Papers exploring how angel investors select deals

Over the last couple of weeks, we have explored some academic research into how angel investors select investments. Here’s a quick recap for you.

A frequent question from entrepreneurs is: How do angels select deals? Often selection of an appealing investment feels random or biased. In the first paper, which you can go download here (if you come back), Attracting Early Stage Investors: Evidence from a Randomized Field Experiment authors Shai Bernstein, Arthur Korteweg, and Kevin Laws examine the characteristics that seem most important to investors in early-stage companies.

Bernstein and Korteweg are from business schools in California, and Laws is from AngelList — a nice combination of academia and real-world practitioners. They were also covering new ground in 2014, with the first experiment showing the causes of particular investment selection.

The experiment was to send 16,981 emails about 21 companies to 4,494 active investors (and really 8,189 emails that were opened by 2,925 investors, as many didn’t open any of the emails) on AngelList during its early years. The emails randomly varied the information shown on three key variables — founding team, traction, and lead investors — and recorded the decisions to “learn more” about the investment opportunities. (This is to address the selection bias of only looking at companies that are actually funded.)

To cut to the chase: investors respond to information about the team, but do not respond to information about traction or lead investors (p.4). The paper confirms experimentally the angel investor cliché that angel investors “back the jockey and not the horse”.

The paper goes on to examine the related questions of “why” information on the team affects investment decisions (investors value execution — “operational capabilities” — more than ideas); and whether focusing on the team actually creates better results (in Section VI: no answer in this paper, though more experienced angels (who presumably have better returns) have the strongest response to team information and lowest reaction to other subjects… suggesting overall “yes it does”).

Several interesting insights or further conclusions emerge:

• The paper highlights a key theme of “growth” investing — how companies move from “human capital focused” (i.e. back the jockey not the horse in the earliest stage) to “asset” focused, as one of the ways companies create enterprise value is to move from founder personality to established business.
• Given how often early-stage investors are accused of “herd behavior” and basing their investment decisions on who the shallow idea of who the lead investor is, it’s interesting to see the experimental evidence that “notable lead” really isn’t a determinant of whether companies get investors’ attention. This is true of the active investors on AngelList; is it true generally?
• What can entrepreneurs learn from this? Team is key! If you’re going to spend extra time on presentation, emphasize the credibility and skillset — especially operational capabilities — of the founding team.

Overall, nice to know the clichés have some experimental validation!

Early-stage investors back the jockeys and not the horses. But that is not everything we need to know about how angel investing decisions are made. Luckily, one source for more ideas is Angels or Sharks? The Role of Personal Characteristics in Angel Investment Decisions, which focuses on the personal characteristics (race, gender, age) of the entrepreneurs being backed. If you are studious, download the paper here.

A paper that doesn’t rely on AngelList data! Instead, authors Thomas J. Boulton, Thomas Shohfi, and Pengcheng Zhu do the work so that we don’t have to: they watched the first eight seasons of ABC’s Shark Tank!

You might know everything you know about angel investing from Shark Tank. (That’s a good start, but you might want to check out VentureSouth’s “Myths of Angel Investing” too…) Angel investing on Shark Tank differs considerably from hometown angel investing at VentureSouth. Nonetheless, the dataset of 1,089 entrepreneurs, 707 ventures, and 14 angel investors on Shark Tank’s earlier seasons gives some interesting insights into how (some) angel investors make decisions.

What does watching every episode of Shark Tank reveal?

• Some academics go the extra mile for a good paper!
• Angels are more likely to fund younger and “better” businesses (higher profit margins and businesses with patents held or pending) (p.2)
• Older entrepreneurs are less likely to receive offers, as are potentially black entrepreneurs (p.2), who are also likely to get lower valuations.
• Generally, younger, female, and black entrepreneurs request lower valuations; Asians and “entrepreneurs from top universities” request higher valuations (p.2) (but do not receive them) (p.23)
• Gender does not seem to matter (p.3).
• “Homophily” is important (p.3) — investors fund people “like them” — with, for example, black investors more likely to make offers to black entrepreneurs, and black founders more likely to take deals from black investors.

First, let’s tackle some objections to using Shark Tank data: presenters are highly selected (including for characteristics like entertainment value) and therefore probably not representative of early-stage companies generally; the investors are equally unusual (celebrities and ultra-HNW individuals with net worths estimated between $70M and $3.4BN) and not typical angel investors; and, more subtly, Shark Tank activity is public so perhaps the impacts of biases and preferences are lessened compared to what happens usually in private? All true, but at least the data makes a change from survey responses and anecdotes.

With these caveats in mind (and which, of course, the authors try to control for and/or examine), what are we to make of these experimental results?

There are some in here that aren’t a surprise. In all walks of life, people like to interact with people “like them”, so the homophily discussion is not a shock. (It may still, of course, be a problem.) The mixed evidence of bias against women might be surprising, if you didn’t read the prior articles we discussed here and here, or any of the previous angel investing literature (see the discussion of prior literature being mixed on p.7). In this case, female Shark Tank contestants request lower valuations (p.18 and table 3 p.37) but are not less likely to receive an offer or a “discount” offer (tables 4–6). If true, this would have significant implications for efforts to equalize funding for female entrepreneurs.

While these primary hypothesis questions combine both the expected and the unexpected, there are several “asides” in the paper that reinforce accepted wisdom in angel investing. As three quick examples:

• A shared geography also increases the likelihood that an offer is made (p.21). Even sharks like to invest close to home.
• Valuations are higher when multiple angel investors compete to make an investment (p.2). Getting a competitive situation going helps maximize value during negotiations
• Ventures pitched by a single entrepreneur are less likely to receive an offer, which is consistent with angel investors having concerns with respect to key man risk. (p.19). Indeed, a company with just one founder does not get into screening at VentureSouth, as there’s too much risk of 100% of the team leaving.

Fun paper. We’ll leave you, as usual, with extra interesting nuggets and observations from the scholars:

• The average firm has $0.26 of sales per dollar of requested valuation (p.14) — so ~4x LTM revenue is the Shark Tank valuation benchmark but…The price-to-sales ratio of approximately 4 is lower than Sievers et al. (2013) who report multiples as high as 13. (p.14) Not much help answering the perennial question of “how do you value early stage companies?”!
• Troy Carter has a 75% bid rate (p.35). I hear you — I want to invest in everything too!

There are plenty more papers examining decision-making of angel investors — and much more on venture capitalists and investors in general. Hopefully these two articles lead you down a fun research path, and help you become better investors.