For reliable excess returns, VC funds need 500 investments
institutionalinvestor.com
institutionalinvestor.com
Edit: the 3rd takeaway is advice to those who're considering to join a "startup" - if VC needs 500 investments to make a 15% return on average, you need 5000 years to get the sames returns as a line worker.
I follow all of the VCs on Twitter and it's very clear from their many, many tweets that they have a far superior intellect than the rest of us which allows them to divinely predict the future.
And between them and their diverse network of other 40 year old, white males they have a rich, deep understand of the customer's wants and needs. And from that they 'select' the startups that best aligns with this understanding.
I even believe that one day VCs will realise that they don't need founders and can just invest in each other. Keeping the prosperity moving.
As a 40yo white male, I resent this generalization.
You should have qualified that further with "...living in the Bay Area".
Not sure if this is sarcasm or not. I'm leaning towards sarcasm, but if there ever was a place where someone would say this with a straight face it would be HN.
It almost certainly is.
> if there ever was a place where someone would say this with a straight face it would be HN.
This is not my impression of HN at all. It might have been true, what, a decade ago? but contemporary HN is pretty sceptical of VCs and VC culture.
A lot of recent exits have been sales to other PE funds rather than to the IPO market.
PE / VC have become an Assets under Management (AUM) game where the GPs only care about the fixed fee they get on the cash invested. With funds locked in for 10 years or more, that's a massive annuity - who needs outperformance?
And if you do need to show liquidity, let's exchange a few assets between the usual suspects...
Pretty ironic jab considering that the Bay Area VC crowd drinks the idpol kool aid so much.
This doesn't necessarily follow. A "line worker"'s downside risk is the opportunity cost they pay for working at a startup, which has a different distribution than the investor's downside risk (the whole investment). At the extreme end I'd argue that e.g. WeWork's investors came out of it worse than the employees.
That's because the less money you have, the more valuable a dollar is.
this is a fairly bad expected value: 10% * 7 * wages - 90% * wages/2 = 25% * wages
So you expect to lose 75% of your wages! Nobody is gonna agree to do that!
A more realistic scenario is 10% * 100 * wages - 90% * wages/2 = 955% * wages
0.5 * 90% + 7 * 10% = 1.15 average.
0.1 * 6 - 0.5 * 0.9 = 0.15.
That is, a 10% chance of a 6 fold gain, and a 90% chance of a 50% loss (-50% gain), gives an expected value of a 15% gain.
Your math is correct also, and has 1 represent no change to your wages instead.
The gain is a one time amount
Wages are recurring income. So when wages fall by 50% you need to value an annuity with half the cashflows as before. The PV of your wage income stream over some time horizon can then be compared with the one time gain.
Otherwise you are comparing a stock concept (wealth) with a flow concept (income)
You can only make so much money from startups by gatekeeping how other people's money is invested. That skill does not an operator make. VCs with operating experience I think operate with a different toolset and underwriting criterion than lifers.
Except that the VC expected return is positive. They just need a sufficient number and diversity of bets to lower their variance to a small value relative to their expected return, which most of them don’t do.
There is also the exclusively state-level regulation of negative expected value games versus federal regulation of positive expected value games.
There is also the liquidity.
But any moral distinctions are arbitrary and unnecessary, based on culture.
Today my colleagues on the federal open market committee and I made some important changes to our policy statement (brrr!)
Why not? positive expected value games seem like a much better thing to post your money into.
The only reason positive expected value financial games exist is because there exist certain external cases that make them profitable almost all the time, such as inflation. But if your trade isn't sticking around for that, they aren't inherently positive expected value.
I have pity for the people that feel they need to split hairs over this.... while paying for insurance.
If you're not in that position, then you're gambling just the same, whether you have -EV or +EV.
Even successful businesses will be destroyed by VC's demanding leverage and higher returns and quick exits.
If either of those 2 things aren't true, you probably shouldn't choose to work at a startup over a large established company.
What does a good VC add that would be hard to get otherwise? The obvious counterpoint to your argument is that good VCs play primarily passive roles in comparison to the good operators they invest in, by a very wide order of magnitude.
A full time VC might see 2000 pitch decks per year, meet with a few hundred of those companies, and end up investing in 5. So they are picking what they perceive to be the top .25% of all pitches they see. If they invested in 20 companies, it would be the top 1%. If they invested in 200 companies, it would be the top 10%. But because these companies are ranked, the expected outcome distribution of the VC's #1 company should be a little better than the #10 company, and a lot better than the #200 company. The further down the list you go, the worse the expected value -- even though some of the lower ranked companies may turn out to be amazing.
So you can't just 40x the number of investments you make and say "expected value is the same but variance is now much lower!!1!" because you would be lowering your bar a lot by expanding the # of investments. And your variance would go down considerably, but so would your expected value.
Rich investors don't need their VC to be super diversified. They can just invest into multiple VC funds and get diversification that way.
Also, it doesn't matter how much risk is in a given VC fund, what matters is how investing part of my porfolio in that VC fund affects the risk of my portfolio!
The lesson is VC funds are more like individual stocks than index funds from an investment perspective. Which is fine. In fact VC funds as a class are like a great class of individual stocks, from an investment perspective.
The problem isn't from an investment perspective at all. It's from the VC perspective. VC's which invest in small numbers of companies are trusting the future of their fund on the role of a dice. That is risk they might want to eliminate for their own good.
The perfect VC with perfect foresight might be able to pick just 1 investment and get the best returns from that.
If returns are distributed on a power-law distribution (with the top performer returning a multiple of the second one and so on), then any deviation between the VC ranking and the outcome distribution of returns is very costly. What if I only invest in my predicted top 5, but the real top 1 is ranked 6 in my estimate?
If what matters is to reliably capture the top performers, then the perfect VC would get the top 5 with only 5 investments. But for imperfect VCs, it might be worth it to invest in 50 just to approach 100% chance of capturing these 5 top performers, the 45 others are just the cost of doing that.
Yep! This is exactly how most funds operate. They invest in 30 or 40 companies over 3-4 years with the hope that 30-40 is enough to hit 1-2 big winners. The more confident a VC is in their picking skills, the more likely they are to invest in 15 or 25 companies in a fund, instead of 30+.
Having the capital and desire to make an investment is the easy part of investing. Actually earning that allocation is difficult.
Yet, most conceptions of investing seem to be shaped by public markets and their ubiquity. That is to say, public market float is taken for granted - when in reality it is missing from every asset class (practically or literally) save for G7 (+China) secondary-market public equities (and now cryptocurrencies).
I think a more realistic “model” of a VCs behavior is one of thresholding - set the bar somewhere and invest in any company that seems to be above that quality bar, with some stochasticity as to which deals you actually win in the end.
> it is a major assumption to think that VCs are good at calculating the expected values of companies in which they make investments.
It's not quite the same as proving VCs can calculate expected values well, but VC is one of the few asset classes with persistence of returns -- meaning having a top quartile fund is correlated with the next fund also being top quartile. In most investment classes, being top quartile across funds is basically uncorrelated. So good VCs tend to be reliably good and not good just because of pure chance.
Source: https://www.morganstanley.com/im/publication/insights/articl... (p 51)
> The fundamental randomness is so high here that any ranking a VC made would likely be garbage
A ranking doesn't have to be perfect, just better than random. E.g. let's say you give me a bunch of companies and ask me to rank them, and I put 60% of the actual top 1% and 40% of the next 1% into my top 1%. I'm making mistakes, but that's still pretty good. As long as I'm directionally right on average, I should do well on the investing side.
Let's say you only pick the top 0.25%, do you do any statistical analysis afterwards to see if this percentage gave the best ROI? Because I would assume that the top 1% at least gets funded by other VCs so it should be possible to do this? Although at the same time I wonder if outsized returns can really be made if there is a VC consensus of the top 1%, my understanding is that the best returns are made in firms that people disagree on.
One big constraint on the # of investments per year for a fund is the amount of time that the fund's partners have. Investors want to differentiate themselves with the help they can provide, and help takes time. As a result, a Series A investor/board member can manage 1-2 new investments per year, while a seed investor might be able to manage 3-8 new investments per year. So # of partners * ~5 investments per year is a good estimate of how many investments a hands on seed fund will do.
There are funds that invest in a lot more companies, but they tend to write small checks and are less hands on.
A simulation alone isn't going to cut it as it involves too many assumptions though it can give rise to reasonable hypothesis (not conclusions).
Obviously, at some scale, you literally tap out of opportunities ... but not at just 2K pitches.
Lol, what. No. Diversification is about correlation, not stock count. If you buy 40 different tech companies, you are not diversified. If you buy 3 etfs, you may be extremely well diversified.
> Analysis shows that this handful of successful deals is responsible for around one-fifth of the total cash returned by the industry. To reliably access the excess returns generated by one in 250 deals, a fund size of more than 500 investments is needed. Anything less risks having a portfolio without any mega-winners.
This only matters from the perspective of the fund manager, not an investor. From the perspective of the investor, investing in 1 big fund with 500 companies is equivalent to investing in 2 small funds with 250 companies.
> This counterintuitive result is further validated by a recent Kauffman Fellows study, which says that at the seed stage, “indexing beats 90 to 95 percent of investors picking deals.” In VC as a whole, it seems from Figure 2 that indexing beats 50 to 75 percent of investors picking deals, since indexing gives second-quartile result
When will people stop saying this trash? Indexing beats lots of things. Indexing beats cash, it beats bonds, it beats CDS. But all those things still exist. And they exist because they are uncorrelated asset classes, just like venture capital.
Diversifying your portfolio across uncorrelated asset classes elevates your long term CAGR assuming each returns stream has positive expectancy. This is why people invest in things that have lower expected returns than stocks - those things have less risk, and more importantly, uncorrelated risk. All of this is finance 101, and yet, publications calling themselves 'institutional investor' still don't seem to understand portfolio theory. I guess then they can't write clickbait articles about the great mystery of venture capital.
There is no mystery in VC. Investors diversify across VC funds. If you are thinking about investing in a VC firm, what you care about is uniqueness of the return stream. You want to be able to pick and choose manages who will themselves make diversified bets, so that your overall portfolio is diversified both across companies, and across perspectives. The system as constructed makes complete sense.
It is also difficult to evaluate the volatility of an asset if the price is evaluated infrequently.
Imagine how good the stock market would look, if you only get the price every 5 years.
Somewhat, yes. It's not that it's completely uncorrelated, but it is less correlated than other public companies tend to be.
> It is also difficult to evaluate the volatility of an asset if the price is evaluated infrequently.
Yep, you're absolutely right. This is sometimes called the 'liquidity premium'. People tend to pay less for illiquid assets than liquid assets, all else equal. Which means that investing in illiquid assets should, all else equal, produce better risk-adjusted returns on average over time, especially if you are selling them after they become liquid.
I think this creates a smoothing effect. For example, during the COVID flash crash, an investor sold their stake in a VC fund, to another investor at the NAV price.
This covers the mathematics of heavy-tailed distributions and a lot of fun applications, and also touches on some other interesting, Taleb-esque topics (fractals, renormalization group).
For financial stuff in this vein (heavy tails), Bouchaud has some books with various coauthors (e.g. Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk Management). Admittedly I have only browsed them, but what little I've read has been good.
Also, on a tangent which may interest you, Charles Martin and Mike Mahoney (of UC Berkeley) have some recent work which uncovers heavy-tailed laws in neural networks. You can get started here and follow the citations: https://arxiv.org/abs/1901.08278.
For reliable excess returns, startup employees need to correctly choose one out of 500 companies.
He literally named his firm “500 Startups.”
https://www.slideshare.net/dmc500hats/investment-thesis-fund...
But in all seriousness, we all know lots of companies would not exist without VC.