Abstract

http://ssrn.com/abstract=2419299
 


 



Skill and Luck in Private Equity Performance


Arthur G. Korteweg


University of Southern California - Marshall School of Business

Morten Sorensen


Copenhagen Business School; Columbia Business School; National Bureau of Economic Research (NBER); Swedish Institute for Financial Research (SIFR)

April 2014

Rock Center for Corporate Governance at Stanford University Working Paper No. 179

Abstract:     
We evaluate the performance of private equity (“PE”) funds, using a variance decomposition model to separate skill from luck. We find a large amount of long-term persistence, and skilled PE firms outperform by 7% to 8% annually. But this performance is noisy, with a large amount of luck, so top-quartile performance does not necessarily imply top-quartile skills, making it difficult for investors (“LPs”) to identify skilled PE firms. Buyout (“BO”) firms show the largest skill differences, implying the greatest long-term persistence. Venture capital (“VC”) performance is the most noisy, making good VC firms hardest to identify, and implying the smallest amount of investable persistence.

Number of Pages in PDF File: 59

Keywords: Persistence, skill, private equity, venture capital, learning

JEL Classification: G11, G12, G24, C11

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Date posted: April 3, 2014 ; Last revised: April 17, 2014

Suggested Citation

Korteweg, Arthur G. and Sorensen, Morten, Skill and Luck in Private Equity Performance (April 2014). Rock Center for Corporate Governance at Stanford University Working Paper No. 179. Available at SSRN: http://ssrn.com/abstract=2419299 or http://dx.doi.org/10.2139/ssrn.2419299

Contact Information

Arthur G. Korteweg (Contact Author)
University of Southern California - Marshall School of Business ( email )
3670 Trousdale Parkway
Los Angeles, CA 90089
United States
HOME PAGE: http://www-bcf.usc.edu/~korteweg/

Morten Sorensen
Copenhagen Business School ( email )
Solbjerg Plads 3
Frederiksberg C, DK - 2000
Denmark
Columbia Business School ( email )
3022 Broadway
New York, NY 10027
United States

National Bureau of Economic Research (NBER) ( email )
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Swedish Institute for Financial Research (SIFR)
Drottninggatan 89
SE-113 59 Stockholm, SE-113 60
Sweden
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