Title page for etd-0824110-122030


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URN etd-0824110-122030
Author Hung-Hsin Chen
Author's Email Address No Public.
Statistics This thesis had been viewed 5112 times. Download 866 times.
Department Computer Science and Engineering
Year 2009
Semester 2
Degree Master
Type of Document
Language English
Title Genetic Programming for the Investment of the Mutual Fund with Sortino Ratio and Mean Variance Model
Date of Defense 2010-07-07
Page Count 142
Keyword
  • genetic programming
  • trading strategy
  • return
  • Sortino ratio
  • risk
  • Abstract In this thesis, we propose two genetic-programming-based models that improve the
    trading strategies for mutual funds. These two models can help investors get returns
    and reduce risks. The first model increases the return by selecting funds with high
    Sortino ratios and allocates the capital equally, achieving the best annualized return.
    The second model also selects funds with high Sortino ratios, but reduces the risk
    by allocating the capital with the mean variance model.
    Most importantly, our model utilizes the genetic programming to generate
    feasible trading strategies to gain return, which is suitable for the market that
    changes anytime. To verify our models, we simulate the investment for mutual
    funds from January 1999 to December 2009 (11 years in total). The experimental
    results show that our first model can gain return from 2004/1/1 to 2008/12/31,
    achieving the best annualized return 9.11%, which is better than the annualized
    return 6.89% of previous approaches. In addition, our second model with smaller
    downside volatility can achieve almost the same return as previous results.
    Advisory Committee
  • So-De Shyu - chair
  • Jen-Chih Yao - co-chair
  • Chia-Ping Chen - co-chair
  • Kuo-Si Huang - co-chair
  • Chang-Biau Yang - advisor
  • Files
  • etd-0824110-122030.pdf
  • indicate in-campus access immediately and off_campus access in a year
    Date of Submission 2010-08-24

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