Index tracking using a hybrid genetic algorithm

Assuming the market is efficient, an obvious portfolio management strategy is passive where the challenge is to track a certain benchmark like a stock index. The goal of the passive strategy is to achieve equal returns and risks. In this paper, we investigate an approach for tracking the Dutch AEX index where an optimal tracking portfolio (consisting of a weighted subset of stock funds) is determined. The optimal weights of a portfolio are found by minimizing the tracking error for a set of historical returns and covariances. The overall optimal portfolio is found using a hybrid genetic algorithm where the fitness function of each chromosome (possible subset of stocks) equals the minimal tracking error achievable. We show the experimental setup and the simulation results, including the out-of-sample performance of the optimal tracking portfolio found