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Evolution Characteristics of Complex Fund Network and Fund Strategy Identification

School of Business Administration, Hunan University, Changsha 410082, China
School of Business, State University of New York at Oswego, Oswego, NY 13126, USA
School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
Author to whom correspondence should be addressed.
Academic Editors: J. A. Tenreiro Machado and António M. Lopes
Entropy 2015, 17(12), 8073-8088;
Received: 29 October 2015 / Revised: 30 November 2015 / Accepted: 1 December 2015 / Published: 8 December 2015
(This article belongs to the Special Issue Computational Complexity)
Earlier investment practices show that there lies a discrepancy between the actual fund strategy and stated fund strategy. Using a minimum spanning tree (MST) and planar maximally-filtered graph (PMFG), we build a network of open-ended funds in China’s market and investigate the evolution characteristics of the networks over multiple time periods and timescales. The evolution characteristics, especially the locations of clustering central nodes, show that the actual strategy of the open-ended funds in China’s market significantly differs from the original stated strategy. When the investment horizon and timescale extend, the funds approach an identical actual strategy. This work introduces a novel network-based quantitative method to help investors identify the actual strategy of open-ended funds. View Full-Text
Keywords: complex fund network; fund strategy; time period; timescale complex fund network; fund strategy; time period; timescale
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Yang, H.; Fang, P.; Wan, H.; Liu, Y.; Lei, H. Evolution Characteristics of Complex Fund Network and Fund Strategy Identification. Entropy 2015, 17, 8073-8088.

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