STUDY ON THE RESAMPLING TECHNIQUE FOR RISK MANAGEMENT IN THE INTERNATIONAL PORTFOLIO SELECTION BASED ON CHINESE INVESTORS

被引：1

作者：

Yu, Mei ^{[1
]}

Bian, Jiangze ^{[1
]}

Xie, Haibin ^{[1
]}

Zhang, Qin ^{[1
]}

Ralescu, Dan ^{[2
]}

机构：

[1] Univ Int Business & Econ, Sch Finance & Banking, Res Ctr Appl Finance, Beijing 100029, Peoples R China

[2] Univ Cincinnati, Dept Math Sci, Cincinnati, OH 45221 USA

来源：

INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS | 2013年 / 21卷

基金：

美国国家科学基金会; 国家教育部科学基金资助;

关键词：

Resampling; portfolio optimization; uncertainty; DIVERSIFICATION; CRITIQUE; MODEL;

D O I：

10.1142/S0218488513400035

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we employ the resampling method to reduce the sample errors and increase the robustness of the classic mean variance model. By comparing the performances of the classic mean variance portfolio and the resampled portfolio, we show that the resampling method can enhance the investment efficiency. Through an empirical study of Chinese investors who invest in both Chinese market and other twelve major financial markets, we show that the resampling method helps to improve the performance of the mean variance model.

引用

页码：35 / 49

页数：15

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