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Empirical study on mutual fund objective classification
作者姓名:金雪军  杨晓兰
作者单位:College of Economics,Zhejiang University,Hangzhou 310027,China,College of Economics,Zhejiang University,Hangzhou 310027,China
基金项目:Project supported by the National Foundation of Social Sciences(No.O2BJY131) and by the Science and Technology Program ofZhejiang Province (No. 021110168)
摘    要:INTRODUCTION Financial theory and practices suggest thatmutual funds can use information advantage andsubdivide financial markets according to prefer-ences of investors. They are the reasons for the em-ergence and tremendous development of the mutualfund industry in recent decades. Mutual funds in-vestors have different risk preference resultingfrom different levels of income, resources of in-come and psychological characters. Consequently,they will choose mutual funds to suit their needs…


Empirical study on mutual fund objective classification
JIN Xue-jun,YANG Xiao-lan.Empirical study on mutual fund objective classification[J].Journal of Zhejiang University Science,2004(5).
Authors:JIN Xue-jun  YANG Xiao-lan
Abstract:Mutual funds are usually classified on the basis of their objectives. If the activities of mutual funds are consistent with their stated objectives, investors may look at the latter as signals of their risks and incomes. This work analyzes mutual fund objective classification in China by statistical methods of distance analysis and discriminant analysis; and examines whether the stated investment objectives of mutual funds adequately represent their attributes to investors. That is, if mutual funds adhere to their stated objectives, attributes must be heterogeneous between investment objective groups and homo- geneous within them. Our conclusion is to some degree, the group of optimized exponential funds is heterogeneous to other groups. As a whole, there exist no significant differences between different objective groups; and 50% of mutual funds are not consistent with their objective groups.
Keywords:Mutual funds classification  Distance analysis  Discriminant analysis
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