The Exchanges

Q What does that, what does that mean for people that don't spend time in that world?

A Yeah, it means you don't take any, um, net exposure to the market, meaning, uh, every hundred dollars of long positions you have, In different companies. You, you also have to have a hundred dollars of short positions. Um, so we're never taking any, um, directional exposure to the market. And, um, you know, for example, in March, 2020, when the market fell 30% in about 20 days, um, we were down one and a half percent. Uh, so whatever's happening in the market would not give you an indication of how well we're doing. Whereas most funds that you heard of, or Cathie Wood, ARC, these types of funds are very exposed to basically risk factors in the market. So we built a market neutral strategy and it's a sophisticated strategy that's really suitable for institutional investors who already have tons of market exposure. They don't need us to buy stocks for them. They want a sophisticated uncorrelated strategy. And so that's what we've built.

AI assessment note: “it means you don't take any, um, net exposure to the market”

Q So that's the master plan, right? Like that's, that's the master plan. That's awesome. I wish I had a master plan, but that sounds, that's pretty awesome to have on.

A Yes, it has been pretty good to direct our energies. Um, and we've never changed it. Um, so yeah, on Numeri, we've, we've got this data. And so it's like, what about this? There are people who are very good at modeling, but don't have any access to data. Let's make sure we can assimilate their intelligence into our hedge fund. And then there are people who already have models, uh, but they have no way of trading because they don't want to be, you know, the new, ten million dollars to use a prime broker or whatever. So then let's make sure they can submit. And that's what numerize signals is. So we're trying to just get all these different sources of intelligence, um, into our fund so that we can be the best and, um, ultimately manage all the money in the world.

AI assessment note: “Yes, it has been pretty good to direct our energies. Um, and we've never changed it.”

Q And how does that work putting all those models together? Is that a, is there like an assembling technique that's well known, or is that something that you guys build?

A We do like, it's literally as simple right now as the steak weighted average. So it's just the average with the stake weights and it's, we've actually tried many times to beat that, but it's hard to beat because if we try something else like, well, why don't we just wait up, wait, the ones that have done well recently, um, then suddenly they don't work and they start doing badly. And so you always, you always want to trust the users to be the ones who know the most and they're expressing how confident they are with the stake. So we, Can never really beat the stake weighted model. However, um, as it comes to trading time in this process, we still have to choose what portfolio to construct. So we have, when we have the meta model, we have predictions on 5000 stocks, and we have to decide which ones to hold in our current portfolio. And, uh, and that is an optimization process that we are in charge of. So we've made our own custom optimizer that minimizes all kinds of market risks and ends up with a final portfolio.

AI assessment note: “it's literally as simple right now as the steak weighted average.”

Q Question from Alex, like, clearly you're getting people excited about the prospects because Alex is asking, why not open to individuals to invest or allow users to passively stake and MR for profits or residual value from the fund?

A It's a good question. I mean, we get that quite a lot. Um, it is, uh, sort of unfortunate that, um, at the end of this process, which is so driven by modern, uh, ideas like, you know, anyone can submit this completely open system. Anyone can join Numeri, anyone can stake, but at the end of this process, we have a hedge fund that is basically closed to everybody except for like seven investors in the world. Um, And the reason it's done that way, though, is that There are regulations about selling hedge funds to, um, people with, it's kind of sad. I think if you have less than a million dollars or whatever it is, you're not considered an accredited investor and therefore certain investment products are not, uh, available to you as if money is the total determinant of whether you're sophisticated.

AI assessment note: “the reason it's done that way, though, is that There are regulations”

Q And people are making a real substantial money with this, right? Like I, did I, did I read correctly? I think I saw like a forty two million number of like payout. Is that the right number?

A Yeah, we have paid out something like that. Um, we've even, I think even just last year we paid ten million dollars. So it's so much higher than the rewards are so much higher than the other data science competitions on online by orders of magnitude. Um, and there's some users that have made more than a million dollars. Uh, and the reason is, is kind of because of crypto, right? Our cryptocurrency, um, is what we use to pay people. So the thing you do have to get your head around, you know, is do I really want to have the risk of holding this cryptocurrency, which, which is quite volatile. Um, but some users buy in for a small amount and then, um, and their stakes end up doing well. And it's also important to note, like, when you do badly on Numeri, it's not like Numeri does well. It's not like we take your stake. It's like, not like we're the house or something. Uh, the, all the staking is happening on the blockchain, and if you do badly, it's just that the NMR gets burned. Um, so it's very user aligned, and, um, that's why I think we have, yeah, about right now over fifteen million dollars at stake.

AI assessment note: “Yeah, we have paid out something like that.”

Q Yeah, could better or crowdsource features have a bigger impact than the models?

A Yeah, so It's a good question because if you know data science, uh, which you probably do, um, a lot of this is about setting up the problem well and having not just good data, but also setting up the data and the problem well. Um, and a lot of the performance comes from, from that. Um, but If we do say a linear model just on our, on our data, it sort of performs okay. Um, if we do our own internal machine learning model on the data, it performs better than that. And if we use everyone's model that's being submitted to Numeri, it's way better than, than even that. So it's always going to be like, yes, there's some edge that's coming directly from the data, but It's very much worth it to get the extra edge, um, especially in the finance domain where, let's say you're, you're current, you're currently 52% right. If you can go to 52 and a half percent right, It's like, it's like a whole different, um, level of, of performance for the end investor, a whole different level of shock ratio or returns and risk. So, um, it's, uh, it's very helpful. However, Uh, Numeri signals is in some ways the crowdsourcing of features. Uh, people can submit whatever data they want, um, on that. So any gaps in Numeri can kind of be filled by the crowdsourcing on signals.

AI assessment note: “Numerai signals is in some ways the crowdsourcing of features.”