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For reliable excess returns, VC funds need 500 investments

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Re: For reliable excess returns, VC funds need 500 investments

#11

Post by vkou »

andreareina wrote: post #8
ry454 wrote: post #3

My takeaways from the article: (1) VC is a casino for the rich and just like gamblers in casinos they have no idea what they are doing; (2) VCs have discovered that standard deviation shrinks like the square root of the sample size, however their understanding of stats seems to be just enough to run a monte-carlo simulation. Edit: the 3rd takeaway is advice to those who're considering to join a "startup" - if VC need…

> 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 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…

The downside distribution is more punishing on the low end. For people who need to pay rent, buy food, and pay medical bills, a 90% probability of losing half your wages is generally not worth a 10% probability of making 7x your wages.

That's because the less money you have, the more valuable a dollar is.

Re: For reliable excess returns, VC funds need 500 investments

#12

Post by erispoe »

lpolovets wrote: post #7

(I'm a VC.) I'm skeptical of simulations like this one because they typically assume that every startup has the same statistical distribution of returns, and whether you pick 15 or 500 startups, each startup will have the same expected value and variance. But in practice it doesn't work like that. 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…

Your explanation makes sense but is predicated on the VC being able to reliably rank these companies along expected returns.

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.

Re: For reliable excess returns, VC funds need 500 investments

#13

Post by chii »

vkou wrote: post #11
andreareina wrote: post #8

Earlier quoted context omitted.

> 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 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…

The downside distribution is more punishing on the low end. For people who need to pay rent, buy food, and pay medical bills, a 90% probability of losing half your wages is generally not worth a 10% probability of making 7x your wages. That's because the less money you have, the more valuable a dollar is.

> a 90% probability of losing half your wages is generally not worth a 10% probability of making 7x your wages.

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

Re: For reliable excess returns, VC funds need 500 investments

#14

Post by cinntaile »

lpolovets wrote: post #7

(I'm a VC.) I'm skeptical of simulations like this one because they typically assume that every startup has the same statistical distribution of returns, and whether you pick 15 or 500 startups, each startup will have the same expected value and variance. But in practice it doesn't work like that. 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…

How do you decide the number of companies you invest in each year? Is this simply a function of the available capital or do you take future capital requirements of the companies you want to invest in into account?

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.

Re: For reliable excess returns, VC funds need 500 investments

#15

Post by vkou »

chii wrote: post #13
vkou wrote: post #11

Earlier quoted context omitted.

The downside distribution is more punishing on the low end. For people who need to pay rent, buy food, and pay medical bills, a 90% probability of losing half your wages is generally not worth a 10% probability of making 7x your wages. That's because the less money you have, the more valuable a dollar is.

> a 90% probability of losing half your wages is generally not worth a 10% probability of making 7x your wages. 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

Your math is wrong.

0.5 * 90% + 7 * 10% = 1.15 average.

Re: For reliable excess returns, VC funds need 500 investments

#16

Post by jariel »

lpolovets wrote: post #7

(I'm a VC.) I'm skeptical of simulations like this one because they typically assume that every startup has the same statistical distribution of returns, and whether you pick 15 or 500 startups, each startup will have the same expected value and variance. But in practice it doesn't work like that. 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…

This is a good point, but I think the point being, you'd 5x your staff and 5x the size of your funnel, thereby ostensibly keeping the same ratio of 'good deals'.

Obviously, at some scale, you literally tap out of opportunities ... but not at just 2K pitches.

Re: For reliable excess returns, VC funds need 500 investments

#17

Post by compsciphd »

ry454 wrote: post #3

My takeaways from the article: (1) VC is a casino for the rich and just like gamblers in casinos they have no idea what they are doing; (2) VCs have discovered that standard deviation shrinks like the square root of the sample size, however their understanding of stats seems to be just enough to run a monte-carlo simulation. Edit: the 3rd takeaway is advice to those who're considering to join a "startup" - if VC need…

one doesn't work at startups to maximize your earnings. you work at a startup because the pay is sufficient for your goals and its work you want to do (ex: because you really believe in the product, you feel you can grow in ways you couldn't in large companies / have impact or control in ways you can't in lage companies or perhaps others).

If either of those 2 things aren't true, you probably shouldn't choose to work at a startup over a large established company.

Re: For reliable excess returns, VC funds need 500 investments

#18

Post by rorykoehler »

lpolovets wrote: post #7

(I'm a VC.) I'm skeptical of simulations like this one because they typically assume that every startup has the same statistical distribution of returns, and whether you pick 15 or 500 startups, each startup will have the same expected value and variance. But in practice it doesn't work like that. 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…

This was my initial thought too but it is tempered by the "deals we passed on" meme that is prevalent in VC circles. A VCs perception of the best companies is not based on reality. Like a gambler a VC has no idea whether their bet is the right one until much later. Sure you can de-risk it based on previous exits of founder etc but the reality is every VC probably passes on more great companies than they invest in.

Re: For reliable excess returns, VC funds need 500 investments

#19

Post by threeseed »

ry454 wrote: post #3

My takeaways from the article: (1) VC is a casino for the rich and just like gamblers in casinos they have no idea what they are doing; (2) VCs have discovered that standard deviation shrinks like the square root of the sample size, however their understanding of stats seems to be just enough to run a monte-carlo simulation. Edit: the 3rd takeaway is advice to those who're considering to join a "startup" - if VC need…

> just like gamblers in casinos they have no idea what they are doing

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.

Re: For reliable excess returns, VC funds need 500 investments

#20

Post by nyrulez »

lpolovets wrote: post #7

(I'm a VC.) I'm skeptical of simulations like this one because they typically assume that every startup has the same statistical distribution of returns, and whether you pick 15 or 500 startups, each startup will have the same expected value and variance. But in practice it doesn't work like that. 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…

They could've done an analysis on the variance of returns categorized by # of investments per fund. That would illuminate if # of investments is a big correlational/causative factor as they claim.

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).

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