[nostrademons]

The comparison I'm trying to draw is about why the models were wrong. Subprime lenders planned for failure too; after all, this is why the loans were subprime, it was expected that a number of them would default. All of this is built into the business model: charge high interest rates on all the loans, to subsidize the cost of some expected number of failures.

The problem is that when the business grew and everyone entered, it changed the assumptions that the models were based upon. A certain percentage of mortgages would blow up when subprimes were 1% of the market. The fatal mistake was assuming that the same percentage of mortgages would blow up when subprimes were 10% of the market, because the process of going for 1% to 10% means writing many more loans and extending credit to buyers who should never have been buying houses in the first place.

[anamax]

> The fatal mistake was assuming that the same percentage of mortgages would blow up when subprimes were 10% of the market, because the process of going for 1% to 10% means writing many more loans and extending credit to buyers who should never have been buying houses in the first place.

There's another problem - the "market share" of subprime loans was underreported by Fannie and Freddie (and they were the largest single buyer of the relevant securities). So, even if your model of forclosures depended on the share of subprime mortgages and was perfect, you got the wrong results because the inputs were wrong.

[gruseom]

YC and subprime seem diametrically opposed to me. YC's risk in a tranche (i.e. one YC round) is bounded from the beginning: they can't lose any more money than they invest, let alone get wiped out if some model happened to be off by a few percent. What assumption is there which, if it shifted, could blow them up? They've already taken their maximum loss by the time the checks are written!

[nostrademons]

Subprime's risk is also bounded: funds buy the mortgages, they're paying a fixed sum of money in exchange for an uncertain payoff in the future, predicted by models.

A large part of what made it blow up is leverage: that fixed sum was often more than the entire capital of the fund. That doesn't apply to YC, I think; to my knowledge, they don't borrow any money to fund the batches. The main investment PG et al makes is in time, energy, networking, and brand name. And that's where it could blow up: fund 10x more startups, most of which fail, and suddenly the YC brand isn't worth anything with investors, PR, employees, etc. Perhaps that's why PG doesn't do it. In this case, his intuition is a perfectly rational response to unintended consequences that are outside the awareness of his conscious thought process.

[gruseom]

I guess what you're arguing is that if YC funded too many startups, the bottom could fall out of the startup market the way it did in the mortgage market. Is that it? But the leverage thing is a huge difference. Another is the markets themselves. If the money in startups all comes from rare cases that pay off a million percent in a few years, well, mortgages surely don't work that way no matter how many layers of indirection the derivatives people concoct.

(Looking upthread, I wonder if your objection really is to the idea that more risk automatically means more reward, so therefore YC should fund 10x more. But clearly the argument is more subtle than that – otherwise, they should just fund everyone who asks them.)

Edit: I have another argument, or perhaps just article of faith: I think there's a major pool of unexploited talent out there, basically wasting away (mostly in corporate jobs) at far below its potential. If many more startups get funded, many more creative endeavors will get going. Most won't be black swans but that doesn't mean they won't be side effects of great good.

If I'm wrong about that, then maybe there is an analogy with subprime, where lenders' (investors') zeal caused them to lend to (fund) ever-crappier borrowers (founders). On the other hand, if I'm right, then this is more about correcting an inefficient allocation of talent in our economy.