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Optimal level of diversification in private equity funds

Abstract

The studies of Gupta & Sapienza (1992) and Norton & Tenebaum (1993) have provided interesting insights into the choice of portfolio strategies by PE firms. However, their argumentation leads to conclusions which need to be scrutinized. The main result of their analysis is that VC firms predominantly involved in seed and early stage financing prefer less industry diversity and a narrower geographic scope in comparison to VC firms focusing on later stage financing. Assuming that seed and early stage investments are riskier than later stage investments, the four authors identified specialization as a strategy to lower the risk of a VC fund. They argue that concentration in particular areas leads to specialized knowledge which allows the PE firm to make superior selection decisions and to provide more value-adding services. If that holds true, specialization should also increase the expected rate of return of a VC fund. Thus, a VC firm could lower its risk and enhance its expected rate of return at the same time by specializing in particular areas. Such a negative risk-return-relationship is at odds with the usual assumption in financial theory that a lower level of risk is related to a lower expected rate of return, and vice versa. Second, if specialization is the dominant strategy for VC firms to lower their risk and concurrently to alter their expected rate of return, why do VC firms still spread their funds across different areas? According to the survey of Norton & Tenebaum (1993), more than half of the respondents’ VC funds had investments in seven or more industries. One third of their sample invested even in ten or more industries. Lastly, gaining specialized knowledge for a certain area is not for free. In order to do so, a PE firm has to invest in specialized assets (e.g. human capital and network ties).15 Moreover, the arguments of Gupta & Sapienza (1992) and Norton & Tenebaum (1993) seem to be contradicted by the results of Weidig & Mathonet (2004) and Schmidt (2004). These studies report risk reduction through ‘naive’ diversification.

Keywords

Optimal Portfolio Risky Asset Capital Asset Price Model Terminal Wealth Portfolio Company 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 16.
    Also compare Markowitz (1999).Google Scholar
  2. 17.
    In the Capital Asset Pricing Model the common factor is the global economy. Thus, systematic risk of an asset is represented by the covariance between the return of the global market portfolio and the return of the asset (Sharpe 1964).Google Scholar

Copyright information

© Deutscher Universitäts-Verlag | GWV Fachverlage GmbH, Wiesbaden 2007

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