Working Paper: CEPR ID: DP14241
Authors: Arpit Gupta; Stijn Van Nieuwerburgh
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.
Keywords: Private Equity; Valuation; Temporal Pricing of Risk; Cross-section of Returns; Buyout; Venture Capital; Real Estate; Infrastructure; Natural Resources; Affine Asset Pricing Models
JEL Codes: G24; G12
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| private equity fund cash flows (G23) | risk-adjusted profits (RAP) (G22) |
| systematic risks (G12) | risk-adjusted profits (RAP) (G22) |
| timing and nature of cash flows (G32) | performance of private equity funds (G23) |
| expected returns on PE funds (G12) | declining over time (C41) |
| cash flow replicating portfolio (G19) | risk-adjusted performance metrics (C52) |