Evaluating the Performance of Mutual Funds— Using the Technology of Data Mining
碩士 === 國立政治大學 === 國際貿易研究所 === 95 === We study the performance of open-end mutual funds in Taiwan, and use the technology of data mining to classify the outperforming and underperforming mutual funds. Classification and regression tree (CART) is the method to evaluate and predict the performance of m...
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ndltd-TW-095NCCU53230272015-10-13T14:08:37Z http://ndltd.ncl.edu.tw/handle/30982617229835979292 Evaluating the Performance of Mutual Funds— Using the Technology of Data Mining 分析共同基金績效-使用資料採掘技術 謝明倫 碩士 國立政治大學 國際貿易研究所 95 We study the performance of open-end mutual funds in Taiwan, and use the technology of data mining to classify the outperforming and underperforming mutual funds. Classification and regression tree (CART) is the method to evaluate and predict the performance of mutual funds. In this paper, we utilize thirteen crucial factors to build trees and pick mutual funds by its classification rules. Moreover, we will verify precision of each tree. We find that the CART is a good tool to evaluate the performance of mutual funds in Taiwan because of its stability in outperforming - underperforming spreads. Moreover, we use two kinds of learning sample to build two trees and pick mutual funds to compose of them into the fund of funds. The results are better than the total average returns monthly, and one of them is better than the mutual funds that its investing target is high-tech stocks. 郭維裕 2007 學位論文 ; thesis 46 en_US |
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碩士 === 國立政治大學 === 國際貿易研究所 === 95 === We study the performance of open-end mutual funds in Taiwan, and use the technology of data mining to classify the outperforming and underperforming mutual funds. Classification and regression tree (CART) is the method to evaluate and predict the performance of mutual funds. In this paper, we utilize thirteen crucial factors to build trees and pick mutual funds by its classification rules. Moreover, we will verify precision of each tree. We find that the CART is a good tool to evaluate the performance of mutual funds in Taiwan because of its stability in outperforming - underperforming spreads. Moreover, we use two kinds of learning sample to build two trees and pick mutual funds to compose of them into the fund of funds. The results are better than the total average returns monthly, and one of them is better than the mutual funds that its investing target is high-tech stocks.
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郭維裕 |
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郭維裕 謝明倫 |
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謝明倫 |
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謝明倫 Evaluating the Performance of Mutual Funds— Using the Technology of Data Mining |
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謝明倫 |
title |
Evaluating the Performance of Mutual Funds— Using the Technology of Data Mining |
title_short |
Evaluating the Performance of Mutual Funds— Using the Technology of Data Mining |
title_full |
Evaluating the Performance of Mutual Funds— Using the Technology of Data Mining |
title_fullStr |
Evaluating the Performance of Mutual Funds— Using the Technology of Data Mining |
title_full_unstemmed |
Evaluating the Performance of Mutual Funds— Using the Technology of Data Mining |
title_sort |
evaluating the performance of mutual funds— using the technology of data mining |
publishDate |
2007 |
url |
http://ndltd.ncl.edu.tw/handle/30982617229835979292 |
work_keys_str_mv |
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