碩士 / 大葉大學 / 管理學院碩士在職專班 / 98 / Due to liberalization and internationalization of Taiwan’s financial markets, investors in multiple financial markets are able to be free to choose different investment tools in order to obtain return. All kinds of investment tools have been closely linked to many investors’ life. The base Fund’s investment is especially essential. This study attempts to use artificial intelligence methods in genetic algorithms, and build a portfolio investment of global real estate funds and offshore gold funds. Through the powerful solving ability of genetic algorithms evolution, the study quickly and effectively finds better portfolio investments in order to provide reference for investors investing portfolio funds.
Empirical results found that: this research and analysis separately tested six quarter’s return on investment(ROI) in 2008 Q2 to 2009 Q3, and found that except ROI in 2008 Q3 lost to ROI of Taiwan Capitalization Weighted Stock Index(TAIEX), S&P500 Index, and Dow Jones EURO STOXX 50 Index. Except ROI in 2009 is less than ROI of TAIEX in Q1 and ROI in Q3 is less than ROI of Dow Jones EURO STOXX 50 index, the rest ROI portfolio investment are totally better than ROI of these three markets mentioned(TAIEX, S&P500 index, and Dow Jones EURO STOXX 50 index), and accumulative total ROI is also significantly higher than these three specific three markets(TAIEX, S&P500 index, and Dow Jones EURO STOXX 50 index). The study shows the outstanding performance of genetic algorithms(GA).
Therefore, I believe that if we carry out portfolio investment by using GA, we will be able to obtain a better fund of funds(FOF) making higher profit than ROI. Genetic algorithm provides superior reference of decision-making model of investment.
| Identifer | oai:union.ndltd.org:TW/098DYU01121091 |
| Date | January 2010 |
| Creators | Chen-Ping Cheng, 鄭貞平 |
| Contributors | Wen-Kuei Lai, 賴文魁 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 79 |
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