In this paper we advance the discussion and describe a recommended approach for constructing a composite private capital benchmark, emphasizing the importance of pooled measures. In it, we also propose a methodology for computing portfolio ranks, which allows the generation of a report containing both pooled and rank measures at all levels of a reporting hierarchy.
Determining whether a portfolio has under- or over-performed requires a benchmark. Private capital portfolios are no different; however, in contrast to listed equities, for these there is no consensus on how to build such a benchmark from sub-components (for instance, vintages or private asset-classes).
In this research brief we explore the pitfalls in measuring portfolio diversification in private capital. To this end we examine two very different methodologies - temporal diversification and cross-sectional diversification - and discuss the shortcomings of each.
In this paper we study a deceptively simple question: how to maintain (or start) a private capital program in such a way as to meet certain goals. For example, suppose one takes over management of a private capital portfolio at a large pension fund, and is tasked with maintaining a valuation of about $1B. At what rate should one commit capital to best achieve this goal?
In this research brief, we compared fund ranks produced by these various performance measures: Internal Rate of Return (IRR), Total Value To Paid-In (TVPI), Kaplan Schoar Public Market Equivalent (KS-PME), Direct Alpha (DA), and Time-Weighted Rate of Return (TWRR). We found that most measures tend to produce similar ranks.
Performance attribution is the process of decomposing a portfolio’s return into subcomponents that are each the result of the decisions that went into the construction of that portfolio. A portfolio is usually assigned a benchmark, and hence the return to be decomposed is its return relative to the benchmark — the active re-turn. If assets are grouped in some way (such as by vintage) then there are two classes of decisions that went into the construction of the portfolio…
In this brief we focus on the effect of two crises — the dot-com crash and the global financial crisis (GFC) — on private capital cash flows, disentangling these effects from those arising from returns. Continue reading.
The results in the first paper showed that contributions and uncalled capital, in addition to age, are a useful predictor of future cash flows. Additionally, we demonstrate that the approach outlined by Takahashi and Alexander underperforms our data-driven models. In this second paper, we deepen this examination, focusing our attention on budgeting for future capital calls.
In this paper we focus on predicting cash flows for private capital funds. We start by discussing the characteristics of cash-flow data that make these predictions challenging, and then examine several models for expected contributions and distributions, and evaluate their performance, both in-sample and out-of-sample.
Performance measurement of private capital investments has been an ongoing challenge for asset owners, asset managers, and investment consultants alike. Internal Rate of Return (IRR), despite its well known shortcomings, is widely used to measure the performance of private capital investments.