Valuing Private Equity Strip by Strip

Arpit Gupta and Stijn Van Nieuwerburgh

No 26514, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We propose a new valuation method for private equity investments. First, we construct a cash-flow replicating portfolio for the private investment, applying Machine Learning techniques on cash-flows on various listed equity and fixed income instruments. The second step values the replicating portfolio using a flexible asset pricing model that accurately prices the systematic risk in bonds of different maturities and a broad cross-section of equity factors. The method delivers a measure of the risk-adjusted profit earned on a PE investment and a time series for the expected return on PE fund categories. We apply the method to buyout, venture capital, real estate, and infrastructure funds, among others. Accounting for horizon-dependent risk and exposure to a broad cross-section of equity factors results in negative average risk-adjusted profits. Substantial cross-sectional variation and persistence in performance suggests some funds outperform. We also find declining expected returns on PE funds in the later part of the sample.

JEL-codes: G00 G11 G12 G23 G32 R30 R51 (search for similar items in EconPapers)
Date: 2019-11
New Economics Papers: this item is included in nep-big, nep-cfn, nep-cmp and nep-fmk
Note: AP CF
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Working Paper: Valuing Private Equity Strip by Strip (2019)
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