Risk Adjustment of Private Equity Cash Flows

Risk Adjustment of Private Equity Cash Flows

Nicola Giommetti and Rasmus Jørgensen

Asset allocation to buyout, venture capital, and other private equity (PE) funds has increased consistently over the past decade. It remains challenging, however, to estimate risk and performance of these funds, especially due to their illiquid secondary market and the consequential absence of reliable return data.

PE returns can be extrapolated from cash flow data as in Ang, Chen, Goetzmann, and Phalippou (2018), but it requires restrictive assumptions on the return-generating process. To avoid those assumptions, Korteweg and Nagel (2016, KN) develops a stochastic discount factor (SDF) valuation framework that uses cash flows instead of returns, and that benchmarks PE against publicly traded assets. Central to the SDF framework is a requirement for proper benchmarking: the SDF must price benchmark assets during the sample period. To satisfy this requirement, KN use a heuristic implementation. They build artificial funds invested in the benchmark assets, and they estimate SDF parameters pricing the artificial funds. In this paper, the authors examine Burgiss’ PE dataset and propose an alternative implementation which estimates a set of SDF parameters so that the subjective term structure of interest rates is determined by market data.