Animal Spirits Podcast - Talk Your Book: Managing Risk Like an Actuary

Episode Date: February 21, 2022

On today's Talk Your Book, we had Julian Koski from New Age Alpha back on to explain the H Factor and how it helps evaluate individual stocks. Find complete shownotes on our blogs...  Ben Carlson��s A Wealth of Common Sense  Michael Batnick’s The Irrelevant Investor  Like us on Facebook  And feel free to shoot us an email at [e-mail] with any feedback, questions, recommendations, or ideas for future topics of conversation.    Learn more about your ad choices. Visit megaphone.fm/adchoices

Today's Animal Spirits Talk Your Book is brought to you by New Age Alpha. Go to New Age Alpha.com to learn about their age factor scoring system for stocks. Welcome to Animal Spirits, a show about markets, life, and investing. Join Michael Batnik and Ben Carlson as they talk about what they're reading, writing, and watching. Michael Battenick and Ben Carlson work for Ritt Holt's wealth management. All opinions expressed by Michael and Ben or any podcast guests are solely their own opinions and do not reflect the opinion of Ritt Holtz Wealth Management. This podcast is for informational purposes only and should not be relied upon for investment decisions. Clients of Ritthold's wealth management may maintain positions in the

securities discussed in this podcast. Michael, we talk a lot on our show about growth stocks, and we've been having more and more conversations in recent months about having sort of a risk management system when investing in these stocks. And that seems so obvious in hindsight, but so hard to do when gross stocks are ripping. So, in 2020, no one was talking about, we need to have some sort of risk management and rebalancing or some sort of overlay to make these painful periods easier to stomach. And that seems to coming to the forefront more and more now. Well, in 2020, as these things were coming to their peak, not that we knew that they were peaking in real time, but a lot of professional investors were like

this does not work over long periods of time. What's happening now is not sustainable in terms of these Zoom being worth more than Exxon, these are at the end of the day businesses and they do eventually trade on fundamentals. The problem is for most investors, certainly I would say myself included, we're not like doing the calculation of, okay, the stock price is this, what sort of implied growth rates is embedded in the stock price and what has the stock historically delivered on the earnings front, the revenue, whatever the fundamental measures that we're looking at. So what the H factor does, by the way, we got a lot of emails last time we had Julian on, what the H factor does is it quantifies the implied growth rate in the stock price

and says, is this a stock that we want to own? It's taking not like baselines from market history, but baselines from the company itself. Has this company delivered in the past? And what's the probability it will deliver in the future? Yeah, I think it's a really compelling story. It's one that defies style boxes. this is more like a chameleon where it could be value, growth, and everything in between, depending on the market environment.

It's not necessarily like a value or a quality or momentum factor. It's taking the company itself and kind of trying to figure out, have people let the pendulum swing too far between fear and greed, basically. I would wonder if you did like some sort of regression analysis, like what does this look like? And again, maybe it just shifts. Maybe it just depends on the market environment. I mean, that was the hardest part for a lot of the valuations. We were seeing these price to sales valuations we've never seen before.

And I guess because a lot of them you had to throw it out historically, we've seen all these charts where you should see a price to sales thing, maybe in the late 1990s for some of these stocks for a select group of growth stocks. But the idea of figuring out, like, can the company actually live up to this? And what is the growth rate they need for this? You're right. That's something that a lot of people just weren't doing at the time. I listened to, this is an Ashonnessy production.

I can't remember if this was a paper or a podcast. I feel like it might have been Chris Meredith or Jesse Livermore. I can't remember talking about Cisco in the late 90s, that it was pricing in a 29% compounded annual growth rate on. I can't remember if it was the top line bottle on whatever. And it actually did like 17%. And it still got crushed because it just couldn't get to where it was. Ben, I want to give a little tease. What did you think about Julian's comment on Tesla?

I think you were surprised on that one, weren't you? You had like three follow-ups of that because you thought he was going to go the other way. Yeah. He was actually saying Tesla kind of has lived up to they've delivered what the stock price has implied kind of the last few years. So I think the words that he was using to describe these things, the age factor calculates the probability of failure. And obviously a low probability of failure is good, high probability of failure you want

to eliminate. But yeah, listen, I can't speak to the fundamentals of Tesla, but I just know that like in In terms of the card deliveries, which obviously has to then translate into the bottom line, top line, whatever. You want to know where Tesla is underdelivered? Elon Musk's memes, underdeliver every time. He's just... Really?

I thought he over-delivered on the memes. Oh, you mean quality? Quality. He's got very low-quality memes. Yeah. All right. Here is our conversation with Julian Koski from New Age Alpha. We're joined today by Julian Koski.

Julian is the chief investment officer and co-founder at New Age Alpha. Julian, thanks for coming back on today. Thanks very much for having me. Love being on the last time. We got a lot of listener feedback on your H factor. So I think that's a good place to start. Let's talk about that. So what you're trying to do with your ETS, which we'll get into, is avoid losers using the H factor that stands for the human factor. Why don't we reintroduce that concept and then we'll go from there. So the human factor basically is a measure that measures how much vague and ambiguous information humans are pricing into a stock. And that's really important because it's the vague and ambiguous information that when

investors start pricing that into a stock and they push a stock up or down, they actually are creating a risk for themselves. And the risk that they're creating is if you impound this information into a stock price, the stock price might go up. But remember, when it goes up, the company is going to have to deliver. more growth to support that price. So when information comes out, like when Steve Jobs passed away, half the investing population see it as a good thing for Apple, half the investing population see it as a bad thing for Apple. The fact is you don't know because it's vague and ambiguous information.

It's not known information. It's not like the financial statements. If you're going to press the financial statements, you're going to get an outcome that everyone pretty much can agree on. But people are not going to agree when you start pricing this vague and ambiguous information. that H factor measures that. We're looking for that high H factor stocks you want to avoid because there's a lot of gambling going on. Think of it in another way. Just people are pressing all this information that they really don't know. Certainly you talked about avoiding losers. There's been a lot of losers to avoid lately, I guess. But how does something like this handle a sea change in the market? Because it seemed like in 2020, we had this first level thinking type of market where it was like Peter Lynch, I know this company, I'm going to buy it. and we saw all this stuff get pretty massively overvalue going into the first couple months of of 2021. And then we've had this shift now where it seems like, okay, we're back to second level thinking and, okay, great company, but that doesn't mean the stock so great because a lot of them

got so overvalued. So how does the H-factor differentiate between those cycles when things are changing so rapidly from the type of stocks people want to own? Well, again, it goes back to what I believe is that a lot of the risk measures we use, the traditional risk measures, don't fully. capture the very problem you've described. And I think you have to step back and ask yourself, what is it that we're trying to understand? First of all, when do you lose money? You lose money when a stock is overpriced. Let's focus on overpricing first. And overpricing comes from one source

only, and that's humans. It's humans are the heart of overpricing. It's not the fundamentals of a company. None of that's going to overprice a stock. What you want to focus on is you want to ask yourself a different due diligence question. The question you want to ask, no matter where the market is, can the company deliver the growth that's implied in that stock price? And the answer to that is yes or no. It either can deliver the growth or it can deliver the growth. Looking at some of these other measures, growth rotations, value rotations, you're just lining yourself up for trouble because you basically looking at where the market is swinging rather than doing the diligence at the individual company level. So when you look

at exactly what you say, what happened in 2020, you've got to look at the risk. surrounding the stock price, not necessarily the company. There's two different risks. The risk that a company is a bad company, that's different. The risk that a stock has been impacted by human behavior, that's what we focus on. Because that's really where you're going to lose money. It's coming from overpricing. It's that behavior. So the H factor does exactly that. The H factor is telling you that if a company's got a low H factor, it means the company has been able to deliver the growth implied in that stock price. And we want to own those companies. And we want to avoid the company. where people or investors are pricing things in there that who knows where that's going? It's unknown. You don't know. It goes back to manage risk like an actuary, not like a portfolio manager. Actories don't underwrite risk based on this kind of vague and ambiguous information. They underwrite risk based on what they know.

So maybe a good poster stock for this sort of thinking is Tesla, where I imagine the implied growth rates are off the charts. Not only that, you have a lot of option activity going on in this. stock that is pretty wild. Do you take into account the amount of either retail traders that are in a given name or the amount of options that are in the name or is it purely fundamentals? Purely math. We ignore all of that completely. No, Tesla, just looking at Tesla today, I'm just looking at Tesla's eight factor score today. It's 10%. It's around 10%, which is low. We would own Tesla based on that. And I would tell you, since 2019, when Tesla's explosive run began,

Tesla's H-factor score has stayed relatively low. What is that telling you? It's telling you that based on whatever Tesla stock price happened after 2019, where I think it traded around $253 a share and then exploded from there, Tesla has delivered the growth implied in the stock price, even when it reached $1,000 a share, it's still delivering that growth. Interesting. I would have expected the opposite.

But the numbers that they've reported in earnings in terms of deliveries and cars and stuff definitely, well, I guess I was saying, at least met expectations. Yes, that's correct. So you want to own those names. Tesla is actually a very good example because there's so much emotion around that. If I take you back to July 2019,

the stock's trading at $253 a share. You've got 169 newspaper headlines out there talking about Tesla. And of those 169 newspaper headlines, 130 of them are negative. You have people like Jim Chainless and Einhorn saying it's going to go to zero, it's going to go bankrupt, But that's that vague and ambiguous information that you got to watch out for.

And in that case, he didn't overpriced test. An underpriced test. Remember, it goes both ways. When this kind of information starts surfacing, it can do harm both ways. If you were short Tesla, then you got killed. Here's what I have to ask you, because those investors that you mentioned are math-based investors. They're not shorting necessarily the story. They're shorting the fundamentals too.

So what are you measuring that is so different from what they're measuring. Well, then somebody didn't do the math because it's quite simple math. The math is actually quite simple here. This is not rocket science math. If you took the stock price today, I think the core difference is, unfortunately, with a lot of models today, those models are very much subject to human behavior themselves. I mean, analysts sit there all day long playing what if games with these models. What we're doing is we're saying, no, forget all that what if games. You only know two things about a stock at any point in time. The two things you know are the stock price and the

financial statements. Now, based on those two things, just do some reverse math. Take the stock price and work backwards and calculate what does that stock price imply in terms of growth rate? It's a lot of math, but it's not hard math to do. And once you've got that implied growth rate, there's another question you have to ask yourself. Well, let's just look back over the past 12 quarters and see how many times Tesla actually delivered that growth rate. And what you saw is Tesla was delivering that growth rate nearly 80% of the time back in July 15. If you knew that, how would you be short that stock? It's just the math and being short just didn't equal each other. This is something missing there. But the math was simple math.

We've seen especially in the last few months, it seems like, some really huge stocks, especially growth names, come out on an earnings day and get just crushed. So Facebook fell 26% in a day. Snapchat fell like 24% that same day and the next day it was up 50% because their numbers were better. Is your H-factor score even taking into account these short-term swings like this? Or is that kind of meaningless to you? Or do you think that your factor can actually pick some of this stuff out when a company is going to just crater like this? We only rebalance our portfolios quarterly, and think about it for a moment. Stocks are going up and down all day long, each factor is changing every day, but you don't

want to react to that. When you want to react is when the new financial statements come out and we update our models and we get a new age factor score, those new financial statements are either going to support what the market's saying or they're not. And at that point, you're going to want to rebalance your portfolio. That's the risk management. A stock can't keep going up and up and up. At some point, the management of that company is going to have to deliver, and at some point,

they won't deliver, and you're going to create a risk for yourself. So the higher the stock price goes, the higher the H factor goes. So at some point, you're going to want to rebalance yourself out of there. And the only time you do that rebalancing is quarterly when you've got new financials, you ignore the rest of the time because it's the market reacting. It's vague. You don't know what's going to really happen. Do you think that interest rates, forget about what it's going to do the stock price, because

we don't know. Do you think that interest rates are going to impact the underlying fundamentals of a business based on their borrowing costs and things like this. It always does, but never to the extent that people think it's going to have. Most of the time, we overshoot in terms of our reactions. And if you look back in time and you look at the last four interest rate increases, you've seen that right after that, within six months of that, growth stocks which supposedly are the stocks that are going to suffer most don't suffer.

In fact, they're outperformed value by about somewhere around 14%. I can't remember the exact numbers, but it's around that number. Now, that's because the reaction is often overblown. What happens is the problem with the market is you can consider the market right most of the times because it's an efficient market. We believe that. The problem with investors is timing. We just get it all wrong in terms of when to be in.

So right now we're going through this so-called rotation between growth stocks into value stocks. Now, do we start jumping in now? Well, it's too late. Value stocks, I believe, in six months from now when earnings come out, might not be able to deliver the growth implied. Why? Because the stock price has gone up. Everyone's piled into these value stocks and growth stocks have been hammered. So watch them now being able to deliver the growth implied. So you just got to be on the other side of the market. Most of the time, it's simply

about being on the other side. It's not necessarily being right or wrong. Just need to be on the other side. How do you square those circles with the market is mostly efficient, but you want to be on the other side? When do you want to be on the other side? You want to be on the other side Exactly in these situations now, it's about measuring this H factor. You want to be on the other side. When you see an H factor, everyone is piling into, say, a Boeing that's got an H factor score of, say, 69%. You want to be out of Boeing because someone's piling into something there that doesn't square

with the underlying financial statements of that company. But the same is true when we get these sector rotations. Are we saying all value, all growth stocks are bad? No, we've got to look at each stock individually. we've got to look at a stock and say, can this company deliver the growth implied in its stock price? And I will tell you, the lower the stock price, generally the easier it's going to be for these growth companies to deliver, and they're going to get rewarded for that. And value stocks that have now got their stock prices inflated because of this rotation are going to find it harder to deliver. So guess what? I believe there will be a lot of earning surprises on the value side, not the growth side.

And again, we'll go piling back into the growth stocks. So a year ago, your models were basically showing growth stocks had these H-factor scores that were just impossible to live up to, and now it's value. So we've gone totally the other way. Not so, no. There were many, many growth stocks, Amazon's of the world that had low H-factor scores. Again, just because the stock price was going up didn't mean the company was now not going to be able to deliver. Every quarter on quarter, they delivered. So therefore, the H-factor stayed low throughout that period. The only time the H-factor will go high is if the stock price goes up and then all of a sudden they don't deliver. Now there's a problem. Now your H-factor's got risk in it. What did the H factors look like of the past 12 to 18 months for these meme stocks like GameStop and AMC? How did those even look? GameStop always had 100% probability that would fail to deliver its growth. The first time we've ever seen 100% probability that will fail to deliver. We don't play in that sphere.

But it's, again, it's markets like gambling. It is gambling. People get a rush from doing this. It's we wouldn't be around if everybody did what we did. It's we essentially betting against them. We think we develop casino like odds. and we are just essentially looking to see when that mispricing is occurring, but we do it using actuarial science. We don't use it using based on traditional portfolio management ideas.

How complicated is the model? In other words, do you go 90 layers deep or are you like, no, these are the big picture items and it's not rocket science? It's simple. It's simple. If anyone's done at discounted cash flow, traditional discounted cash flow starts with an analyst making assumptions about the growth assumptions about a model. They then put in the expenses and project the earnings and then they put in this cost of capital and they come up with the stock price. In our case, you start with the stock price and you don't make any assumptions. We don't know what the expenses are going to be. We don't know what the margins are going to be. Just use as published. And it's one big formula and you work

backwards to calculate the assumptions. Essentially, in the past, you rely on somebody giving you the assumptions. We're actually trying to calculate the assumptions. We're trying to see what they should be, not what you think they're going to be. So for a lot of these tech companies, in the past, people would say, we've never seen big companies grow like this before. But you didn't look at those past growth assumptions and create a baseline. You said, how does this company do relative to what I said in the past? So a company like Amazon that's grown over any baseline that you could have seen for a company in the past, you just kind of threw that baseline out the window and said, no, we're using

Amazon relative to what it's performed like. Is that the basic idea? Well, two things. The first thing you want to know is what's Amazon currently trading at? And then you work backwards to calculate its implied growth rate. Once you've got its implied growth rate, then compare that implied growth rate to the prior 12 quarters of growth rates and see where it falls on a distribution. If Amazon's trading at $100 a share, and that means they've got to ship 1,000 packages per quarter, and let's assume for a moment they've shipped 1,000 packages per quarter for the past 12 quarters, well, there's about 100% chance they're going to do it again in the next quarter. Now, if Amazon's trading at $5,000 a share, and that requires now that they ship 10,000 packages,

well, the probability of them doing that is just dramatically dropped now if they haven't done that. That's the simple math of it. That is as simple, is it? My wife would make sure all those packages get delivered because she orders so much in Amazon. She's the floor there. I assume that these 50 names, so it's a 50 name product, these 50 names are equally weighted at every balance. H-factor weighted. So the lower the probability, the more we want of it.

lower the risk of failure. Remember, low probability, low risk of failure. So that we own more. So this is stale. It says of December 31st, but it's just so incredible to see Apple with the biggest holding in the portfolio given the fact that Apple is the biggest company in the world. And even at it towering above the rest, it still is relatively, or I guess you would say fairly value, better than fairly valued relative to its underlying fundamentals. That boggles the mind that a company so giant can still be valued fairly relative to its underlying fundamentals. Have we ever seen companies of this size grow this quickly? It's not saying it's fairly valued.

It's actually saying it's underpriced. That's what it's saying. Because it's saying the math is telling you that relative to the price it's trading at, Apple consistently delivers the growth implied in that stock price. That's the key. That's all that matters. What beta it has, what volatility it has, well, how big it is, irrelevant. Can the company deliver the growth implied in that stock price?

Tesla is doing that. They're delivering the growth implied in that stock price. That's what I would suggest to any investor is what you have to look at. And you have to look at each name discreetly. You can't look at them and say, all value stocks are good. All growth stocks are bad. That is as crazy as it can get. That's when you're going to get hurt.

Obviously, this stuff is cyclical. But how many of these companies or sectors do you find are included in your index and your product on a regular basis? Do you have companies that have been in here for 10, 15, 20 years? No, no, no, no, no. The H-factor changes a lot. Every quarter that H-factor is changing. But on a yearly basis, getting to portfolio turnover, the portfolio turns over around about

100 to 125% on an annual basis. So Apple's the kind of company that could be in and out of the index quite often then. Yeah. And remember, that's what the H-factor is doing for you. It's doing the risk management for you because it's saying, look, at some point Apple stock price might get to a point where all of a sudden the expectations of growth delivery are very high and it misses. Well, you don't want to own the stock at that time.

Now, that's what the H factor does for you, because by quarterly rebalancing, it's just removing those high H factor names, and the low H factors are staying there, and once it reallines itself again, it'll be included again. So the H factor is not a style box thing, which I find really fascinating. No, not at all. It's a chameleon. It can be anything at different points in the market cycle. Is there any type of market environment that is either better or worse, or is it more or less random?

What we know about the H factor score is that low H factor scores outperform high. H-Factor scores 65% of the time on a quarterly basis. So 35% of the time, high-h-factor beat low-h-factor. It was not good. But think of that as a casino. I mean, look at those odds, 65% of the time. On an annual basis, it's closer to 100% of the time. Now, in certain market conditions, we've noticed the H-factor underperforming. That is market conditions like March 2009, where suddenly you get the risk on trade, where there's this massive snapback in the market into risk. Same as happens when you go from large cap to small cap. At that point, if you think about it, our H-factor score hasn't had time to catch up. The market's taking a bet and is going

in that direction, but we are still waiting for fundamental data to come out to support that. When you get these moments of volatility, especially on the risk, when there's risk on, that's when we have that. And it's only occurred four times in the history of us doing this, but it does happen. And at that moment, risk on, the H-factor hasn't called. up yet. Now, we've talked about growth versus value here. And it seems like there's this other new asset class that's almost like innovation or disruption. It's the Kathywood Arc Fund. She's talked in recent months that her portfolio is down 50%. Some of these innovation names, a lot of them are down 60, 70, 80%. Are you seeing H-factor score on some of these innovation names that are just like

off the charts looking great? Or do you think some of them were penalized for a good reason? So we just look at ARC for a moment and maybe we talk about that. I'm not one to criticize other fund managers work and what they do. But what is happening is if you look at ARC today, the median H factor is quite low for ARC. In fact, their own names that from our perspective have a low probability of failure. The problem is on the risk management side. So not rebalancing the portfolio every quarter has left her vulnerable now to essentially owning names that went too high. And if you were the last investors in, you really got hurt now. And that's what the H factor does. It's constantly rebalancing so that you're not caught owning names that have got a lot of risk

associated with them now. The concept is good. The H factors are low, but hasn't rebalanced the portfolio properly. So in my view, in my view, when I say properly, there's just too much risk in the portfolio because of the lack of rebalancing. So you say that you manage risk like an actuary, not a portfolio manager? That's right. I like that. That's a good tagline. So talk to us about how you manage risk at the sector level, how do you think about that? Generally, we're agnostic to that. Again, it comes down to can the company deliver the growth implied in its stock price. We could have five names, all essentially that could deliver that. But for purposes of building an index, which is normally what we do, we will limit the

exposure to 3% in any one particular sector. And we do do that in AVDR, which is the one ETF that you've got there. We do limit the exposure to sectors. We're generally agnostic to it, But you do put those controls in place. You don't want to be overexposed completely to one sector. You said 3%. What does that mean exactly, that 3%. For each sector, maximum number of stocks for inclusion to be no more than 20, maximum of 3% of overweight per sector against the same name in the S&P 500.

So if energy, for example, is small, you're not going to all of a sudden be 20% energy. No. Speaking of energy, how does that work? How do you imply probabilities of growth when you have a sector that is so exposed to a commodity. It's the very same math, but you're doing it at the company level. So it's the same thing. You're looking at an Exxon of the world. You want to see, well, what kind of growth does Exxon have to deliver? It doesn't escape the realities of having to deliver growth based on a stock price. So we do it exactly the same way. So you're a sector agnostic, but are there times where you see energy

specifically, I guess it was probably a number of years ago where this whole entire sector has scores that are out of whack. And it looks like this sector is in like secular decline. So you see that on occasion? We saw that. I think that was 2007. You saw that. And the age factor kept us out of those names. So because the age factors were so high. Same in you looked at home builders and banks and pre the 2008 collapse. What had happened was the age factors were all names we wouldn't own. The way this works best is out of the S&P 500, the more concentrated your portfolio around the lowest H factor names, the better. So I'll give you an example. A 20 stock portfolio long of the S&P 500.

So long 20 names with the smallest names was up 38% last year. Now, we have that product, whereas the same 50 names was up around 28%. So you give up a lot by accepting this higher H factors into your portfolio. You're going to get a much higher standard deviation, a much large amount of volatility. But the more concentrated you are around the lowest H factor names, the better the performance. That's how to work. So can you talk about the fundamentals, the inputs that you're looking at? So, for example, let's say that there was.

a one-time legal settlement that just wiped out a company's earnings for the quarter. Is that something that you would normalize? Like, how does that work? What are the underlying metrics? It does. It gets normalized in the process. All of those one-time events, things like that, all get normalized at that point in time. So, Julian, it sounds like you and your co-founder, Armin, started this methodology really in private markets, correct? That's right. If you tried to apply that there these days, because we're seeing all these crossover funds now where people are investing in public companies and then private companies, how does that space look to you or do you not pay attention to it anymore? We're not really investing in that space,

but you're correct in Ben, and what you're saying is we started there. What happened in the year 2000, you had people walking through our door telling us their company is worth a billion dollars they're selling stuffed teddy bears and they're coming in. So we didn't know what to do. We had a fund. We didn't know what to do. So the idea was, let's not argue about valuation over here. We're going to get it wrong in any case. Let's figure out what those valuations imply. And let's build our term sheets, because we were investing capital in these companies, let's build our term sheets not around what the valuation was going to be, but what was our expectation or what they had to deliver.

And that worked really well, because very quickly the argument changed to, well, I can't deliver that. Well, now you can see exactly why your valuation is wrong. I think people just thumbsuck valuation. So, Julie, maybe a good closing question is talking about expectations. What were the expectations going into the launch of this sort of product? this was a new realm for you. And what has that process been like in terms of getting in front of investors and selling

the product and investor feedback? What has that all been like? From our side, I think it's been pretty great. And the reason it's great is because, as you can see from what I'm telling you, we're telling investors a completely new and different story. And we're not only telling them the story. We're supporting that story with tools that they can use that they're not going to get anywhere else.

If you think about it, investing in our products is very much secondary to the relationship. The first part of the relationship is, how do we build value in an advisor's business by telling him something he's never heard before? Because that's the key to building a practice. There's just too much replication out there. Everybody's doing the same thing. So what are you doing that's different? Well, what we're doing is very different. And when you support that with tools, the idea of capital raising becomes much easier at that point in time.

Because I'm not telling you another factor story. I'm telling you something you can only get with us. What sort of tools are you talking about and where can investors find them? So it's the H Factor system that we have, which basically gives you all the H Factor scores every day for all the stocks out there. But it also gives you the H Factor scores for all the ETFs out there. So you can come and look up ARC and look at all their holdings and see what that H Factor score is for that individual ETF. I might just say right now, how do I find that? Because I want to make sure people can check that out.

Well, you won't be able to get, I've got to provide you a login, but what I would suggest you do is we can send you the information to it into the podcast so that you've got it so that they can just contact our portfolio specialists and we will make it available to them. Perfect. All right, Julian, thanks again for coming on. We will make sure to include everywhere people need to go in our show notes. We appreciate you coming on. Pleasure. All right. Thank you to Julian. Remember, if you have more questions about this and Julian told us that they got a ton of questions last time, go to New Ageelphid.com. Send us an email, Animal Spearspot at gmail.com.

Thank you. Thank you. Thank you.