The Compound and Friends
00:11:46 · Josh Brown, Alex Altmann, Michael Batnick
[00:11:46] S0: You just run run it internally and keep your mouth shut. I'll keep my mouth [00:11:49] S1: shut from a from a beach. [00:11:50] S2: But you have the data. So the way that a lot of gamblers lose, just a casual gambler, there's, whatever, 20 games over the weekend, and they'll bet on 11 of them, and there's obviously no edge. You don't have to sway at every pitch. You don't have to bet every game. But when there is reason, when the data says, hey, whatever, 80% of the time, do nothing. Right? Mostly noise. But 20% of the time, we have a 54% chance of of making contact, and we'll swing when it makes sense to do so.
00:12:19 · Alex Altmann
[00:12:19] S1: Yeah. And so in in our case, obviously, we'll work on kind of the opposite where we're we're generally looking for the 80 fives, 80 to 85, nineties in some cases, hit rates, where we'll look at kind of the forward return profiles, whether it's on the S and P, whether it's on a a particular style factor, whether it's even on a sector. And the the hit rates look really attractive based upon pretty robust, not just backtests, but just very long sort of out of sample and in sample periods. So good case in point. Right? So our main framework that helps guide whether we wanna be bullish or bearish, we... It's called BETTY. It's Barclays equity timing indicator. We were originally gonna call it betting, but then kinda compliance had a bit of an issue with that, unsurprisingly. And it's... All it is is that you say we have all the data. Everyone has access data. If I told you what all of these inputs were, you could build it yourself. It's... There's no secret source. It's just a case of aggregating a bunch of stuff that's already available in the market and knowing that when a significant or a sufficient number of them are flashing either positively or negatively, you know in your head and and on paper statistically what the forward returns of the S and P are more likely than not going to do. We have the whole the whole thing laid out, and that's really our guiding light with... From a quantitative framework. And then the qualitative framework is the positioning. It is talking to customers. It's all... It's knowing what the organized narrative is in the market. And, hopefully, this is where it becomes more of an art than a science. You've got the science bit. Right? The art bit is pulling it all together. This is a bit that AI hasn't figured out yet. It's like pulling it all together in a way that you can say, okay. All the ducks are in a row. I think we got... Know, now we... To use your parlance, we have to take a swing.
00:14:04 · Josh Brown, Alex Altmann
[00:14:04] S0: Can you go back to what you said about the order? How how you get to narrative? It start... Like, it starts with it starts with what... Because I agree with the the premise. I just... I sort of think, like, whatever Price is doing, that becomes the story that everybody accepts. It just takes a little while for that to be transmitted around the street. And then it's it's funny. Like, you hear you hear people saying something on Thursday. Like, five people will say the same thing, and they arrive there because of whatever price just told them. It almost never works the other way where somebody is going against price and and people accept that narrative. Does that make sense, like, I'm trying to ask you? [00:14:48] S1: It it it does. And and that's, I would mostly... For the most part, I would think... I think of that as noise. It is because people will use price to justify Yeah. Narrative, or they'll explain something x post because a price moved a certain way rather than necessarily providing real intelligence behind it and go actually... You know, challenging the view. Does does that make actual sense? [00:15:15] S0: Right?
00:15:15 · Josh Brown, Alex Altmann, Michael Batnick
[00:15:15] S0: Right? [00:15:15] S1: And so, again, that's not always the case, but there's oftentimes in the market where things just move because maybe there's a big print someone had to put through a certain trade, and it was it was done in a sloppy fashion. Moves price, everyone said, oh, what just happened? That's particularly prone, like, in the oil market at the moment. You know, oil will move around by a dollar or 2, and then everyone jumps to a conclusion that some random headline from someone you've never heard of. [00:15:43] S0: The reason. [00:15:43] S1: Yeah. That's the reason. It's like, okay. Maybe there was an algo that responds to a certain headline that's obviously the world we live in, but more often than not, it's just noise. [00:15:51] S2: Do you do you take every qualitative signal... Our quantitative signal? And the reason I ask is if you say it's just data and everybody has the data, then there's got to be something else. You need some sort of, I don't know, situational awareness for lack of a better phrase here. So for example, the analytics in football might say go for it on fourth and one every time, but there could be... Well, it's like, yeah, but we have the momentum. Our defense is strong. This offense sucks. Just punt it away and live to see another day. So how much of the qualitative overlay dictates it? Or do you just... It's just a 100% quantitative. 82% chance we go no matter what.
00:16:22 · Alex Altmann
[00:16:22] S1: No. No. No. The the quantitative aspect is really important. That... That's what I was referring to before and where there's art rather than just just science. There are plenty of strategies in the marketplace that are just literally, you know, inputs and outputs. And if it's good quality inputs, you get good quality outputs and vice versa. But I... I'm a big believer that the discretionary overlay is really powerful. It's really important. And, you know, I kind of experienced that firsthand when I was running money as well in insofar that if you just rely on a quantitative process and you inside your own bubble, I think it can work. Clearly, there's guys who have had phenomenally successful careers running those kind of strategies. But for me, personally, I believe there's real power in in talking to the community and getting a really good qualitative assessment of what that... The zeitgeist is, and then building the quantitative framework alongside that to see if they match up or if there's a discord. Right? And if there's some kind of dissonance between the two, then that's to me is usually where there's a real opportunity. Because I'm a big believer personally that... And today, in this environment, is a perfect example of that, where you've got this so called prevailing narrative that suddenly everyone is bearish on AI, right, because of what happened in the financing space or or whatever it may be. And, I conduct surveys. We just sent out a survey just today, which we conducted yesterday. Had 200 investors that came, which is a pretty good sample size from from the Wall Street community. And it's a high quality survey, and the and the feedback was overwhelmingly not bearish on on AI. Right? Only 60% of people that responded thought that we had a financing problem. I'm like, how can that be? We have a financing problem because we've just gone through one over the past two weeks, so that number should have been a 100%.
00:18:03 · Michael Batnick
[00:18:03] S2: So what does that tell you?