Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Computing | en_US |
| dc.creator | Lee, Kwok-keung | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/3429 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Stock advisor for small investors : a rule-based expert system | en_US |
| dcterms.abstract | Owing to the fast growing economy, free trading policy, and efficient market operation in Hong Kong, both foreigners and local people are attracted to participate in the financial investment activities. There are more and more small investors trying to protect their accumulated saving against inflation by investing their money in stock market. However they, especially those new to the market, wonder how the market trend can be predicted so that they can follow the signal of buy or sell and earn a reasonable profit, or at least to offset the inflation rate. Newspaper and magazine provide more enough information and strange figures than that a novice investor can digest all and use. This research makes use of the recent popular Artificial Intelligent technique to assist and promote the technical analysis in stock investment. An Expert Shell, KAPPA-PC, is used as the core of Knowledge Based System (KBS) with the supplement of Visual Basic for Application (VBA), which is an object-oriented programming language embedded in Microsoft Excel version 5, as a front end processor for data and graphic manipulation. Three main categories of technical analysis - momentum, moving average, and support/resistance line - in turn they contain several theories - are employed as the knowledge base of the system. The product provides a good graphic interface and facilities for tracing causes that give rise the results. These let the user operate the system without referring to a detail manual. Moreover, the teaching features of the system is ready for novice investors to study. Through the manual input form of the system, investors can explore the theories and reveal how the prediction can be derived by means of adjusting the weightings and even the independent variables. In sum, this research is a pilot study in applying KBS to stock investment. | en_US |
| dcterms.extent | 1 v. (various pagings) : ill. ; 30 cm | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 1996 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Investments | en_US |
| dcterms.LCSH | Stocks | en_US |
| dcterms.LCSH | Expert systems (Computer science) | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b12350321.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 6.98 MB | Adobe PDF | View/Open |
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