5 ms·

I don't really understand what the debate is about. Even if the market is totally 'bimodal' valuations matter the same way as in a non bimodal market. Expected

by nadam 16y ago

I don't really understand what the debate is about. Even if the market is totally 'bimodal' valuations matter the same way as in a non bimodal market. Expected return is orthogonal to expected Risk. Let's say the market is so bimodal that a startup fails or becomes google. Then the expected return is: p * G where 'p' is the chance of becoming Google, 'G' is Google's value. Basically investors' bid for valuation is their bid for what p is. The story is only that if they say that the company's value is X while the startup says it is 2 * X that means that they say p = p1 while the startup thinks p = 2 * p1 Of course valuations matter. It matters linearly. In any market. Even in the most risky markets. I can decrease my risk by diversifying my investments into lots of different high risk assets and my expected return remain the same, but I can only increase my expected return by buying in at low valuation. This is exactly what YCombinator does. This is just very basic math. TL;DR: The fact that investors care about valuations does not mean they don't recognize that the success distribution is bimodal.

soundsop 16y ago
If p is bimodal, then p = 2*p1 is not possible. Either p = 0 or p = 1. The values in between do not occur. Then the only thing to quibble over is G. But if you believe p = 1 for a company, what's the point of quibbling over G?
- india 16y ago
  No. The event being bimodal only implies that the probability is centered around two values, not that p =1 or p = 0 for those values. For example, take a biased coin that turns up head once in a million. This is bimodal with p(head) = 10^-6. PG's argument appears to be that the error in your estimate of p is almost always larger than the value of p and one should invest as long as 2*p is also within the estimation error.
  - jessriedel 16y ago
    > PG's argument appears to be that the error in your estimate of p is almost always larger than the value of p and one should invest as long as 2*p is also within the estimation error. I don't think this is correct under canonical Bayesian reasoning. All uncertainties (whether because of ignorance or "objective uncertainties") can be bundled into your probability assessment. There is no "error" on your probability. I'm not expert though. I'm only....80% sure.
qq66 16y ago
I think even Kleiner Perkins would rather have invested in Google at a $7.5 million valuation than a $75 million valuation as they did. However, negotiating hard on valuation can cause you to lose the opportunity to invest, and the people who argue "bimodal" are saying that this is a poor strategy since it may lock you out of the best deal of the decade just for a few quibbling valuation points.
jessriedel 16y ago
Yes, exactly right, except with two caveats. Doubling the valuations means you get to make half the number of bets--thereby halving your expected returns--except... (1) ...if the price of finding a given start-up to invest in is significant. You've already paid the search cost before you decide on the valuation. Extreme example: It costs $100 to find each start-up, and you are arguing over a valuation of $1 or $2. Paying $1 instead of $2 won't let save you enough cash to find another start-up. (2)...if the market cannot be approximated as infinite because there are only a couple of Googles. In other words, when valuations drop to half, you can only double the number of bets if there are other similar bets to be made. So when Paul Graham says >Did they not understand that the big returns come from a few big successes, and that it therefore mattered far more which startups you picked than how much you paid for them? He's either mistaken or (more likely) he's implicitly suggesting that one or both of the above factors are very strong. But if so, why not be explicit about it in his original piece?

by nadam 16y ago

soundsop 16y ago

If p is bimodal, then p = 2*p1 is not possible. Either p = 0 or p = 1. The values in between do not occur. Then the only thing to quibble over is G. But if you believe p = 1 for a company, what's the point of quibbling over G?

india 16y ago
No. The event being bimodal only implies that the probability is centered around two values, not that p =1 or p = 0 for those values. For example, take a biased coin that turns up head once in a million. This is bimodal with p(head) = 10^-6. PG's argument appears to be that the error in your estimate of p is almost always larger than the value of p and one should invest as long as 2*p is also within the estimation error.
- jessriedel 16y ago
  > PG's argument appears to be that the error in your estimate of p is almost always larger than the value of p and one should invest as long as 2*p is also within the estimation error. I don't think this is correct under canonical Bayesian reasoning. All uncertainties (whether because of ignorance or "objective uncertainties") can be bundled into your probability assessment. There is no "error" on your probability. I'm not expert though. I'm only....80% sure.

qq66 16y ago

I think even Kleiner Perkins would rather have invested in Google at a $7.5 million valuation than a $75 million valuation as they did. However, negotiating hard on valuation can cause you to lose the opportunity to invest, and the people who argue "bimodal" are saying that this is a poor strategy since it may lock you out of the best deal of the decade just for a few quibbling valuation points.

jessriedel 16y ago

Yes, exactly right, except with two caveats. Doubling the valuations means you get to make half the number of bets--thereby halving your expected returns--except... (1) ...if the price of finding a given start-up to invest in is significant. You've already paid the search cost before you decide on the valuation. Extreme example: It costs $100 to find each start-up, and you are arguing over a valuation of $1 or $2. Paying $1 instead of $2 won't let save you enough cash to find another start-up. (2)...if the market cannot be approximated as infinite because there are only a couple of Googles. In other words, when valuations drop to half, you can only double the number of bets if there are other similar bets to be made. So when Paul Graham says >Did they not understand that the big returns come from a few big successes, and that it therefore mattered far more which startups you picked than how much you paid for them? He's either mistaken or (more likely) he's implicitly suggesting that one or both of the above factors are very strong. But if so, why not be explicit about it in his original piece?