How to underwrite angel track records in less than 2500 word
The sequel is ALWAYS better than the original right? Well I certainly believe so. At least this time….
David Zhou (of Cup of Zhou) and I had so much fun, and such a warm reception to our last piece on the risks of early stage venture fund investing, that we decided we had to do it again.
This time, we started by listing out the pros, cons, and doesn’t matters of an angel investing track record as it relates to building a fund. We took that list and turned it into this post.
This is a hot topic, and people tend to have very hardline approaches on this. What sets David apart, and what makes me so excited to collaborate with him is that he has the incredible ability to bring nuance to the debate. He lays out how he thinks, in addition to what he thinks, which both provides a deeper understanding of the topic, but also an acceptance where disagreements happen. This was one of those processes where I couldn’t stop smiling every time we went back and forth on edits.
You can read David’s version of the post (and while you are there you should subscribe to his blog) here. Now, on to the post:
Venture is a game of outliers. We invest in outlier managers, who invest in outlier companies, capitalizing on outlier opportunities.
Angel investments have excelled at catching and generating outlier outcomes. However, in recent years, angel checks are not just a critical piece of the capital stack for startups, they are also a way where amazing people can learn and grow into spectacular investors. In the past 20 years, angel activity has gone from a niche subsection, to a robust industry with angel groups all over the world, and the emergence of platforms to facilitate their growth.
As LPs, we see this every day. A common story that we diligence is the angel turned institutional VC. This process is what allows aspiring GPs who come from all walks of life, with often quite esoteric track records, to raise funds and prove they can be exceptional venture capitalists. These people are often the outliers at the fund level. The non-obvious investors who are taking their angel investing experience and turning it into elite cornerstones of the venture ecosystem. For example:
Chris Sacca maxed out his credit card to invest in Photobucket, which he eventually used to pitch Lowercase Capital Fund I and less than a decade prior, he was $2M in debt.
Arthur Rock, having done a few years of angel investments, goes to raise his first $5M fund that returns $90M in 1968. Then goes on to invest $2.5M for 50% of the company two guys with no business plan started. By the way, that became Intel.
And how five angels hosting monthly lunches in the 1950s each go on to found IVP, US Venture Partners, Sutter Hill, and Asset Management Company.
Each of these angels-turned-investors returned their earliest believers many times over. And these are far from the only examples.
So, as an allocator, it is logical to want to pattern match to the angel investor turned GP as a way to assess how good a manager might be in building their firm. However, with more venture firms than there have ever been, and more ways to access angel-investing, differentiating signal from noise has never been harder. The hardest being where the track record is too young, too limited, and there’s not enough to go on. So it begs the question: How the hell do you underwrite an angel track record that’s still in its infancy?
The simple answer is you don’t. At least not completely. You look for other clues. Telltale signs.
So, our hope with this piece is to share what we each look for – most of which is beyond the numbers. The beauty of this piece is that even while writing it, Ben and David have learned from each other Socratically on how to better underwrite managers.This is one that can be pretty controversial, and we don’t agree on everything. So, let us know what you think….
Understanding the returns:
Every pitch deck we look at has a track record slide. Usually this is some amalgamation of previous funds (if they have any), advisor relationships, and angel investing track record. Angel investing track record is usually the largest number in terms of TVPI or IRR. However it also has the least clear implications, so we need to be careful in understanding what it means. Here are the steps we take in understanding the track record.
Step 1: Filtering the Track Record
First, we get aggressive with filtering the track record the GP shows you. Not the select investments track record on the deck, but the entire track record including advisor shares, SPVs, funds, and any other equity stake. We do this as angel track records are usually the result of opportunistic or inbound access over a long period of time. The companies in their angel portfolio don’t necessarily relate to their thesis or plan for their fund. So cutting the data by asset type and starting with thesis vs off thesis investments is a helpful starting point.
Next, it’s helpful to understand the timeframe. Funds have fixed lifespans [1], and strict deployment time periods, which we call vintages. In order to understand the performance, we break down the time periods of their investments including entry date, exit date, values relative to median at that time, and average hold period. Naturally, also, we do note entry valuation, entry round, exit valuation, and ideally if they have it price per share. Having the afore-mentioned will help you filter returns, especially if a GP is pitching you a pre-seed/seed fund, but the bulk of their returns come from one company they got into at the Series B.
Lastly, it’s helpful to group investments into quartiles. Without sounding like a broken record, it's important to remember that venture is fundamentally outlier-driven. Grouping the investments, understanding them at the company specific level vs aggregate is critical to the next phase, which is understanding the drivers of the track record.
Also, it’s important to note that some vintages will perform better than others. And as an LP, it’s important to consider vintage diversification (since no one can time the market) and what the public market equivalent is. For a number of vintages, even top-quartile venture underperforms the QQQ, SPY, and NASDAQ. A longer discussion for another post. Cash, or a low-cost index is just as valid of a position as a venture fund.
Step 2: Understanding the Drivers
Once you have broken down the data, we want to understand the real drivers behind the returns from the track record. We tend to start by asking these questions:
Are there other outliers in the off-thesis investments?
What are the most successful on-thesis investments?
Has any money actually been delivered, or is it entirely paper markups?
What is the GP’s valuation methodology? [2][3]
For the on-thesis investments that returned less than 10X the check size, what did this individual learn? How will that impact how this GP makes decisions going forward?
How much of a GP’s track record is attributed to luck?
And simply, do the founders in the GP’s supposed track record even know that the GP exists?[4]
With respect to the second-to-last question, if their on-thesis track record has more than 10 investments, we take out the top performer and the bottom performer, is their MOIC still interesting enough? While there is no consistency of returns in venture, it gives a good sense of how much luck impacts the GP’s portfolio.
The last question is extremely prescient, since the goal of a GP trying to build an institution – a platform – is that they need the surface area for serendipity to stick to compound. Yesterday’s source of deal flow needs to be worse than today’s. And today’s should be eclipsed by tomorrow’s. As LPs, we want the GPs to be intimately involved in the success of their outliers not because attribution of value add matters, but because great companies bring together great teams. Great teams aggregate and spawn other ambitious people. Ambitious people will often leave to start new ventures. And we want the GP to be the first call. More on that in the next section.
Step 3: Transferability to a Fund
Lastly, the analysis will need to shift from purely quantitative to qualitative guided by the quantitative. We are moving from the realm of backward-looking data, into forward projection. The main question here is how do all the data points we have point to the success of the fund and the differences in running a fund versus an angel portfolio such as:
Fixed deployment periods
Weighted portfolio risks
Correlation risk between underlying portfolio companies
Information rights and regulatory requirements
Angel check size vs fund’s target check size
One heuristic that we use is that of finding the “hyper learner.” The idea is basically, how fast is this person growing, learning and adding it into their decision-making around investing. Do they have real time feedback loops that influence their process, and can they take those feedback loops to the next level with their fund? Essentially, understanding that what matters with emerging VCs is the slope, not y-intercept, so can you see how their decisions will get better?
While everyone learns differently, some of the useful thought experiments to go through include:
What is the GP’s information diet? Where are they consuming information through channels not well-documented or read by their peers?
How are they consuming and synthesizing information in ways others are not?
How does each iteration of their pitch deck vary between themselves? [5]
Do you learn something new every conversation you have with the GP?
Overall, this is more a bet on the person learning how to be a great fund manager, and can’t all drive from just pure angel investing track record.
The details the numbers can’t tell you:
“We spend all our time talking about attributes because we can easily measure them. ‘Therefore, this is all that matters.’ And that’s a lie. It’s important but it’s partial truth.” — Jony Ive
Angel track records can point to how serious the potential GP is about the business of investing. At the same time, there are factors outside of raw numbers that also offer perspective to how fund-ready a GP is. Looking through the details, it is important to ask in the lead-up to making the decision to run a fund, how have they spent their time meaningfully? For example:
What advisory roles have they taken? What impact did they deliver in each? For those companies and firms, who else was in the running? And why did they ultimately go with this individual?
Have they taken independent board seats? Why? What was the relationship of the founder and board member prior to the official role?
If they’re a venture partner or advisor to another VC firm, what is their role in that firm? When do they get a call from the GPs or partners of that firm?
Is the angel/advisor part of non-redundant, unique networks?
Does the angel/advisor have a unique knowledge arbitrage that founders want access to?
Does the GP’s skillset match the strategy they’re proposing?
Money isn’t the only valuable asset. Time, effort, experience, and network are others. Especially if an angel has little capital to deploy (i.e. tied up in company stock, younger in their career, saving up for a life-impacting major purchase like a house), the others are leading indicators to how a network may compound for the angel-turned-GP over time.
Anti-portfolio
Lastly, one of the hardest parts of understanding angel investing track record is the anti-portfolio as popularized by BVP. As picking is such an important aspect of a GP’s job, understanding how the person has previously made investment decisions based on the opportunities they are pursuing and what they missed out on is critical.
The stopwatch really starts counting when the angel decides that she wants to be a full-time investor one day. The truth is no third party will really know when that ticker starts, outside of the GP’s own words. And maybe her immediate friends and family. While helpful to reference check, it’s her words against her own.
Instead, we find their first angel check or their first advisory role as a proxy for that data point. The outcome of that check isn’t important. The rationale behind that check also matters less than the memos of the more recent checks. Nevertheless, it is helpful to understand how much the GP has grown.
But what’s more helpful is to come up with a list of anti-portfolio companies. Companies within the investor’s thesis that rose to prominence during the time when that individual started to deploy. And within good reason, that individual may have come across during their time angel investing or advising. In particular, if the angel has not been able to be in the pre-seed. More often than not, folks investing in that round are friends and family. If they are in the seed round, the questions that pop up are:
Did she not see it?
Did she not pick it?
Or, did she not win it?
For the latter two questions, how much has she changed the way she invests based on those decisions? And are those adjustments to decision-making scalable to a firm? In other words, how much will that scar tissue impact how she trains other team members to identify great companies?
Contradictions
One of the most important truths in venture is that to deliver exceptional returns, you have to be non-consensus and right. This ultimately derives from someone being contradictory, with purpose throughout their life.
There is beauty in the resume and the LinkedIn profile. But it often only offers a snapshot into a person’s career, much less their life. So we usually spend the first meeting only on the GP’s life. Where did she grow up? How did she choose her extracurriculars? Why the college she chose? Why the career? Why the different career inflection points?
We look for contradictions. What does this GP end up choosing that the normal, rational person would not? And why?
More importantly, is there any part of their past the GP does not want us to know? Why? How will that piece of hidden knowledge affect how she makes decisions going forward?
Naturally, to have such a dialogue, the LP, who more often than not are in a position of power in that exchange, needs to create a safe, non-judgmental space. Failure to do so will prevent candid discussions.
In Closing
It is extremely easy to over-intellectualize this exercise. There are always going to be more unknowns to you, as an LP, than there are knowns. Your goal isn’t to uncover everything. Your time may be better spent investing in other asset classes, if that’s the case. Your goal, at least with respect to underwriting emerging managers, is to find the minimum number of risks you can stomach before having the conviction to make an investment decision.
And if you’re not sure where to start with evaluating risks, the last piece (Ben’s blog, David’s blog) we wrote together on the many risks of investing in emerging managers may be a good starting point.
Footnotes:
[1]We are choosing to ignore evergreen funds for the purpose of this article, but we know they exist.
[2] Beware of GPs who count SAFEs as mark ups. While we do believe most aren’t doing so with deception in mind, many GPs are just not experienced enough in venture to know that only priced rounds count as marks.
[3] Separately, is the GP holding 2020-early 2022 marks at the last round valuation (LRV)? Most companies that raised during that time are not worth anything near their peak. Are they also discounting any revenue multiples north of 10-20X? How a GP thinks here will help you differentiate between who’s an investor and who’s a fund manager.
[4] This may seem callous, but we have come across the instance multiple times where an aspiring GP over states (or in one case, lied) their position on the cap table. Founder reference checks are a must!
[5] David sometimes asks GPs to send every version of their current fund’s pitch deck to him, as an indicator on how the GP’s thinking has evolved over time. Even better if they’re on a Fund II+ because you can see earlier funds’ pitches. Shoutout to Eric Friedman who first inspired David to do this.