So if you can break that down and also, like, how ShortFinder finds the stocks and then how, what's the methods that it, it, like, comes up with the report.

Yeah.

Yeah.

So everything on ShortFinder that, that you see there, it's all in service of the risk scores that get assigned to each of the stocks, and that, those risk scores come out of a machine learning engine.

So that's really what is at the core of, of ShortFinder is a machine learning model.

And the machine learning model is using data from about, at this point, 10 and a half, 11 years of, of history, uh, of every stock that has been listed in the US with a market cap under a billion.

Um, and there's some other criteria that, uh, we've had in place to, uh, try to filter out some of the, the really crazy stocks at the bottom that are trading, uh, w- with tiny floats and, uh...

And, um, and what else? So where do you see ShortFinder in the, in the future? Like in the near future?

Let's dive in.

David and everyone here, it's, um, it's great to be here at the Friendly Bear Conference in Mexico City.

My name is Justin Hibbard and I have a company called Capital Scope that makes a product called ShortFinder, which is a retur- research platform for researching stocks to sell short.

So you can identify stocks that look, uh, attractive to short sellers there.

We have, uh, machine learning models that are processing over 10 years of data to, uh, come up with predictions.

In any event, this is not gonna be a commercial for ShortFinder.

This is gonna be an educational presentation.

You're good.

What happened there? Yeah.

Yeah, so I was in, I was what's called a bivocational pastor.

So I had to have another job on top of being a pastor.

Not like being a pastor isn't enough of a job.

So it was always, I had a full-time job teaching.

I was an educator.

And then I was a part-time, quote unquote, part-time pastor.

So tell me how that went for you.