What Is the Stanford GSB Search Fund Study?
The Stanford Graduate School of Business Search Fund Study is the most comprehensive longitudinal dataset on the search fund asset class. The 2024 edition — covering data through December 31, 2023 — tracks 681 search funds formed since the model's inception in 1984. It is the closest thing the ETA community has to an authoritative benchmark for investor returns, searcher economics, and asset class characteristics.
Every investor considering ETA co-investments and every searcher evaluating the traditional search fund model should understand what this study shows — including its limitations.
The Headline Numbers
The 2024 study reports a 35.1% aggregate IRR and 4.5x aggregate MOIC across all tracked funds. For companies that have already exited, the numbers are stronger: 42.9% IRR for exited companies. Solo searchers returned 30.3% IRR; partner searches returned 40.5% IRR.
These are not median numbers — they are aggregate figures, which means outsized wins pull the average up significantly. The return distribution tells the more complete story.
The Return Distribution: What Investors Actually Experience
Of acquired companies in the Stanford dataset: - 11% returned 10x or more invested capital - 17.5% returned 5x–10x - 25% returned 2x–5x - 18.5% returned 1x–2x - ~28% resulted in partial or total loss
This means roughly 69.5% of acquired companies returned positive results for investors. The remaining ~30% — roughly one in three deals — lost capital. The distribution is highly skewed: the top decile of deals drives a disproportionate share of the aggregate returns.
For investors, this distribution underscores the importance of diversification across multiple deals rather than concentration in a single transaction.
What the Acquisition Economics Look Like
The 2024 study shows a median purchase price of $14.4 million for traditional (funded) search fund acquisitions, at a median EBITDA multiple of 7.0x. Median EBITDA at acquisition was $2.2 million, with a median EBITDA margin of 27%.
These numbers reflect the traditional, fully-funded search model — where a searcher raises $400K–$600K in search capital from 10–15 institutional investors before beginning the acquisition process. Self-funded searches typically target smaller businesses (sub-$3M EBITDA) at lower multiples (3–5x), resulting in different acquisition economics and a different return profile.
The Scale of the Market
In 2023 alone, 94 new search funds launched — a record number. The acquisition success rate across all tracked funds is 63%: of every 100 searchers who raise traditional search capital, approximately 63 successfully close an acquisition. The median time from first investor capital to acquisition close is 20 months.
What This Means for Searchers
The 63% acquisition success rate is meaningful: more than one in three traditionally funded searchers does not close a deal, returns capital to investors, and moves on. That figure is lower for self-funded searches, where the financial pressure to close is higher and the infrastructure support (management fee, LP network) is absent.
The top industries for closed acquisitions in the 2024 data: healthcare (25%), business services (25%), software and technology (22%), and tech-enabled services (16%). These sectors reflect where sustainable, recurring revenue is most consistently found in the small business market.
What This Means for Investors
A 35.1% aggregate IRR compares favorably to traditional private equity (typically 15–20% net IRR for top-quartile managers) and dramatically outperforms public market benchmarks over equivalent periods. The caveat is deal-level risk: the distribution is wide, and roughly 30% of deals lose money.
Investors who co-invest deal-by-deal — rather than through a blind pool — can apply their own diligence and selectivity, potentially improving their portion of the return distribution. The key variables are operator quality and business quality. Both are assessable before capital is committed.
Limitations of the Data
The Stanford study tracks traditional, funded search funds — not self-funded searches, which have become the dominant model by volume over the past five years. Self-funded searches operate under different economics (no management fee, higher founder equity, often smaller target businesses) and their returns are not comprehensively tracked in a comparable longitudinal dataset.
Additionally, aggregate IRR figures are materially influenced by the timing of fund formations and exits relative to broader economic cycles. Results from funds formed in different years vary significantly.
*Source: Stanford Graduate School of Business, 2024 Search Fund Study (data through December 31, 2023), tracking 681 search funds. Past performance is not indicative of future results.*