Nowcasting Net Asset Values: The Case of Private Equity
63 Pages Posted: 14 Jan 2020 Last revised: 1 May 2020
Date Written: April 16, 2020
We apply advances in analysis of mix frequency and sparse data to estimate "unsmoothed" private equity (PE) Net Asset Values (NAVs) at the weekly frequency for individual funds. Using simulations and a large sample of buyout and venture funds, we show that our method yields superior estimates of fund asset values than a simple approach based on comparable public asset and as-reported NAVs. The market beta of an average buyout [venture] fund, at 1.05-1.10 [1.20-1.32], is notably lower than previous studies suggest, while nudging higher exposures results in inferior nowcasts. The overall risk of a median buyout [venture] fund is 33% [38%] per year if measured in standard deviations of total returns, an increase of 10  percentage points relative to the series based on as-reported NAVs. However, we find significant variation in systematic and idiosyncratic risk within and across vintages---the risk-return profile based on the samples from the 1990s is not representative of currently operating funds. Our method easily accommodates additional data, such as individual holdings, relevant M&As, etc; and applies to other illiquid portfolios. As an example application, we show how the cross section of appraisal biases and nowcast errors evolved around the 2008 financial crisis. The case yields insights on private markets in the aftermath of COVID-19.
Keywords: Private Equity, Venture Capital, Leveraged Buyouts, Institutional Investors, State Space Models, Machine Learning
JEL Classification: G23, G24, G30
Suggested Citation: Suggested Citation