Title page for etd-0727118-000856


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URN etd-0727118-000856
Author Bing-Yang Chiang
Author's Email Address akimoto1231ia@gmail.com
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Department Computer Science and Engineering
Year 2017
Semester 2
Degree Master
Type of Document
Language English
Title Using Fuzzy Sets to Speed up the Optimization of Group Stock Portfolio
Date of Defense 2018-07-23
Page Count 105
Keyword
  • diverse group stock portfolio
  • fuzzy grouping genetic algorithm
  • grouping problem
  • individual repair mechanism
  • portfolio optimization
  • Abstract Investment is always an interesting and important issue for people since international financial crisis is hard to predict and government’s policy may have influence on economic. In the past, many scholars have proposed research on portfolio issues. In some of these studies, group stock portfolios (GSP) are utilized to provide various alternative stocks to an investor. Previous studies have also observed that diversity of industries within a group can affect the performance of a final GSP. Therefore, in this thesis, the diversity of industries was taken into consideration, and two approaches for finding the diverse group stock portfolio (DGSP) have been designed. In the first approach, a new chromosome representation and an enhanced fitness function are applied to find a better DGSP with lower risk than before; moreover, we design a fuzzy grouping genetic algorithm (FGGA) which utilizes fuzzy logic to dynamically tune the parameters in the evolution process for finding appropriate DGSPs. In the second approach, we employ the multi-objective genetic algorithm to find different solutions (Pareto solutions) based on the two objective functions, Sharpe ratio and group balance. In addition, a mechanism is also designed in the proposed approaches to repair non-feasible chromosomes in the population. Through the above improvements, the proposed approaches can not only focus on finding the best solution, but also speed up the evolution process. Finally, experiments made on two real datasets also show that the proposed approaches are effective and efficient.
    Advisory Committee
  • Kawuu W. Lin - chair
  • Katherine Shu-Min Li - co-chair
  • Ming-Chao Chiang - co-chair
  • Chun-Hao Chen - co-chair
  • Tzung-Pei Hong - advisor
  • Files
  • etd-0727118-000856.pdf
  • Indicate in-campus at 3 year and off-campus access at 3 year.
    Date of Submission 2018-08-29

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