Black Swan Seed Rounds(blog.samaltman.com)
blog.samaltman.com
Black Swan Seed Rounds
http://blog.samaltman.com/black-swan-seed-rounds
101 comments
I like this. My favourite rubric in this area is "there are no Black Swans only Xmas Turkeys." I think that is similar to your view - that all the evidence we need to deduce an out come is available in front of us if we have the right model (human farmers are charitable to turkeys is a bad model, 23rd of December will not result in another free meal is a better model)
I am surprised that investing, especially with Mr Altmans connections and experience, is still a 1/8 crap shoot and that's with no IPOs / exits. It indicates that the model we hold for what the world will look like in 5,10,20 years is far far from complete.
I am surprised that investing, especially with Mr Altmans connections and experience, is still a 1/8 crap shoot and that's with no IPOs / exits. It indicates that the model we hold for what the world will look like in 5,10,20 years is far far from complete.
I think that 1/8 sounds amazing actually, let's look at some totally theoretical and extremely simple numbers (basically all we can work with in this case without doing some significant legwork to try and sniff out the actual investments).
To keep it simple let's invest $100 in each of those 40 companies. He defines success as companies that have grown at least 100x over. We know 5 companies have hit that mark and know basically nothing about the other 35 that we'll just consider failures (even though they might only be 10x or 50x[a success in other areas for sure]).
Failed$ = ($100x)35 x is the multiplier on that money across all 35 companies. Perhaps he lost it all and it's 0, maybe it's slightly above 1, who knows. Regardless, in this totally mad eup case the total potential loss (ignoring potential to be invested elsewhere) is $3,500 or 87.5% of initial outlay.
The remainder using the simple information and interpretation available to us looks like this:
Success$ = ($100* 100) * 5 = $50,000
That is 12.5x the initial outlay of $4,000. Making 12.5x your outlay in presumably only a handful of years is massive. Obviously growth doesn't mean exactly 100X, but I just wanted to show that a handful of hits (and I think 5/40 is bigger than a handful) can easily pay for everything else and more.
Reread the article, this is only 2-3.5 years of duration. That seems insanely quick for these kinds of results.
To keep it simple let's invest $100 in each of those 40 companies. He defines success as companies that have grown at least 100x over. We know 5 companies have hit that mark and know basically nothing about the other 35 that we'll just consider failures (even though they might only be 10x or 50x[a success in other areas for sure]).
Failed$ = ($100x)35 x is the multiplier on that money across all 35 companies. Perhaps he lost it all and it's 0, maybe it's slightly above 1, who knows. Regardless, in this totally mad eup case the total potential loss (ignoring potential to be invested elsewhere) is $3,500 or 87.5% of initial outlay.
The remainder using the simple information and interpretation available to us looks like this:
Success$ = ($100* 100) * 5 = $50,000
That is 12.5x the initial outlay of $4,000. Making 12.5x your outlay in presumably only a handful of years is massive. Obviously growth doesn't mean exactly 100X, but I just wanted to show that a handful of hits (and I think 5/40 is bigger than a handful) can easily pay for everything else and more.
Reread the article, this is only 2-3.5 years of duration. That seems insanely quick for these kinds of results.
Taleb's book is basically anti-science, in the sense that he's making a (good) case about the dubiousness of the epistemology underlying the scientific method. In the colloquial sense though a black swan has just come to mean an event that most people didn't expect.
I've only read Fooled by Randomness and The Black Swan, but those at least aren't anti-science at all. The argument is that in physics as our ability to measure the world goes up, so does our ability to accurately predict it to an extremely high degree of precision, and we've relied on this fact to build an expectation that the same is true of all sciences, and this is simply wrong, especially because it looks like any fault in prediction is just a flaw in measurements. As soon as we humans making our imperfect decisions enter the equation, a treacherous but inherent element of pure unpredictability appears and unless we temper our faith in our ability to predict the world through models, we stay prone to being surprised by black swans.
I think there's a difference from a Powerball jackpot. There, the upper limit is defined. Whereas there's no upper limits on Sam's investments.
They're perhaps not black swans in the sense that Sam is aware they may increase in value, but other than that they seem to match the criteria in a way that Powerball doesn't. Taleb has spoken specifically about how black swans are not lottery tickets because of this calculability.
They're perhaps not black swans in the sense that Sam is aware they may increase in value, but other than that they seem to match the criteria in a way that Powerball doesn't. Taleb has spoken specifically about how black swans are not lottery tickets because of this calculability.
The limit doesn't matter so much as striking it in the first place. Realistically, all of the mentioned investments are within the realm of reasonable thought. The presumption of a black swan is that it is completely outside the ability for one to rationally assess a system then predict it with decent success. 5/40 would be a phenomenally high success rate.
Lottery is totally not black swan, which is exactly what I was trying to say. Despite having prior knowledge of the company's situation (unlike a completely random lottery), it seems to me that these investments are closer to the lottery than black swan.
You don't place bets on a specific black swan, but you could place a different, outside bet on a disrupting event (kind of the idea of antifragile, benefiting from disorder). I think under Taleb's comments in Antifragile, living life as an artist as opposed to someone who is inherently reliant on the stability of say, an office job, is placing that bet every day.
Lottery is totally not black swan, which is exactly what I was trying to say. Despite having prior knowledge of the company's situation (unlike a completely random lottery), it seems to me that these investments are closer to the lottery than black swan.
You don't place bets on a specific black swan, but you could place a different, outside bet on a disrupting event (kind of the idea of antifragile, benefiting from disorder). I think under Taleb's comments in Antifragile, living life as an artist as opposed to someone who is inherently reliant on the stability of say, an office job, is placing that bet every day.
The point is that is that you can precisely calculate the (negative) expectation value of investing in lottery tickets. Or even the expectation value of lottery tickets.
But you can't calculate the expectation value of startup investments. One outlier skews the whole sample, and there is no limit on how high.
Taleb explicitly placed startup investments as those that are antifragile.
But you can't calculate the expectation value of startup investments. One outlier skews the whole sample, and there is no limit on how high.
Taleb explicitly placed startup investments as those that are antifragile.
I also misunderstood this
It's more like when a small group of people split a large powerball jackpot
[A Black Swan is] more like when a small group of people split a large powerball jackpotWhy is it even unusual for multiple people to split a large powerball? By definition: a large powerball means there's more tickets and thus more possible matches for the random draw.
Another minor point: there's gotta be dozens of people playing the Lost numbers, the Miami heat starting lineup, etc... every time, so there are natural clusters of group splitting jackpots for lotto winners .
Another minor point: there's gotta be dozens of people playing the Lost numbers, the Miami heat starting lineup, etc... every time, so there are natural clusters of group splitting jackpots for lotto winners .
I just said group because presumably he wasn't the only investor in those companies, so a group of people stand to profit. If he was the only investor I would have said individual. It's also meant to highlight the fact that multiple people are in on this, whereas an actual black swan event is something that tends to be much more difficult to predict or be a part of.
I would be amazed if someone could go 5/40 in predicting black swan events under their original definition.
I would be amazed if someone could go 5/40 in predicting black swan events under their original definition.
I think the "group" here splitting the Powerball implied a group of people collectively owning/splitting a single winning ticket (such as an office, team, or family pooling money to buy a block of tickets) rather than more than one winning ticket splitting the jackpot.
Much like a group of investors investing in early stage companies.
Much like a group of investors investing in early stage companies.
Ahh, I see the confusion now, sorry. Thanks, edited for clarity.
> I think there's a difference from a Powerball jackpot. There, the upper limit is defined. Whereas there's no upper limits on Sam's investments.
Statistically, you can still define a finite expectation value for an unbounded probability distribution, just as you can compute a finite value for an infinite sum.
Statistically, you can still define a finite expectation value for an unbounded probability distribution, just as you can compute a finite value for an infinite sum.
How does that work?
In the general case, you'd take whatever formulas you have for return rate and corresponding probability (e.g. exponentially lower chances of exponentially higher returns), and feed that into a definite integral from -infinity to infinity (0 to infinity in the case of a model like investment return rate where you theoretically can't lose more than you put in). Consider, for instance, that the area under a standard normal curve (like any probability distribution) is 1, yet that curve extends infinitely in both directions, and there's a non-zero chance of it producing an arbitrarily large value.
If you have a continuous analytic model, you can integrate that analytically (or for the various standard models, just look up the answer based on the parameterization). If you have a discrete analytic model (a step function), you can construct an infinite series. If you have a model based on discrete statistical samples and extrapolations thereof, you can use a combination of numeric integration/summing and model-based bounds.
So, even though the total possible return on a business venture is potentially unbounded, you can still establish a finite expectation value for it.
If you have a continuous analytic model, you can integrate that analytically (or for the various standard models, just look up the answer based on the parameterization). If you have a discrete analytic model (a step function), you can construct an infinite series. If you have a model based on discrete statistical samples and extrapolations thereof, you can use a combination of numeric integration/summing and model-based bounds.
So, even though the total possible return on a business venture is potentially unbounded, you can still establish a finite expectation value for it.
> Whereas there's no upper limits on Sam's investments.
There's no public company with a valuation above $1 trillion, so there's an implied upper limit in practical terms.
There's no public company with a valuation above $1 trillion, so there's an implied upper limit in practical terms.
I don't follow your logic here. What rules do seed stage startups break when it comes to Black Swan theory?
It simply doesn't apply. A black swan is a rare event that is almost certain to happen (or at least one of them will) that will destroy vast amounts of wealth. Because they are so rare and it's so hard to predict which one will actually happen, people don't prepare for them so they do an incredible amount of damage to the financial system.
The idea is orthogonal to seed round investing.
The idea is orthogonal to seed round investing.
It simply doesn't apply. A black swan is a rare event that is almost certain to happen (or at least one of them will) that will destroy vast amounts of wealth.
Black swan events are unpredictable and have enormous impact. Whether they're positive or negative is irrelevant. I'm reading the comments on this page and it seems many people are confused about the term. If you're interested in the connection to business and startups, check out this book: http://www.amazon.com/The-Black-Swan-Improbable-Robustness/d...
In the very first sentence of the book description, it defines a black swan event: "A black swan is an event, positive or negative, that is deemed improbable yet causes massive consequences."
It's used quite a bit to describe startup success. Paul Graham wrote about this in one of his essays as well. I think the term fits perfectly for this blog post.
Black swan events are unpredictable and have enormous impact. Whether they're positive or negative is irrelevant. I'm reading the comments on this page and it seems many people are confused about the term. If you're interested in the connection to business and startups, check out this book: http://www.amazon.com/The-Black-Swan-Improbable-Robustness/d...
In the very first sentence of the book description, it defines a black swan event: "A black swan is an event, positive or negative, that is deemed improbable yet causes massive consequences."
It's used quite a bit to describe startup success. Paul Graham wrote about this in one of his essays as well. I think the term fits perfectly for this blog post.
It's true. I think so many of us assume black swans are negative because we first heard the term to describe the subprime mortgage mess.
The non-computability of the probability of the consequential rare events using scientific methods (owing to the very nature of small probabilities).
Success rate is computed and regularly measured by VCs. Otherwise rule of thumbs like 7/2/1 (On average 7 startups will just fail outright, 2 might make your money back, 1 will make you a profit) wouldn't exist.
Success rate is computed and regularly measured by VCs. Otherwise rule of thumbs like 7/2/1 (On average 7 startups will just fail outright, 2 might make your money back, 1 will make you a profit) wouldn't exist.
There's no evidence here that successful seed companies are more likely to look like bad ideas than unsuccessful seed companies. If 4/5 black swans look like bad ideas when they start, but 4000/5000 of this year's startups also look like bad ideas, then there's no effect to explain. The only lesson is that seed investing is just throwing darts.
And being wealthy and well connected.
Sam, could you (or any other Angel investor) talk frankly about the money your put in and what your exact returns have been. How much have you had to reinvest in later rounds too. I can't find any really experienced angel to talk frankly about this with me.
Paul Buchheit has blogged very candidly about his angel investing numbers: http://paulbuchheit.blogspot.com/2011/01/angel-investing-my-...
Cool, thanks. That's def the type of insight I was looking for. It's surprising that someone as credentialed as Paul Buchheit has had such "modest" success/returns on his investments. $1.2MM also seems like a very conservative sum for someone of his net worth.
That's over 2 years, he's had more exits since then. You really need to wait about 7-10 years to get an idea of the returns. See mikeryan's comment.
That post is dire need of a follow up. Would be great to see where some of the more final numbers end up of his three he's still looking forward to Weebly is still kicking at a $500M valuation, Meraki was acquired for 1.2B and Wufoo got a small acquisition at $35M
At Startup School Europe he mentioned[0] backing justin.tv too which may be about to have a large exit[1].
[0] http://theinflexion.com/blog/2014/07/26/notes-from-startup-s...
[1] http://upstart.bizjournals.com/news/wire/2014/07/25/how-pers...
[0] http://theinflexion.com/blog/2014/07/26/notes-from-startup-s...
[1] http://upstart.bizjournals.com/news/wire/2014/07/25/how-pers...
in 5 years, when the numbers should be real, i will shared all my aggregate data.
the normal warning i give people: seed investing has always been hard, and likely to continue to get harder. valuations are up on average maybe 3x since i started, and it's not clear the companies are 3x more valuable.
the normal warning i give people: seed investing has always been hard, and likely to continue to get harder. valuations are up on average maybe 3x since i started, and it's not clear the companies are 3x more valuable.
> valuations are up on average maybe 3x since i started,
> and it's not clear the companies are 3x more valuable.
In a constrained supply there might be an argument that things that wouldn't have been funded before, now are, and those represent less value creating ideas. But it seems YC is always oversubscribed, would that keep the quality high?
Is the vision of the investors getting cloudy, or more specifically are there still companies that are 3x as valuable but they are being funded elsewhere?
Or is just the capital availability pushing down the yield price on seed rounds?
I don't have any answers, but its interesting to think about.
> Or is just the capital availability pushing down the yield price on seed rounds?
This is almost certainly the case - I recall valuations in 2009 / 2010 vs now, and the gap is absolutely crazy. A lot of that has to do with the deluge of angel money floating around partially as an offshoot of the big-name IPO's like Facebook, but more broadly, we are in a financial world that is desperately chasing yield anyway it can get it - and a seed round is the lowest level commitment of it (that and the high end rounds). The rub, as it lies, is the middle tier.
This is almost certainly the case - I recall valuations in 2009 / 2010 vs now, and the gap is absolutely crazy. A lot of that has to do with the deluge of angel money floating around partially as an offshoot of the big-name IPO's like Facebook, but more broadly, we are in a financial world that is desperately chasing yield anyway it can get it - and a seed round is the lowest level commitment of it (that and the high end rounds). The rub, as it lies, is the middle tier.
Surely value going elsewhere is a Good Thing. There are few places for value created by investment to go if not back to Capital, and especially if you cannot see it going in balance sheets, and that's usually to wider society.
Investment in trains/railroads in the 19C seems a good example. Perhaps the first eyrie canal almost single handed my built the wealth of the USA - having all that return to the Mayor of NY might not be the best idea.
I think we can all we the potential value of many of the start ups on the scene - and I think it is a positive that it is hard for them to capture all that value.
Investment in trains/railroads in the 19C seems a good example. Perhaps the first eyrie canal almost single handed my built the wealth of the USA - having all that return to the Mayor of NY might not be the best idea.
I think we can all we the potential value of many of the start ups on the scene - and I think it is a positive that it is hard for them to capture all that value.
Surely the simplest explanation would be that angels investors in the valley have been making money, and are therefore investing more.
Can you comment in general on when you consider a seed round to be overpriced, and what exactly goes into that determination?
I see several seed rounds (~$1-2m rounds - not sure if this is also the size you're referring to) on crowdfunding sites priced at $10m or so pre-money, with revenues just starting to approach ~$100k per month, and so far haven't invested in any because they all struck me as overpriced. They would definitely have been way cheaper a few years back in that same situation.
I see several seed rounds (~$1-2m rounds - not sure if this is also the size you're referring to) on crowdfunding sites priced at $10m or so pre-money, with revenues just starting to approach ~$100k per month, and so far haven't invested in any because they all struck me as overpriced. They would definitely have been way cheaper a few years back in that same situation.
>[...] it's not clear the companies are 3x more valuable
However, companies are probably somewhat more valuable, right? I mean, the world seems to be learning about entrepreneurship the same way it was learning about manufacturing during the industrial revolution. That to me would indicate that the average value of startups is increasing.
However, companies are probably somewhat more valuable, right? I mean, the world seems to be learning about entrepreneurship the same way it was learning about manufacturing during the industrial revolution. That to me would indicate that the average value of startups is increasing.
to be clear: i don't think seed investing is random. far from it. i just think it's really important to think independently and take the time to really get to know founders and understand businesses instead of just following other investors.
Curious thought- you mention the (unsurprising) thought that people who are good at fundraising aren't necessarily good at running a company.
But, all other things being equal, I'd expect someone who's good at "winning" at the game called "raising money" to be the type of person who is better at winning at other games, e.g. running a good company. In other words, while being good at raising money doesn't necessarily mean they're good at running a company, I'd still take them over the "average person".
You seem to imply the opposite in your post - is that really right? Maybe people who are good at fundraising have spent too much time/energy on that vs. getting good at building a company? That sounds specious to me.
But, all other things being equal, I'd expect someone who's good at "winning" at the game called "raising money" to be the type of person who is better at winning at other games, e.g. running a good company. In other words, while being good at raising money doesn't necessarily mean they're good at running a company, I'd still take them over the "average person".
You seem to imply the opposite in your post - is that really right? Maybe people who are good at fundraising have spent too much time/energy on that vs. getting good at building a company? That sounds specious to me.
If the skillsets needed to found a company are largely independent and time spent learning them is a limiting factor - both of which are true in my startup experience - then time spent learning the fundraising skillset cuts into time spent learning customer development, or the particulars of your market, or engineering, or hiring, or management. You'd expect skill at fundraising to be anti-correlated with some other important skill, then, because you don't have time to get good at some other skill you need.
I've never seen a startup where the founders knew everything they needed to at company formation. Usually it's one giant, steep learning curve.
I've never seen a startup where the founders knew everything they needed to at company formation. Usually it's one giant, steep learning curve.
That makes sense.
But let's say you have some underlying quality, say intelligence or ambition or determination or "grit". This quality will probably correlate with success at both fundraising and building/running a company.
Now I don't have anywhere near the experience of YC or even you, but I wold imagine that at least intelligence and determination are positively correlated with both. So I'd expect someone who is good at fundraising to also be good at the rest.
There could be a few reasons why this might not be the case. It could be that we're looking at a small subset who have already passed an intelligence/determination threshold, above which these 2 traits matter less, and time spent developing the proper skills matters more. It could be that there are other factors in raising money or building/running companies which matter more, which would be an interesting conclusion to me.
Or it could be that I've made an error in reasoning somewhere :)
But let's say you have some underlying quality, say intelligence or ambition or determination or "grit". This quality will probably correlate with success at both fundraising and building/running a company.
Now I don't have anywhere near the experience of YC or even you, but I wold imagine that at least intelligence and determination are positively correlated with both. So I'd expect someone who is good at fundraising to also be good at the rest.
There could be a few reasons why this might not be the case. It could be that we're looking at a small subset who have already passed an intelligence/determination threshold, above which these 2 traits matter less, and time spent developing the proper skills matters more. It could be that there are other factors in raising money or building/running companies which matter more, which would be an interesting conclusion to me.
Or it could be that I've made an error in reasoning somewhere :)
Some underlying qualities correlate positively with success in both. Some correlate negatively. Charm, for example, or salesmanship.
My late grandfather was a master salesman. People would believe what he said, because he himself believed it when he said it. He was also amazingly good at knowing what people wanted to hear. What he wasn't so good at were trivial things like "facts" and "truth": those things often got in the way of believing the most useful thing at the moment.
Several times I've had pals at software companies where the CEO has great sales skills. Every time it's gone great at the beginning, because they get plenty of initial customers. But then things get ugly, because the CEO's promises aren't constrained by the realities of software development. It's death by a thousand cuts as tech debt mounts. Or key customers leave because the CEO consistently promises things that can't be delivered. Or some other ending where ugly reality eventually intrudes upon the CEO's beautiful vision.
I'm sure some people are great at raising money because they're great at building companies. But I'm equally sure that some people are great at raising money because they're terrible at running companies.
My late grandfather was a master salesman. People would believe what he said, because he himself believed it when he said it. He was also amazingly good at knowing what people wanted to hear. What he wasn't so good at were trivial things like "facts" and "truth": those things often got in the way of believing the most useful thing at the moment.
Several times I've had pals at software companies where the CEO has great sales skills. Every time it's gone great at the beginning, because they get plenty of initial customers. But then things get ugly, because the CEO's promises aren't constrained by the realities of software development. It's death by a thousand cuts as tech debt mounts. Or key customers leave because the CEO consistently promises things that can't be delivered. Or some other ending where ugly reality eventually intrudes upon the CEO's beautiful vision.
I'm sure some people are great at raising money because they're great at building companies. But I'm equally sure that some people are great at raising money because they're terrible at running companies.
Let's say that having high intelligence makes you 5% more effective per standard deviation at everything you do, but deliberate practice makes you 10% more effective per week at whatever you practice.
Now take two founders, one of whom is twice as effective at fundraising as the other. There are a couple possibilities: maybe he spent 7 weeks more time practicing fundraising than the other, or maybe he spent 6 weeks more and is 2 standard deviations more intelligent. If he spent 7 weeks more time practicing, then the other founder who devoted that to, say, customer development will know the market twice as well. But even if he spent 6 weeks practicing and gets a boost from his higher intelligence (equivalent to 1 week of practice), the other person is still 60% more effective at the other stuff.
This model is very much simplified, but illustrates a big point that I took a long time to learn: small broad-based improvements take much longer to pay off than targeted, high-% improvements in narrow areas. So yes, being intelligent is nice, it helps slant every skill you learn in your favor. But it is no substitute for actually practicing hard and removing errors.
There are similar counterintuitive principles at work in many other areas. I've found that engineering tools or frameworks that promise a few percent improvement in productivity are rarely worth learning and almost never worth developing unless they have a huge userbase, because it may take you 2 months to develop them but if they save you 5% in development time it'll take 40 months to break even, by which time they're probably not applicable anymore. Similarly, you are almost always better off hiring the person with little experience who is really passionate about your company, rather than the guy who is seemingly a genius at everything he does but really doesn't care about you or what you do. It's probably also behind the YC advice to be "narrow and deep" when building for customers; you can improve the product much more quickly when directly targeting a small userbase than when trying to please a large one.
Now take two founders, one of whom is twice as effective at fundraising as the other. There are a couple possibilities: maybe he spent 7 weeks more time practicing fundraising than the other, or maybe he spent 6 weeks more and is 2 standard deviations more intelligent. If he spent 7 weeks more time practicing, then the other founder who devoted that to, say, customer development will know the market twice as well. But even if he spent 6 weeks practicing and gets a boost from his higher intelligence (equivalent to 1 week of practice), the other person is still 60% more effective at the other stuff.
This model is very much simplified, but illustrates a big point that I took a long time to learn: small broad-based improvements take much longer to pay off than targeted, high-% improvements in narrow areas. So yes, being intelligent is nice, it helps slant every skill you learn in your favor. But it is no substitute for actually practicing hard and removing errors.
There are similar counterintuitive principles at work in many other areas. I've found that engineering tools or frameworks that promise a few percent improvement in productivity are rarely worth learning and almost never worth developing unless they have a huge userbase, because it may take you 2 months to develop them but if they save you 5% in development time it'll take 40 months to break even, by which time they're probably not applicable anymore. Similarly, you are almost always better off hiring the person with little experience who is really passionate about your company, rather than the guy who is seemingly a genius at everything he does but really doesn't care about you or what you do. It's probably also behind the YC advice to be "narrow and deep" when building for customers; you can improve the product much more quickly when directly targeting a small userbase than when trying to please a large one.
You could think of it this way. If someone is really, really good at sales, would you expect them to also be great at (say) general management too? I wouldn't.
A company needs all kinds of complementary skills but in the beginning it only has whatever the founders can bring with them.
A company needs all kinds of complementary skills but in the beginning it only has whatever the founders can bring with them.
That's a good point.
Let's put it this way - if someone is really good at sales, I'd think they're more likely to be good at general management, given enough time to learn that skill.
In the cases of companies, since the founder's job is usually to learn whatever skills are relevant for the current state of the company, and then execute those reasonably well, I'd expect the founder to learn the currently relevant skill of fundraising, then later to learn the currently relevant skill of managing a small startup, then later to learn the currently relevant skill of managing a larger company, etc.
Let's put it this way - if someone is really good at sales, I'd think they're more likely to be good at general management, given enough time to learn that skill.
In the cases of companies, since the founder's job is usually to learn whatever skills are relevant for the current state of the company, and then execute those reasonably well, I'd expect the founder to learn the currently relevant skill of fundraising, then later to learn the currently relevant skill of managing a small startup, then later to learn the currently relevant skill of managing a larger company, etc.
Your argument essentially boils down to 'anyone great at X should (eventually) also be great at Y'. I don't believe that and it seems like a difficult thing to persuade you of -- at least right now.
Also, think about the time component. Even if your viewpoint were true, there isn't always time in a startup to become proficient in a skill you don't yet have. If it were that easy, startups would be a lot simpler.
Also, think about the time component. Even if your viewpoint were true, there isn't always time in a startup to become proficient in a skill you don't yet have. If it were that easy, startups would be a lot simpler.
"I don't believe that and it seems like a difficult thing to persuade you of -- at least right now."
Well, evidence to the contrary should persuade me. But isn't that pretty much the definition of IQ? A kind of "general intelligence quotient" which is broadly applicable to many different skills? E.g. I'd expect Stephen Hawking to be pretty good at chess if he ever decided to apply himself at it.
Well, evidence to the contrary should persuade me. But isn't that pretty much the definition of IQ? A kind of "general intelligence quotient" which is broadly applicable to many different skills? E.g. I'd expect Stephen Hawking to be pretty good at chess if he ever decided to apply himself at it.
When I was a TA at my college, in the introduction to CS class, I noticed the following:
1. There existed people who clearly were, in general, intelligent, hardworking people who completely and totally DID NOT GET computer science. It was frustrating dealing with them, because they were accustomed to the idea that if they put in effort, they mastered subjects -- but it wasn't happening for CS. At least, in a semester.
2. There were people who really "got" iterative programming but were completely flailing when it came to functional programming.
3. There were people who really "got" functional programming but were completely flailing when it came to iterative programming.
Now, on some level, I'm sure that there is an underlying general intelligent/merit thing going on. Nobody who got into my college was an idiot. I'm sure that even the people who were struggling were doing better than would a hypothetical person with a mental disability whose development never got past the 6-year-old level.
But it seemed clear to me that there is a measure of differential, narrow aptitude in the realm of computer programming, not just general aptitude. I would imagine that there is also narrow aptitude in sales, investing, running a company, etc.
1. There existed people who clearly were, in general, intelligent, hardworking people who completely and totally DID NOT GET computer science. It was frustrating dealing with them, because they were accustomed to the idea that if they put in effort, they mastered subjects -- but it wasn't happening for CS. At least, in a semester.
2. There were people who really "got" iterative programming but were completely flailing when it came to functional programming.
3. There were people who really "got" functional programming but were completely flailing when it came to iterative programming.
Now, on some level, I'm sure that there is an underlying general intelligent/merit thing going on. Nobody who got into my college was an idiot. I'm sure that even the people who were struggling were doing better than would a hypothetical person with a mental disability whose development never got past the 6-year-old level.
But it seemed clear to me that there is a measure of differential, narrow aptitude in the realm of computer programming, not just general aptitude. I would imagine that there is also narrow aptitude in sales, investing, running a company, etc.
FYI, You make a similar point to Joel Spolsky (I forget the article, but he specifically mentions recursion and pointers as things that some people just don't get).
The Guerilla Guide to Interviewing (version 3.0) http://www.joelonsoftware.com/articles/GuerrillaInterviewing...
it's really important to think independently and take the time to really get to know founders and understand businesses
Will this view carry over to YC interviews? 10 mins does not engender this outcome.
Will this view carry over to YC interviews? 10 mins does not engender this outcome.
no. at the stage of YC, we're looking for something very different. (though we do try to think independently :) )
we put a small amount of money into a large number of companies. the most important thing is that we not miss a potential huge company; we're willing to make a lot of mistakes of inclusion to that end.
when you're making just a small number of high-dollar bets, you have to handle it very differently.
we put a small amount of money into a large number of companies. the most important thing is that we not miss a potential huge company; we're willing to make a lot of mistakes of inclusion to that end.
when you're making just a small number of high-dollar bets, you have to handle it very differently.
There is some non-zero amount of luck involved in one of YC companies becoming huge. Do you think you have insights into which ones are more likely than not? given that you have pre-screened the companies to include strong founders, is there predictability above and beyond that initial screen?
This is intuitive - Startups that follow all fail - Investing in startups should be the same
Curious if there are patterns in why the hot ones Fail ?
Curious if there are patterns in why the hot ones Fail ?
Don't forget that any startup has by definition a low probability of success - maybe the best ones have something like 20% (a ballpark) - so I don't think there's a definite pattern to predict successful startups.
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A recent blog post [0] from the Economist stated that buying random stocks on the stock market actually performs better than valuation-weighted investment and conscious investment. I wonder if the optimal strategy is to just invest randomly?
[0]: http://www.economist.com/blogs/freeexchange/2014/06/financia...
[0]: http://www.economist.com/blogs/freeexchange/2014/06/financia...
That strategy only makes sense for markets that are close to "informationally efficient", e.g., the public stock market.
I don't get it. The strategy involves throwing darts at randomly sorted stock listings. It uses absolutely no information other than the fact that the company is public. It actually implies that information is harmful. It's vulnerable to people setting up lot's of companies to win the investment lottery, so everyone can't do it, but otherwise I don't get what you mean.
So the idea is that in an efficient market, all the information in the market is already factored into the actual price of the stock. If the market has rich information, then it's very good at telling you what companies are good, but that doesn't help you actually invest in them -- because that information is already in the price of the stock.
In other words, when you're buying a stock, you don't actually care about whether the company is in an absolute sense good or bad, you care about whether it's relatively better or worse than what other investors think it is. In a perfectly efficient market, the answer is basically that it's always exactly as good as other investors think it is. Then your returns are based on random unpredictable shocks and the total trend of the market.
In a truly perfect market, it wouldn't matter what you invested in -- everything would have the same return. Your only real choice would be to invest narrowly or broadly, for risk/reward.
In other words, when you're buying a stock, you don't actually care about whether the company is in an absolute sense good or bad, you care about whether it's relatively better or worse than what other investors think it is. In a perfectly efficient market, the answer is basically that it's always exactly as good as other investors think it is. Then your returns are based on random unpredictable shocks and the total trend of the market.
In a truly perfect market, it wouldn't matter what you invested in -- everything would have the same return. Your only real choice would be to invest narrowly or broadly, for risk/reward.
Even with perfect current information, you can't necessarily predict future performance. So it's not that everything would have the same return. I think that the randomization would come to play in evaluating growth stocks because you'd have the same understanding as everyone else and simply decide to gamble on risk vs reward.
I wouldn't attribute the growth or collapse to random shocks, though those would of course play a role. I'd say that new products and distribution methods would still cause rapid and somewhat unpredictable growth or collapse.
Straight value investing would be more difficult with perfect transparency and efficient information, though it might work out as a dividend thing.
I wouldn't attribute the growth or collapse to random shocks, though those would of course play a role. I'd say that new products and distribution methods would still cause rapid and somewhat unpredictable growth or collapse.
Straight value investing would be more difficult with perfect transparency and efficient information, though it might work out as a dividend thing.
Yes, sorry, we're saying the same thing, but I phrased it badly.
All stocks in a perfectly efficient market have the same EXPECTED return -- differential behavior can and will still occur, but it is necessarily unpredictable. Investing in any one stock is as good as investing in any other stock, in terms of expected returns. Now, there's still room for strategy in such a market: it's like, imagine the difference between betting $1 on a fair die, with one of two possible betting options: Either a 1-5 gets you nothing and a 6 gets you $7, or a 1 gets you nothing, a 2-4 gets you your $1 back, and a 5-6 gets you $2. In both cases, your expected return is 16% gain -- over enough iterations, you'll expect to gain money. But they are different in terms of risk/reward.
(And you can get similar risk/reward tradeoffs by investing broadly or narrowly in a perfectly efficient market.)
All stocks in a perfectly efficient market have the same EXPECTED return -- differential behavior can and will still occur, but it is necessarily unpredictable. Investing in any one stock is as good as investing in any other stock, in terms of expected returns. Now, there's still room for strategy in such a market: it's like, imagine the difference between betting $1 on a fair die, with one of two possible betting options: Either a 1-5 gets you nothing and a 6 gets you $7, or a 1 gets you nothing, a 2-4 gets you your $1 back, and a 5-6 gets you $2. In both cases, your expected return is 16% gain -- over enough iterations, you'll expect to gain money. But they are different in terms of risk/reward.
(And you can get similar risk/reward tradeoffs by investing broadly or narrowly in a perfectly efficient market.)
Valuation-weighted information is harmful. Remember the rule is to "buy low, sell high". When you weight by valuation, you're explicitly overweighting stocks that are valued highly by the market; in other words, you're buying high and selling low.
In theory you can do better with fundamental-weighting (i.e. weighting by revenues, earnings, P/E, PEG, etc.), but there are a lot of subtleties to a stock's future performance that are not captured in the financials and are exploitable against an investor that only naively looks at them. You end up with an investor that's picking up companies that are looting their future prospects for cash because their market is disappearing.
In theory you can do better with fundamental-weighting (i.e. weighting by revenues, earnings, P/E, PEG, etc.), but there are a lot of subtleties to a stock's future performance that are not captured in the financials and are exploitable against an investor that only naively looks at them. You end up with an investor that's picking up companies that are looting their future prospects for cash because their market is disappearing.
How about inverted valuation-weighing, then?
That's actually an interesting idea, except that you have no idea of knowing whether a company is worth very little because the market undervalues it, because it's intrinsically a small company, or because it's about to go bankrupt. An inverted valuation-weighted fund would put that vast majority of assets into stocks that are worth just above nothing. I suspect that a good portion of these are companies that are about to go bankrupt - probably a much bigger proportion than the ones that are small and about to take off, or the ones that are small and overlooked. Investing in companies that are about to go bankrupt isn't really a sound strategy.
The ultimate problem is that stock market returns are a future-prediction problem. When a stock does better than expected, it goes up. When it does worse than expected, it goes down. Doing this reliably includes both having a complete understanding of the rest of the market's expectations and knowledge of the future, which is pretty challenging.
I think that behavioral-finance approaches, which gauge the emotions of your fellow investors, have actually been shown to work pretty well. "Be fearful when others are greedy, and greedy when others are fearful." Hard to put that in an index, though.
The ultimate problem is that stock market returns are a future-prediction problem. When a stock does better than expected, it goes up. When it does worse than expected, it goes down. Doing this reliably includes both having a complete understanding of the rest of the market's expectations and knowledge of the future, which is pretty challenging.
I think that behavioral-finance approaches, which gauge the emotions of your fellow investors, have actually been shown to work pretty well. "Be fearful when others are greedy, and greedy when others are fearful." Hard to put that in an index, though.
> An inverted valuation-weighted fund would put that vast majority of assets into stocks that are worth just above nothing. I suspect that a good portion of these are companies that are about to go bankrupt - probably a much bigger proportion than the ones that are small and about to take off, or the ones that are small and overlooked. Investing in companies that are about to go bankrupt isn't really a sound strategy.
I don't know, isn't that what the junk-bonds guys did in the '80s, and more recent value investors? I could believe that the market still undervalues companies that are about to go bankrupt (but might not).
I don't know, isn't that what the junk-bonds guys did in the '80s, and more recent value investors? I could believe that the market still undervalues companies that are about to go bankrupt (but might not).
Because you are missing an important piece of information in angel investing, the buy price. Efficient market hypothesis says that for a publicly traded stock the stock price is the correct price, however a non-public stock wouldn't have a well established price.
Here's an interview with a guy who runs indices that are not valuation-based and seem to do better:
http://www.ritholtz.com/blog/2014/07/masters-in-business-rob...
http://www.ritholtz.com/blog/2014/07/masters-in-business-rob...
A random buy is likely to be smallcap-biased, as there's simply more of them.
Smallcaps performed quite well over the past decade. Same strategy would not backtest with the same levels of success during any period.
Smallcaps performed quite well over the past decade. Same strategy would not backtest with the same levels of success during any period.
That's really an argument for buying index funds, since the costs and fees of buying and selling random stocks would eat away any profits very quickly.
(Even just buying and holding truly random stocks is still less likely to be a better investment strategy than index funds after taxes and fees are taken into account, let alone the volatility).
(Even just buying and holding truly random stocks is still less likely to be a better investment strategy than index funds after taxes and fees are taken into account, let alone the volatility).
A few more reasons raising a quiet/controversial seed round might be a good signal:
1. Publicly raising a large seed round creates a lot of hype when the product might not be ready yet, or even before there's any product/market fit. As a founder, that creates a lot of pressure to satisfy the hype, and also might cause you to attempt building a product that satisfies the opinions of the blogosphere, rather than your customers. In contrast, when you raise a quiet round, you can build your product and achieve product/market fit without worrying about the outside world, instead focusing purely on your customers.
2. If no investors are questioning the model, you should be alarmed. Almost by definition, no company seeking a seed round has proven revenue model. Knowing this risk, you should expect some fraction of investors to be questioning it. If none are, then it's likely a signal that they've been swayed by smooth-talking founders who are very good at raising investment, but, as you mention, not necessarily fit or ready to build the business they're hyping.
So if we assume quiet seed rounds help with success, this leads to some questions about YC, which is essentially a loud seed round. Namely: should you announce your YC acceptance before you have product/market fit? Should you go through YC in stealth mode until ready to capitalize on hype?
It seems your observations can tell us a lot about the value, or anti-value, of product hype. The lesson seems to be, in the words of Denzel Washington/American Gangster, "the loudest person in the room is probably the weakest."
1. Publicly raising a large seed round creates a lot of hype when the product might not be ready yet, or even before there's any product/market fit. As a founder, that creates a lot of pressure to satisfy the hype, and also might cause you to attempt building a product that satisfies the opinions of the blogosphere, rather than your customers. In contrast, when you raise a quiet round, you can build your product and achieve product/market fit without worrying about the outside world, instead focusing purely on your customers.
2. If no investors are questioning the model, you should be alarmed. Almost by definition, no company seeking a seed round has proven revenue model. Knowing this risk, you should expect some fraction of investors to be questioning it. If none are, then it's likely a signal that they've been swayed by smooth-talking founders who are very good at raising investment, but, as you mention, not necessarily fit or ready to build the business they're hyping.
So if we assume quiet seed rounds help with success, this leads to some questions about YC, which is essentially a loud seed round. Namely: should you announce your YC acceptance before you have product/market fit? Should you go through YC in stealth mode until ready to capitalize on hype?
It seems your observations can tell us a lot about the value, or anti-value, of product hype. The lesson seems to be, in the words of Denzel Washington/American Gangster, "the loudest person in the room is probably the weakest."
I suspect there's also an inverse correlation between the amount of money raised at an early stage and founder focus going forward.
It's easy to interpret a large seed round as early success and become side-tracked or overestimate what your company's impact really is at that stage. Which can impact focus and lead to disaster.
It's easy to interpret a large seed round as early success and become side-tracked or overestimate what your company's impact really is at that stage. Which can impact focus and lead to disaster.
While there might be a point where an effect like this would take place, I think you'd have to raise an extremely substantial seed round for that. I don't think it would be a truly inverse correlation, at least not a normally distributed one. It would probably be one sided as well, because getting no funding shouldn't increase focus.
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"Make your own decisions" is good advice, but I think the main question is whether there exists any reliable means of distinguishing the good contrarian vs. bad contrarian investments--or whether it's just luck. The title seems to imply that the answer might be just luck.
What's an approximate range of $ raised/valuation that makes for a Black Swan seed round in your opinion? It's hard for me to understand what the implications are of this besides "don't believe the hype" without having some relative sense of that.
Isn't basing the multiplier on valuations at the latest investment round disingenuous? After all, its just a number the owners and investors hope someone will eventually pay for the company. It's the asking price set by people hoping for large returns.
Well it's a number that some people (the investors in that round) DID pay for a chunk of the company. If those investors have any sway on the board then it's well below the asking price for the entire company.
A valuation based on an investment round is the valuation of the complete company, not just the amount invested. So if I invest $1M for 10% of a company, that "values" the company at $10M.
In the case of competitive seed rounds (like mentioned Optimizely), would be interesting to hear why someone like Sam's money was accepted over others -- any thoughts?
Does Sam Altman continue to do angel investing or now that he's running YC he's stopped as part of their policy?
So investing at the seed stage is random. I'm surprised that VCs don't help new companies more in the early stage to mitigate some of the common failure patterns, for example the list PG had in 2006. Perhaps couples counseling for YC founders? Every little bit reduces investor risk even a little.
http://www.paulgraham.com/startupmistakes.html
http://www.paulgraham.com/startupmistakes.html
"Engineered random". Sam still gets a better deal flow than most of angel investors are out there, so even "meh" companies with high risk have passed some initial filter.
Any angel investor without the name or brand recognition gets much worse deal flow plus the companies subject to negative selection bias, as they've been rejected by sama, SV Angel, YC, etc.
Any angel investor without the name or brand recognition gets much worse deal flow plus the companies subject to negative selection bias, as they've been rejected by sama, SV Angel, YC, etc.
he lists four: teespring, zenefits, stripe, and optimizely. anyone know the fifth?
This essay might be remotely insightful if Sam explained why great companies "often look like bad ideas at the beginning" and "look really risky at the seed stage".
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Teespring and Zenefits I've never even heard of until today. Are they rolling in the bank and disrupting their respective industries?
And Stripe, there was huge pent-up demand for a PayPal alternative before they came on the scene. How could anyone say that was a "black swan" bet? It doesn't make sense.
And Stripe, there was huge pent-up demand for a PayPal alternative before they came on the scene. How could anyone say that was a "black swan" bet? It doesn't make sense.
Teespring at least is doing very, very well.
Their affiliate program is incredibly successful, allowing people to procedurally design, test and sell t-shirts through various channels.
When Stripe came out it did not compete with Paypal, it competed with companies like Braintree. Stripe was never just a traditional payment gateway. It created an API for payments and a dashboard for managing invoices and recurring customers.
Pent-up demand for a PayPal alternative are from sellers who have a customer facing PayPal payment mechanism. Customers know they're paying with Paypal and customers usually have a PayPal account they use to pay you with. PayPal can hold on to customer funds like a bank.
With Stripe, a customer doesn't know you're using Stripe and if they had a Stripe account they wouldn't be able to see all the purchases they made at various sites that used Stripe, they're just not the same thing.
PayPal now owns Braintree, so they now do compete with Stripe.
Pent-up demand for a PayPal alternative are from sellers who have a customer facing PayPal payment mechanism. Customers know they're paying with Paypal and customers usually have a PayPal account they use to pay you with. PayPal can hold on to customer funds like a bank.
With Stripe, a customer doesn't know you're using Stripe and if they had a Stripe account they wouldn't be able to see all the purchases they made at various sites that used Stripe, they're just not the same thing.
PayPal now owns Braintree, so they now do compete with Stripe.
I recall Stripe was being positioned as a PayPal alternative to collecting international funds, but that wasn't the point.
My point is there is no black swan here. Far from it. It makes no sense in this context.
My point is there is no black swan here. Far from it. It makes no sense in this context.
Let me give what I felt was a popular opinion when stripe launched: it seems like an iterative improvement with nice docs and a nice API - but what's to stop Braintree or anyone else from copying that tomorrow?
I think most investors would have claimed that Stripe would probably make money but would never get huge. Now they're pushing $2B - that is an extremely unlikely outcome and so fits sama's definition of black swan.
I think most investors would have claimed that Stripe would probably make money but would never get huge. Now they're pushing $2B - that is an extremely unlikely outcome and so fits sama's definition of black swan.
You should probably state what time period you are referring to when you recall hearing about Stripe..
I do not recall Stripe being positioned as a PayPal alternative really ever, but certainly not when it launched.
I also believe that Sam was first made aware of Stripe much earlier than most people and it probably did seem like quite a black swan at the time.
I know the very first time that I heard the idea for Stripe it was definitely considered a "crazy" idea. I would easily categorize it as a black swan investment.
I do not recall Stripe being positioned as a PayPal alternative really ever, but certainly not when it launched.
I also believe that Sam was first made aware of Stripe much earlier than most people and it probably did seem like quite a black swan at the time.
I know the very first time that I heard the idea for Stripe it was definitely considered a "crazy" idea. I would easily categorize it as a black swan investment.
The argument that Stripe was a black swan comes because getting into established industries with significant regulation used to be considered dead on arrival, now it's hip.
That's the heroic narrative used by investors like Sam, but I don't believe it.
Did you invest in Stripe (or start a similar company)?
It obviously was a difficult bet - young founders, powerful incumbents - plenty of risk and unknowns.
That said, I believe a good seed investor will spend a lot of time with the founders and the team before pulling the trigger. You'd be surprised at how few investors actually do that.
It obviously was a difficult bet - young founders, powerful incumbents - plenty of risk and unknowns.
That said, I believe a good seed investor will spend a lot of time with the founders and the team before pulling the trigger. You'd be surprised at how few investors actually do that.
His rules:
1. The disproportionate role of high-profile, hard-to-predict, and rare events that are beyond the realm of normal expectations in history, science, finance, and technology.
2. The non-computability of the probability of the consequential rare events using scientific methods (owing to the very nature of small probabilities).
3. The psychological biases that make people individually and collectively blind to uncertainty and unaware of the massive role of the rare event in historical affairs.
http://en.wikipedia.org/wiki/Black_swan_theory
On a related note, Antifragile is a fun read. Taleb is extremely sure of himself, and extremely passionate. His books and ideas (culminating in Antifragile) can be pretty seductive in the moment.