Yale Case. By: Daniel Lazier, Jacob Thomas, and A. J. Wasserstein
Since the 1980s, the SF model has grown exponentially. According to Stanford’s 2024 study, nearly 100 traditional search funds were launched in 2023 alone, and almost $700 million was invested in 2022–2023.
The model’s attraction lies in its reported returns: aggregate IRRs in the mid-30% range and MOICs around 4.5x. However, the Yale study questions whether individual investors actually achieve these outcomes. It analyzes real investor data rather than entrepreneur-reported results, to determine how investors truly fare once access, selection, and capital allocation constraints are considered.
Study overview:
The research draws on a dataset from 12 investors across 23 funds, representing 1,192 investment decisions:
- 768 involved actual acquisitions (64% conversion rate).
- Data includes each investor’s participation, allocation, and resulting MOICs.
- Both exited and ongoing deals are considered, using current valuations when applicable.
This provides a unique, granular look at how investor behavior (access, selection, and sizing) affects realized portfolio outcomes.
Key findings:
1/ Actual investor returns are lower than the Stanford benchmarks
- The weighted average MOIC across all investors is 2.5x, compared with 4.5x reported by Stanford.
- The mean MOIC excluding broken searches is 2.78x, and the median is 1.6x.
- No investor or fund in the Yale sample achieved Stanford-level returns.
- While these results still compare favorably with traditional PE (median MOIC ≈ 1.8x), they reveal that the SF index substantially overstates what most investors actually experience.
2/ Returns vary widely due to access and allocation
- Stanford’s dataset functions as an index of all SF outcomes, assuming universal access and equal weighting.
- In reality, investors face access constraints (they do not see or are not invited into every deal) and must make allocation decisions (how much to invest in each opportunity).
- Portfolio results therefore vary significantly. Some investors overbet on duds or miss the biggest winners, creating dispersion in actual outcomes.
3/ Dependence on “Griffins” – rare 10x+ deals
- Exceptional outcomes (MOIC > 10x), labeled “griffins” by the authors, are exceedingly rare but disproportionately drive portfolio success.
- Only 3% of Yale’s sample reached this level, versus 11% in Stanford’s data.
- Removing these few outliers sharply reduces overall portfolio MOICs—illustrating how much performance depends on a handful of extraordinary deals.
4/ The distribution of outcomes is highly skewed
- 58% of investments produced MOICs below 2.0x.
- Only 31% of completed deals exceeded 3.0x.
- Mean MOIC (2.78x) is significantly higher than the median (1.6x), confirming a right-skewed distribution with a long tail of rare winners.
- The pattern resembles venture capital more than private equity: a few “griffins” offset many mediocre or losing investments.
5/ Number of bets does not ensure better performance
- Statistical analysis found no significant correlation between the number of deals backed and portfolio MOICs.
- More bets may improve access but do not guarantee exposure to the best deals or better weighting on winners.
Investor & entrepreneur implications:
1/ SF investing is harder than it looks
- The data challenges the perception that ETA investing consistently delivers exceptional returns.
- Success requires superior access, selection, and capital allocation, which only a minority of “super investors” achieve.
- Many new entrants underestimate the difficulty of matching Stanford-level performance.
2/ Portfolio results depend heavily on outliers
- Missing even a single 10x+ deal can materially depress overall returns.
- Capturing these outliers often requires privileged access to top entrepreneurs or established status within the ecosystem.
- Most investors will see MOICs between 2x–3x, translating to roughly 15–25% IRRs over five years, strong but far from the headline figures.
3/ Entrepreneurs should set realistic expectations
- Only about half (51%) of searchers generate a positive return (≥ 1.0x).
- Including broken searches, the odds of achieving a meaningful outcome (> 3.0x) are closer to 20%.
- Aspiring entrepreneurs should remain optimistic but base expectations on median, not exceptional, results.
Comparison with Stanford’s Findings
| Metric | Stanford (2024) | Yale (2025) |
| Aggregate MOIC | 4.5x | 2.5x |
| 10x+ Outcomes | 11% | 3% |
| Total Losses | 34% | 23% |
| Partial Losses | 66% | 77% |
| Acquisitions as % of Searches | 63% | 64% |
The Yale results suggest that Stanford’s figures, while accurate for the population of entrepreneur-reported outcomes, do not represent what investors can realistically achieve, since few can access every deal or allocate optimally.
In short, the Stanford benchmark is an aspirational index, not a practical proxy for actual investor performance.
Conclusions:
- SF investing delivers solid but variable results. Most portfolios fall short of headline Stanford returns, clustering around 2.0x–3.0x MOIC.
- Success depends disproportionately on access and luck. Capturing even one “griffin” can elevate an entire fund’s performance.
- The asset class resembles VC more than PE, with many low or moderate outcomes and a few exceptional ones driving averages.
- Investors should approach ETA with humility and patience, recognizing that it is neither easy nor guaranteed, and entrepreneurs should calibrate expectations accordingly.
Read the full case in: https://som.yale.edu/sites/default/files/2025-10/How%20are%20Search%20Fund%20Investors%20Really%20Faring.pdf
