Asset Allocation Optimization Using Covariance-Based Portfolio Modeling

This study investigates the use of the Markowitz portfolio optimization model to construct an investment portfolio with the lowest possible level of risk while maintaining a predefined return target. The research is grounded in Modern Portfolio Theory, which examines the relationship between expected returns and the risk associated with financial assets. To ensure an adequate degree of diversification, the analysis is based on stocks representing different sectors of the economy. The study includes the calculation of logarithmic returns, volatility indicators, and the covariance matrix of asset returns. Using the obtained data, an equally weighted portfolio was evaluated and subsequently optimized through the mean-variance framework and constrained optimization techniques. Numerical computations were performed using Microsoft Excel. The findings indicate that portfolio risk can be significantly reduced without compromising the desired level of expected return. The results confirm the practical value of mathematical methods in investment management and highlight the effectiveness of the Markowitz approach for portfolio decision-making in financial markets.