A Model for Core-Satellite Investment in Tehran Stock Exchange Using the Hybrid Approach of Exact and Heuristic Algorithms

In this study, the effective method of asset allocation characterized by risk control, cost reduction and out-performance with respect to the market benchmark has been investigated. In this regard, the optimal asset allocation in the core and satellite portfolio including the degree of risk aversion were studied. The core component of the portfolio represents an index fund selected by the use of a heuristic genetic based algorithm, which assures the level of risk-return realization comparable to the market index. The satellite component is consisted of selected mutual fund investment units and is managed actively in order to beat the market index.
An EGARCH model was used in order to simulate the required data, and a multi goal objective function as maximizing the excess return and minimizing the variance relative to the index was implemented for the modeling of the core-satellite problem.
The results of the analysis implies on the direct relationship between the degree of risk aversion and the weight allocated to the core component. The calculations also indicate the out-performance of the constructed portfolio relative to the market index and its good tracking ability based on criteria such as correlation and root mean squared error using out of sample data.