Stock Portfolios Optimization at the Industry Level Regarding Constraints in Practice: Liquidity, Transaction Cost, Turnover & Tracking-error

This study seeks to optimize stock portfolios at the industry level for an intended investment company by considering some limitations (the amount of liquidity of each industry in a month, transaction costs, portfolio turnover, and tracking error) in practice.

The research hypothesis was initially tested. In the first stage, the optimization was implemented without considering the restrictions. Then, the optimization was implemented by imposing all the constraints except the tracking error. In the third stage, the optimization was implemented by placing all the constraints.

The obtained results proved portfolio optimization statistically significant and indicated that it had a higher Sharpe ratio than the construction of a random portfolio. The first step of this study showed that the intended company was far from the efficient frontier. Also, to maximize returns, minimize risks, and maximize the Sharpe ratio, the weights of the industries were needed to be changed (the weight of the sugar and pharmaceutical industries are recommended to be increased). The second phase approved that the company was still far from the efficient frontier and the efficient frontier had become smaller and moved downwards and to the right (the weight of the sugar and pharmaceutical industry are recommended to be increased more than the weight of others). The third step showed that the company was still far from the efficient frontier and the efficient frontier had become smaller and moved downwards and to the right (the weight of the metal and chemical industry are required to be higher than others).

Applying real-world constraints may end in different consequences.