| Author: | Lee, Man-shun |
| Title: | DSS of portfolio optimization using genetic algorithm |
| Other Title: | Decision support system of portfolio optimization using genetic algorithm |
| Degree: | M.Sc. |
| Year: | 2010 |
| Subject: | Hong Kong Polytechnic University -- Dissertations Stock exchanges -- China -- Hong Kong -- Data processing. Decision support systems Genetic algorithms Portfolio management -- Mathematical models |
| Department: | Department of Computing |
| Pages: | x, 54 leaves : ill. (some col.) ; 31 cm. |
| Language: | English |
| Abstract: | The dissertation presented the building of a DSS (Decision Support System) that used Genetic Algorithm in optimizing the selection of various assets in the Hong Kong stock market in order to achieve an optimized Portfolio. The problem was a typical Resource allocation problem to optimize the objective. It has been quite a few research works on applying Genetic Algorithm in Portfolio Optimization, there was study in exploring the use of tree structure in genomic representation, while the array representation has been blamed for held responsible for not effectively inherit parents traits in the cross-over (reproduction) stage. The genomic representation presented in this dissertation was still using array representation; moreover the suggested representation method offered the mechanism to pass the good combination assets into the next generation. Furthermore the Genetic Algorithm proposed in this Dissertation took into account of the fact that stock trading in the market has to be conducted in lots, there was no fractional lots can be purchased, while many researches commonly assumed the fractional lots transaction was possible if the capital amount was big enough such as corporate investor. The Genetic Algorithm representation in this dissertation did not make use of the normalization, which could lead to the problem of creating fractional lots in the solution space. Consequently the suggested representation made the problem becoming an integer programming problem as well. The initial experimental results showed a property of the Sharpe Ratio that the author not awarded before. It also shred a new light on the bottle neck of the optimization approach and DSS construction. The dissertation suggested a direction of further work on improving the processing speed of the DSS. It was believed the application of the proposed Array representation could apply. Genetic algorithm effectively and the construction of a DSS in helping home investor was possible. |
| Rights: | All rights reserved |
| Access: | restricted access |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| b23910896.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.15 MB | Adobe PDF | View/Open |
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