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The Man Who Knows Whether Any Startup Will Live or Die

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Re: The Man Who Knows Whether Any Startup Will Live or Die

#31

Post by brudgers »

colanderman wrote: post #6

> According to the U.S. Bureau of Labor Statistics, about half of all businesses fail within five years. > He [...] thinks that even a model that’s only right about 50 percent of the time could help investors and entrepreneurs avoid particularly bad ideas ...does he have a bridge to sell me too? What am I missing? (One can simply predict "always succeeds" and will be right half the time.)

Perhaps what has been missed is the difference between a single coin flip and a combination of coin flips?

Consider one startup.

    f(x) = #fail
succeeds better than 50%, and

    f(x) = #succeed
succeeds less than 50%. This is due to the nature of startups.

Sure, it's easy to get about 50% accuracy for one startup by flipping a coin:

    f(x) = if rand(1) > 0.5 then #fail else #succeed
But consider the case of two companies A and B. There are now four outcomes:

   A = #fail, B = #fail
   A = #succeed, B = #fail
   A = #fail, B = #succeed
   A = #succeed, B = #succeed
If we flip a coin, we have to flip it twice. Our probability that two coin flips match the correct tuple is 25%, and bumping that up to 50% is a massive improvement.

Investors diversify their portfolios. In a portfolio of 100 startups there's probably a winner. Improving the selection of companies means reducing the number of a fund's portfolio companies necessary for a reasonable probability of a winner. More smaller yet successful funds makes capital more efficient.

Better pruning of boolean search spaces has real value. Hence:

    When predicating that a company will fail, 
    he adds, they’re right 88 percent of the time.

Re: The Man Who Knows Whether Any Startup Will Live or Die

#33

Post by Someone1234 »

mojuba wrote: post #28

I wonder if they use Bayesian logic, because they should. I also suspect that even though the article does not disclose a lot, the major factor at play in their model is the market sizes. I'm pretty sure their online version would heavily rely on the industry/segment you select. In other words it's a business-plan-looking-good approach which in today's rapidly changing world becomes less and less relevant. So I'll re…

> I wonder if they use Bayesian logic, because they should.

Looking at his qualifications, I think it is safe to say he too took statistics 101.

Re: The Man Who Knows Whether Any Startup Will Live or Die

#34

Post by cousin_it »

gerhardi wrote: post #20
falcolas wrote: post #19

Earlier quoted context omitted.

> He basically admits his model is no better than a monkey Well, technically, a monkey with a coin to flip. "Heads this startup will succeed, tails it will fail"

Now coin flip wouldn't be anything near 50% accurate, unless there is a world where more than a small fraction of startups survive!

A coinflip is always 50% accurate, no matter how improbable the event you're trying to predict. If I flip a coin to predict whether Cthulhu will rise tomorrow, I have a 50% chance of getting it right.

Re: The Man Who Knows Whether Any Startup Will Live or Die

#35

Post by kylebrown »

TeMPOraL wrote: post #27
normloman wrote: post #21

I wish this guy the best in improving his algorithm. If it really worked, it could do a lot of good. But the economy is so complex, I doubt he'll ever make the model more accurate than a coin toss. I predict the model will just make people overconfident in their investment decisions.

Investing is anti-inductive; if his algorithm actually starts to be used in investment decisions, people will keep gaming it until it will no longer be a useful signal.

Reflexive is the term used by George Soros: http://en.wikipedia.org/wiki/Reflexivity_(social_theory)#In_...

Re: The Man Who Knows Whether Any Startup Will Live or Die

#36

Post by jmilloy »

tarkofski wrote: post #16

"He admits the models will never be perfect, but thinks that even a model that’s only right about 50 percent of the time could help investors and entrepreneurs avoid particularly bad ideas that, to the untrained eye, look like excellent opportunities." He basically admits his model is no better than a monkey

Eh, this isn't a statement about his own models, and it's obviously a gross oversimplification anyways. You should focus on some of the earlier statements which give an indication of that his models aren't just a "GOOD/BAD" classification. As a silly example, if my model which predicts age based on a photo was right 50% of the time, that's pretty good because there are more than two ages. If it predicted birthday and was right 50% of the time, that would be incredible.

Furthermore, the models should probably be described as forecasts and not predictions, and as such can't be right or wrong. Which is mainly just to emphasize that the statement is an oversimplification.

Re: The Man Who Knows Whether Any Startup Will Live or Die

#37

Post by mox1 »

mojuba wrote: post #15
adwf wrote: post #11

Earlier quoted context omitted.

Because the current rule of thumb is that ~9/10 startups fail. If you can reduce that to a 50/50 bet, you've made quite an improvement.

Not really. What the article says is, the model would predict 50% of time whether a company will fail or not, which doesn't make sense, because 50% for a binary prediction (i.e. fail or not) is exactly nothing. So maybe it's just bad or confusing wording in the article, the guy actually meant to say something else.

I think it's easier to relate to a coin flip if we use an "unfair coin".

90% of the time the coin flip returns tails (aka fail).

10% of the time it returns heads (aka win).

For a given coin flip, their algorithm can predict the results 50% of the time. At this point I don't remember the calculations off the top of my head, but it involves a Binomial distribution.

Re: The Man Who Knows Whether Any Startup Will Live or Die

#38

Post by jmilloy »

colanderman wrote: post #6

> According to the U.S. Bureau of Labor Statistics, about half of all businesses fail within five years. > He [...] thinks that even a model that’s only right about 50 percent of the time could help investors and entrepreneurs avoid particularly bad ideas ...does he have a bridge to sell me too? What am I missing? (One can simply predict "always succeeds" and will be right half the time.)

I wrote this below, but several things are clear here:

- This isn't a quote and should be taken with a grain of salt. Oversimplification, poor wording, and basic misunderstanding on the part of the author are at fault.

- We don't know what the models outputs are. If they are simply SUCCEED / FAIL, then yes, 50% correct is not very helpful (unless of course it is right more than 50% of the time on big winners). If the outputs are more granular (likelihood of success, expected ROI, etc), then being "right" means a lot less and, to the extent that it does mean something, being right 50% of the time is much more helpful.

Imagine being right 50% of the time guessing about getting through airport security. If you're guesses are "WILL" or "WON'T", then 50% is terrible. If you're guesses are like "through in 23 min 53 sec" then 50% is incredible. If you're guesses are like "70% of being through in 15-20 minutes", what does "right" mean?

Re: The Man Who Knows Whether Any Startup Will Live or Die

#39

Post by ballpoint »

I'm not sure having better predictors of what businesses are good is necessarily a good idea. Part of the attraction of silicon valley is that it takes some of the risk out of trying new things, even if they might be bad ideas. This culture of trying things leads us to find the occasional really good idea. If we sit around all day plugging our ideas into models to see if, statistically speaking, the will succeed, we won't find the really novel ideas that look bad but are actually good.
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