Research

• To analyze whether PE outperforms public markets.

• Over the past 15 years, PE has outperformed both the S&P 500 and the MSCI World.
• Over L15Y buyout has generated 5x at a CAGR of 13% and S&P 500 3x at an 8% CAGR.
• Industry specialization of GPs results in higher return multiples.
• More active involvement with portfolio companies results in higher returns.

• To test fund performance prediction models using machine learning (ML) algorithms.

• The tested models showed an accuracy of 69% in terms of selecting buyout funds whose performance exceeds a predetermined performance threshold, suggesting that there is indeed a meaningful benefit for quantitative models in fund selection i.e. nearly 70% of the time the ML algorithms alone were able to select fund manager that outperformed the public market benchmarks.

• The paper proposes a new framework aimed at evaluating utility costs to imperfectly diversified PE investors relative to a fully diversified benchmark

• Funds-of-funds are generally worth their fees-on-fees for small, constrained investors.
• An investment program of about 5 PE funds per year results in negligible costs of underdiversification.
• A generalist FoF strategy outperforms direct fund investing for relatively risk-averse investors whose portfolios consist of fewer than five PE funds per year.
• for many LPs, the famed performance persistence in PE is actually less important for portfolio choice than diversification considerations.

• Development of a framework allowing for a fair comparison across different skill levels

• Careful selection of choices such as the default investment for uncalled and uncommitted capital, the level of diversification across both funds and vintages has a meaningful impact on the risk-adjusted returns of a private asset portfolio.
• Uplift in risk adjusted returns is about 15% for buyout funds.
• Fund diversification can significantly improve risk-adjusted returns: from 0.25 (return per year/annual return volatility) with one fund per vintage to almost 0.70 with five funds, and 1.00 for ten.

• To explore the links between operational changes and investor returns and in the process open up the black box of value creation in private equity using unique data.

• We find evidence of economies of specialization - an action item is more likely to be successfully implemented if the fund’s other deals pursue related actions, especially in the case of governance engineering and operational improvements.
• Portfolio companies significantly improve operations, boost top-line, engage in financial engineering, and reduce their working capital needs. Most of these changes turn out not to be temporary: they persist even after PE firms exit.
• Successful implementation of plans is an important predictor of returns, while no single strategy on its own predicts returns. This has a potentially important implication for LPs: rather than selecting which PE funds to invest in based on their intended strategies, LPs should base their fund selection on a track record of successful execution of value creation plans.

To investigate individual manager performance and its persistence.

• There is evidence for deal-level gross PME performance persistence.
• In explaining the cross-section of deal returns, the individual is around four times more important than the PE organization.
• Interestingly, none of the typical human capital variables (age, gender, MBA, PE tenure) has explanatory power in the cross-section of deal returns.

To estimate the extent to which manager skill affects the returns from their private equity investments

• The variance of actual performance is higher than would be expected by chance, suggesting that some investors consistently outperform.
• An investor’s skill level in fund selection is a more important driver of their returns, than luck or access to managers.
• An increase of one standard deviation in skill leads to a three-percentage point increase in IRR.

• To build a risk framework for assessing the risk of illiquid assets and constructing a portfolio of such assets.

• Overall, risk for real assets lies between that of equities and that of bonds.
• The safest asset class is private debt via direct lending, while the riskiest is private equity via secondaries.
• Fund of funds are the least risky type of investment among PE funds.

• To evaluate the performance of private equity (“PE”) funds, using a variance decomposition model to separate skill from luck

• Large amount of long-term persistence, and skilled PE firms outperform by 7% to 8% annually.
• Buyout (“BO”) firms show the largest skill differences relative to VC, implying the greatest long-term persistence.
• The reported coefficients show that the previous fund’s performance strongly predicts the performance of the subsequent fund.

• To explore the application of some of the key principles of Modern Portfolio Theory (MPT) to private equity portfolio management.

• It is possible to get a performance improvement as large as 20% in some public pension fund portfolios by applying MPT to PE portfolios. On average, the Modified portfolios produce a 10% improvement across all of the individual portfolio experiments, with a maximum of improvement of 18% (CALPERS).
• The results indicate that an Efficient Frontier consisting of portfolios that have optimal risk/return characteristics also exists for Private Equity.

• To review and challenge the key myths that have historically guided and continue to guide investor selection behavior by analyzing industry-wide and investor-specific performance data.

• The performance of a fund does NOT directly track the performance of the prior funds i.e. good funds do not continue to do well and bad funds do not continue to do badly.
• Persistence is limited and at most restricted to a window of 3 funds. In general, there is decreasing correlation between successive funds performances.
• The analytical selection of good managers is a much better strategy than simply going with the managers that have delivered strong performance in the past

• To analyze the relationship between certain GP characteristics and fund performance

• Selection schemes only based on past GP performance measures do not improve portfolio performance significantly above the median
• Instead, the key to improving fund selection is to use the correct combination of several key criteria. The key criteria include relative historical performance (i.e. against a peer group) as well as measures of GP experience

• To analyze investment styles and performance across several different classes of investors, known as limited partners

• On average, endowments’ average annual returns from PE funds are nearly 14% greater than the average investor.
• Endowments and public pension funds generally are much less likely to reinvest in a given partnership than all other LP classes.
• Moreover, these two classes of LPs are better at forecasting the performance of follow-on funds. Follow-on funds in which endowments decide to reinvest show much higher performance than those funds where they decided not to reinvest.
• Performance is positively correlated to the number of endowments investing in the fund, but negatively related to the number of banks investing.
• The performance of university endowments is correlated with measures of the quality and loyalty of the student body
• Experience, sophistication, and access – attributes commonly associated with LP skill – are among the top factors that cause a wide variation in the returns that institutional investors realize from private equity.

• To assess the risk profile of the different types of PE investments

• Diversification is of utmost importance in private equity, because it significantly reduces risk:
  • A direct investment has a 30% probability of total loss.
  • A fund (or a portfolio of direct investments) has a very small probability of total loss.
  • A fund-of-funds (or a portfolio of funds) has a small probability of any loss.