1. Economics and Management School, Wuhan University, Wuhan 430072, China; 2. Institute of Systems Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Abstract：Based on multi-agent modeling and simulation method, this paper uses particle swarm optimization (PSO) swarm intelligence algorithm to simulate the learning mechanism and evolution rule of outside investors' valuations under the condition of information interaction, and establishes an equity auction model of venture capital exit on the basis of mechanism design. Simulation analysis of equity auction model on Swarm platform shows that the above-mentioned equity auction mechanism can significantly improve the revenue of venture capitalist, and help venture capitalist to predict the change of outside investors' valuations and auction participation. Simulations of equity auction model's parameters find that venture capitalist can further improve their income by introducing more outside investors to participate in the auction; even outside investors overemphasize the importance of one single learning ability, the relatively satisfactory equity auction results also can be achieved eventually. The study of this article can provide policy references for venture capitalist.
郑君君, 张平, 饶从军, 邵祥民. 基于Swarm的股权拍卖机制设计与仿真研究[J]. 系统工程理论与实践, 2014, 34(4): 883-891.
ZHENG Jun-jun, ZHANG Ping, RAO Cong-jun, SHAO Xiang-min. Research on mechanism design and simulation of equity auction based on Swarm. Systems Engineering - Theory & Practice, 2014, 34(4): 883-891.
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2014, Vol. 34 
