Title page for etd-0705120-173343


URN etd-0705120-173343 Statistics This thesis had been viewed 159 times. Download 11 times.
Author Wei-ting Wu
Author's Email Address No Public.
Department Institute of Industrial Management
Year 2019 Semester 2
Degree Master Type of Document Master's Thesis
Language zh-TW.Big5 Chinese Page Count 114
Title Empirical Research on Investing in ETF Yuanta Taiwan 50 and ETF Yuanta Taiwan High Dividend with Moving Average
Keyword
  • moving average (MA)
  • stochastic indicators (KD)
  • technical analysis
  • index stock funds
  • index stock funds
  • technical analysis
  • stochastic indicators (KD)
  • moving average (MA)
  • Abstract Technical analysis is most commonly-used tool in determining the right time to buy and sell stocks. Many studies have been published on technical analysis. This study is adopting the moving average(below called as MA) on the subject. In which the trading modules are created by different time periods of MA. The samples consist of Yuanta/P-shares Taiwan Top 50 ETF (below called as the 0050) and Yuanta/P-shares Taiwan Dividend Plus ETF(below called as the 0056). The results show that the long-term performance of MA as a single technical indicator is unstable better than the time deposit rate. And the strategy set by golden crosses of two MA and stop orders is far better than other investments modules.
    ¡@¡@The best 0050 module is ¡¨MA60-120 + stop loss 15% + stop profit 30%¡¨, in which total return rate is 73.84% (single average return rate 9.23%; settlement times 8) and win rate is 55.56%. The best 0056 module is ¡¨MA60-120+ stop loss 15% + stop profit 15%¡¨, in which total return is 99.11% (single average return rate 5.83%; settlement times 17), and win rate is 75% . Based on the above results, the moving average in technical analysis can indeed be used as a reference for investment methods.
    Advisor Committee
  • Cheng-yi Lin - advisor
  • Ya-hui Lin - co-chair
  • Yan-chun Cheng - co-chair
  • Files indicate in-campus access immediately and off-campus access at 1 years
    Date of Defense 2020-06-16 Date of Submission 2020-07-05

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