Abstract
The Markowitz and index models are widely used in portfolio optimization to achieve optimal asset allocation and maximize returns while controlling risk. However, in practical investment scenarios, additional constraints often need to be considered to ensure the feasibility and effectiveness of the portfolio strategy. This research focuses on incorporating realistic additional constraints into the Markowitz and index models for portfolio optimization. The study utilizes historical financial data and statistical techniques to estimate expected returns, variances, and covariance matrices. The Markowitz model is modified to incorporate the additional constraints, allowing for more realistic and accurate portfolio optimization outcomes. The index model is also adapted to consider the impact of these constraints on the construction and performance of passive investment portfolios.
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