TY - GEN
T1 - Analytic Hierarchy Process (AHP) in Portfolio Selection Based on Information Granularity
AU - Zhao, Kaixin
AU - Dai, Yaping
AU - Ji, Ye
AU - Sun, Jiayi
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - Analytic Hierarchy Process (AHP) is a multi criteria decision-making method, which can describe and transform the qualitative problems quantitatively, and then get the quantitative analysis results in accordance with the causal relationship between decision attribute. In this paper, a granular Analytic Hierarchy Process, which introduces the granularity mechanism, is proposed to solve the portfolio selection problem under the mean-risk framework. In the proposed method, the scale value of scheme layer is no longer limited to nine positive integers from 1 to 9, which gives granularity attributes to the comparison of advantages and disadvantages in a specific criterion layer between different schemes. The proposed method reflects small differences between different alternative schemes through granularity attribute, so it can provide rich decision information for decision makers. Three numeric examples from the real-world financial market (China Shanghai Stock Exchange) are provided to illustrate an essence of the proposed method.
AB - Analytic Hierarchy Process (AHP) is a multi criteria decision-making method, which can describe and transform the qualitative problems quantitatively, and then get the quantitative analysis results in accordance with the causal relationship between decision attribute. In this paper, a granular Analytic Hierarchy Process, which introduces the granularity mechanism, is proposed to solve the portfolio selection problem under the mean-risk framework. In the proposed method, the scale value of scheme layer is no longer limited to nine positive integers from 1 to 9, which gives granularity attributes to the comparison of advantages and disadvantages in a specific criterion layer between different schemes. The proposed method reflects small differences between different alternative schemes through granularity attribute, so it can provide rich decision information for decision makers. Three numeric examples from the real-world financial market (China Shanghai Stock Exchange) are provided to illustrate an essence of the proposed method.
KW - Analytic Hierarchy Process (AHP)
KW - Decision-making
KW - Information Granularity
KW - Portfolio Selection
UR - http://www.scopus.com/inward/record.url?scp=85091599463&partnerID=8YFLogxK
U2 - 10.1109/CCDC49329.2020.9164421
DO - 10.1109/CCDC49329.2020.9164421
M3 - Conference contribution
AN - SCOPUS:85091599463
T3 - Proceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020
SP - 886
EP - 891
BT - Proceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 32nd Chinese Control and Decision Conference, CCDC 2020
Y2 - 22 August 2020 through 24 August 2020
ER -