Constructing a Personal Asset Allocation Model with Particle Swarm Optimization – An Example for Wealth Management

• Main Authors: Jer-Yi Tien, 田哲溢
• Other Authors: Chao-Chang Chiu
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/21978913401065220982

碩士 === 元智大學 === 資訊管理學系 === 94 === Given the current benefits structure of the Taiwan Employee Retirement Income Security Act (TERISA), two pension plans (defined contribution and defined benefit) are examined to discuss the asset allocation of personal accounts, which may include N target investment strategies. The study proposes Particle Swarm Optimization to be compared with Genetic Algorithms for carrying out asset allocation and the findings indicate that Particle Swarm Optimization outperforms Genetic Algorithms in both solution quality and calculating time. The adequacy of the pension plans is examined by an actuarial model based on the hypothesis that all the variables are set as random, including simulated salary growth rate, inflation rate, interest rate, and investment return rate. The accumulated value and income-replacement ratio of personal accounts are further evaluated to construct an asset allocation model adequate for everyone according to each individual’s risk tolerance level.