Benjamin Felix

Awesome.

That was great, John.

Thanks so much for coming on and summarizing the work that you guys have done.

All right.

That was cool.

It was cool to have John slides and kind of see what they presented to the class.

I thought that was just kind of neat to have a peek into that.

I thought John was great.

This was his first podcast ever.

And I thought he spoke really well.

Well, it came back so quickly, right?

That's one of the crazy things about higher frequency of return data is that you can see these crazy events.

Even with daily returns, it can be even crazier.

There can be these massive short-term drawdowns that bounce back.

And it's like, if you look at annual data, things just look a lot smoother than if you look at monthly and then likewise with monthly versus daily.

So that finding I think does make sense.

Totally.

For that part, basically what we found was that the new simulation method makes the return distributions look more similar to actual historical return distributions than what we had been doing previously.

Is that a good summary?

We could see that when we do our expected returns update, which we do twice a year.