Finance syndication in the venture capital industry
We use a database of venture capital deals in Europe to analyse the effects of syndication within the venture capital industry. The database describes funds including their volume, investors and partners, and other information deal-related to the funds / investors. Ventures are segmented into industries, stages and locations.
There is evidence that the way venture capital firms interact has significant influence on the performance of their portfolio companies, as a result, their funds (see Hochberg et al., 2007).
Secondly, there is evidence showing that historical development and the particular structure of social networks in Silicon Valley is one of the key factors, which fostered relatively higher growth and development of the region compared to other regions in the world (Castilla, 2003). However, the literature analysing diverse aspects of the venture capital industry in Europe, in particular the development of networks, is still comparatively scarce compared to the analyses of Silicon Valley. Therefore, we will analyse such effects in-depth for European market players.
We examine the current state and development of networks through syndications within venture capital deals of the past ten years in different regions, with the aim of analysing different types of agents within networks, and understanding whether they are significant for the status of the venture capital industry in related regions.
We found evidence that the effects of syndications vary between different regions. The first results show that this is due to different economic policies within the regions and the financing culture in general. Furthermore, there are indications that connections to strong players outside of Europe have an influence on the local and regional landscape.
We intend to expand our dataframe to Europe and North America in order to conduct deeper research on the role of the world leading venture capital firms (mainly from Silicon Valley). We will also analyse different stages of networks in respect to the development of investment hypes and try to find optimal positions within networks in order to maximise the returns on funds.
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