Narayan Chowdhury

You want to dig into the data.

You want to have some grounding for your beliefs in data.

And I think the scary part, as I look at it, is the data is very often plagued with holes, non-reporting, self-biased reporting.

it's lagged.

And so the slice of data we get to look at is either just not relevant for this current market, or the thing that it tells you was relevant for a prior regime.

And so there's been a regime shift, or there's been a underlying firm shift such that the conclusion you draw from the data is not helpful.

So let me mention some examples of this, like

You might look at a data set of, say, this is an analysis I've done, but you could look at, say, first-time funds out of some data set that you've paid for, maybe your own data.

After 23 years for us, for example, we have a rich data set of our own to mine from.

But you draw some conclusion.

Well, what confidence do you have that it's representative of a population?

There are some data sets where, you know, I'm looking at these vintages and it doesn't include this fund and this fund and this fund, like 40 really compelling funds that are just not in the data set.

Right.

And you might be led to believe that first time funds underperform or have more risk or have less risk.

But the paucity or the N in a particular, the number of observations in a particular year are like four because you were looking at, say, Israeli infrastructure as your slice.

And so very hard to do data analysis when the data, I'd say, is problematic.

I hope that's published soon.

I'd love to see that.

Yeah, things like that would be great.

But obviously you don't, it'll probably be anonymized.