[sickpig]

from the article:

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

dunno why but I can't stop thinking that tossing a coin could achieve the same goal :)

[joshyeager]

That only works if startups fail 50% of the time. If they fail more frequently, a coin flip would be wrong.

[kylebrown]

Its not clear from the article which factor the 50% figure applies. I doubt its the overall odds ratio, but rather the likelihood given some priors. For example, given a prior that 90% of startups fail, what is the likelihood that this particular startup will succeed? If the prior is already factored in, then the model predicts no better than a coin flip.

The point made in the article is that investing at the odds of a coin flip would be better than investing with incorrect risk assumptions (ie. buying into "particularly bad ideas").

[sickpig]

I stand corrected, you're right. I'm supposed to know better.

[jgeralnik]

Nope, you're still right.

Assume startups fail 90% of the time. 50% of the time your coin comes up tails, and you claim the startup will fail. 50% of the time your coin comes up heads and you claim the startup will succeed.

You guess correctly 0.5 (the chance your coin comes up tails) * 0.9 (the chance the startup fails) + 0.5 (heads) * 0.1 (success) = 0.5 of the time.

[crdb]

1% * (+500,000,000) + 5% * (+5,000,000) + 94% * (-100,000) >> 50% * (+100,000) + 50% * (-100,000)