The exploration in construction optimization of the volume, rise, price of trading, and turnover rate stocks using Genetic Algorithms

• Main Authors: LIN, HONG-YUAN, 林宏遠
• Other Authors: KUNG, CHIEN-FENG
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/75688342186560205661

碩士 === 國立高雄應用科技大學 === 資訊管理研究所碩士班 === 105 === Past studies have shown that turnover rate in short-term trading markets has a considerable relationship with stock returns. For the public investors, in addition to holding a good trading strategy in many turnover rate of the stock group, how to find out particular features of the stock in the future in many turnover rate of the stock group to stabilize the stock market is the answer which investors want to know mostly. This study hopes to construct an efficient and scientifically based investment decision-making to help retail investors likely to invest more accurately. Besides, the most important purpose of investing in stocks for investors is to maximize the reward and minimize the risk as well. The profit factor come in to be an indispensable assessment of performance on how to select the profitability of the stock characteristics as well as the use of multi-party information to make a good investment decision-making. This is surely the common goal to pursuit in the broader market short and long period for investors. On this purpose, this study uses the Tick data of the original stock market in 10 minutes to sort out the BBAND, KD, RATIO, and use GA in the wake to improve and select the best investment “Combination and index parameters”. The profitability of the turnover rate during the training period is unified and analyzed according to the characteristics. The results indicates that the turnover rate stock on a basis of the characteristics of the high rise can exceed the market returns and bring Excess pay in the broader market both short and long period.