Animal Spirits Podcast - Talk Your Book: Large Cap Alpha

Episode Date: August 14, 2023

On today's show, Michael and Ben are joined by Francisco Bido, Senior Portfolio Manager for the Integrated Alpha group of F/m Investments to discuss: screening companies, growth vs value investing, investing in Apple, avoiding Tesla, and much more!    Find complete show notes on our blogs... Ben Carlson’s A Wealth of Common Sense Michael Batnick’s The Irrelevant Investor Feel free to shoot us an email at [e-mail] with any feedback, questions, recommendations, or ideas for future topics of conversation.   Check out the latest in financial blogger fashion at The Compound shop: https://www.idontshop.com Past performance is not indicative of future results. The material discussed has been provided for informational purposes only and is not intended as legal or investment advice or a recommendation of any particular security or strategy. The investment strategy and themes discussed herein may be unsuitable for investors depending on their specific investment objectives and financial situation. Information obtained from third-party sources is believed to be reliable though its accuracy is not guaranteed.   Investing involves the risk of loss. This podcast is for informational purposes only and should not be or regarded as personalized investment advice or relied upon for investment decisions. Michael Batnick and Ben Carlson are employees of Ritholtz Wealth Management and may maintain positions in the securities discussed in this video. All opinions expressed by them are solely their own opinion and do not reflect the opinion of Ritholtz Wealth Management. Wealthcast Media, an affiliate of Ritholtz Wealth Management, receives payment from various entities for advertisements in affiliated podcasts, blogs and emails. Inclusion of such advertisements does not constitute or imply endorsement, sponsorship or recommendation thereof, or any affiliation therewith, by the Content Creator or by Ritholtz Wealth Management or any of its employees. For additional advertisement disclaimers see here https://ritholtzwealth.com/advertising-disclaimers. Investments in securities involve the risk of loss. Any mention of a particular security and related performance data is not a recommendation to buy or sell that security. The information provided on this website (including any information that may be accessed through this website) is not directed at any investor or category of investors and is provided solely as general information. Obviously nothing on this channel should be considered as personalized financial advice or a solicitation to buy or sell any securities. See our disclosures here: https://ritholtzwealth.com/podcast-youtube-disclosures/ Learn more about your ad choices. Visit megaphone.fm/adchoices

Today's Animal Spirits Talk Your Book is brought to you by FM Investments. Go to FM-dashinvest.com to learn more about their quant-active strategy for large-cap U.S. stocks. That's FM-dashinvest.com. Welcome to Animal Spirits, a show about markets, life, and investing. Join Michael Batnick and Ben Carlson as they talk about what they're reading, writing, and watching. All opinions expressed by Michael and Ben are solely their own opinion and do not reflect the opinion of Redholz wealth management. This podcast is for informational purposes only and should not be relied upon for any investment decisions. Clients of Ridholt's wealth management may maintain positions in the securities discussed in this podcast.

Welcome to Animal Spirits with Michael and Ben. Ben, when you think concentrated manager, stock selector, you're probably think of a value investor, no? Buffett style, munger, value and yes, value investing, not necessarily growth and not necessarily quant either. Yeah, those are two things that you don't see that off. And number one is quant growth. And number two is concentrated growth. I wonder why that is.

Is it because it's so, it's been so difficult to beat the NASA? That can't be it. Or maybe I'm just making it up. Maybe there are and I just don't know about it. It may be, maybe the range of outcomes is wider in growth stocks between the really big winners and the big losers. That could be it. Yeah, that's a good question.

So it's also, I don't want to step in too much from this episode, but I think in my experience, large-capped stocks, beating like the S&P 500, for instance, has to be one of the hardest benchmarks in the world to beat. That's my personal opinion on this thing. And we talked to a portfolio manager today whose fund has managed to beat the S&P and he. Oh, Russell, 1,000 growth.

Oh, Russell, sorry. Close enough. Well, yeah, but it has beat the S&P, and it's interesting to hear his thoughts about this. So we talked to Francisco Bodeau today. from FM investments. They use a quant process, but also have a qualitative screen in it to make it more concentrated, which makes sense. It's almost like the old Joel Greenbat. Remember, he had the magic formula? Yeah, the magic formula. And then you could pick

30 stocks from it or something. It kind of reminded me of that a little bit. Where you have an overlay, that's the quant screen, but then you also, based on the environment, pick stocks based on your thoughts on how things are going. Here's our conversation with Francisco Bidot. We are joined today by Francisco Bidot. Francisco is the senior portfolio manager at FM Investments. Francisco, welcome to the show. Thanks for having me. We're talking today about the FM Investment Large Cap Focused Fund,

and we recently had another focused mutual fund manager on the show, and it's very nice speaking to somebody that has conviction because one of the trends in your industry in the mutual fund space has been, do no harm, or don't stray too far from the benchmark, And then, of course, you get something that ends up looking very much like the benchmark. Talk to us a little bit about the genesis of your fund. Why the concentration?

How long have you been in business and that sort of stuff? Well, I've been managing the same strategy in large card form and an old cap form and also has a long shirt. Our mutual fund is the flagship. And that one is, that's where the ticker is I-A-F-L-X come around. And it's been around for a good 12 years. And performer has been pretty starlit throughout. If you look at the SMA account for the strategy itself, it's a five-star and morning star, and the mutual fund is four stars. And, you know, it's been a great year so far.

And the reason for that is that we have a very strong process, which you follow very, very strictly that we call quant active. And you've got to wonder, quant active, it's really spelling out, you know, what the process is about. It's part quant. That's phase one, phase two is active. And a typical question that I get is, isn't everybody quanta-active nowadays? And my answer to that is, we're different. You know, it's quanta-active, but we have a framework to address risk management, to address stock picking, to address all the pieces they're going to put forward management

in a very rigorous way, almost that it can be done by a computer, except that we don't trust the computer 100% for obvious reasons. Computer don't know anything about COVID, but the pandemic when it happened, it didn't know anything about Brexit, and so on. You know, so you still need a human in the loop there, but we have a lot of the things we set in a very set framework, which you call quantactive. How much narrowing down does your, if it's a screen or whatever it is that, how much narrowing down do you do?

And is your universe, I don't know, the Russell 1,000 or the SP500, and then how much does your process of the quant side of things narrow things down and then how much is the qualitative side of things from there? Well, the quant side, we start out with about 3,000 names, you know, all cap names, and then we classify them by market capitalization and see where they land and so on. But basically, after we apply our screens, we end up typically with about 80 names. And from those names, then you've got to parse it and pick up which are your large caps and your small caps and so on.

So it's not a fixed cutoff, which we want to have that way. You know, a lot of these quant screens just pick the top 100 names, for example, right? We don't do it that way. And we don't normalize our scores, meaning them when the scores are. are bad, if we wanted to tell us the truth, the things are bad. So if we only have 12 candidates and it has happened, we saw that over COVID and so on, only 12 names we can pick from. Then we want to see it that way because it's telling us something about the market environment. But overall, if I have to pick an average number for you, it'll be 80, about 80 names.

So if you get into a situation like that, we only have a handful of names, are you overweighing those names or are you raising cash in that instance? No, no. What we do is we look at what we own in contrast to what is being suggested to bring in into the portfolio. So we look at two things. We look at the risk. You know, if we decide to bring a certain company in, how does it impact the risk of the portfolio? That's my tracking error, projected tracking error. Does it go up? Does it make it higher? That's to diversify the risk a little more. If I have a lot of IT and bringing a bank, you know, that's going to take the risk down a little bit. So we look what is proposed by the Kwan system, and then Alex and myself, he used to come in sense, basically, right?

And our years of experience to really nail it. And it's consistent. We've done the same thing since the beginning of time. Francisco, this is a growth-oriented strategy. And so the things that you're screening for, I'm guessing you can correct me from wrong, probably look different than what a traditional value investor might screen for. So I'm sure you're looking at, you know, maybe typical things that everyone would look for, like things like margin. But what else is in the process that might be distinct from how you think about it versus what somebody else might look at?

That is really a good point. And I would like to emphasize that we're not strictly a growth portfolio. We look at earnings and revenue acceleration. So we're looking at companies that, you know, at certain point in time, they're acting like really strong growth companies. It could be Campbell Soup. It can be Clorax. It can be American Express. It can be McDonald's or Starbucks and so on.

As well as it can be Netflix or META or Apple. So it does tend to overweight a lot of the growth companies, but it doesn't mean that we can't take a value company because you're looking at the earnings and revenues momentum. We believe that over time, this leads to price momentum. And it's important to know that we're not chasing any trends. We're looking at fundamentals first. So we'll look at earnings and revenues, acceleration.

Why is it that is doing what they're doing? Why is it accelerating? And you can go back and reverse engineer that, and you can see that these companies, for example, Campbell's Soup, to give you an example, a few years back, they came up with a new line of organic products, and all of a sudden they became one of the companies in our screen. It's typically a growth company?

Absolutely not. But at that point in time, they were acting like a growth company, and that's when we want to hold them. Is there any valuation components? where you say, you might say, hey, this company is doing great. Their earnings and their revenue are accelerating. However, you know, the market seems to have a consensus view because it's trading at 30 times sales.

Is there any sort of risk management on how much you're willing to pay for this earnings acceleration? Well, it depends. And it all depends. You know, what the name is and what, how strong our scores are, which comes from the Kwan system, obviously. But then Alex and myself sit down and really have a, you know, a heart to heart about the company and about the fundamental numbers and everything else that it's not captured by the

quant screen, which includes a macro environment and so on. So we do look at valuation, but it's not in the quant screen. It's a discretionary component that we look afterwards. For example, if we're looking at Apple, you know, if Apple came in today, it's been in the portfolio for a long time, but Apple is 30 times. You just remind me of that. So it's 30 times. It's a time to buy Apple. And, you know, depending on what the portfolio looks like at the time, in terms of Alcup capture in terms of what sector it's exposed and so on, then it might not be the best choice. It's a very eclectic view of what happens in the active layer afterwards.

And the important thing to realize is that I created the active layer, I mean, the quant layer. So I know his strengths and its weaknesses. So when Alex and I talk, I know, you know, it's talking not because we are, you know, shooting the breeze or anything like that. We know where the strategy is probably going to benefit from any halls that. the quant layer might have or any blank sites, right? Because it's looking back at data. And here's the market with a rising interest rate environment, for example, well, where is that? There have been interest rate increases over time, but which ones are the same as this

one? You can go back and not find one single example. So for that reason is that we have the two layers. All right. So this is a bit of a two-parter. So my first question is, and then I'll ask the follow. My first question is, what's the, what's a turnover on this sort of strategy? So you're active how active it's very active i think uh in terms of turnover it's high it's over a hundred percent uh we only have 27 names and a lot of that you know the and it depends that you compute turnover uh those 27 names 27 do not lead the proponent by years end it's not that it's a it flows and outflows make that turnover look the way it does so if you look at the names that we had uh the beginning of the year and the names that we have now we're probably different about

four names. But there have been a lot of women in the flows that creates a turnover. So Apple, for example, you said Apple's been in the portfolio for a long time, one of the best performing companies of all time, certainly one of the best companies of all time. However, Apple is not necessarily growing the way that they weren't swore, at least in the top line. Now, there's all sorts of levers that they can pull. Who knows what the next $10 billion category that they seem to create every few years. They really are in a class of their own. But I was looking at revenue growth year over year.

It's been negative year over year for the last three quarters. Is Apple entering a different phase of its life cycle, for lack of a better word? Right. I don't believe so. I think, you know, it's easy for us to get spoiled and think that they can maintain that, you know, for years to come. But, you know, it's okay for an incredible company like that to take a pause. you know, to actually go down to her for a year or a year or a year or so. And that's where I see Apple.

If you look, for example, the last earnings report, then you see that the services sector actually did quite well, and it's growing. What took ahead was basically hardware, iPhones, Macs, and so on. Anything that's hardware took ahead, you know, decreased, but the services went up. That's the Apple TV and so on and the music and you name it, right? So these things tend to be cyclical. And every once in a while, both cycles for the hardware and the services align and you get a bigger wave and you get a bigger bump, right?

We love those when they come over, but it's not always the case. I think the important thing is just to survive when the hardware is not doing great and just keep pushing on the ones that are doing great. And by the way, just to add more color on Apple, it would not be, this is not the first time that it's done this. It had negative revenue growth for a couple of quarters in 20. 2016. It did it again in 2019. So this is not without precedent. Right, exactly. Yeah, attention to go in cycles. But if you look at the, uh, the Intel report, the latest Intel

report, I think there is a quote there about the PC cycle bottoming out. So, uh, their numbers are a little bit more encouraging. So if you map that to Apple and you map that to the fact that the consumer in the US is spending, you know, look at the, uh, MasterCard report. They're spending on cruises, they're spending on the, a lot of things that are pure with discretionary. So, despite the high interest rates, you know, things are turned around. So these things are cyclical. We respect the hard order to come back up. I have a, I'm doing this podcast on a Mac.

I have AirPods, an Apple watch, and an iPhone, so I'm not going to question Apple anytime soon. Personally, for my experience, dealing with active managers, I think the large cap U.S. space is probably one of the hardest places to outperform. I don't know if it's the research or the fact that the U.S. makes up so much of the global market cap, and it's gotten so much more concentrated in recent. decades, but it seems like that space is much harder outperform. What has your experience been like trying to do this in a more concentrated manner? And how do you feel about investing in large-cap or all-cap stocks? Because I mean, I guess you could say all-cap is a rustle-3,000, but it's still dominated by the biggest stock. So what is your feeling about how difficult it

is to help perform in this space? Right. Yeah, it's not easy, but it's easier than small cap. Why do you say that? Because a lot of the small-care companies have the same amount of analyst coverage and analysis that the large caps have. So the markets tend to be, if you want to use a more academic term, a little bit more efficient as you go up in market sides. So there's a lot more research on it, a lot of more good data available for the big companies, right? And for the small companies, you go and maybe one analyst or no analyst follows them. So what do you rely on?

The last earnings reports and a lot of hope. So they're pros and cons to everything. Yes, it is a hard area to outperforming, but I think we found our niche there. And I need just to be concentrated. Today, we hold 27 names in the mutual fund. And we are benchmark aware. We know where the Russell 1,000 growth is at any point in time. We know that.

But we're not focused on tracking it. We just pick the things that we like and we manage our risk. So we're not picking something because it's on the benchmark. If you look at our active share, it should be north of 60% for the mutual fund. That's interesting. I've heard, I've actually, I've heard what you just said about, small versus large, but it's usually the opposite. That's what I was thinking.

People usually say because there is, because there is so much analyst coverage, that's what makes the market much more efficient and therefore difficult to beat. I've never heard anybody say that and then conclude that it's actually easier. So I'd be curious to hear a little bit more on that. Sure. I mean, it all depends on how you treat the benchmark, right? If you treat the benchmark is something that you've got to match, you know, I work with funds that hold 120, 150 names.

if you have all that many names you really have the much of a choice but to be the bench you know and then you find one or two names and try to beat it there maybe get a 50 beeps here and there and that's about it the way that we do it is completely different we don't do that at all we got 27 names and there was a point a kid you're not in the past i don't remember what year it was where i have 90% active share so everything i have was not on the bench so if you pick the right names then you really have a chance so you just can't be the benchmark. If you're more concentrated, have more conviction in what you're doing on your process, which we do, Alex and I really believe on what we're doing. And, you know, our process

has not changed its exception. It's the same scores. It's the same exact ideas. And it's everything is exactly the same. The discretion component does change because market change in well, right? So we can't treat the market now as we treated it in five years before the interest rates were not going up, right? So it's a different situation, but there's a way to factor that in. I'm curious about your process. You talked about how you built this model and you created it, and you know and understand the model, but occasionally you'll get more active with it. So does that mean that you disagree with your model at times when it'll say this stock looks great? It should go on the portfolio on the quant side of things, and you say, I don't think so.

I know because of the macro environment or whatever else is going on. How often are you disagreeing with the model that you created? That's a really good question. And you've got to be surprised by my answer. The answer is never. And I can tell you why. and I can tell you why in a second because I designed the process

in such a way that it gives you choices so if I need three names to come out of the portfolio and it's giving me 10 you know the quality is going to give me 10 I'm making this up right so I don't have to argue with it too much I just got to find the one that we've all agreed

the model agrees because they're giving me 10 and I'm not going to pick from those 10 I'm not going to stray from that so we call that what the screen delivers the approved list and we never absolutely never straight from the approved list so we're never overriding the model The model is always given, here, your 10 choices across different sectors, pick three.

And then we sat down and do our analysis and all these are the best for the portfolio. So we're never disagreeing with it. It's not on purpose. This is a good question, you know, because if you look at a lot of quant products, you know, they override their processes. Every show up, and we don't. We designed the process to such a way that it gives up options. So we don't have to do those overwrite. Francisco, you mentioned earnings acceleration a bunch of times.

one of the craziest earnings acceleration in terms of guidance that I've seen, especially from a large-cap company recently, is Nvidia. I think they guided from like maybe 7 to 11 billion, it was really outrageous. I would guess that guidance does not factor in because that's not necessarily quantitative. It's just where management sets their goal posts. How do you think about what companies have to say about their future earnings potential? Is that completely noise or is that, is there quantitative aspect of that that you take seriously? Yeah, there's both a quantitative aspect and an active aspect to that.

So in the quantitative score, we have a score we call the F score, F as in fundamental score, and that's really the main driver of the portfolio. We use the F score really to handicap the stocks that we like. And after that, you know, we have another score independent of that, which is called the M score versus a momentum score.

But I must clarify that the fundamental score is really the important one. The other score is there to ensure that we're actually being paid for the risk that we take. So the fundamental score, the F score, has about 70 time series to go into it. There's a lot of

information. And some of that information is forward-looking information. You know, FY1, FY2, forward-looking consensus views for any stock. So some of that does factor into the score itself, into the quant layer. However, we do pay attention to what the company is saying, what, you know,

verbally was not going into the score, and if there are any concerns. So that's the active side. So, it factors in both ways, both on the quantum side and on the active side. One of the companies that is conspicuously absent from this portfolio, and listen, you're a large growth manager. It's hard to avoid what's being called the Magnificent Seven. Two of them that are not in the portfolio, correct me if I'm wrong, are Tesla and Meta. Can you talk to those?

Right. Actually, meta is in right now. So it's only one missing. Yeah, the only one that's missing there is. Tesla. And the reason that Tesla is missing is because it's just not meeting our screen. You know, as I said, mentioned earlier, we do follow a very rigorous process. And Tesla has been in the portfolio in the past. At some point, it fell out of favor. And it never has come back through the screen. It's not that we don't like the company. It's that we don't think it's a great

company. But we would be very foolish to actually override the screen and we know we can pick well from there. So Tesla's not on that screen. So it's not meeting the quant layer. So that's why it's not there. When it does, again, you know, when a company starts giving the weight that we like it, that's our strength that we're going to go and, you know, enter with an entry-level position, which is right in the middle of the pack of the portfolio, not, you know, around 2.5%. So that position sizing was going to be the next question, actually, because a lot of quant strategies, if they're more diversified, will just equal weight a portfolio or maybe market cap weight it. How do you handle the weighting of it? Because you have more concentrated portfolio,

but you do have higher weightings in your big names. Do they grow to that size or do you double down on positions at times? So 90% of the names in the portfolio, we try to keep a below 6% that they never get below 6%. 90% of the name count. And the reason that we want to do that is because, in my experience, where many years are experienced working for big mutual funds and so on, that you don't want your portfolio to win because of one name. I rather that it wins because the portfolio is built well.

So with that, it pretty much ensures that, you know, my experience in the way that our client system works. They'll let any position go over 6%. If they go over 6%, say that as an AMD, and that's happened a few times. It goes, oh, here it is, 6.5%, almost 7%, trim it down back to court. Allow it a little bit time to grow and catch a little bit off,

you know, take a little bit off the top there. but in general any name in the portfolio enters at here's a darky name at the centroid you look at the standard you know at the bell curve of all the weights in the portfolio and some are bigger than two and a half some are less than two and a half it's said that two and a half it's right at the center of the belt curve so that's how we enter we do not incrementally enter a position we just slap right into it and when we actually we do the same thing we're gone either we like it or not here's another forgive me for another two-part question but How often are you getting inputs?

I imagine it's quarterly as companies release earnings. Is that accurate or is there something else that I'm missing? The F score, which are referring to, will behave like a step function. It will go flat for a while for about a quarter, right, and then jump when the new numbers come in. But we actually compute our scores on a daily basis, and that's because we also track the consensus views, as I mentioned earlier. And those tend to change on a daily basis, right? So we track those very carefully. So, yeah, so we got this really, you know, Ripley line here and then it jumps or earnings reports or jumps down or up.

That's how it works. So the second part of that question would be, how do you avoid the buy the rumor, sell the news effect? Because I was always taught that price leads fundamentals, right, that people anticipate or the market anticipates earnings acceleration. So like, let's use Uber as an example. And now maybe this is short term. You would say this is noise and it's not significant for how you're managing money. But Uber has been knocking it out of the park, had an incredible run into an incredible earnings report, and the stock is down 10% since it reported earnings, which is that just noise

to you? Do you not care about those short term pullbacks? How do you think about that? Right. Uber is not one of our holdings. I haven't seen that name in the list for a long time, maybe in a year or two. But just generally speaking. Yeah, generally speaking.

Well, that happens, you know, we just stress our process. We look at the numbers first. If the numbers don't match, if it's not in our approval, that means that our quant system is not agreeing. And we don't disagree with the quantum system, like I said earlier, right? So that's one thing. Now, assume for example that the fund system does agree and we actually buy the company, and the company doesn't get rewarded. What do we do with it?

Now, we've got to wonder, you know, like we went into a situation like that last year with the information technology sector, right? We got, you know, we got cream. We had a big IT exposure. However, we still end up in the 50%, you know, in the middle of the pack of the morning, our rankings, you know, because we have a good risk management. But, you know, we just held on to the names because the scores are solid. The market is not rewarding them, but it's just a matter of patience that we can be patient. So if you look at what happened this year, it came back. Boom, there it is. And there we were. Right. We didn't have to really reposition the portfolio to take

advantage of the, you know, artificial intelligent inflection point or craze, whatever is going on out there, right? We're already positioned for it. We believe that we had good names. And we believe that the market was just not doing the right thing and not giving it the right kind of reward, given the acceleration that they had. I assume the sales process for the portfolio is similar to the buy in that if a company you own does not show up in your quantitative screen anymore, it leaves a portfolio. Is that correct? Yes, that's correct. Basically, there are two reasons to leave the portfolio. One, the screen deteriorates, we have a threshold.

You know, when they oscillate, they bump around and all of a sudden, and a couple of them drop here. And then we've got to wonder, they're going to bounce back over the board. order or that they're permanent. If they're permanently, then, then, you know, Alex and I, we call it the kick me sign. We put a little kick me sign on the back with a little tape. And then at some point it goes out. It's never an emergency, right? We pick the right moment.

We pick our fights. See, what else can we bring in that can match that stock and even do better? You know, and then we'll take it from there. So the first thing that deteriorates is the score. Sometimes the score, this doesn't happen often, but it happened with Peloton. We own Peloton, you know, way back. Excuse me? Oh, okay. Yes. We did. At some point, it was an attractive name, you know. Michael wrote a Peloton in 2020 for a couple of weeks.

Until they brew otherwise. But the point is that the data was coming in great, but the active side started seeing the risk with management and not taking ownership of the instances that we're having with the treadmills, you know, the right kind of ownership that we thought they should be having. Like all this thing,

just tell people that you did wrong and you're going to fix this. Instead, they try to blame and pass it around. Like, oh, that's not good. We're out of Peloton. Despite the fact that the numbers were okay, that's going to go on layer. But we can't disagree.

at that level. You know, we have to be in sake. Francis, last question from me. You have a lot of names in your portfolio that might be impacted by AI wherever it goes. Yeah, I have a bunch of names, actually. So I'd be curious to hear how you would handle the following. So let's say that AI is is not overhyped and that we do get the sort of earnings acceleration that the market is hoping to see. What happens if we, if we do get that, and these names go parabolic, like not, not like in video right now, but like truly, truly like 1999 type stuff where you'll see, you know, crazy three standard deviation overbought type of move.

Would you, would you say, okay, the earnings are accelerating, but we're up, I'm making this up. This name is up 300% in the last five months. We have to take profits. Like, how would you think about that sort of scenario should arise? Right. And they're two triggers, basically, for us. Their number one is that, remember, we have a position size, right?

So let's say that it's right. So the company goes over 6% and it's now, you know, all of a sudden from one day to the other, in a week, it goes up to 7.5. You know, we have to reassess, take off some, you know, get it back below 6%. It's such a way that it could keep property, but takes them off. So that's the number one thing. And the other second thing that we would do in that situation is look at the overall. risk at the portfolio. You know, if we have these names that are parabolic, you know, these AI names that are

parabolic, can we balance the portfolio with some really good financials or some consumer staples, for example, that if the market does this, a lot of a sudden, because it's risky, right, if doing that parabola, that it can actually end up in a good spot. So the risk management kicks in quite often, you know, like it's always there. It's not that we're going to put the risk management constraints on, you know, when the market It is bad. When it goes parabolic, it's always hot. So the number one thing that it will kick in is the position size.

If not the position size, then active management, we'll look at the tracking error. We'll look at the marginal contributions to risk of each one of these companies and see if we're really getting paid for it. You know, and really evaluate the situation for what it is. But again, you know, the most important thing for us is not so much any individual name or any individual sector or the matter of being. What we want is to help portfolio to do well. Kind of like think about it as a baseball team. Instead of having one or two good players, you want everybody at base sits and doubles, as opposed to somebody, a bunch of strikeouts and everybody, every once in a while,

somebody gets home run. You know, we don't want that. We want the whole portfolio to do well. So that's the philosophy, basically. So we're really not tuned in. I'm winning because of a particular name. We want to win because you have a strong portfolio. Perfect.

Francisco, where can we send people to learn more about your strategy? You can go to the FM Acceleration website. There's a link for Integrated Alpha, and that's where all my strategies are in. And they can always look at the ticker of Morningstar, IAFLX, and in the major platforms, you know, InvestNet and so on. There's research all over for it. All right. Well, link to all that in the show notes. Francisco, thanks so much for coming on.

We appreciate your time. Thank you. This is what's been a pleasure. Thanks to Francisco. Thanks to FM Investments, remember FM-invest.com to learn more and send us an email, I don't at gmail.com. Thank you.