Developing a Robust Portfolio Rebalancing Model Considering Fundamental Factors

Portfolio rebalancing is one of the most important parts of investment management. After forming a portfolio by an investor, due to changing prices in the market, the portfolio value deviates from its initial amount. Therefore, the investor needs to rebalance the investment portfolio to achieve their goal. On the other hand, the fundamental factors of companies do not remain constant over time due to reasons such as changes in the country's economic situation and changes in policies related to the purchase, production and sale of company’s products. Furthermore, in order to select the best stocks that are prone to grow, it is essential to pay attention to the fundamental factors of companies by examining important financial ratios, including net profit ratio, return on assets (ROA), return on equity ratio (ROE), debt ratio (DR) and other ratios. In this research, a multi-objective model for the portfolio rebalancing problem is developed to consider the fundamental factors of stocks. To include the fundamental factors to the model, TOPSIS technique is applied. In addition, due to considering several goals in the model, multi-choice fuzzy ideal programming is applied to solve the model. Also, due to the variety of investors' expectations and the uncertainty of some parameters, including the ratio P/E and expected stock return, the uncertainty in the parameters of the model has been taken into account and the model is formulated using Bertsimas and Sim's approach from robust optimization approaches. In addition, by adopting Constant Proportion Portfolio Insurance strategy (CPPI) and maintaining the stop loss in specific time periods such as three months, the developed model is solved using the real data of the Tehran Stock Exchange and its results have been analyzed. In summary, the results show that the return and the Sharp ratio of the proposed portfolio is better than the traditional models.