Presentation a model for crediblistic multi-period portfolio optimization model whit bankruptcy control

Subject Areas : Industrial Management

snoor modaresi ¹ , farshid kheirollah ² , mehrdad ghanbari ³ , babak jamshidinavid ⁴

1 - Department of accounting , Kermanshah Branch, Islamic Azad University ,Kermanshah, Iran.
2 - Department of accounting, Razi University, Kermanshah, Iran
3 - Department of accounting , Kermanshah Branch, Islamic Azad University ,Kermanshah, Iran
4 - Department of accounting , Kermanshah Branch, Islamic Azad University ,Kermanshah, Iran.

Received: 2018-05-20 Accepted : 2018-09-09 Published : 2018-09-22

Keywords: accumulated risk, bankruptcy control, Multi-period portfolio optimization, portfolio uncertaint, expected value of investor,

Abstract :

In this research, a mathematical model has been presented for optimizing multi-period portfolios with a bankruptcy control approach. The goals of optimizing the multi-period portfolios include: 1- maximizing the expected outflow of the investor 2- Minimizing accumulated risk 3- Minimizing the uncertainty of the portfolio''''s returns during the investment period, that achievement of these three objectives has been evaluated by two limits of bankruptcy control and the maximum and minimum adjustments of investment amounts during the investment period. The Hybrid Particle Swarm Optimization (Hybrid PSO) algorithm has been considered as the proposed solution for solving the model and a practical example has been presented to illustrate the application of the proposed model, which includes a portfolio with 17 different types of stocks from the companies listed in Tehran Stock Exchange For the three-year period from 2014 to 2016, the daily returns of these companies have been used as inputs for the model. Three different modes for the weights of the goals of optimizing the portfolio of multi- period portfolios have been determined using the sensitivity analysis table. In the end, the state of investment, which the investor equates to all three goals of optimizing the weight, has been the most suitable state for optimizing a multi-period of portfolios. the results has been compared with other algorithms Experimental results have shown that the algorithm proposed by this research for solving the model has been more appropriate than other algorithm.

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