optimization: a case study on Vietnamese stock market dynamics

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月1日

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  • Stéphane Goutte,
  • Hoang-Viet Le,
  • Fei Liu,
  • Hans-Jörg von Mettenheim

摘要

This study investigates the application of Multiple Criteria Decision Analysis (MCDA) methods for portfolio selection in the Vietnamese stock market using daily stock price data from the VN100 index spanning January 2015 to November 2023. Creating 150 criteria based on stock returns, volatility, and correlation, we employ five popular MCDA methods and four weighting methods to compare the performance of up to 500 portfolios. While MCDA methods may not effectively differentiate between stocks with higher and lower future returns, they consistently excel in selecting portfolios with superior risk-adjusted returns and lower drawdown compared to both the benchmark and the traditional Mean-Variance (MV) method. The PROMETHEE II (Preference Ranking Organization Method for Enrichment of Evaluations) method stands out as a robust performer, and the CRITIC (Criteria Importance Through Intercriteria Correlation) weighting method emerges as a reliable choice for constructing portfolios with favorable risk-adjusted returns. Moreover, the MCDA methods demonstrate potential computational efficiency over the tested MV implementation, enhancing their practicality. These findings highlight the practical utility of MCDA, particularly PROMETHEE II with CRITIC weighting, for navigating the complexities of portfolio optimization in dynamic emerging markets like Vietnam, offering a compelling alternative to traditional approaches.