Benjamin Felix

And they also mentioned that, well, the aggregate IPO data that we just talked about is terrible.

If you sort IPOs on profitability,

the more profitable ones aren't so bad.

So if you're investing in negative earnings stocks at IPO, yeah, you did poorly.

But if you start by profitability, the more profitable stocks, that shows up in Professor Ritter's data too.

That was interesting.

That surprised me.

So they are really just looking at expected returns more so than a blanket exclusion of IPOs.

They also noted when we were chatting about this, that they are totally aware of the issues surrounding index inclusion post IPO.

And so they try not to be on the same side of indices when they're buying and selling.

They try to be on the opposite side or stay neutral during the rebalancing period.

That was interesting.

They have their own way of dealing with IPOs, but they're not doing a blanket exclusion or waiting period in the way that Dimensional does.

They'll all introduce their own tracking error, whatever you want to call it.

They'll introduce performance differences relative to each other.

If we held all else equal, but just had one fund that's going to invest in IPOs within five days, one fund that's going to wait six to 12 months, and one fund that is going to do what Avantis does,

all else equal and just let the IPOs be different, there'd be pretty meaningful tracking error more than any fee differences across the funds, which comes back to the question for the investor.

Marco talks about this in his paper too.

Knowing that you're going to introduce tracking error from doing something, you have to have a lot of conviction.

Knowing that you can live with tracking error, that the expected long-term outcome is good, which is an interesting question because in the short term, there's going to be a lot of noise.