How Much of Buy & Build Outperformance Is Actually Multiple Arbitrage?

In the first volume of this series, I looked at Hammer et al. (2022), who provide fairly strong evidence that private equity-backed Buy & Build investments have historically generated above-average equity returns, even though PE investors tend to pay a premium for companies that are suitable as initial platforms.

That result is interesting on its own, but for anyone who has actually underwritten or executed a Buy & Build strategy, it immediately raises a more important question: where does the additional return really come from?

There are several possible answers, and in reality they usually overlap. The platform can grow organically, acquisitions can generate revenue and cost synergies, management can professionalise the acquired companies, additional scale can improve margins and reduce risk, leverage can amplify the resulting equity returns, and the larger group can ultimately command a different valuation at exit.

There is, however, another mechanism which is both much simpler and, based on the empirical evidence, surprisingly important: a PE-backed platform can acquire smaller businesses at valuation multiples materially below the multiple at which the platform itself is valued, and once those acquired earnings sit inside the larger group, they can effectively be revalued at the platform multiple.

Put differently, a meaningful amount of value can be created by buying EBITDA at one multiple and subsequently owning that same EBITDA inside an asset valued at another multiple.

This is exactly what Philipp Heisig, Jonas Kick and Bernhard Schwetzler examine in Multiple Arbitrage and Buyout Performance: Evidence from Buy-and-Build Deal-Level Data, and what makes the paper particularly useful is the level of detail in the transaction data available to the authors.

The current study analyses 161 Buy & Build investments, while the detailed underlying dataset described in an earlier version of the research contains 971 related add-on acquisitions, including information on enterprise values and EBITDA multiples paid for individual bolt-ons.

That gives the authors something that is often missing in private equity research: the ability to look beyond the platform at entry and exit and ask, transaction by transaction, what was actually bought, at what valuation and how that affected the economics of the overall investment.

The core question becomes:

How much of the apparent growth in a Buy & Build strategy was actually generated by the business, how much was simply acquired, and how much additional value was created because the acquired EBITDA was purchased at a lower multiple than the platform?

That distinction sounds technical, but it changes the interpretation of Buy & Build performance quite materially.

The problem with conventional Buy & Build performance analysis

Assume a PE investor acquires a company with €10 million of EBITDA and, five years later, exits a business generating €30 million.

At first glance, that looks like exceptional growth. If you simply calculate the CAGR between €10 million and €30 million, you arrive at approximately 25% annual EBITDA growth, which in a normal investment presentation would probably be highlighted as one of the main value creation achievements of the holding period.

The problem is that this number tells you almost nothing about how the EBITDA actually increased.

Suppose that the platform acquired companies contributing €15 million of EBITDA during the holding period and that only the remaining €5 million of growth came from organic growth, margin improvement and synergies across the combined group.

The story now looks very different.

The platform did not operationally grow from €10 million to €30 million. A substantial part of the increase was purchased with additional capital, and the return generated by that purchased EBITDA depends not only on what happened to the business after acquisition, but also on the price originally paid for it.

This is where Heisig, Kick & Schwetzler improve on the conventional attribution framework.

Instead of treating the entire increase in EBITDA as one homogeneous source of value creation, they distinguish between organic growth, inorganic growth through acquisitions, and what they call the add-on sourcing effect, which captures the value created when acquired EBITDA is purchased below the valuation multiple of the platform.

That distinction is important because, particularly in aggressive Buy & Build strategies, a large proportion of what appears in the value creation bridge as “EBITDA growth” may actually have been bought rather than created.

And once you recognise that, the price paid for the acquired EBITDA becomes central to the return analysis.

How the add-on sourcing effect works

The cleanest way to understand the mechanism is through a simple example.

Assume a platform generates €10 million of EBITDA and is valued at 10x EBITDA, resulting in an enterprise value of €100 million.

The platform then acquires a smaller company generating €2 million of EBITDA at 6x, paying €12 million for the business.

The investor has now paid a total of €112 million for €12 million of combined EBITDA, which means that the effective blended acquisition multiple has fallen from 10x to approximately 9.3x.

Nothing operational has happened at this point. Revenue has not grown organically, margins have not improved, there are no procurement savings, no cross-selling benefits, no duplicated overheads have been removed and the market has not changed its view on the value of the platform.

Yet, if the combined €12 million of EBITDA is now valued at the platform's original 10x multiple, the combined enterprise value becomes €120 million.

The investor has paid €112 million for something that is theoretically worth €120 million.

That €8 million difference exists because €2 million of EBITDA was acquired at 6x and subsequently sits inside an asset valued at 10x.

This is the add-on sourcing effect.

One point that is worth being very clear about is that this mechanism is different from conventional exit multiple expansion, because the platform multiple does not need to increase at all for the effect to occur. The platform can remain valued at 10x throughout the entire holding period and the investor can still generate a valuation uplift simply by lowering the blended acquisition multiple through cheaper add-ons.

That is why I think the effect is more structural to Buy & Build than the usual “entry multiple versus exit multiple” discussion sometimes suggests.

The effect is economically meaningful

The authors find that the sourcing effect makes a material contribution to Buy & Build performance.

The current version of the research estimates that the sourcing effect accounts for roughly 8% of equity value CAGR across the B&B investments analysed.

An earlier detailed version of the same study provides another perspective on the magnitude and estimates that approximately 21.2% of EBITDA CAGR across the full sample could be attributed to the sourcing effect, with a very similar figure for realised investments.

These measures should not be mixed mechanically because equity value CAGR and EBITDA CAGR are different concepts and the methodology evolved between versions of the paper, but both point in the same direction.

The valuation at which add-on EBITDA is acquired is not a secondary assumption in a Buy & Build model. It can be one of the central drivers of the return.

This is one of the points from the paper that resonates most with what I have seen in practice.

In an investment committee paper, we can spend a great deal of time discussing organic market growth, cross-selling, procurement synergies, management upgrades, integration costs and margin expansion, while an assumption such as “average add-on acquisition multiple: 6.5x EBITDA” can sit relatively innocently somewhere in the model.

But if the platform itself is valued at 10x or 12x, the gap between the platform multiple and the add-on multiple may be one of the most important pieces of the entire investment case.

It therefore deserves to be analysed with the same level of scrutiny as organic growth, margin expansion and exit valuation.

Multiple arbitrage is partly hidden inside “EBITDA growth”

This also creates a problem for conventional PE value creation bridges.

A typical bridge decomposes equity value creation into three broad components: EBITDA growth, multiple expansion and deleveraging.

For a standalone buyout, this is usually a reasonable framework.

For a Buy & Build, however, it becomes much less clean because a meaningful part of the EBITDA growth may have been purchased rather than generated, while the value attached to that purchased EBITDA may itself contain a valuation effect.

If the platform starts with €10 million of EBITDA and exits with €25 million, while €10 million of that increase came from add-on acquisitions, then attributing the full increase to “EBITDA growth” creates a misleading picture of what happened economically.

The investor did not create all of that EBITDA. The investor bought a large part of it.

And if the acquired EBITDA was purchased at 6x while the platform is valued at 10x, some of the resulting value increase is economically closer to multiple conversion than to operating growth.

When the authors adjust the conventional attribution framework to reflect this, the importance of multiple conversion increases materially. In the earlier detailed analysis, it accounts for approximately 35.5% of performance across the full B&B sample, compared with a lower contribution under a more conventional decomposition.

The precise percentage is less important to me than the broader implication.

Valuation mechanics appear to account for a larger share of historical Buy & Build performance than a standard EBITDA-growth bridge would suggest.

That means that when we say a B&B investment “grew EBITDA substantially”, we should be much more precise about what we actually mean.

The most important test: removing the sourcing effect

For me, the strongest part of the research is what happens when the authors compare Buy & Build investments with comparable non-B&B private equity investments and then remove the benefit created by acquiring add-ons below the platform multiple.

Before adjustment, Buy & Build investments outperform, which is broadly consistent with the conclusion of Hammer et al. and other earlier research.

The authors then construct a price-adjusted performance measure that removes the add-on sourcing effect and repeat the comparison.

The result changes materially.

Once the sourcing effect is excluded, Buy & Build outperformance declines significantly and moves much closer to the performance of comparable non-B&B investments.

This is a much more important result than simply showing that multiple arbitrage exists.

It suggests that a meaningful part of the historical performance advantage associated with Buy & Build can be explained by the ability to acquire add-on EBITDA below the valuation multiple of the platform.

From an underwriting perspective, this changes the framing of the question entirely.

The question should not simply be:

Can we find and acquire enough companies?

It should be:

Can we acquire enough high-quality EBITDA at a sufficiently attractive valuation relative to the platform, and can we maintain that spread for long enough to make the strategy work?

Those are very different questions, and in my view the second one is much closer to the real economics.

Fragmentation is not enough

This has direct implications for one of the most common arguments in Buy & Build investment cases: market fragmentation.

Almost every consolidation thesis contains some version of the same slide: there are hundreds or thousands of independent companies, the largest players have relatively low market shares and a long tail of founder-owned businesses remains available for consolidation.

That is useful information, but on its own it tells you very little about whether the Buy & Build economics are actually attractive.

A market can remain highly fragmented statistically while becoming unattractive economically if too many well-capitalised consolidators are competing for the same targets.

Once several PE-backed platforms are active in the same market, founders become more educated about valuation, advisors become better at running competitive processes, sellers start benchmarking themselves against larger platforms rather than against other small businesses, and the valuation discount available on smaller companies can compress very quickly.

The market map may therefore still show hundreds of independent companies, while the actual economics of acquiring those companies have deteriorated substantially.

I would therefore think about the attractiveness of a B&B market as something closer to:

Fragmentation × executable acquisition volume × sustainable multiple spread

All three elements matter.

A market with 1,000 theoretical targets may be a poor Buy & Build market if almost all credible companies are already expecting 9–10x EBITDA, while a market with 150 realistic targets may be considerably more attractive if good businesses can repeatedly be acquired at 5–6x while the platform itself is valued at 10–12x.

This formula is my interpretation rather than something directly tested in the paper, but it follows naturally from the sourcing-effect mechanism identified by the authors.

The acquisition pipeline should be measured in EBITDA, not logos

The same logic changes how I look at an acquisition pipeline.

A presentation showing 100 potential targets can look impressive, but the number itself does not tell you much.

I would much rather know how many of those businesses are genuinely actionable, what EBITDA they represent, how many owners are realistically willing to sell during the planned holding period, what level of competition exists for the better assets, what percentage could plausibly be sourced bilaterally, and at what valuation those businesses are actually likely to transact.

The more relevant question is therefore not:

How many targets are there?

It is:

How much EBITDA can we realistically acquire at a meaningful discount to the valuation of our own platform?

That is a much more useful way to define acquisition runway, because a B&B strategy does not create value simply by having hundreds of theoretical targets in the market.

It creates value by repeatedly deploying capital into attractive acquisitions at prices that preserve the economics of the strategy.

The difference between those two concepts can be very large.

Being good at Buy & Build also means being good at buying

The research also changes how I think about M&A capability itself.

We normally describe a strong B&B platform as one that can source opportunities, execute transactions, integrate acquired companies, realise synergies and retain key management teams.

All of those capabilities clearly matter.

However, the paper suggests that one more capability deserves to sit alongside them:

valuation discipline.

Imagine two platforms that both begin with €10 million of EBITDA, both acquire another €20 million of EBITDA during the holding period, both integrate the acquisitions equally well and both eventually exit at 10x EBITDA.

The only difference is that Platform A buys the €20 million of acquired EBITDA at an average of 6x, while Platform B pays 9x.

Platform A spends €120 million to acquire the additional EBITDA.

Platform B spends €180 million.

At exit, the acquired €20 million of EBITDA is worth €200 million at the group valuation of 10x.

Platform A has therefore generated €80 million of gross valuation uplift from the multiple spread, while Platform B has generated only €20 million.

The businesses can look almost identical at exit, but the returns to shareholders can be completely different because one platform was simply much better at buying.

This is why acquisition count is such a poor KPI for Buy & Build success.

The better question is what was acquired, at what valuation, how that acquired EBITDA performed after the transaction and what valuation it eventually received as part of the group.

Add-on multiple inflation should be a core downside case

If add-on pricing is an important source of B&B returns, then the practical implication is fairly obvious: add-on multiple inflation should be explicitly stress-tested in every Buy & Build investment case.

Assume the base case is built around a platform acquired at 10x EBITDA, add-ons acquired at an average of 6x and an exit at 10x.

The structural spread is very attractive.

But what happens if the realistic add-on multiple is 7x rather than 6x?

What happens at 8x?

What happens at 9x?

And perhaps more importantly, what happens if the add-on multiple increases over time?

This is a scenario that I think is often more realistic than assuming one constant acquisition multiple throughout the holding period, because a successful consolidation strategy can make its own market more expensive.

The first acquisitions demonstrate that there is a well-capitalised buyer in the sector, competing sponsors notice the opportunity, advisors become more active, sellers gain better valuation benchmarks and other PE firms may launch competing platforms.

As a result, the platform may be able to acquire the first few companies at 6x, the next group at 7x and the later transactions at 8–9x.

The strategy may still work perfectly well, but the return profile can look very different.

If a B&B model collapses because the average add-on multiple increases by one turn, that is important information about the robustness of the investment thesis.

The second half of the arbitrage happens at exit

There is another important question that the authors address.

Buying smaller companies cheaply is only half of the multiple-arbitrage mechanism.

For the strategy to work, the acquired EBITDA must subsequently receive the valuation multiple of the combined group.

If a platform buys €2 million of EBITDA at 6x and an exit buyer later says that the original platform EBITDA is worth 10x while the acquired EBITDA is still only worth 6x, then most of the theoretical arbitrage disappears.

The authors therefore examine whether exit buyers differentiate between different sources of EBITDA growth.

Their results provide preliminary evidence that they largely do not.

In other words, once the acquired earnings are part of the combined platform, the exit market appears to value them similarly to the rest of the group's EBITDA.

This is what completes the economic mechanism.

The platform acquires €1 of EBITDA in a small business at 6x, integrates it into a larger group and can eventually sell that same €1 as part of an asset valued at perhaps 10x or 12x.

That is the fundamental conversion taking place.

Why would an exit buyer accept that?

At first sight, this may sound irrational.

If a PE sponsor acquired a company at 6x three years earlier, why should another buyer suddenly be prepared to pay 11x for the same earnings?

The answer is that the earnings may no longer carry the same risk profile because, by the time of exit, they may sit inside a very different business.

Before acquisition, a small company might depend heavily on one founder, operate in a single geography, have weak reporting, limited management depth, customer concentration, relatively unsophisticated systems and a very limited universe of potential buyers.

After several years inside a larger group, the same underlying earnings may sit within a diversified platform with professional management, central finance, institutional reporting, stronger systems, better financing access, a broader customer base and a much larger universe of strategic and financial buyers.

From an economic perspective, there can therefore be perfectly rational reasons why those earnings command a higher valuation after integration.

This is why I think the term multiple arbitrage can sometimes be slightly misleading.

It sounds as though the return comes purely from moving numbers between valuation buckets.

Sometimes it does.

But in a successful Buy & Build, part of the re-rating may reflect genuine improvements in the quality, resilience and liquidity of the underlying asset.

Pure arbitrage versus earned re-rating

For that reason, I find it useful to distinguish between two different forms of multiple uplift.

The first is pure multiple arbitrage.

A company is bought at 6x, very little changes operationally, it is consolidated into a group valued at 10x and the acquired EBITDA therefore effectively moves from a 6x valuation to a 10x valuation.

That is predominantly a pricing effect.

The second is earned re-rating.

A company is bought at 6x, integrated into a larger organisation, management is strengthened, reporting improves, customer concentration declines, commercial capabilities improve, margins increase and the acquired business becomes part of a genuinely higher-quality platform.

The resulting EBITDA is then valued at 10x.

There is still a multiple uplift, but calling the entire uplift “arbitrage” would ignore the actual transformation that took place.

In practice, successful Buy & Build strategies probably contain both effects, and the interesting question is not whether arbitrage exists, but how much of the eventual valuation uplift comes from pure pricing mechanics and how much has actually been earned through operational improvement.

The research shows that the pricing effect is economically important, but it cannot fully determine how much of the eventual re-rating reflects pure arbitrage and how much reflects a genuine improvement in asset quality.

That distinction matters because it tells you something about how repeatable and sustainable the return really is.

This does not mean Buy & Build is just multiple arbitrage

It would be easy to overinterpret the paper and conclude that B&B outperforms simply because PE buys small companies cheaply and later sells them at a higher multiple.

I do not think that is the right conclusion.

When the authors remove the sourcing effect, B&B performance moves materially closer to that of non-B&B peers, but they do not show that all outperformance disappears.

There are still several other value creation mechanisms at work, including organic growth, margin improvement, cost and revenue synergies, professionalisation, deleveraging, strategic repositioning and conventional multiple expansion.

The sourcing effect is therefore an important part of the Buy & Build story, but not the entire story.

This distinction matters because a B&B strategy built exclusively around multiple arbitrage is fragile.

If acquisition multiples rise, the thesis weakens.

If exit multiples decline, the thesis weakens.

If the acquired businesses deteriorate during integration, the thesis weakens.

If the group does not genuinely become an institutional-quality asset, the exit buyer may simply refuse to apply the expected valuation.

Multiple arbitrage is a powerful tailwind, but it should not be the only source of return.

How I would change the underwriting

For me, the main practical value of the paper is that it changes the questions I would ask when evaluating a Buy & Build investment.

The first question is what the real multiple spread is, not between the platform and some generic “small company” benchmark, but between the platform and the specific types of businesses that the acquisition strategy actually intends to buy.

The second is how much EBITDA can realistically be acquired at that spread, because a large theoretical target universe is irrelevant if only a small portion is actionable at attractive valuations.

The third is how sustainable the spread is, particularly as competition increases, founders become more sophisticated and the platform eventually has to move from very small bilateral transactions into larger and more competitive processes.

The fourth is what happens if the exit multiple does not increase at all, because a strong B&B case should ideally produce an attractive return without relying on conventional multiple expansion.

And the fifth is whether the combined business will genuinely deserve the assumed exit multiple, because the financial logic of the sourcing effect only works if the acquired EBITDA is successfully transformed into credible platform EBITDA.

These questions connect the valuation mechanics directly to the operating model and make it much easier to see where the actual risk in the strategy sits.

Integration is what protects the multiple

This is another reason why I do not see operating improvement and multiple arbitrage as competing explanations for Buy & Build success.

In many ways, they reinforce each other.

The initial multiple spread creates a structural source of value when smaller businesses are acquired below the platform valuation, while good integration protects that value by making the combined business genuinely deserving of the higher multiple.

If the platform completes ten acquisitions but leaves ten separate systems, ten separate management structures, inconsistent reporting, duplicate functions and limited central control, the group may have become larger without becoming meaningfully better.

In that situation, the exit buyer may not give full credit for the acquired EBITDA.

The spreadsheet may show a €30 million EBITDA group, but the buyer may see a loosely connected collection of businesses requiring another three years of integration.

That is why the apparently financial concept of multiple arbitrage eventually comes back to operations.

The sourcing spread creates the opportunity; integration determines whether the market lets you keep it.

A better definition of Buy & Build success

The paper reinforces something that I think is often overlooked in the way B&B strategies are discussed.

The number of acquisitions is not a useful measure of success on its own.

A platform that has completed twelve acquisitions is not necessarily better than one that has completed five.

The more relevant questions are what EBITDA was acquired, at what price, how that EBITDA performed after acquisition, what synergies were realised, how much organisational complexity was introduced, whether the group became genuinely stronger and what valuation the acquired earnings eventually commanded at exit.

A good Buy & Build platform should ideally become progressively better at acquisitions as the strategy develops, because management learns, integration processes become repeatable, reporting becomes standardised, sourcing improves, financing becomes easier and the platform's reputation with sellers grows.

That is the kind of compounding I would want to see.

If every new acquisition makes the next acquisition harder, the platform may be growing in size while deteriorating in quality.

The key takeaway from Heisig, Kick & Schwetzler

The most important conclusion from this research is not that multiple arbitrage exists.

Anyone who has worked on Buy & Build strategies already knows that smaller businesses often trade at lower valuation multiples than larger institutional platforms.

The real contribution is that the authors are able to measure the effect using actual add-on transaction data and show that it explains a meaningful part of historical Buy & Build performance.

Even more importantly, when the sourcing effect is removed, the historical performance advantage of B&B investments over comparable non-B&B investments becomes significantly smaller.

That is a powerful result because it means sourcing is not merely the front end of the acquisition process.

Sourcing itself is a value creation capability.

A platform that can repeatedly acquire good businesses at attractive relative valuations has a genuine economic advantage over another platform pursuing exactly the same consolidation strategy but consistently paying full prices.

For me, this is one of the most useful ways to think about the economics of Buy & Build.

The strategy is partly about improving companies, partly about building scale and partly about integration, but it is also about converting low-multiple EBITDA into high-quality platform EBITDA without paying the platform multiple to acquire it in the first place.

When this works together with genuine operating improvement, the return potential can be extremely attractive.

When the acquisition-price spread disappears, the strategy becomes much more dependent on execution.

And if the investment case requires both aggressive operating improvement and aggressive multiple assumptions to generate an acceptable return, there is probably very little room for error.

What comes next

After Hammer et al. and Heisig, Kick & Schwetzler, there is one obvious question left.

We now have evidence that Buy & Build investments have historically outperformed, and we have evidence that multiple arbitrage explains a meaningful part of that outperformance.

The next question is whether Buy & Build also creates measurable operating improvements in the underlying companies.

Do margins improve? Does productivity improve? Are there genuine synergies? Or are we primarily observing the effect of acquiring, aggregating and re-rating EBITDA?

That is the subject of Buy & Build, Deconstructed — Vol. 3, where I will look at the research by Bansraj, Smit & Volosovych on operating performance and synergies in European Buy & Build strategies.

Main research discussed

Heisig, Philipp and Kick, Jonas and Schwetzler, Bernhard, Multiple Arbitrage and Buyout Performance: Evidence from Buy-and-Build Deal-Level Data (January 13, 2026). Available at SSRN: https://ssrn.com/abstract=6100327 or http://dx.doi.org/10.2139/ssrn.6100327