شماره ركورد كنفرانس :
3741
عنوان مقاله :
Portfolio optimization using SAW and TOPSIS methods
عنوان به زبان ديگر :
Portfolio optimization using SAW and TOPSIS methods
پديدآورندگان :
Sedighi Motabah sedighi.mojtaba91@gmail.com Islamic Azad University , Zamani Paricheher zamany2007@yahoo.com Islamic Azad University
كليدواژه :
سيستم فازي , مديريت پرتفوليو , بهينه سازي پرتفوليو , تصميم گيري چند معياره
عنوان كنفرانس :
سومين كنفرانس بين المللي مديريت و مهندسي صنايع با تاكيد بر مديريت دانش، تعالي و توانمندي رقابتي
چكيده فارسي :
This paper is intended to demonstrate the application of a new use of MCDM techniques: the SAW and TOPSIS for portfolio allocation. The portfolio selection decision is a fundamental problem in financial investments where the future performance of assets is generally uncertain but may be related to different attributes and factors. MCDM therefore has great potential to contribute to the portfolio selection decision. Instead of relying solely on the mean and variance, as in the traditional mean variance method, the criteria used in this presentation are the first four moments of the portfolio distribution. Each asset is valued based on its marginal impact on the upper moments of the portfolio, as indicated by trapezoidal fuzzy numbers. Then, a focus-based defocus is applied to transform the blurred numbers into fragile numbers, which can be used to extend SAW and TOPSIS. The other significant advantage is that compared to the mean value variance analysis the portfolio weights achieved by SAW and TOPSIS remain well diversified
چكيده لاتين :
This paper is intended to demonstrate the application of a new use of MCDM techniques: the SAW and TOPSIS for portfolio allocation. The portfolio selection decision is a fundamental problem in financial investments where the future performance of assets is generally uncertain but may be related to different attributes and factors. MCDM therefore has great potential to contribute to the portfolio selection decision. Instead of relying solely on the mean and variance, as in the traditional mean variance method, the criteria used in this presentation are the first four moments of the portfolio distribution. Each asset is valued based on its marginal impact on the upper moments of the portfolio, as indicated by trapezoidal fuzzy numbers. Then, a focus-based defocus is applied to transform the blurred numbers into fragile numbers, which can be used to extend SAW and TOPSIS. The other significant advantage is that compared to the mean value variance analysis the portfolio weights achieved by SAW and TOPSIS remain well diversified