A Practical Framework For Comparing Venture Fund Performance To Public Indexes

Private investors often ask the same question: Do venture firms outperform public markets?

Here is the framework I used based on the recent data from Andreessen Horowitz (a16z) as an example, since they released the performance of all their funds on the back of a $15 billion fundraise—their largest haul to date.

So I took historical data of a16z fund performance since 2009 (summarized by Packy McCormick/Not Boring) and ran an apples-to-apples comparison versus the Nasdaq-100 Total Return index (XNDX).

The headline result is provocative but important:

Under reasonable assumptions, the average a16z fund net return to LPs came out slightly below the Nasdaq-100 total return over the same period (based on a simplified cash flow model), despite dramatically worse liquidity.

Of course, this specific example does not mean that public markets always outperform VC funds. Please also note that past performance does not guarantee future results.

But the following framework can be helpful when comparing the performance of venture firms with that of public markets. First, let’s consider which return metric is useful for a VC fund to compare its performance versus a public market benchmark.

TVPI Vs. IRR

Venture performance is often marketed as multiples, not annualized returns.

• DPI (distributions to paid-in capital) measures cash-on-cash return by investors. It’s calculated as distributions divided by invested capital.

• TVPI (total value to paid-in capital) is the ratio of: (distributions plus remaining value) divided by invested capital.

Those are useful snapshots. But multiples ignore time. A 3.0x over 15 years is not the same as a 3.0x over seven years.

To compare venture returns to public markets, it’s helpful to convert the multiple-style disclosures into a time-aware measure, such as IRR (internal rate of return), which requires assumptions about when capital is called and returned.

The Public Benchmark

For the public-market baseline, I used XNDX: Nasdaq-100 Total Return index—the version that assumes dividends are reinvested.

That matters. Dividends aren’t huge in tech, but they’re not zero, and over long horizons, they compound.

My Methodology

Because we don’t have actual LP cash flow schedules for each fund, I had to use a few assumptions to get net IRR figures for each fund.

1. Equal-dollar investor across funds (simple average by design)

I treated the “typical investor” as someone who keeps allocating a similar amount to each a16z fund over time. That’s why I used a simple average return across funds, not size-weighting.

Weighting matters if your goal is to estimate dollars returned by the whole a16z platform. But my goal here was to find out what the “average fund experience” looks like for a steady allocator.

2. Capital calls: evenly over the first three years

For each fund, I assumed paid-in capital is called evenly across the first three years, starting with the vintage year (a common pattern for venture drawdowns).

3. Distributions: modeled as a single lump at year 10

I modeled all realized distributions implied by DPI as arriving in a single lump at year 10 of each fund’s life. If a fund’s vintage is after 2015, then I assumed the distributions were made in 2024 (on average).

Is that a simplification? Yes. Could shifting distributions earlier or later change IRR? Yes—timing always matters for IRR. But given we lack actual distribution schedules, this “average-year” approach is a reasonable approximation.

4. Remaining value: realized at the measurement date

I treated the unrealized portion (TVPI minus DPI) as remaining value realized on September 30, 2025 (the date the performance snapshot is “as of”). That means the IRR is partly dependent on a16z in-house valuations—another unavoidable limitation.

5. Nasdaq comparison: mirrors the same contribution schedule

For Nasdaq, I simulated the same behavior: invest one-third of capital in each of the first three years (matching each fund’s paid-in schedule), then hold until September 30, 2025, valued off XNDX.

Using this model and excluding 2024 and 2025 vintages (too young for signal), the results came out:

• Average a16z LP net IRR: 22.2%

• Average Nasdaq equivalent IRR: 22.9%

As you can see, in this particular example, the returns for LPs didn’t exceed the average market return.

Liquidity considerations are even more important than the 0.7% return difference. Venture requires patience, and DPI can lag for many years, meaning “returns” may remain mostly paper for a long time.

Fees Explain A Lot

I also ran a rough gross return estimation by adding back typical 20% performance fees (carry) charged on LP profits and 2% (percentage of assets) management fees.

The resulting 27.7% gross IRR is well above the Nasdaq benchmark, even before accounting for fund-level expenses (charged on top of management fees) and the cash drag effect (cash reserves, cash flow timing mismatch).

Takeaways For VC Fund LPs

1. Analyzing net IRR, not just TVPI/DPI, is important: Multiples are important, but you want to consider cash flow timing, as well, to enable comparing fund returns to public benchmarks.

2. The game is longer than you might think: Even a best-in-class venture fund can take over 15 years to exit all investments, while selling LP stake often results in a hefty discount to NAV.

3. Don’t forget the intangibles beyond a VC fund’s returns: Access to co-investment deals, learning, networking/community and exposure to the latest tech trends are all important intangible benefits to look for.

4. Investing directly is also an option: If you have access to quality deal flow, another option is to experiment with direct startup investing and compare returns with your VC fund LP positions.

Read the original article here:
https://www.forbes.com/councils/forbesfinancecouncil/2026/03/04/a-practical-framework-for-comparing-venture-fund-performance-to-public-indexes/