Please use this identifier to cite or link to this item:
http://dspace.cityu.edu.hk/handle/2031/3663| Title: | Stock prediction |
| Authors: | Leung, Yiu Fai |
| Department: | Department of Computer Science |
| Issue Date: | 2006 |
| Supervisor: | Dr. Rynson Lau |
| Abstract: | Stock prediction is always an absorbing topic. Enormous efforts have been contributed by scholars but until now, there is still hardly a conclusion. This research aims to predict stock trend by using traditional technical indicators and soft computing techniques. Existing prediction techniques are studied and evaluated. Five popular technical indicators are used as input of two classifier, naïve bayes and k nearest neighbors for decision making. A trading strategy system is implemented to simulate trading environment. Historic data of the Heng Seng Index, Dow Jones Index, HSBC (005), MeiKin (335) and Wing Lung (0096) are used to evaluate prediction methods. |
| Appears in Collections: | Computer Science - Undergraduate Final Year Projects |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| fulltext.html | 164 B | HTML | View/Open |
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