摘要
运用PSO群体智能算法模拟信息交互条件下外部投资者报价决策的学习机制和演化规律,在此基础上设计了实现风险投资退出的股权拍卖机制。Netlog仿真结果表明,所设计的股权拍卖机制能在一定程度上揭示股权的真实价值,并降低竞买人和卖方之间的信息不对称程度。进一步的仿真分析结果表明:适当的激励力度对外部投资者的投标报价具有显著影响;引入更多的竞买人能产生更有利于风险投资家的拍卖结果;即使外部投资者过于强化单一的学习能力,最终也可得到相对理想的拍卖结果,从而证明了所设计的股权拍卖机制具有广泛的适用性。
This paper uses PSO swarm intelligence algorithm to simulate the learning mechanism and the evolution of outside investor＇s tender offer,and designs a reasonable equity auction mechanism. Netlogo simulation results show that the above-mentioned equity auction mechanism could reveal the real value of equity and has the ability to reduce information asymmetry degree. Further simulation analysis shows as follows： reasonable incentive could significantly affect outside investor＇s tender offer;the introduction of more bidders could produce more favorable auction results;although outside investors overemphasize the importance of a single learning ability, the satisfactory auction result could be achieved eventually,which proves the broad applicability of equity auction mechanism.
出处
《技术经济》
CSSCI
2013年第3期118-124,共7页
Journal of Technology Economics
基金
国家自然科学基金项目"基于演化博弈与多主体仿真的风险投资股权拍卖机制研究"(71071120)
关键词
股权拍卖
PSO群体智能算法
信息不对称
仿真分析
风险资本退出
equity auction
PSO swarm intelligence algorithm linformation asymmetry
simulation analysis
venture capital exit
