We examine style drift in venture capital investing using 344,491 VC firm-financing rounds between 1980 and 2010. We locate each VC financing round in one of twenty styles, and develop a measure of a change in a VC's styles ("style drift") that is time consistent and independent of firm size. VC...

Using a big data set of venture capital financing and related startup firms from Crunchbase, this paper develops a machine-learning model called CapitalVX (for "Capital Venture eXchange") to predict the outcomes for startups, i.e., whether they will exit successfully through an IPO or...

While venture capitalists (VCs) can choose from thousands of potential syndicate partners, many co-syndicate with small groups of preferred partners. We term these groups “VC communities.” We apply computational methods from the physical sciences to three decades of syndication data to...

While VCs can choose from thousands of potential syndicate partners, many prefer to co-syndicate with partners drawn from small groups of preferred partners, whom we term "VC communities." Using computational methods from the physical sciences, we identify communities from three decades of...