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|Other Titles: ||Bond funds investment knowledge system|
|Authors: ||林蔚;Lin, Wei|
|Keywords: ||債券基金;知識工程;Bond Funds;knowledge system|
|Issue Date: ||2016-01-22 14:57:40 (UTC+8)|
本研究重新分類、整理，歸納對債券基金影響的因素，如殖利率、違約率、經濟發展強弱、匯率強弱等等因素，依照這些因素建置一個以債券基金為知識庫－債券投資推論系統BIKS(Bond Investment Knowledge system)，透過BIKS系統以及使用者輸入的狀況說明，推薦投資者一個較中立、客觀的第三方建議，供投資者做為參考。
Bond funds provide both high liquidity and stable revenue for investors. In recent years, higher growth in people invests on bond funds than they do for another type of investments. For instance, the number of Taiwanese’s investment on bond funds increased from 17,293 to 77,058, in year 2008 to 2013. The growth rate is 346.6% in five years. At the same time, the total amount that invested on bond funds, for both domestic and foreign ones, increased from 773,107 M to 1,466,061 M in year 2008 to 2013. Total growth rate reached to 89.63%.
Although the number of people who invested on bond funds increased significantly, the way to choose bond funds relies solo on broker’s recommendation. This situation would leave wholly the issues to the broker’s consideration and might be little concern about the investors themselves.
This research aims to reclassify the factors that would affect bond funds, such as yield to mature, default rates, exchange rates, and each economic growth rates for each country. These factors for world-wide countries would be huge. By knowledge engineering, we build a USA-central model for all countries. According to this model, we build up a Bond Investment Knowledge system (BIKS) which mark the both the expert view among the factors and the investors attributes. After capturing the data through system, BIKS could come up with investment suggestions for investors.
To test the validity of BIKS, we virtually built three economic situations in the BIKS. The BIKS came up with the corresponding suggestions for investors in these three situations. All the economic situations and the corresponding suggestions were given to the domain expert to examine the validity. As a result, BIKS indicated high consistence with the domain expert.
|Appears in Collections:||[資訊管理學系暨研究所] 學位論文|
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