I previously published this at Techcrunch.
The good news for Techcrunch readers: Every major study conducted to date has placed angel investors’ IRR between 18 and 38 percent, as summarized by my Partner John Frankel and Professor Robert Wiltbank in prior Techcrunch articles. The bad news: the data on angel returns has historically been difficult to obtain, analyze, verify, and therefore rely upon.
Despite the inherent difficulties in quantifying angel returns, we think that the aforementioned studies have significant implications for angel-stage investors, for several reasons:
- Even if there is some bias, the median IRR is still far higher than any other asset class. It seems unlikely that the reporting problems above account for all of it. Every major angel study conducted to date has shown high IRR.
- The results don’t generalize to all angels, but they strongly suggest that more professional, institutional investors should do even better than individual amateur angels.
- Even if the methodology is full of holes, it is still useful for generating theories on angel-stage opportunities. That is what we are doing through our own investments.
Small, agile funds are in an excellent position to take advantage of opportunities in the angel space. As Jon Calligan of True Ventures explains, “The numbers just don’t add up. There are a minimum of 2,000 companies per year getting funded and coming out if incubators, and there are only 750 VCs that call themselves ‘active.’ But when you look at who is doing at least two deals a quarter, the numbers fall to just 200 firms. Those firms are only going to do a few Series A deals a year.” In fact, 97 firms have invested at least $1M a quarter for four straight quarters. AngelList co-founder Naval Ravikant concludes, “The real winners here are going to be the seed funds and early stage VCs that can write a $1 million to $2 million check. They’re buying into companies post-seed funding, with traction, at prices that aren’t significantly higher than angel prices.”
With all that said, the data is definitely weaker here than, say, the data Identified (ff VC company) uses to gamify your job search. There are hundreds of thousands of active angels at any given time, and they are bound to no legal reporting requirements on their investments beyond filing tax returns. The only way to get data is to reach out to individual angels. Unfortunately, angels aren’t easy to find; many intentionally keep a low profile. Researchers are forced to rely on angel group registries and word of mouth. Even if a sufficient number of angels are identified and surveys sent out, most of those angels will fail to respond or give incomplete data. Obtaining accurate return data for angel investments is therefore a daunting task. Given that angels deploy almost as much capital as VCs ($22.5 billion for angels versus $29.5 billion for VCs), however, it is worth the effort to do so.
We believe the most reliable studies are Returns to Angel Investors in Groups and Expected Returns to Angel Investors, both of which use the Kauffman Foundation’s Angel Investor Performance Project (AIPP) dataset and place angel IRRs north of 30 percent. Data was collected from 1,137 exits on 3,097 investments, but only 602 exits have enough variables reported to be fully usable. Even so, AIPP is still easily the largest angel dataset. All exits occurred between 1990 and 2007—the vast majority after 2000.
Despite the relatively large sample size, we do not believe it is necessarily representative of the overall angel market for two reasons. First, all respondents are accredited and belong to angel groups. Results can only generalize to other angels with these characteristics. Second, all investments are equity instead of debt. 40% of actual angel investment dollar value is debt, which has a lower expected return.
Two biases are of particular concern (and seem to plague all angel return studies): self-selection bias and survivorship bias. The lack of a significant difference in returns between high and low response rate angel groups surveyed somewhat counters the concern with self-selection bias. The aforementioned Robert Wiltbank, co-author of Returns to Angel Investors in Groups, makes two generic arguments on the subject of survivorship bias in a later article (Siding with the Angels: Business Angel investing – promising outcomes and effective strategies). First, it is possible to access inactive angels through their groups, meaning that some angels who have discontinued their activities may nevertheless be among the respondents. Second, sampled angels still have ongoing investments. Since positive exits take longer, the results should be negatively skewed. Moreover, some of the sampled angels will fail later even if they haven’t already.
In order to determine the extent to which these biases may be affecting results, Expected Returns to Angel Investors includes a few “bias tests,” most of which point to modest bias or none at all. First, larger deals and deals involving multiple angels are more likely to be reported accurately. Only one metric showed statistical differences between these deals and others. This outcome suggests that respondents were reporting honestly. Second, the overall returns from AIPP are comparable to other datasets (though the IPO percentage is a bit higher).
Some VCs have adopted the principle that typical angel returns must be “atrocious.” After all, if the average VC fund barely returns investor capital, how could amateurish angels with more risk and worse deal flow possibly do better? As it turns out, the conventional wisdom is wrong. The claim that typical angel returns are atrocious is demonstrably false, and no amount of tortured reasoning or unsystematic anecdotal evidence will prove it true.
However, it is absolutely true that any one angel deal is very risky. We think the bare minimum level of diversification needed to get good returns as an angel investor is 20 companies, and few angels have the time, patience, and resources necessary to make 20 angel investments. This creates a market opportunity for formal angel groups (which have been shown to increase returns for their members) and for institutions which focus on angel-stage investing.
Thanks to intern Matt Joyce for help researching and drafting this.