Alpha Exchange · October 28, 2026 · 52 min

Randy Cohen, Professor of Entrepreneurship & Finance Harvard Business School Co-Founder, PEO Partners

With Randy Cohen

Summary

Randy Cohen of Harvard Business School and PEO Partners argues that public markets can replicate much of private equity's return profile by targeting the factors that LBO targets already share: high profitability, high payout, low multiples, low risk and small size, with added leverage of roughly 0.3-0.4 turns. He concedes PE keeps two edges, inside information and operational improvements net of control premiums. He claims a liquid PE product for investors who cannot meet million-dollar minimums will trail PE gross by 3-6% a year, but its roughly 600 basis point fee advantage over PE's heavy fee load, which he cites from a CalPERS study, lets it match or beat PE net. Dean Curnutt pushes back that PE's return smoothing is a bug, not a feature, and that the hidden mark-to-market risk matters most. Cohen also warns that seven megacap tech names now make up about 30% of the US market, versus ten names at about 17% in 2013, and says large language models are making research on 10-K risk-factor changes cheap enough to generate many candidate stock ideas.

Key takeaways

Randy Cohen on Private equity: PE outperforms public markets through inside information and operational improvements net of control premiums.
Dean Curnutt on Private equity: PE's smoothed returns are a bug, not a free benefit, and investors must watch mark-to-market risk.
Randy Cohen on US stock market outlook: US index concentration has more than doubled, with seven mega-caps now about 30% of the market.
Randy Cohen on Enterprise AI adoption & AI software: LLMs make previously infeasible quant research ideas practical, which is game-changing for finance research.

What was said, by company and theme

4 views from 2 speakers. Every quote is checked against the episode's transcript (how).

Private equity

Randy Cohen · Harvard Business School
PE outperforms public markets through inside information and operational improvements net of control premiums.
PE does better than a public-market investor could replicate for two reasons. First, PE funds have inside information on companies that public investors never receive, and trading on it would be illegal anyway. Second, PE can make operational improvements to companies. Against that, PE pays a control premium to gain control, but Cohen argues the net of operational gains minus the control premium still leaves something for investors, so PE is outperforming.
“PE has edge from inside information. They have edge from the net of operational improvements minus the control premium.”at 35:15
Dean Curnutt · Macro Risk Advisors
PE's smoothed returns are a bug, not a free benefit, and investors must watch mark-to-market risk.
Curnutt agrees with the 'volatility laundering' label for PE's smoothed reported returns. He says Cliff Asness calls the smoothing a feature rather than a bug, but Curnutt argues it is a bug and that it is hard to believe investors are getting something for free from it. As a derivatives-focused investor, he says the mark-to-market risk that smoothing hides is what matters most.
“Cliff will also say it's become a feature, not a bug, but it is a bug. It's hard to look at that and think that you're really getting something for free.”at 38:04

US stock market outlook

Randy Cohen · Harvard Business School
US index concentration has more than doubled, with seven mega-caps now about 30% of the market.
Cohen compares the largest companies in 2013 with today. In 2013 the ten largest companies made up about 17% of the market and included JPMorgan, ExxonMobil, Johnson & Johnson and Microsoft, so the economy's health was tied to a broad group. Today seven companies make up about 30% of the market, more than double the concentration, and they cluster in software and high tech. He says this is why a portfolio should not be built around the top names, and that a separate allocation should exist for diversification.
“Last I looked like seven companies were, like, 30% of the market as opposed to 10 companies being, like, 17%. So it's double... More than double the concentration.”at 46:04

Enterprise AI adoption & AI software

Randy Cohen · Harvard Business School
LLMs make previously infeasible quant research ideas practical, which is game-changing for finance research.
Cohen points to Lauren Cohen's pre-generative-AI paper. It used machine learning to compare each company's 10-K risk factor section year over year. When the wording changed, the stock on average performed badly afterwards, since lawyers only change risk language when they see a serious risk. He argues that LLMs such as Claude now make this kind of research cheap enough to generate around 50 candidate ideas and select the six that hold up, reducing the hours of researcher time needed to check them. Quant funds are already using this internally, and a friend at a top quant fund now asks Claude for work that once required junior analysts. He calls it game-changing.
“it's obvious the kinds of things that you can now do that would have just been too hard back in the day. And it's super exciting... And it is absolutely game changing.”at 49:59

Topics

AI-driven quant research
PE outperformance vs public markets
PE return smoothing
PE returns replication via public factors
index concentration in megacap tech
liquid PE for individual investors
liquid PE replication

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