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Aim of the paper

To analyze whether PE outperforms public markets.

Key takeaways

• 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.

Aim of the paper

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

Key takeaways

• 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.

Aim of the paper

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

Key takeaways

• 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.

Aim of the paper

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

Key takeaways

• 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.

Aim of the paper

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.

Key takeaways

• 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.

Aim of the paper

To investigate individual manager performance and its persistence.

Key takeaways

• 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.

Aim of the paper

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

Key takeaways

• 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.

Aim of the paper

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

Key takeaways

• 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.

Aim of the paper

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

Key takeaways

• 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.

Aim of the paper

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

Key takeaways

• 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.

Aim of the paper

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.

Key takeaways

• 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

Aim of the paper

To analyze the relationship between certain GP characteristics and fund performance

Key takeaways

• 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

Aim of the paper

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

Key takeaways

• 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.

Aim of the paper

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

Key takeaways

• 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.