Designing of a heuristic algorithm for the optimal tracker fund selection: the case of Tehran stock exchange index

The optimal allocation of financial resources in capital market is one of the major issues in the field of investment decisions. Making an effective decision in this regard requires the existence of appropriate investment fields, instruments and analytical techniques in the capital market. One of this efficient techniques which in addition to having unique benefits, is also recognized as the foundation of new investment strategies, is called index tracking. By considering the importance and the undeniable role of this approach in the prosperity of capital markets, its investigation and implementation has been considered in this research and so the problem of optimal TEDPIX tracker fund selection is studied via the hybrid approach of genetic algorithm and quadratic programming. We should mention that, for the data simulation and provision of the conditions needed to implement the suggested algorithm, the heuristic approach of neural network is also being used. The Results of data analysis showed the high accuracy and appropriate performance of the portfolios created by this hybrid approach in several times of iterations, so that accessing similar and better performance compared to the index could be considered as its unique characteristics.