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Comparing business performance of mutual funds

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SKU: PROJ1348 Categories: 2013 Projects, 2014 Projects, Final Year Projects, Online Dotnet Projects Tags: academic projects, Android project 2013-2014, Android project Abstract, Android project list, btech projects, dotnet project 2013-2014, dotnet project Abstract, dotnet project list, elysium technologies abstract, elysium technologies chennai, elysium technologies coimbatore, elysium technologies company, elysium technologies courses, elysium technologies erode, elysium technologies inpant traning, elysium technologies internship, elysium technologies jobs, elysium technologies madurai, elysium technologies mou, elysium technologies pondychery, elysium technologies projectlist, elysium technologies projects, elysium technologies ramnad, elysium technologies salem, elysium technologies software, elysium technologies tirunelveli, elysium technologies trichy, Final Year Projects, java project list, java projects 2013-2014, java projects Abstract, madurai software company, matlab project 2013-2014, matlab project Abstract, matlab project list, mtech projects, phd research work, Php project 2013-2014, Php project Abstract, Php project list, Power Electronic project 2013-2014, Power Electronic project Abstract, Power Electronic project list, project center Bangalore, project center chennai, project center coimbatore, project center Erode, project center Hyderabad, project center Kollam, project center madurai, project center Pandicherry, project center ramnad, project center Salem, project center Tiruneveli, project center trichy, research center, Students Projects, Vlsi project 2013-2014, Vlsi project Abstract, Vlsi project list
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Comparing business performance of mutual funds

Abstract— Comparing business performance of mutual funds. There are many Mutual Funds rating companies in the market. Rating companies have different standards to evaluate Mutual Funds such as risks, incomes and some referable indexes. The study is aim at setting a score criterion to discuss the performance of equity fund, ETF and Index Fund. The objects of this study include eight domestic funds which are set up more than one year. We collect the data which are set up before August, 2008.The study uses Text Mining to choose proper variables. By Cluster Analysis, the similar characteristics of risk and return can be distributed into same group. We analyze the performance of the Mutual Funds for each group. Furthermore, each fund gets scores through the score criterion and tries to compare the study with Morningstar, Lipper, and Fund-Watch. Finally, Discriminant Analysis can determine that new data may be distributed into which cluster.The main conclusions are: 1. According to risk and return, Cluster Analysis can divide Large-sized Equity Fund into three clusters. ETF and Index Fund can also divide into three clusters by the same way. Besides, there are obvious differences between each cluster.2. On the basis of the result, JF (TAIWAN) Taiwan Fund is the best performance in Large-sized Equity Fund. Polaris Taiwan Top 50 Tracker Fund is the best in ETF and Index Fund.3. The accuracy is about 96.03% in Large-sized Equity Funds and 97.35% in Index Funds by Discriminant Analysis. In term of the study, it is immediate to find out the result of cluster and performance evaluation for new data.4. Morningstar, < Final Year Projects > Lipper and Fund-Watch are common rating companies in the market, but the rating of Large-sized Equity Fund is different. In business recession, they can evaluate a better fund relatively, but the evaluated fund can’t increase profit. In this study, the way of rating bases on the outcome of Cluster Analysis and score of the funds. It can not only reduce the loss and risk but also provide objective and useful information to investors.

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