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Aneesh, it's hard to provide an objective experience if you use fake data. Nevertheles, based on the data we analyzed, a 500k valuation was the most likely outc

by kirill 18y ago

Aneesh, it's hard to provide an objective experience if you use fake data. Nevertheles, based on the data we analyzed, a 500k valuation was the most likely outcome for the profiles of entrepreneurs you entered, working on a startup for approx 2 hrs/week. Remember that this is a 3-year prediction and the hours is relevant to that initial timeframe pre-funding. Many of those teams will have increased their hours/week during those three years; and 500k is an indication that they are most likely to achieve an angel round within 3 years, but not much more.

aneesh 18y ago
> "a 500k valuation was the most likely outcome for the profiles of entrepreneurs you entered" (emphasis added) Exactly my point. Given 100 startups with that profile, you can say with some confidence that the average outcome will be 500k. But you're ignoring the distribution! It's very risky to make the bet that one individual startup will be worth 500k. I'm not saying you should make better predictions. I'm saying that it's a very risky game to make mathematical predictions on individual valuations at all. Most machine-learned models aren't better than humans, they're just much, much faster than humans. It's a bold bet you're making if you're trying to be better than humans at predicting valuations. Models don't allow for intangibles like "killer sales ability" that may not be reflected in your degree or past job, but that a VC can pick up on 5 minutes after meeting you. See my reply to Sam's post here: http://news.ycombinator.com/item?id=272015 http://news.ycombinator.com/item?id=272015 Edit: Someone put in the relevant numbers for WebVan or Pets.com. I think those two failed within ~3 years.
ntoshev 18y ago
This looks like the result from selection bias: did you include data from failed startups in your survey? If you tried to account for this, how did you do it?

by kirill 18y ago

aneesh 18y ago

> "a 500k valuation was the most likely outcome for the profiles of entrepreneurs you entered" (emphasis added) Exactly my point. Given 100 startups with that profile, you can say with some confidence that the average outcome will be 500k. But you're ignoring the distribution! It's very risky to make the bet that one individual startup will be worth 500k. I'm not saying you should make better predictions. I'm saying that it's a very risky game to make mathematical predictions on individual valuations at all. Most machine-learned models aren't better than humans, they're just much, much faster than humans. It's a bold bet you're making if you're trying to be better than humans at predicting valuations. Models don't allow for intangibles like "killer sales ability" that may not be reflected in your degree or past job, but that a VC can pick up on 5 minutes after meeting you. See my reply to Sam's post here: http://news.ycombinator.com/item?id=272015 http://news.ycombinator.com/item?id=272015 Edit: Someone put in the relevant numbers for WebVan or Pets.com. I think those two failed within ~3 years.

ntoshev 18y ago

This looks like the result from selection bias: did you include data from failed startups in your survey? If you tried to account for this, how did you do it?