Fuzzy regression model for forecasting impact of venture capital network and underwriter network on IPO premium

Abstract

In recent years, social network analysis is one of the top 20 fields of artificial intelligence. Based on the network signal theory, this study examines the influence of the dual network embeddedness on the premiums of Chinese initial public offerings (IPOs). In this paper we proposed fuzzy regression model for forecasting the impact of venture capital network and underwriter network on IPO premium based on some hypothesis. We find that: (1) Enterprises embedded in the central position of venture capital network will increase the IPO secondary market premium; (2) Secondly, employing underwriter in the central position of underwriting network will increase the IPO secondary market premium; (3) As venture capital are getting closer to the central position of venture capital network, the influence of underwriter network centrality in underwriting network on the increase of IPO secondary market reaction will gradually weaken. The research shows that occupying central position both in venture capital syndication network and underwriting network have the functions of sending signals, then increase the IPO secondary market premium, but the functions of different network signals will replace each other.