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Venture capital investments through the lens of network and functional data analysis

Author

Listed:
  • Christian Esposito
  • Marco Gortan
  • Lorenzo Testa
  • Francesca Chiaromonte
  • Giorgio Fagiolo
  • Andrea Mina
  • Giulio Rossetti

Abstract

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 in- vestors, and a weaker but still detectable association with centrality measures of small investors and features describing firms as knowl- edge 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).

Suggested Citation

  • Christian Esposito & Marco Gortan & Lorenzo Testa & Francesca Chiaromonte & Giorgio Fagiolo & Andrea Mina & Giulio Rossetti, 2022. "Venture capital investments through the lens of network and functional data analysis," LEM Papers Series 2022/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    • Handle: RePEc:ssa:lemwps:2022/07
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    References listed on IDEAS

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    Keywords

    Network analysis; functional data analysis; venture capital; investment trajectory.;
    All these keywords.

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