Title page for etd-0825108-120447


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URN etd-0825108-120447
Author Yu-Ping Lin
Author's Email Address ypinglin8@yahoo.com.tw
Statistics This thesis had been viewed 5643 times. Download 3238 times.
Department Information Management
Year 2007
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Use Genetic Algorithms to Construct Mutual Fund Portfolio Based on Perceived Risk Levels
Date of Defense 2008-07-21
Page Count 102
Keyword
  • perceived risk levels
  • asset allocation
  • genetic algorithm
  • mutual fund
  • Abstract Because the government changed laws and opened the market progressively in recent years, the financial market in Taiwan becomes more and more liberal and international; every investor has to face a more complicated investitive environment. They can choice many investitive objects and tools, but how to choice the best one is a big problem for them and the risk in the financial market becomes much higher. Mutual fund is a popular investment tools in recent year. One of the mutual fund’s benefits is the diversity of investment and effectively disperses risk..
      In August 2006, the government in Taiwan opens up the market of mutual fund; the investors can buy offshore mutual funds in many channels, so they can choice many kinds of mutual funds, about 1,400 in April 2008. Also, every investor that can beat the level of risk is so different, it maybe make them confused and really want to know which one is much better and do asset allocation very well. Therefore, how to design a good portfolio for different perceived risk levels of investors is a worthful topic in the academia and the really world.
    This research uses the genetic algorithm to construct mutual fund portfolios based on perceived risk levels, use fund return, standard deviation, Alpha, Beta, Sharpe, IR and Sortino indicators to select funds of a portfolio and calculate portfolio return and standard deviation, then do asset allocation. This research change funds in every portfolio every month using Sliding Windows method from Jan 1, 2001 to Dec 12, 2007, totally 84 times.
      The result of this research is every portfolio average return wins benchmark index average return. The standard deviation of every portfolio also wins benchmark index standard deviation. It shows this research can beat benchmark index effectively and also can decrease the risk of portfolio return, then we can get a good fund portfolio for different perceived risk levels of investors
    Advisory Committee
  • Stephen Yang - chair
  • Yuh-Jiuan Tsai - co-chair
  • Bing-Chiang Jeng - advisor
  • Chia-Mei Chen - advisor
  • Files
  • etd-0825108-120447.pdf
  • indicate in-campus access immediately and off_campus access in a year
    Date of Submission 2008-08-25

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