Possible Insight

The VC "Homerun" Myth

with 9 comments

In spreading the word about RSCM, I recently encountered a question that led to some interesting findings.  A VC from a respected firm, known for its innovative approach, brought up the issue of “homeruns”.  In his experience, every successful fund had at least one monster exit.  He was concerned that RSCM would never get into those deals and therefore, have trouble generating good returns.

My initial response was that we’ll get into those deals before they are monsters.  We don’t need the reputation of a name firm because the guys we want to fund don’t have any of the proof points name firms look for.  They’ll attract the big firms some time after they take our money.  Of course, this answer is open to debate.  Maybe there is some magical personal characteristics that allows the founders of Google, Facebook, and Groupon to get top-tier interest before having proof points.

So I went and looked at the data to answer the question, “What if we don’t get any homeruns at all?”  The answer was surprising.

I started with our formal backtest, which I produced using the general procedure described in a previous post.  It used the criteria of no follow-on and stage <= 2, as well as eliminating any company in a non-technology sector or capital-intensive one such as manufacturing and biotechnology.

Now, the AIPP data does not provide the valuation of the company at exit.  However, I figured that I could apply increasingly stringent criteria to weed out any homeruns:

  1. The payout to the investor was < $5M.
  2. The payout to the investor was < $2.5M
  3. The payout to the investor was < $2.5M AND the payout multiple was < 25X.

It’s hard to imagine an investment in any big winner that wouldn’t hit at least the third threshold.  In fact, even scenarios (1) and (2) are actually pretty unfair to us because they exclude outcomes where we invest $100K for 20% of a startup, get diluted to 5-10%, and then the company has a modest $50M exit.  That’s actually our target investment!  But I wanted to be as conservative as possible.

The base case was 42% IRR and a 3.7x payout multiple.  The results for the three scenarios are:

  1. 42% IRR, 2.7x multiple
  2. 36% IRR, 2.4x multiple
  3. 29% IRR, 2.1x multiple

Holy crap!  Even if you exclude anything that could be remotely considered a homerun, you’d still get a 29% IRR!

As you can see, the multiple goes down more quickly than the IRR. Large exits take longer than small exits so when you exclude the large exits, you get lower hold times, which helps maintain IRR.  But that also means you could turn around and reinvest your profits earlier.  So IRR is what you care about from an asset class perspective.

For comparison, the top-quartile VC funds currently have 10-year returns of less than 10% IRR, according to Cambridge AssociatesSo investing in an index of non-homerun startups is better than investing in the funds that are the best at picking homeruns. (Of course, VC returns could pick up if you believe that the IPO and large acquisition market is going to finally make a comeback after 10 years.)

I’ve got to admit that the clarity of these results surprised even me.  So in the words of Adam Savage and Jamie Hyneman, “I think we’ve got to call this myth BUSTED.”

(Excel files: basecase, scenario 1, scenario 2, scenario 3)

Written by Kevin

August 23, 2011 at 3:10 pm

9 Responses

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  1. How would one invest in a “none-homerun” vc index fund? Is there such a vehicle or it’s just a matter of choosing the right VC with a consistent track-record?

    Hendrick Lee

    August 25, 2011 at 10:33 pm

    • That’s what we’re building at RSCM. 

      Anonymous

      August 26, 2011 at 6:27 am

  2. I can think of several reasons why the VC comparison does so poorly vs the Rightside model:
    1) later stage, lower risk, lower returns
    2) VCs as a class underperforming expectation (as you mention)
    3) VCs displaying adverse selection bias
    4) cost of doing VC deals eats into IRR

    What relative weight would you give each of these reasons if you had to hazard a guess?  Are there other reasons you believe should be added to this list?

    Rafe Furst

    August 26, 2011 at 1:29 am

    • The biggest problem is with the asset class as a whole.  Average 10 year returns for the asset class are zero to negative.  Of course, there are always some outliers.  But it’s hard to know which of the outliers are lucky and which are good.  Personally, I have some gut feel about this, which unfortunately I can’t really trust as an evidence-based guy.

      I think the proximal causes of the poor asset class performance are twofold.  First, the large-value exit market has been awful for 10 years.  Second, it’s much cheaper to start a technology company these days so there are relatively fewer deals that can absorb the number of dollars traditional VCs want to put to work (this could be a source of adverse selection, but it’s hard to tell from the data).  I think both of these trends are likely to continue.

      The second big problem is lack of diversification.  Most VC funds invest in so few companies that they have to be incredibly good to avoid a random string of bad outcomes.  Investors can ameliorate this problem by using a fund-of-funds, but then they’re paying two layers of management and carry fees.

      Anonymous

      August 26, 2011 at 6:43 am

  3. I have only looked at this briefly, and my comments may reflect this.

    1.  It seems that your business model isn’t really an investment fund, but rather an investment platform.  You want lots of small seed companies to join, and if they do more operational experts will be attracted to your advisory board.  More operational experts will attract more small seed companies.  If it works, you may have a nice catalyst effect, if there are network effects in the advisors and small seed companies.

    2.  If that is the right analysis of your business model, then the value of the platform is dependent on how big a monopoly you can obtain – a monopoly value  that is unrelated to the probability that one company becomes a monster hit.

    That is my initial impression, please feel free to correct  my mistakes.

    michael webster

    August 28, 2011 at 7:26 am

    • We hope to eventually grow it to be a platform. In fact, we’ve got a bunch of crazy idea for down that road. But for now, we’re focused on deliverying initalt proof that we can attract goood compaies. invest in them, and keep the companies moving.

      kevindick

      August 28, 2011 at 1:01 am

  4. […] a fair bit of Moneyball-type analysis using the available evidence for technology startups (see here, here, here, here, here, and here).  But I thought I’d take this opportunity to make the […]

  5. What is the best way to angel invest a million dollars?…

    @Michael. Actually, that’s something of a misperception. As I’ve demonstrated from the AIPP data, it’s true that most of the gains come from a small proportion of the investments. But these are not what people typically think of as “huge winners” …

    Quora

    March 22, 2012 at 4:48 am

  6. […] I documented how I applied this strategy to the AIPP data set, complete with filtered data file, in this post. In principle, you could create a filtered data file for your own strategy as described in this […]


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