Dynamic managing of investment portfolios based on vector autoregression models and multivariate volatility models

Theoretical part of the paper covers the problem of dynamic management of investment portfolios in a term of mean-variance analysis in cases when information about pricing models of asset returns and volatility of their errors is known. This problem is one of a type of models of multi-step optimization of discrete systems for given constraints functions in the terminal step and on the control variables. The practical part examines the characteristics of optimal portfolios which asset returns are predicted by the VAR models and the covariance matrixes of the assets using multivariate models of volatility.