论文标题
通过网络和功能数据分析的视角投资风险投资
Venture Capital investments through the lens of Network and Functional Data Analysis
论文作者
论文摘要
在本文中,我们根据具有吸引投资的能力来表征风险资本支持的公司的业绩。该研究的目的是确定从公司和投资者关系的网络结构建立成功的相关预测指标。为了关注卫生部门的交易级数据,我们首先在公司和投资者之间建立了一个两部分网络,然后应用功能数据分析(FDA)来逐步得出二进制,标量和功能性结果捕获的成功指标。更具体地说,我们采用不同的网络中心度措施来捕捉早期投资在公司成功方面的作用。我们的结果对不同的规格具有牢固的态度表明,成功与公司及其大型投资者的中心度度量具有牢固的积极联系,并且与小型投资者的中心度度量和特征相关的较弱但仍然可检测到的关联,并将公司描述为知识桥梁。最后,根据我们的分析,成功与公司和投资者的传播权力(谐波中心性)无关,也与投资者社区(聚集系数)和传播能力的紧密联系(poteerank)相关。
In this paper we characterize the performance of venture capital-backed firms based on their ability to attract investment. The aim of the study is to identify relevant predictors of success built from the network structure of firms' and investors' relations. Focusing on deal-level data for the health sector, we first create a bipartite network among firms and investors, and then apply functional data analysis (FDA) to derive progressively more refined indicators of success captured by a binary, a scalar and a functional outcome. More specifically, we use different network centrality measures to capture the role of early investments for the success of the firm. Our results, which are robust to different specifications, suggest that success has a strong positive association with centrality measures of the firm and of its large investors, and a weaker but still detectable association with centrality measures of small investors and features describing firms as knowledge bridges. Finally, based on our analyses, success is not associated with firms' and investors' spreading power (harmonic centrality), nor with the tightness of investors' community (clustering coefficient) and spreading ability (VoteRank).