Parameterizing Opportunity Set Risk and Search Costs within Venture Capital Markets

71 Pages Posted: 19 Aug 2014 Last revised: 5 Dec 2018

Date Written: December 4, 2018

Abstract

This study develops a theoretical model that parameterizes cross-sectional differences in opportunity set risk within venture capital markets. The theoretical model shows clusters of venture capital activity can be induced by non-monotonic relations that obtain between search costs for projects with the best risk-return profiles, and the opportunity (return) benefit of deal screening. The model generates functional forms for deal screening costs, and consistent with normativeness of ambiguity aversion, provides a formal theoretical rationale for dichotomy of deal screening ability (equivalently, reputation) from portfolio performance. Theoretical predictions demonstrate outcomes typically attributed to either of preferences or ability are endogenously induced by VCs' spatial location, as such provide formal evidence for presence of ambiguity aversion (uncertainty as to sources of VCs' success) in populations of VCs' investors. Without recourse to data on transaction volumes, model parameters successfully rank venture capital markets in states of California, Massachusetts, and New York as three of the most efficient venture capital markets. The study generates two robust empirical metrics, and efficiency parameters for cross-sectional variations in opportunity set risk.

Keywords: Venture Capital, Investments, Opportunity Sets, Search Costs, Risk, Deal Screening, Market Efficiency, Rational Expectations, Equilibrium Prices

JEL Classification: G24, G11, G14

Suggested Citation

Obrimah, Oghenovo A., Parameterizing Opportunity Set Risk and Search Costs within Venture Capital Markets (December 4, 2018). Available at SSRN: https://ssrn.com/abstract=2482215 or http://dx.doi.org/10.2139/ssrn.2482215

Oghenovo A. Obrimah (Contact Author)

FISK University ( email )

1000 17th Ave N
Nashville, TN TN 37208-3051
United States
4049404990 (Phone)

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