벤처투자조합(VC)의 성과보수 계약: 기준수익률을 중심으로
Copyright 2024 THE KOREAN ACADEMIC SOCIETY OF BUSINESS ADMINISTRATION
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Using 2,234 fund-level data over a period of 20 years from 2002 to 2022 collected from the Disclosure Information of Venture Capital Analysis (DIVA), this paper examines the determinants of hurdle rate in the performance contracts between Limited Partners (LPs) and General Partners (GPs) of venture capital partnerships and further investigates the impact of the hurdle rate on the fund performance. The paper shows that the economic factors at the time of fund establishment – namely, fund characteristics, GP characteristics, fund classification, and the vintage year - explain about 34.4% of the total variation in the hurdle rate. Furthermore, this paper also shows that the hurdle rate predicted ex-ante by the economic factors is positively correlated with ex-post performance of the fund while the discretionary (i.e. unpredicted) hurdle rate is negatively correlated with ex-post performance of the fund. To the best of authors' knowledge, this paper is the first to show the determinants of the hurdle rate based on a novel dataset. Moreover, this paper also shows preliminary evidence of efficient contracting between LPs and GPs by showing that the ex-ante predicted hurdle rate positively predicts ex-post performance of the fund.
Keywords:
venture capital, hurdle rates, performance contract, fund performanceReferences
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∙ The author Hyun Jong Na is an assistant professor of accounting at the Hanyang University Business School. He earned his bachelor's degree in accountancy from the University of Illinois - Urbana Champaign and has work experience at JKL Partners Private Equity. He earned his master's in business administration (major in accounting) from Seoul National University and his Ph.D. in business administration (major in accounting) from The George Washington University. His main research areas include disclosure, fundamental analysis, big data, and AI.
∙ The author Seung Woo Hong is a Ph.D. student at the Hanyang University. He earned his bachelor‘s degree from the same university and worked at KPMG Samjong as a certified public accountant (KICPA). Currently, he serves at Grant Thornton Daejoo, offering accounting, tax advisory and valuation services for VC firms and startups.