5 ms·

The hard part is figuring out which 1% of our investments will yield 99% of our returns.

vannevar 14y ago
I would argue that no one actually figures that out. The obvious implication of the fact that VC returns follow a power law is that VCs have no real expertise in picking winners, but are merely riding along on the underlying structure of the market. They invest in X number of companies and one of them hits so big for reasons no one can consistently explain that it covers the losses on the remainder. The rest is just ritual and hand waving.
- jackaltman 14y ago
  that could definitely be right. There do seem to be a number of funds that consistently hit winners more often year after year (say, something like 15% winners vs. 10%) an alternative explanation to the best funds being good at finding winners is that they are good at avoiding the investments that have a low chance of being homeruns. this is where I was heading with my last paragraph but realized it requires a whole new post.
  - diego 14y ago
    Citation? What funds are better at picking winners consistently year after year?
    - jackaltman 14y ago
      I think Sequoia, YC, USV and some others have probably had statistically significant outsized returns. Always hard to know because if you let enough people try someone is going to flip a coin heads 10 times in a row, but I do think some funds have created sustainable advantages (through winner-picking skills or otherwise).
      - marcosdumay 14y ago
        That may be because they are big. (YC may not be big in terms of money invested, but they are in terms of number of startups.) It may also be because they somehow help those startups succeed. Thus, they don't pick winners, they make winners. Another possibility is that successful startup founders self select themselver into those founds.
        deleted 14y ago
        [deleted]
- SatvikBeri 14y ago
  This is a really interesting question. Humans tend to be pretty good at accepting things that are mostly random, or mostly skill-based, but have a surprisingly hard time with things that involve a combination of skill and luck. For a great example of this, watch amateur poker players. This is just as true in investing-people tend to espouse either "all skill" (e.g. Warren Buffett") or "all luck" (one common interpretation of the Efficient Market Hypothesis.) Even defining skill in investing is difficult. High-risk investments tend to have a high return, so skill is getting an outsized return compared to the amount of risk involved. But the simple measures of risk (e.g. Beta) are not good actual measure of risk. For example, a company whose stock price suddenly plummeted is often a good investment since the market tends to overreact to bad news. Furthermore, the stock is now lower-risk because it has less to lose. But it will appear extremely high risk by most common measures. I think it's a decent assumption in VC to treat all investments at stage X as equally risky. E.g. angel investments are one category, series A as another. This is obviously not 100% perfect but is a decent approximation. Then we can ask the following question: how did Sequoia Capital's series A investments in a certain time period (say 2000-2005) perform compared to all other series A investments? It's important that you look at all of a VC's investments and not just a particular fund, because firms will often bury their bad funds. I have no idea if that kind of data is available anywhere, though.
  - vannevar 14y ago
    That's a good start, but even if no firm outperformed the average, there might still be skill involved. The question is, what is the a priori probability of success for a given class of investment? To answer that, you'd have to account for investment opportunities that weren't taken by anybody. But of course there's no way to know whether an unfunded startup would have been successful. So the VC community can rest easy knowing that they are insulated from objective evaluation, unless a VC emerges whose sole criterion for funding is that everyone else turned the investment down.

I would argue that no one actually figures that out. The obvious implication of the fact that VC returns follow a power law is that VCs have no real expertise in picking winners, but are merely riding along on the underlying structure of the market. They invest in X number of companies and one of them hits so big for reasons no one can consistently explain that it covers the losses on the remainder. The rest is just ritual and hand waving.

jackaltman 14y ago
that could definitely be right. There do seem to be a number of funds that consistently hit winners more often year after year (say, something like 15% winners vs. 10%) an alternative explanation to the best funds being good at finding winners is that they are good at avoiding the investments that have a low chance of being homeruns. this is where I was heading with my last paragraph but realized it requires a whole new post.
- diego 14y ago
  Citation? What funds are better at picking winners consistently year after year?
  - jackaltman 14y ago
    I think Sequoia, YC, USV and some others have probably had statistically significant outsized returns. Always hard to know because if you let enough people try someone is going to flip a coin heads 10 times in a row, but I do think some funds have created sustainable advantages (through winner-picking skills or otherwise).
    - marcosdumay 14y ago
      That may be because they are big. (YC may not be big in terms of money invested, but they are in terms of number of startups.) It may also be because they somehow help those startups succeed. Thus, they don't pick winners, they make winners. Another possibility is that successful startup founders self select themselver into those founds.
      - deleted 14y ago
        [deleted]
SatvikBeri 14y ago
This is a really interesting question. Humans tend to be pretty good at accepting things that are mostly random, or mostly skill-based, but have a surprisingly hard time with things that involve a combination of skill and luck. For a great example of this, watch amateur poker players. This is just as true in investing-people tend to espouse either "all skill" (e.g. Warren Buffett") or "all luck" (one common interpretation of the Efficient Market Hypothesis.) Even defining skill in investing is difficult. High-risk investments tend to have a high return, so skill is getting an outsized return compared to the amount of risk involved. But the simple measures of risk (e.g. Beta) are not good actual measure of risk. For example, a company whose stock price suddenly plummeted is often a good investment since the market tends to overreact to bad news. Furthermore, the stock is now lower-risk because it has less to lose. But it will appear extremely high risk by most common measures. I think it's a decent assumption in VC to treat all investments at stage X as equally risky. E.g. angel investments are one category, series A as another. This is obviously not 100% perfect but is a decent approximation. Then we can ask the following question: how did Sequoia Capital's series A investments in a certain time period (say 2000-2005) perform compared to all other series A investments? It's important that you look at all of a VC's investments and not just a particular fund, because firms will often bury their bad funds. I have no idea if that kind of data is available anywhere, though.
- vannevar 14y ago
  That's a good start, but even if no firm outperformed the average, there might still be skill involved. The question is, what is the a priori probability of success for a given class of investment? To answer that, you'd have to account for investment opportunities that weren't taken by anybody. But of course there's no way to know whether an unfunded startup would have been successful. So the VC community can rest easy knowing that they are insulated from objective evaluation, unless a VC emerges whose sole criterion for funding is that everyone else turned the investment down.