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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/105528

    Title: 以共演化式遺傳演算法輔助動態股票投資決策分析
    Other Titles: Using co-evolutionary genetic algorithm to assist dynamic stock investment analysis
    Authors: 夏承億;Hsia, Cheng-Yi
    Contributors: 淡江大學資訊管理學系碩士班
    張應華;Chang, Ying-Hua
    Keywords: 遺傳演算法;共演化模式;馬可夫決策;動態股票投資決策;最佳化;Genetic Algorithms;Co-evolutionary mode;Markov decision process;Dynamic stock investment decisions;Optimization
    Date: 2015
    Issue Date: 2016-01-22 14:58:21 (UTC+8)
    Abstract: 股票投資為時下眾多理財工具中的一種,其風險與報酬是相對的,想要獲得高額的報酬得承擔較高的風險,一般投資民眾缺乏專業知識與資料分析的能力,其投資決策多依電視股市交易分析節目或一些小道消息來進行決策,但股市的行情變化快速,投資者想要在股票市場裏獲利,必須慎選股票,並在適當的時機進場交易,以及最佳的資金配置。因此,如何制定正確的投資策略,成為眾多投資者關注的議題。
    In the rapid changes stock market, investors want to get profit that they must carefully choose stocks, buy or sell the stocks at the appropriate time and with the best capital allocation strategy. How to make the right investment strategy is the subject of investors. There are many ways to assist the development of decision for stock investment strategy. But when investors consider too many investment criteria, it is easy to lose objectivity and proper analysis to determine the importance of the evaluation criteria. Especially when investors take into account new guidelines when to make investment decision. The traditional decision making methods just can only re-evaluate the decision problem and cannot be accumulated the importance of criteria before adding new guidelines. It is difficult to make decision. Furthermore, investors often miss the good opportunity to do stock transaction and do not know how to allocate investment funds.
    For this reason, this study integrated co-evolutionary genetic algorithm with Markov decision process to help investors develop a dynamic stock investment strategies system. The genetic algorithms have the ability of parallel search in breadth space. The co-evolutionary mechanism has simulated human thought patterns. These making the process of the genetic algorithm can implement with adjustment in the dynamic changes environments. And by Markov decision process, the decision system can inform investors when must to adjust the portfolio and to identify the appropriate stock timing, the stock selection and the capital allocation. The complete stock investment strategy allows investors to obtain excess returns when invest in the stock market.
    Appears in Collections:[資訊管理學系暨研究所] 學位論文

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