<p>Portfolio rebalancing is a critical aspect of investment management, ensuring that an investment portfolio remains aligned with an investor's objectives over time. Due to changes in the economic environment and company policies, the fundamental situation of companies evolves. This paper presents a multi-objective model for portfolio rebalancing based on the Constant Proportion Portfolio Insurance (CPPI) strategy, with the objectives of minimizing risk, minimizing transaction costs, and maximizing the portfolio’s fundamental criteria. The model incorporates interval uncertainty in parameters such as the price-to-earnings ratio and is reformulated using a robust optimization approach. A revised multi-choice goal programming method is applied to solve the model. The proposed method is evaluated in both bullish and bearish market cycles, as well as during a financial crisis, to ensure its robustness and performance across varying market conditions. The results show that, without rebalancing, the investor incurs greater losses during bearish markets. However, by implementing the proposed rebalancing strategy, the portfolio’s floor value is maintained, and the portfolio experiences only a slight decrease in value during market downturns. Additionally, by incorporating fundamental factors, the strategy leads to higher returns and lower risk in bullish markets compared to other strategies.</p>

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A Multi-Objective Robust Optimization Model for the Portfolio Rebalancing Problem with Constant Proportion Portfolio Insurance Strategy: Evidence from the US Stock Market

  • Mohammadhossein Vafaeikhah,
  • Amir Abbas Najafi,
  • Fatemeh Rezaei

摘要

Portfolio rebalancing is a critical aspect of investment management, ensuring that an investment portfolio remains aligned with an investor's objectives over time. Due to changes in the economic environment and company policies, the fundamental situation of companies evolves. This paper presents a multi-objective model for portfolio rebalancing based on the Constant Proportion Portfolio Insurance (CPPI) strategy, with the objectives of minimizing risk, minimizing transaction costs, and maximizing the portfolio’s fundamental criteria. The model incorporates interval uncertainty in parameters such as the price-to-earnings ratio and is reformulated using a robust optimization approach. A revised multi-choice goal programming method is applied to solve the model. The proposed method is evaluated in both bullish and bearish market cycles, as well as during a financial crisis, to ensure its robustness and performance across varying market conditions. The results show that, without rebalancing, the investor incurs greater losses during bearish markets. However, by implementing the proposed rebalancing strategy, the portfolio’s floor value is maintained, and the portfolio experiences only a slight decrease in value during market downturns. Additionally, by incorporating fundamental factors, the strategy leads to higher returns and lower risk in bullish markets compared to other strategies.