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The Cost of Capital for Alternative Investments


Jakub W. Jurek


Princeton University - Bendheim Center for Finance; National Bureau of Economic Research (NBER)

Erik Stafford


Harvard Business School - Finance Unit

June 15, 2011

Harvard Business School Working Paper No. 1910719

Abstract:     
We develop a simple state-contingent framework for evaluating the cost of capital for non-linear risk exposures, and show that properly computed required rates of return are meaningfully higher than indicated by linear factor models. Given the large allocations of typical investors in alternatives, many have not covered their cost of capital, despite earning an annualized excess return of 6.3% between 1996 and 2010. A simple derivative-based strategy, which accurately matches the risk profile of hedge funds, realizes an annualized excess return of 10.2% over this sample period, while providing monthly liquidity and complete transparency over its state-contingent payoffs. Linear clones based on popular factor models deliver annualized risk premia of 0-3% over the same period.

Number of Pages in PDF File: 55

Keywords: hedge funds, downside risk, replication, performance evaluation, risk management, endowment model

JEL Classification: G12, G23, G31

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Date posted: January 14, 2013  

Suggested Citation

Jurek, Jakub W. and Stafford, Erik, The Cost of Capital for Alternative Investments (June 15, 2011). Harvard Business School Working Paper No. 1910719. Available at SSRN: http://ssrn.com/abstract=1910719 or http://dx.doi.org/10.2139/ssrn.1910719

Contact Information

Jakub W. Jurek (Contact Author)
Princeton University - Bendheim Center for Finance ( email )
26 Prospect Avenue
Princeton, NJ 08540
United States
(609) 258-4037 (Phone)
HOME PAGE: http://www.princeton.edu/~jjurek
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Erik Stafford
Harvard Business School - Finance Unit ( email )
Boston, MA 02163
United States
617-495-8064 (Phone)
617-496-7357 (Fax)
Feedback to SSRN (Beta)


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