AllAboutAlpha | May 28, 2013 01:37AM ET
In 2010, we started the development of i2X by taking a deeper look into the economics of seed stage investing. A Kauffmann study on returns of angel groups showed 27% annualized returns at a median return of -20%. This summarizes the central challenge in seed investing: outstanding average returns, but at unacceptable risk levels.
The risk problem can be put into perspective by a simple thought experiment: if you capture one Facebook at seed stage, it offsets over 5000 total losses in the same portfolio within 7 years. One Dropbox creates a 2x return for a 500 startup portfolio, even if all others return 0% p.a.
But thought experiments are not actionable. As long as we don’t know the empirical truth of portfolio returns, seed investing will remain an irrational act. Our mission was to find a filter and reference point that enables the design of a structured seed stage investment framework.
15 Accelerators With 1000+ Historic Start-ups
Our approach for building this reference point was the new generation of startup accelerators that had emerged over the past few years. We chose 15 leading accelerator programs as our analytics target, and started the analytics process. The first step turned out to be the most difficult: building a comprehensive data layer that would entail all investment rounds, dates and valuations for every historic start-up in these ecosystems. This was a daunting task: we had to develop new ways to acquire highly confidential data, and build a system of proprietary algorithms to complete missing data points with sufficient accuracy by using reference points in the wider VC data universe.
After 12 months of endless operational and mathematical hacking of the problem, we finally achieved our goal: an advanced robust data engine that minimized the margin of error, and provided us with a uniquely complete picture of the i2X accelerator ecosystem and over 1000 technology startups from our accelerator network. All we had to do now was to create an analytics layer on top of this data matrix to simulate fund performance and risk.
Today, the i2X engine provides us with analytics on-par with elite scientific hedge funds, and allows us to simulate risk/return profiles across different accelerators with a high level of accuracy.
The results provide us with a comprehensive insight into the economics of “Breeding Pioneers”. The following projections simulate the outcomes for one specific fund design (the exact design is confidential, but think a combination of clusters such as 10% consumer web startups / DreamIt Ventures, 15% enterprise start-ups / Y-Combinator, etc.) across four portfolios sizes: 5, 25, 75 and 100 start-ups.
Advanced Analytics Reveal the Empirical Performance of Seed Stage Portfolios
To simulate the outcome, we run 600 simulations per portfolio size that randomly pick start-ups in the target clusters from the historic data base. Each blue dot represents the annualized returns of one portfolio (Fig. A1-A4).
The simulation reveals an interesting dynamic moving from a 5 to a 100 start-up portfolio: the median return moves up dramatically from 4.4% to 23%, the spread of returns gets reduced from a 180% spread to a 75% spread, and the entire set of returns moves up.
We see how the distribution for the smallest portfolio (Fig. B1) stretches far across the spectrum, indicating a high level of risk. The distribution peak is frighteningly close to the 0% return mark, and a significant portion of returns are negative. Going up to 25 (Fig. B2), 75 (Fig. B3) and 100 (Fig. B4) start-ups in each portfolio, we see how the distributions get narrower, indicating a lower spread and risk, and how both peak and larger share of distributions move away from the 0% return mark into higher yield territory.
The results are a far cry from our optimized portfolio, and resemble traditional venture capital performance. It returns roughly 0% per year at a 53%
chance of loss, a median of 0.1%, and a poor 4% chance of making more than 10% per year (Fig. D).
Structured Optimization Achieves A Superior Risk/Return Profile
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