Debunking the VC Narrative: Why "Outliers and Ownership" Is Only Half the Story

"We need at least 10% ownership to make it worthwhile."

I hear this every week in VC circles I hear smart people saying that is paramount Investment committee meetings, LP presentations, WhatsApp groups. It's become gospel.

They nod along to pitch decks promising that “10%” while hunting for "unicorn potential" in markets where unicorns barely exist, without asking if that number actually moves the fund’s returns.

Here's the uncomfortable truth: it's mathematically flawed. And outside Silicon Valley's capital-abundant ecosystem, this obsession with ownership percentages and outlier hunting is quietly destroying returns for LPs, while everyone congratulates themselves for being "disciplined investors."

Time for some tough love. (read listening to “welcome to the jungle” - GnR)

Before diving into the math, let's establish the reality about outcome magnitude outside the US tech epicenter.

The Outlier Gap is Massive:

• Silicon Valley outliers: Averages are skewed by companies like Meta ($1T+), Google ($2T+), Apple ($3T+), with dozens of $100B+ companies (massive even at IPO)

• Global outliers: Nubank ($50B), Meli (120B), Spotify ($50B), Adyen ($40B), Revolut ($74B) — impressive, but 10-20x smaller. While impressive, the largest exits often pale in comparison.

• Typical successful exits: According to a PitchBook analysis, the median US tech exit between 2015 and 2024 was $120M. In contrast, the median tech exit in Latin America was just $18M.

This isn't a temporary gap. It's structural. Market sizes, capital availability, and exit dynamics create fundamentally different playing fields.

Yet somehow, we've imported Silicon Valley's "find outliers and maximize ownership" playbook without adapting the underlying math. The result? VCs worldwide chasing high stakes in companies that can never scale large enough to return a fund, while simultaneously hunting for unicorns that barely exist in their markets.

Let me be clear, of course we should look after scalable startups and try to have as much ownership as possible in startups with unicorn potential, however we must understand how dim the odds are.

The dominant narrative combines two radical assumptions:

1. "Just find the outliers" — Hunt for those rare 100x companies

2. "Ownership is everything" — Secure 10%+ stakes minimum

This creates a tough cocktail: VCs demand high ownership in early-stage deals while expecting outlier-level returns in markets where both are statistically remote.

Let me show you why both assumptions are remote — and what actually works.

I analyzed comprehensive institutional research covering 387 funds, BRL 181 billion in deployments, and the complete lifecycle performance of Latin America's most mature venture ecosystem. The brutal truth? 28 years of venture capital data1 proves this strategy is mathematically designed to fail.

Common Sense: "Only outliers’ matter. Find the next unicorn or fail."

The problem is that outlier hunting assumes virtually infinite upside, but markets have ceilings. A "unicorn" in an emerging ecosystem might exit at $1B, not $100B. According to LAVCA, 75% of all Latin American exits are strategic acquisitions, not massive IPOs. This data confirms that the most common liquidity path is not a massive outcome, but a smaller-to-mid-size acquisition.

The Mathematical Reality from institutional research:

• 62% of mature VC funds (10+ years old) returned capital with profit (DPI > 1.0)

• Mean VC returns: 15.6% IRR, 2.6x TVPI

• 25.3% of VC funds achieved >30% IRR (not just the "lucky few")

If only extreme outliers drove returns, these numbers would be impossible. And you ignore the Expected Value of a portfolio is the weighted expected value of each investment. More than half of all funds are profitable through distributed success models, not lottery tickets. Your portfolio's success depends on optimizing for this reality, not a fantasy outcome.

Common Sense: “High ownership is necessary to achieve better returns”

In reality, “high ownership” only has meaning when seen in the context of fund size. That only matters when it’s proportionally meaningful to the fund. An 8% stake in a micro fund can move the needle far more than 15% in a mega-fund. At the end of the day, it’s about weighted exposure and realistic exit scenarios.

The Mathematical Reality from recent market analysis: One should benchmark ownership targets with a) fund size and b) invested company risk-return profile. For early-stage checks, good expectations might look like this:

• $20M fund: 2–3% target ownership can be impactful

• $40M fund: 4–6%

• $60M fund: 6–9%

• $80M fund: 8–12%

• $100M fund: 10–15%

The gap exists because larger funds require proportionally larger allocations in individual winners to materially affect overall returns. One should calibrate ownership to fund size and exit realities. The real skill isn’t hitting an arbitrary ownership %, it’s but structuring positions that can actually move your fund’s returns.

Also, you pay an option premium for high ownership because companies know you "need" 15% and will price in your desire. This leads to higher valuations for the "privilege" of access. The entry price is the paramount KPI at the deal level, because it directly dictates our ability to achieve a high potential for the fund.

The Mathematical Reality from recent market analysis:

• Seed valuations increased 4.7x from 2017-2023 across emerging markets

• A strategy achieving 10x returns in 2017 would only generate 2.1x returns at 2023 prices

• Real case study: Company valued at 40x revenue needs 140% CAGR for 6 years just to deliver 10x returns

Ownership obsession forces exponentially higher entry prices. You're not being disciplined—you're being mathematically reckless.

The Paradox: The smaller fund achieves higher MOIC (5x vs 4x) but generates lower absolute profits per deal/fund (2.5M vs 8M). However, the fund impact percentage is actually higher (10% vs 6%) per deal with the same ownership. more details below.

The same 10% stake means something entirely different for a $20M fund than for a $100M fund

Smaller funds: Can demand better pricing due to smaller check sizes

Larger funds: May accept higher entry points to deploy capital more efficiently

Example:

• 20M fund→100M (5x MOIC) = $80M absolute profit

• 100M fund→400M (4x MOIC) = $300M absolute profit

In the example above, the larger fund generates 3.75x more absolute profit despite lower relative returns. For large allocators that is really important, especially because high returns in huge sums are very, very difficult. But for fund construction purposes, the smaller fund's strategy is more mathematically efficient.

Smaller funds that win on entry pricing often face two traps: larger funds distorting the market by chasing high ownership at inflated valuations, and small funds themselves mistaking their price advantage for an ownership advantage—forgetting that percentage alone means nothing without meaningful fund impact.

Stop thinking about ownership. Start thinking about Fund Ownership Exposure (FOE). FOE tells you what percentage of your fund a successful exit will return. It's the only number your LPs care about.

This formula calculates the net gain (profit from the investment) as a percentage of the fund. It's not about gross exposure—it's about actual profit contribution to fund returns.

$20M Fund FOE Optimization:

• Investment: 500K for 2M shares at 0.25/share (10% of $5M post-money)

• Exit: 25M valuation = 1.25/share

• FOE: (1.25−0.25) × 2M shares ÷ $20M fund = 10% fund return from one deal

$100M Fund FOE Optimization:

• Investment: 2M for 2M shares at 1.00/share (10% of $20M post-money)

• Exit: 80M valuation = 4.00/share

• FOE: (4.00−1.00) × 2M shares ÷ $100M fund = 6% fund return from one deal

The Math: Both achieve target ownership, but the smaller fund gets higher FOE due to better entry pricing access. This isn't about ownership — it's about fund size determining viable entry points.

Not to mention that High ownership strategies force you to find unicorns. FOE-driven strategies let you win on companies that can realistically reach U$20-25M exits.

Reality Outside Silicon Valley: And guess which exits actually happen outside Silicon Valley? 80% of tech exits are under $50M. (Hint: check LatAm exit data—80% of tech exits are under U$20M, even starker than rest of the world.)

FOE strategies target this reality where blind ownership strategies ignore it. And the Smaller the fund, the FOE math becomes even more unforgiving, and the ownership theater becomes literally impossible to sustain.

1. Start with Fund Math, Not Deal Math: Before evaluating any opportunity, ask: "If this succeeds at realistic scale, can it return 20-50% of my fund?" If not, pass.

2. Position Size Beats Ownership: A $500K investment returning 5x moves your fund more than a $100K investment returning 20x. Math doesn't care about your feelings.

3. Target Realistic Scale with Exit Paths: Look for companies that can realistically reach $20-50M enterprise values AND have $500M-$1Bi optionality AND have clear strategic acquirers or IPO paths.

4. Target ownership that moves the needle: Focus on price per share and total investment size. Your LPs don't care how much you owned—they care how much you returned.

5. Prioritize Liquidity: Better to own 5% of something that exits in 4-7 years than 15% of something trapped forever.

This isn't about abandoning fundamentals. It's about applying correct fundamentals to your market reality.

Real fundamentals:

• Disciplined position sizing (6-10% of fund per deal)

• Realistic exit scenarios based on actual market data

• Liquidity analysis: Who will buy this company and when?

• Discipline focused on maximizing exposure at the right price, not ownership craze

Vanity fundamentals:

• "We need double digits minimum ownership"

• "We're hunting for outliers"

• "High ownership gives us control"

• "This could be the next [insert Silicon Valley unicorn]"

"How many companies need to succeed?" Answer: 4-6 companies delivering 4-8x returns = successful fund

"What's your mathematical model?" Answer: FOE optimization targeting 2-4% fund contribution per investment

"How do you manage binary risk?" Answer: Quality-first selection creates graduated return distribution

"What's your realistic exit analysis?" Answer: Every investment has 3-5 modeled scenarios with identified strategic buyers

Global venture ecosystems are maturing, but we're still making basic mathematical errors imported from markets with completely different dynamics.

The dual obsession with outliers and ownership feels sophisticated but represents lazy thinking. It's easier to demand "10%+ minimum" and hunt for "unicorn potential" than to do the hard work of evaluating realistic scale, optimal position sizing, and liquidity paths.

FOE forces real discipline. It makes you think about fund returns, not vanity metrics. It prioritizes realistic exits over fantasy outcomes. It separates concentrated, thoughtful investing from diversified lottery playing.

The best VCs globally already get this. They think in fund mathematics, not ownership theater. They optimize for FOE, not ego.

The question is: Are you ready to abandon comfortable myths for uncomfortable math? Your LPs are counting on it.

The data doesn't lie. The traditional narrative? Well….

At Airborne Capital, we've built our entire investment thesis around this mathematical reality.

This piece reflects experience across 70+ investments and building high-performing portfolios in evolving venture ecosystems. The math doesn't lie—regardless of geography—but you need to adapt.