SVM-based venture capital management team performance evaluation model

Ma Xiaoning, Tian Zengrui
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引用次数: 1

Abstract

With the launch of fund of fund as well as the growth of private and institutional investors, demand for professional venture capital (VC) management team for China's VC market is day by day on the rise thus performance evaluation on VC management team has attracted great attention in VC research area. Currently, it has not yet established a systematic VC management team performance evaluation system, neither had an authorized evaluation method. In combination of literature review and interview with senior experts in VC industry, this paper proposes a performance evaluation system suitable to China's VC management teams based on Balanced Score Card(BSC), which contributes both to investors and VC management team themselves. Meanwhile, Support Vector Machine (SVM) is introduced into the performance evaluation, and the evaluation issue is transformed to a classification issue. The result shows that SVM-based VC management team performance evaluation model has superior evaluation effects compared with traditional evaluation and classification method, to some extent easing the evaluation problems such as high subjectivity, weak extension ability and small volume samples.
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基于svm的风险投资管理团队绩效评价模型
随着基金的基金的推出以及私人投资者和机构投资者的增长,中国风险投资市场对专业风险投资管理团队的需求日益增加,因此对风险投资管理团队的绩效评估受到了风险投资研究领域的高度关注。目前还没有建立系统的VC管理团队绩效考核体系,也没有授权的考核方法。本文结合文献综述和对风险投资行业资深专家的访谈,提出了一种适合中国风险投资管理团队的基于平衡计分卡(BSC)的绩效评估体系,这对投资者和风险投资管理团队都有好处。同时,将支持向量机(SVM)引入到性能评价中,将评价问题转化为分类问题。结果表明,基于支持向量机的VC管理团队绩效评价模型与传统的评价和分类方法相比具有更优的评价效果,在一定程度上缓解了评价主观性高、可拓能力弱、样本体积小等问题。
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