Multivariate Portfolio Optimization under Illiquid Market Prospects

The aim of the current research is to optimize the multivariate portfolio optimization algorithms under illiquid market (commodity and financial) perspective. In this regard, an optimization model for portfolio risk-return assessment with LVaR constraints is investigated using reasonable financial and operational scenarios. This approach is achieved by minimizing LVaR. The research method is descriptive and correlational. The statistical population is the companies admitted to the Tehran stock exchange, which were selected by systematic elimination sampling (screening) of 100 companies that were present in the stock exchange during the financial years of 1392-1399.The required information was extracted through the new Rah Avard software and the official website related to the Tehran Stock Exchange Organization. The unit root test of the variables was investigated using the method of Lin and Chui, and the basics of econometrics were discussed, and the variables were investigated using the vector auto-regression method (VAR) using Eviews and MATLAB statistical software. Based on the results, it can be said; Liquidity affects commodity and financial markets. Also, the effect of optimization algorithms and modeling techniques on portfolio management and risk assessment was confirmed