MULTIPARAMETRIC APPROACH TO PORTFOLIO STRUCTURE OPTIMIZATION AND DYNAMIC REBALANCING BASED ON THE MARKOWITZ MODEL

The increasing relevance of investment asset management tasks in a volatile macroeconomic environment necessitates a shift from heuristic strategies to formalized approaches that integrate quantitative methods of evaluation and forecasting. This article examines a multiparametric mechanism for optimizing the structure and dynamic rebalancing of an investment portfolio, grounded in the H. Markowitz model. The theoretical and applied framework of the algorithm accounts for complex interdependencies between returns, risks, and the covariance structure of assets. A quarterly rebalancing procedure is implemented, incorporating sectoral and capitalization-based diversification, as well as both fundamental and technical analysis. The inclusion of constraints on asset volatility and cross-correlation characteristics is substantiated. Empirical validation of the algorithm is conducted using data from publicly listed Russian companies, followed by a comparative assessment against the IMOEX index as a benchmark. The results demonstrate the outperformance of baseline return levels and confirm the efficiency of the proposed algorithm amid the limited predictability of market dynamics.