An Genetic-Algorithm Model for Taiwan Stock Index Portfolio

• Main Authors: Bian, Jyh-Shang, 卞志祥
• Other Authors: An-Pin Chen
• Format: Others
• Language: zh-TW
• Published: 1996
• Online Access: http://ndltd.ncl.edu.tw/handle/82315334057535445505

碩士 === 國立交通大學 === 資訊管理研究所 === 84 === The purpose of this study is to use the powerful searching ability ofgenetic algorithm to construct a stock selection model for Taiwan stockindex portfolio. The genetic model will be compared with the Capitalization-Weighted-Nonstrtified Model and Capitalization-Weighted-Stratified Model,which are purposed by Meade and Salkin. From the data analysis, it was discovered that GA stock selection model is stable when its fitness fuction return value reaches a asymptotic limit.It shows that the GA stock selection model is reliable. In the results of comparism amount these models, the portfolio constructed from GA stock selection model is better than the other two to track the Taiwan stock index.In addition, the GA stock selection model has a great characteristic, thestability, no matter how many stocks the portfolio contents. The more stocksthe portfolio contents, the better tracking results are. All of the threemodel exhibit that it is exactly match the portfolio theorem. After the dataanalysis of GA stock selection model effective period and forecasting powerare considered, it shows that 288 days is the information cycle of Taiwan stock market. However, when the stock elements increase, the longer leaningdata-area is better. In summary, the powerful space-aearching ability of genetic algorithm is a really feasible manner to develop a constructing model in portfolio kingdom.