What a search fund actually pays for a company

The median company bought by a search fund in 2024 and 2025 cost $16.0 million, earned $2.5 million of EBITDA and changed hands at 6.2 times EBITDA, according to the Stanford Graduate School of Business 2026 Search Fund Study. For 2022 and 2023 the same median was about 7 times. The number that matters more than either, if you are the searcher signing the letter of intent, is where 6.2 sits against everyone else buying companies of that size. It sits almost exactly on top of them, and that decides where a searcher's return now has to come from.

The study is the reference work on the model. Peter Kelly, Stefanos Zenios and Dom Ng at Stanford track more than 850 traditional, investor-backed search funds formed in the United States and Canada since 1984, with data through 31 December 2025. Self-funded searchers who buy with an SBA loan and their own savings are not in it. The headline returns are the ones quoted in every searcher's fundraising deck: an aggregate internal rate of return of 33.9 percent, a return on invested capital of 4.75 times, and a public market equivalent of 2.88 against the S&P 500. This essay is about the less-quoted numbers underneath them.

I price private companies for a living, more than a thousand of them, and before that I spent years on the buy side in corporate development at Fortune 500 scale. When a searcher asks me whether a price is fair, the real question is almost never fairness. It is whether the deal still works, for the people funding it, at that price. Here is the arithmetic I use to answer it.

What 6.2 times buys

The median search fund acquisition in the 2024 and 2025 cohort was a company with an enterprise value of $16.0 million, $2.5 million of EBITDA and a 25 percent EBITDA margin. Across the study's whole history the median purchase price is $13.5 million, at about 6.3 times. The industries searchers targeted most in 2024 and 2025 were services, software and education.

That is not a small business in the Main Street sense, and the difference matters for anyone comparing prices. Most of the transactions in the Felpel Private Company Index are online and asset-light companies under $5 million of enterprise value, and they trade on seller's discretionary earnings, a measure that adds the owner's own pay back into profit. Their median is 2.67 times SDE. A searcher's target is priced on EBITDA, after a market salary for the chief executive, because the searcher is about to become that chief executive and draw that salary. The two multiples are not the same unit. Putting 2.67 next to 6.2 as if one were cheap and the other expensive is the most common mistake I see in this corner of the market.

Searchers pay the going rate for their size

The fair comparison is against other buyers of companies the same size, on the same EBITDA basis. Two independent sources cover that band.

The IBBA and M&A Source Market Pulse survey for the second quarter of 2026 reported that transactions between $5 million and $50 million averaged 5.8 times EBITDA, the highest reading since the first quarter of 2022. In my own index, the $5 million to $50 million band clears at a median 6.4 times EV/EBITDA. That band is drawn from a broader universe than the online and asset-light core of the index, and it is a median where IBBA reports an average, so read it as a second opinion on the level rather than a matched control.

Put the three side by side: search funds paid 6.2 times, the band's average was 5.8 and its median 6.4. Three sources that share no data land within about half a turn of one another.

That convergence is the finding. Part of the original case for the search fund was an arbitrage: a capable operator buys a solid company from a retiring founder with no institutional buyer in sight, at a price below what a professional acquirer would pay. At the median, in the current data, that discount is not visible. A searcher backed by a dozen or so investors is paying roughly what private equity funds, independent sponsors and strategic acquirers pay for a company of that size, which is what you would expect in a band where the same IBBA survey found 87 percent of deals above $5 million drew three or more offers.

None of that makes the model broken. It means the return has to come from running the company better and growing it, not from having bought it cheaply. And that puts the entry multiple under a different kind of pressure.

What one turn of entry multiple costs

The multiple is the one variable in the deal that a searcher sets on the first day and cannot change afterwards. Here is what it does to the equity, on an illustrative version of the median company. It is a worked example, not a client.

Take $2.5 million of EBITDA. Assume senior debt of 3.0 times EBITDA at close, which is $7.5 million, half of it repaid over a five-year hold. Assume EBITDA grows 12 percent a year to about $4.4 million, which is a good five years rather than a base case. Assume the company sells at the end for the same multiple it was bought at. Ignore fees, search costs and the searcher's own stake, so that what is left is the whole equity return before anyone splits it.

At 5.0 times, the price is $12.5 million, the equity cheque is $5.0 million, and it comes back as about $18.3 million: 3.7 times the money, roughly 30 percent a year.

At 6.2 times, the price is $15.5 million and the equity cheque is $8.0 million. It comes back as about $23.6 million, which is 2.9 times, roughly 24 percent a year.

At 7.0 times, the price is $17.5 million, the equity is $10.0 million, and the result is about $27.1 million: 2.7 times, roughly 22 percent a year.

Notice where the extra price goes. Lenders size debt off EBITDA, not off the purchase price, so every additional turn the searcher pays is funded entirely with equity. Moving from 5.0 to 6.2 times raises the price by 24 percent and the equity cheque by 60 percent. That is why a turn of multiple hurts a leveraged buyer far more than the change in the headline price suggests.

Now change one assumption. Buy at 6.2 times and sell five years later at 5.0. The same company, the same growth and the same debt paydown return about $18.3 million on $8.0 million: 2.3 times, about 18 percent a year. The operating work was identical in every case. The difference is entirely the price paid on the first day and the price available on the way out.

The famous return is mostly a tail

This is where the headline numbers need careful reading. The same Stanford study reports that if you strip out the funds that returned ten times or more, the aggregate return on invested capital falls from 4.75 times to about 2.8 times, and the internal rate of return from 33.9 percent to about 27 percent. The asset class is excellent. A large share of that excellence sits in a small number of outcomes.

Set that next to the illustrative median deal above. Bought at the median multiple, run well for five years and sold at the same multiple, it produces about 2.9 times at the company level, before the searcher's share, the step-up on search capital and fees come out. That is roughly the return of the whole asset class once the tail is removed. Paying the median price and executing well gets a searcher's investors to the ex-tail average. Paying a turn above the median quietly spends the margin that execution was supposed to earn.

The acquisition data adds a second pressure. Historically 58 percent of concluded searches ended in a purchase, according to the study, and for funds launched between 2021 and 2024 the figure is about 48 percent. A successful search typically takes around 20 months, and the median searcher raised about $550,000 of search capital to fund it. A searcher in month 19 with most of that spent has every incentive to stretch for the deal in front of them. That is the moment the multiple is most likely to drift above the band, and the moment an investor should ask the hardest questions about it.

Where searchers actually lose the half turn

In my experience, overpayment rarely looks like overpayment at the time. It looks like one of three reasonable-sounding decisions.

1. Pricing the headline EBITDA instead of the verified one. At 6.2 times, every $100,000 of EBITDA that does not survive quality of earnings is $620,000 of price. Axial's Dead Deal Report on 75 lower middle market transactions that broke in 2025 found that 21.3 percent died on a quality of earnings discrepancy in EBITDA. Those are the deals where the discrepancy was found. The ones where it was not found closed, and they are the overpayments. I have written separately about what that report checks.

2. Paying for the same growth twice. A seller's growth shows up once in the multiple, because a buyer pays more for a growing company, and again in the earnings the buyer's model projects. If 12 percent a year is already inside the 6.2, the model cannot also credit it to the searcher's plan.

3. Treating structure as if it were price. A seller note or an equity rollover can bridge a gap in a letter of intent, but it does not change what the company is worth. The IBBA survey for the second quarter of 2026 found sellers receiving 83 to 92 percent of consideration in cash at close, so a searcher who wins at a higher headline number by pushing a large share into a note has usually bought a different deal, not a cheaper one. I have covered what a letter of intent does and does not lock in elsewhere.

What to do with this

If you are searching, write down the band's going rate before you write the first letter of intent. For a company with $2 million to $3 million of EBITDA, the current evidence puts it between about 5.8 and 6.4 times. Anything above that range needs a named reason in dollars, not a feeling about quality, and your model should show the deal still working if you sell at 5.0.

If you are funding searchers, ask for the same test. Ask to see the deal at the entry multiple, at one turn higher, and with an exit a turn lower, and ask where the equity cheque lands in each case. A searcher who can answer that quickly has already priced the company rather than the opportunity.

And if you are a seller being approached by a searcher, understand what they are. They are not a discount buyer. At the median they are paying the market rate for your size band, with less capital behind them than a fund and more personal stake than anyone else at the table. Judge the offer on the price and the cash at close, not on the buyer's category, which is the same point I have made about strategic buyers.

Common questions

What multiple do search funds pay for a business?

For companies acquired in 2024 and 2025, the median search fund paid 6.2 times EBITDA, according to the Stanford Graduate School of Business 2026 Search Fund Study, on a median enterprise value of $16.0 million and median EBITDA of $2.5 million. For 2022 and 2023 the median was about 7 times, and across the study's full history it is about 6.3 times.

Do search funds buy companies more cheaply than other buyers?

Not at the median. The IBBA and M&A Source Market Pulse survey for the second quarter of 2026 put the average multiple for $5 million to $50 million transactions at 5.8 times EBITDA, and the Felpel Private Company Index puts the median for the same band at 6.4 times EV/EBITDA. Search funds, at 6.2 times, sit between the two, so the return has to come from operating and growing the company rather than from a discounted entry price.

What returns have search funds produced?

The Stanford 2026 study reports an aggregate internal rate of return of 33.9 percent, a return on invested capital of 4.75 times and a public market equivalent of 2.88 against the S&P 500. The returns are concentrated: excluding funds that returned ten times or more, the aggregate return on invested capital falls to about 2.8 times and the internal rate of return to about 27 percent.

How long does a search take, and how many searchers buy a company?

A successful search typically takes around 20 months. Historically 58 percent of concluded searches ended in an acquisition, according to the Stanford study, falling to about 48 percent for funds launched between 2021 and 2024. In that recent cohort, partnered searches acquired at 58 percent against 43 percent for solo searchers.

Why does the entry multiple matter so much to a searcher?

Because lenders size debt off EBITDA, not off the purchase price, so every extra turn a searcher pays is funded with equity. In an illustrative deal with $2.5 million of EBITDA and senior debt of 3.0 times EBITDA, moving from 5.0 to 6.2 times raises the price by 24 percent but the equity cheque by 60 percent, and cuts the equity multiple on the same operating result from about 3.7 times to about 2.9 times.

Related reading

• How an independent sponsor prices a deal before the money exists.
• Quality of earnings: the report that moves the price.
• A letter of intent locks in everything except the price.
• Why size sets the valuation multiple.

Go deeper

If you are about to sign a letter of intent and want to know whether the multiple sits inside the band or above it, let's price the company off the transactions before the model gets built around the number, or read more of how I think about it.

Tomasz Felpel is an investor, founder, and advisor in private markets and healthcare, based in New York. He is a three-time founder of Value Alpha, an AI-powered private-markets valuation platform, Sonnerie VC, an early-stage healthcare venture firm, and Pond. Previously he led corporate development and M&A at Fortune 500 scale, pricing more than 1,000 private companies. Columbia Business School EMBA. Read the full story.