The Impact Of Proper Venture Portfolio Construction-Optimized DPI & IRR
This post is an exercise in isolating the impact of optimal diversification, staged capital deployment (across multiple rounds) as the research frames, and a focus on the real rate of return investors should care about — the Internal Rate of Return (IRR).
TLDR:
Simply stated, risk management has an outsized impact on returns for venture investors. Diversification, dollar-cost averaging, data-driven decision making — what professional investors call ‘Process Alpha’.
However, most ‘typical’ venture funds are grossly under-diversified. Properly diversified venture funds dramatically outperform the ‘typical’ venture fund.
Staging your capital deployment properly over multiple rounds dramatically improves the IRR for investors, regardless of the MOIC/DPI. And given the natural failure rates of startups (usually within the first 2 or 3 yrs), optimizing on how much you invest in each round improves the risk-adjusted returns available.
Lastly, the overlooked QSBS tax incentives (Sec 1244 & Sec. 1202) optimizes the after-tax risk and return profile, but goes largely ignored by venture investors.
DETAILS
Fred Wilson published a terrific piece recently on startup failure rates (see HERE).
In Fred’s piece he provided the portfolio return averages within a16z’s portfolos:
- 25% fail outright
- 25% return < 1x
- 25% return between 1x to 3x
- 15% return between 3x to10x
- 10% return >10x
For the sake of this discussion, let’s average these, and presume a16z put an equal amount in each of the portolio companies in this example (BIG assumption, I know).
- 25% fail outright
- 25% return .5x
- 25% return 2x
- 15% return 6.5x
- 10% return 30x
The weighted average multiple on invested capital on the above assumptions would be 4.6x.
- (.25 x 0 +.25 x .5 +.25 x 2 +.15 x 6.5 +.1 x 30)
If we assume the upper bound of the a16z ranges, the multiple would be 7.5x.
- (.25 x 0 + .25 x 1 + .25 x 3 + .15 x 10 + .1 x 50)
Both of theses sets of assumptions would put them clearly near the top of the ‘typical’ concentrated portfolio:
Note: What we don’t know is the timing of cash-flows (both the investment activities and the timing of the returns) on the a16z numbers to calculate a proper Internal Rate of Return.
IMPORTANCE OF DIVERSIFICATION
Given the impact on the outsided returns coming from such a small % of venture portfolio holdings, the impact of proper diversificaion to improve the odds of having an outsized return is reflected in the table above.
However, the ‘typical’ early stage venture fund does far worse.
For for ‘typical’, let’s assume:
- 25 holdings
- 66% of capital deployed at the Seed Round (yrs 1 &2)
- 25% at the A Round (yr 3)
- 10% at the B Round (yr 5)
- Distributions yrs 8–10.
‘TYPICAL’ Return Expectations (extrapolated from the data table)
- Median Return — 2.96x; 16+% IRR
- 25th Perentile — 3.67x: 20+% IRR
This is clearly below a16z’s stated return numbers — as would be expected — regardless of which set of assumptions you presume.
(Note: Since the original drafting of this piece, Dan Gray produced an interesting piece on the first 5 a16z venture fund returns. While the ‘batting average’ numbers offered by a16z might be true, that didn’t mean it translated to compelling alpha for their investors. Another validation that portfolio construction matters.)
TIME VALUE OF MONEY
What serious investors do understand is the impact of time on a more appropriate calculation of return —Internal Rate of Return (IRR).
Example #1:
If you get a 3x return on your money, which is better (assume 40% of capital was deployed in yr 1, 60% in yr 2):
- The 3x with exits/distributions between year 3 and 5 (ave. yr 4)
- The 3x with exits/distributions between years 7 and 10 (ave. yr 8.5)
The answer is obvious — the shorter the term, the higher the IRR; 60% and 16+%, respectively.
Example #2 — Optimized for DPI and IRR:
What if a venture fund applied optimized diversification of 100 companies, at the Seed round, AND optimized for IRR by deploying capital across multiple rounds (still maintaining proper diversification), with exits in years 8–10 (ave. yr 9):
- Seed Round: 100 companies, equal weighted, and only 15% of total fund capital (per The Kelly Criterion). Expected return per the table above (top quartile/25% of funds’ return); 5.5x, IRR; 25+% annualized return.
- A Round: 60 of the top performing companies from the Seed round, equal weighted, and 30% of total fund capital (per Kelly Criterion). Expected return per the table above (top quartile/25% of funds’ return); 6.17x, IRR: 38+% annualized return.
- B Round: the 30 best A round companies, equal weighted, with the remaining capital of 55% (Kelly Criterion again). Expected return per the table above (top quartile/25% of funds’ return); 4.2x, 50+% IRR.
The return across all 3 rounds at the entire fund level; 5x, 35+% IRR.
This makes sense when looking at the Seed round returns compared to the B round portfolio and the entire strategy; higher multiple, but lower IRR due to the average time the capital is tied up.
This strategy is illustrated below:
MEDIAN RETURNS
Even when applying the ‘median’ fund returns per the table above, when executed across this strategy the fund would still deliver compelling returns: 3.54x multiple, and a 28+% annual IRR!
TAX-EFFICIENT RETURNS — QSBS OPTIMIZED
An overlooked opportunity for fund managers is to optimize on the after-tax returns for their taxable LPs. By utilizing BOTH QSBS tax benefits; Sec. 1244 (losses deductible against ordinary income) and QSBS Sec. 1202/1045 exchanges ($10M of gains PER TRANSACTION tax-free), the pre-tax and after-tax returns can be the same.
If a fund were structured as discussed and illustrated above, even with the median return expectations, then investors could realized 28% annualized returns tax-free!
WHAT’S POSSIBLE
This is all possible should GPs of venture funds study the available research and published white papers showing how.
Or they could launch a fund immediately by going HERE.
Referencable Research
Note: The spreadsheet calculating the returns above is available — joe@angelspan.com. For illustrative purposes, all returns are calculated before fees.
A Tale of Two Squirrels: The Not So Simple Math Of Venture Portfolio Size — Matt Lerner
The Venture Capital Risk and Return Matrix — Industry Ventures
Dirty Secret: Venture Reserves Aren’t Always a Good Thing — Sapphire Ventures
What’s The Optimal Portfolio Strategy For a Venture Fund — VCAdventure
Why Venture Capitalists Should Invest Like Poker Players — Prof. Claudia Zeisberger
Top VCs Firms Don’t Outperform The Broader Market at Seed — AngelList
