Avtandil Liluashvili


Purpose. The author targets the creation of an analytical investment framework by emerging existing statistical techniques. The paper aims to introduce a framework constructed for the Georgian economy that can assist investors in analyzing the medium-term implications of different macro scenarios. For this, a tactical and strategic asset allocation decision-making framework was developed to optimize portfolios by employing a Balanced Portfolio approach, with the help of forecasted macroeconomic variables using econometric techniques (VECM – Vector Error Correction Model; Taylor rule estimation with OLS –Ordinary Least Squares). The author also intends to lay the foundations for future research regarding the investment characteristics of the emerging market.

Design/methodology/approach. The first forecasts of inflation and policy rate are obtained with the Vector Error Correction and Taylor rule models. Macroeconomic forecasts/projections are then applied to link asset price developments derived from Monte Carlo simulations. Finally, the Balanced Portfolio approach is utilized to optimize asset weights given different scenarios.
Findings. The results show that this approach lowers risk in all assumed scenarios and obtains better returns compared to plain vanilla  efficient-frontier optimization. Portfolios have better risk-return profiles than before optimization with this approach. These results were obtained by using the macro model described in the paper.

Originality. The paper aims to introduce a framework that is a combination of multiple well-established macroeconomic and investment models in the academic community, which is tailored for a developing economy such as Georgia. Thus, the originality of the research rests in the method of choosing specific techniques, variables, and connections between different models to best estimate the optimal portfolio given the objective of the investment.