OPTIMIZATION MODELS AND FORECASTS FOR EFFECTIVE MANAGEMENT OF INVESTMENT PORTFOLIOS

Authors

  • Khaydarov Khumoyun Begmurod o‘g‘li 3rd-Year PhD Doctoral Student, Tashkent State University of Economics Department of “Finance and Financial Technologies” Author

Keywords:

Particle swarm optimization, genetic algorithm, artificial neural networks, simulated annealing, Markowitz model, Value at Risk (VaR), Conditional Value at Risk (CVaR), Fuzzy (uncertain) approach

Abstract

Today, one of the most important concerns of investment and financial managers is making prompt and optimal decisions in the presence of large volumes of data and information related to stock and capital markets. In particular, as the level of diversification within investment portfolios increases, it becomes critically important to make sound decisions while taking into account constraints related to expected returns, asset risk levels, liquidity, and other variables.

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Published

2026-01-07

Issue

2026: ICDE -CANADA -JAN

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

OPTIMIZATION MODELS AND FORECASTS FOR EFFECTIVE MANAGEMENT OF INVESTMENT PORTFOLIOS. (2026). Innovate Conferences, 1-2. https://innovateconferences.org/index.php/ic/article/view/570