In this podcast, Motley Fool analyst Bill Barker and host Deidre Woollard discuss:

  • How Domino's continues to compete for its share of stomach.
  • The importance of loyalty programs and the worry of loyalty fatigue.
  • If Walgreens' new CEO will keep steering the company toward healthcare.

Deidre interviews Professor Michael Robbins on his new book, Quantitative Asset Management: Factor Investing and Machine Learning for Institutional Investing.

Claim five Motley Fool dividend recommendations here: www.fool.com/dividends.

To catch full episodes of all The Motley Fool's free podcasts, check out our podcast center. To get started investing, check out our quick-start guide to investing in stocks. A full transcript follows the video.

10 stocks we like better than Domino's Pizza
When our analyst team has a stock tip, it can pay to listen. After all, the newsletter they have run for over a decade, Motley Fool Stock Advisor, has tripled the market.*

They just revealed what they believe are the ten best stocks for investors to buy right now... and Domino's Pizza wasn't one of them! That's right -- they think these 10 stocks are even better buys.

See the 10 stocks

 

*Stock Advisor returns as of October 16, 2023

 

This video was recorded on Oct. 12, 2023.

Deidre Woollard: Your emergency pizza is ready. Motley Fool Money starts now. Welcome to Motley Fool Money. I'm Deidre Woollard here with Motley Fool analyst Bill Barker. Bill, how are you doing today?

Bill Barker: Good thanks for asking.

Deidre Woollard: Well Bill, earning season is starting to kick in. I'm steeling myself for the onslaught of 3, 4, 5, 10 companies a day. How do you deal with that tide of information?

Bill Barker: It tend to focus on what's in the headlines to a very limited extent and the specific companies that I'm most responsible for following as a analyst here at greater detail. It's the best time, it's the most real information. So I don't mind it.

Deidre Woollard: I love it. It's the best time. Yes. Well, we've got some earnings stay to talk about. Let's talk first about Domino's Pizza. Same-store sales down a little bit. Domino's is interesting to me because I think people think of it as it's selling pizza and of course, it's selling pizza. But that's really part of the puzzle when you think about the business, because it's a franchise business, it's definitely a selling supplies business. What metrics are important with Domino beyond just like they're selling more pizza?

Bill Barker: Well boy, that is a big one.

Deidre Woollard: That is a big.

Bill Barker: It is a very big one. Beyond that what the store count is, the new store count year to year. What the cash-on-cash returns are per store and per new store, are they cannibalizing any of the existing stores? I think that it's a relatively easy business to follow because it's got a simpler business plan than many others. Despite the franchise fees and all that, it's about how many pizzas they can sell more than anything else. They've expanded the menu beyond pizza. That's helps at the margins, but the core business hasn't changed too terribly much.

Deidre Woollard: No, it is still all about the pizza. One of the things that's interesting though is they are investing heavily in technology. They're partnering with Microsoft, and they are passing some of that cost on to the franchisees for things like the app. How much are the collaborations that they're doing. How much are you factoring that into looking at the business as a whole?

Bill Barker: Well, Uber Eat collaboration is interesting. Domino's is still doing the deliveries, and so they're just visible on the Uber eats app. They've already got a very well-developed online presence and have for years. That's been one of the big contributors to their success. They're just expanding into Uber eats in the sense that people see them there rather than their own ads. There are people who will only order from Uber Eats right now. That's how they just choose to get their food delivered. They probably don't realize it's Domino's that's delivering rather than Uber. Over time, and this is going to be, I think, for a market roll out initially and then it's going to expand from there. Potentially quite a bit of additional business for Domino's with relatively little investment, but it'll cut into the margins.

Deidre Woollard: But no, the investment is definitely happening on their app and driving their customer loyalty and improving things on that end as far as the technology goes.

Bill Barker: Yeah, they want people to order from them rather than through they don't want to split the profits with Uber eats if they don't have to, so making addition the loyalty program, getting people to come back directly to them, just as a hotel would rather have you book directly at their site rather than through Expedia or hotels.com or any of the other ways that you can get the same thing. But Expedia or all the intermediaries have their loyalty programs and the hotels have their loyalty programs. Same dynamic here, where Domino's wants to develop the app experience and the online experience as well as it can. So that it's getting all the money that it can from the sale, it's the same endpoint work that they've got to do.

Deidre Woollard: Yeah, let's talk a little bit about the loyalty program. They announced something earlier this week. Very PR driven story, but really made me think about their loyalty program. They launched this thing where they call it but like a free emergency pizza. Well, it's really just buy one, get one later. But they call it an emergency pizza. Sounds funny. It got a lot of headlines. But the other part of that story too, is they've also lowered the barrier to entry for the program. They're really trying to get that loyalty program going, they're trying to make sure that people become part of that. You just made a good point about Uber because of course, Uber have their memberships and their loyalty programs. I'm wondering, when do you think that the loyalty program is going to grow with Domino's? Does this have to become part of the system? How much do you factor loyalty programs into thinking about the value of the business?

Bill Barker: Well, it shows up in the numbers. It shows up in the margins. I think that giving you buy one, get one later pizza, getting a little bit of advertising coverage for that is all to its benefit. I think that everybody out there, grocery stores, the little discounts you get by joining their loyalty programs, certainly the airlines. There are people who become quasi-addicted to the miles, the points, the free stuff they can get at the margins. The more that you make people think and part of the equation of making people think they're getting a value of extra rewards from being in the loyalty program is to create real rewards in Domino's. It's easy, you get a free pizza rather than you get access to the airport lounge or something like that. But the emergency pizza, I guess offers some interesting advertising possibilities that I can think of.

Deidre Woollard: Yeah, I do wonder if there's going to be loyalty program fatigue though. For some things, like airlines of course you're a member of those. It just makes sense, I think everybody I know is a Starbucks reward. You go in and get your coffee eventually. Sometimes you get free one, that's a good thing. But eventually, do people get sick of managing all of these different rewards and does that lead us more toward that idea of a super app where things get consolidated? I always feel like we go through these cycles of consolidation and then unbundling, and then consolidating again.

Bill Barker: A super app for all rewards.

Deidre Woollard: For all rewards. Hey, maybe for all the food.

Bill Barker: Has somebody tried that yet?

Deidre Woollard: Not yet. Maybe they should.

Bill Barker: To a certain degree, it's meant to be your phone so that you don't have to remember all the things. You don't carry a card with you that you pull out, check out at every establishment that it can just live on your phone. That I suppose is the solution to the too many loyalty reward programs and numbers that you would have to remember and cards that you would have to carry.

Deidre Woollard: Yeah, that makes sense. They should just put it in the iPhone wallet. One more thing about Domino's. When people talk about the company, they worry about the debt a little bit. You have five billion in debt here. That's a lot of pizza. How should investors be thinking about that debt?

Bill Barker: Well, I think that it is a lot of debt. I think that's a fair thing to look at. It has worked out to the benefit of shareholders because debt has been relatively cheap. The debt before the last 18 months was an extremely good way to fund growth compared to issuing more equity. I don't blame them for that. Then they have a target. I think it's 4-6 times bit or something like that on the debt. As long as they are maintaining and they are what their target range for the debt is, I think that you can look at how that translates into additional profits for the company through the growth, but if debt becomes more and more expensive and they don't have that much debt to pay off in the next three years, so no one should worry about whether they would run into any serious financial trouble. Of course, the business is very predictable. The cash flow appears every day, people eat every day. It's a business that can maintain more debt because of the predictability of the cash flows. But it's a lot of debt for a company of this size.

Deidre Woollard: But the fact that it's not coming due any time soon is at least a little bit of a comfort, I guess.

Bill Barker: Hopefully from everybody's perspective it will be cheaper to borrow in the future than it is today. Homeowners and businesses, and everybody except people who have savings in bank accounts, they don't mind higher interest rates. But everybody else is pretty much hoping in the future is cheaper. If it is, Domino's debt will be less of a problem than if it gets to be more expensive.

Deidre Woollard: God, I hope that.

Bill Barker: Math.

Deidre Woollard: That is in fact math. Let's talk about another company that reported today. You and I were on the motley fell morning show for our membership. Yesterday, we talked a little bit about Walgreens and Boots Alliance, because they announced a new CEO, Tim Wentworth, who has a strong healthcare background. Walgreens is interesting. It is really moving into that healthcare business. They're growing that mostly through acquisition, but debt is a factor here. It's costing them a lot of money. Looking at this company, when you see a company in general, in the midst of this real change and focus, how do you assess the value of the long term strategy, especially when it's an older company like this?

Bill Barker: Well, I assessed it in the numbers and what management says about the strategy. They may haven't heard the conference call today. This was the first chance from the new CEO to talk about whether there are any changes in the pace of the rollout or the use of funds to acquire rather than to do something smaller scale within the stores.

Bill Barker: So far it has not worked out terribly well for shareholders and I think that the transition to a CEO with more healthcare background, particularly in the PBM space, is good because that's a big part of Walgreens money, is negotiating and managing the PBM relationships and surviving them. Somebody who knows where the bodies are buried is going to be useful.

Deidre Woollard: The results came in below estimates. Part of that is just less COVID vaccines, less COVID testing. But even though the results came in below estimates, the stock was up. I think some of that is new CEO bounce, maybe a little bit of hope that they're going to have a new strategy or just the idea that after six weeks of an interim CEO at least, there seems to be a plan forward. Do you think that might be what's causing a little bit of that?

Bill Barker: I have to guess, having not heard the conference call, that something in there was useful. I think that the stock is down so much this year that simply not delivering bad news or news as bad as it might have been, especially after the CEO abruptly left. There might be questions about whether another shoe is going to drop, so with the stock down 30-some percent this year, today's report had an easy act to follow. Now, a lot of the time, somebody new to the equation will come in. I don't think that there has been time to do this. Just dump a whole lot of things, the big bath theory of getting all the bad news out right away, and they're like. That's my fault, so we'll just take a bunch of write-downs and we'll just put all of the losses in a big bucket and therefore they don't count. I don't think there was time to do that for this report. The mess on top line, small as it was. I think market just is taking a sigh of relief. I think that there isn't any particularly bad news this time.

Deidre Woollard: They did talk a little bit in the release about the cutting costs and I think the market wants to see that. They've seen a lot of acquisitions and now they want to see this cost-cutting. They want to see finding where they can make some savings. You're right. It hasn't performed well over the past few years. A tough business for pharmacy overall because now you've got Walmart, Amazon, Costco. Everybody's getting into the pharmacy game and I'm wondering if Walgreens has to make this payoff in order to survive because really these businesses are moving from being retail essentially to now being retail and increasingly healthcare and services.

Bill Barker: Maybe so. It is a problem that your traditional business, which has worked very well and has allowed you to grow a lot is being now attacked by Walmart, Amazon, and Costco. That's a lot. [laughs]. That's a lot to deal with. They've got to have some strategy for what that world is going to continue to look like and the one that they have gone with has not translated into profits yet. But they're in a good space, they're trusted healthcare name, more so than those others and there's an opportunity there. But large drugstore chains don't survive just because they get large.

Deidre Woollard: Very true. I mean, if we're betting on the demographics of the aging of America with this one. All right, Bill. I'm going to wrap up with a silly question. What's your pizza order?

Bill Barker: My pizza order usually involves a lot of meat with pizza.

Deidre Woollard: What? Do you like a sausage and a pepperoni?

Bill Barker: Something like that? Whatever's available. Yours?

Deidre Woollard: I'm a pineapple person. 

Bill Barker: I don't know about that.

Deidre Woollard: Thanks for your time today, Bill.

Bill Barker: Thank you.

Deidre Woollard: If you're a regular Motley Fool Money listener, you're probably well aware of how dividend stocks have the potential to really supercharge your portfolio's returns. Dividends have accounted for around 40% of the total return of the S&P 500 since 1930 and of course, have been an important tool for all-time greats like Benjamin Graham and Warren Buffett. Our top-notch analysts at Motley Fool Stock Advisor certainly agree and put together a list of five quality dividend paying that are also recommendations in our Stock Advisor service. The report is free to you just as a thank you for listening to our podcast. No purchase is necessary. Just go to fool.com/dividends and we'll email it directly to your inbox. That's fool.com/dividends to claim your five dividends stock recommendations now. Will AI take over the investing world? I sat down with Professor Michael Robbins, author of the book Quantitative Asset Management to talk about how quantitative investing works and the potential endangers in AI-driven investing. Let's start at the beginning. Quantitative Asset Management people have probably heard it said a lot, but not necessarily understand exactly what it is and how it differs from other investing approaches.

Michael Robbins: It's in the news a lot lately, and in fact, I think most investors now are quantitative in one way or another. But people I think, misunderstand the purpose of it and think it's about coming up with a number, a scale, a metric to judge a trade when really it's about the process of thinking through the trade in a disciplined structured way, which I think works for everyone, even people who aren't great at math.

Deidre Woollard: That would be me. Your book focuses on a lot of different types of modeling, so how can a qualitative investor like me get a better understanding of some of the models used in quantitative analysis and get a little more comfortable with some of those numbers?

Michael Robbins: Well, there's lots of great information out there, and a lot of these models are accessible to people without a lot of knowledge. Although it's a little dangerous to use a powerful tool without a good understanding. But some of these tutorials are really intuitive and interesting. You could think of, for instance, a linear regression, as a way to put a line on a chart full of dots so that the line is as close to as many dots as possible. The way they do that is they measure the distance between the dots and the line and try to make the sum of those distances small. In fact, the real way they do it is they take the square of those distances. A lot of the other more powerful machine learning methods are based on that thing. They might use a different way to measure things or a different line. Or maybe they use that line, divide two different types of dots instead of trying to find a line that's closest to fit them all. That's a second type of problem called classification.

Michael Robbins: Even in this short discussion, this simple analysis, we sought the two major types of quantitative analysis, regressions and classification. It can be intuitive and a lot of videos show this graphically with all sorts of colors and moving graphics and I think it's pretty accessible for a lot of people. But then these much more complicated models, the ones that people are so excited about lately, like the large language models, they're harder to grasp. It's harder to get a true understanding of those things. It's a little like quantum physics, once you move out of the realm of what you're used to and the intuition about the world around you and things become abstract, it's hard to get a really good understanding, to be able to use those tools properly.

Deidre Woollard: That's an interesting point you made about the difference between intuition because so much of qualitative investing is thinking about what you feel about a company, what you know listening to the earnings calls. You look at the numbers too but you also are going on a lot of intuition. Whereas quantitative is really different from that. Thinking about modeling in general, what are the limitations of it and when maybe should we put the modeling to the side and go a little more on the intuition?

Michael Robbins: That's a really great question and there's a lot packed into that. But all models are limited almost by definition. It's just prohibitively difficult to build a model complex enough to take everything into account. An important feature of quantitative investing is if you do your testing, you run a bunch of experiments and you know what you've tested and what you haven't. You have that envelope, that parameter that you're comfortable in. You know you've tested these things and you are pretty reasonably sure that you understand what's going on. In quantitative investing, it's pretty clear what you don't know. You may be right, you may be wrong, but if you haven't tested it before, you really don't know. That's a great feature in a way of thinking. If you're qualitative, if you're intuitive, it could be very powerful, but you're also always a little unsure and sometimes more unsure than others, and a lot of times your mind plays tricks on you and your comfort level informs you of how much you believe in something. If you're comfortable with a situation, you have the intuition that you know what's going on, and that's not at all necessarily true. With quantitative investing, you know exactly the limits of your knowledge. Importantly when you're trading, you should have an investment thesis. You should have a reason for investing, and that's the difference between investing and gambling. When that thesis is violated, when you're out of your depth, you should exit your trade even if you're making a lot of money.

Because if you're making a lot of money and you don't know why, maybe you'll start losing a lot of money and not know why. The important thing is you should know why. For me and people like me, quantitative investing gives you that comfort level that you actually know where that barrier is, you know what you've tested and what you haven't. Also very importantly, and this is something maybe some amateur traders don't think so much about, when things don't go well, people want to force you to stop what you're doing. They get uncomfortable, they get afraid, and it's important to be able to defend yourself and your trade. If you have tests you can say, hey, look, we've experimented with this, we've seen this in our experiments. You're uncomfortable, I get that. I understand what you're feeling, but your feeling is not as valid as our experiments. Until you have a good reason for us to exit our trades, we have a good reason to stay in them. Whereas if you're intuitive, your reasons might be great, but they're a little harder to convince people of, and that may turn into someone forcing you to exit a trade before you have to.

Deidre Woollard: I want to talk a little bit about AI and how it might change the world of investing even more that it has. You mentioned earlier the large language models. What should we be looking for? How does it impact your world?

Michael Robbins: It's already had a tremendous impact and it will continue to do it, but I think the story is really changing. Machine learning and artificial intelligence are really just an evolution of statistics. If you're in the field, you recognize that there are just maybe a more powerful way to do statistics. Some of them are a little more removed than others. Large language models are very different from simple linear regressions, but it is an evolution and it will certainly affect everything. It's already pervasive even if you haven't noticed it yet. Netflix uses it to help you pick your movies. Certainly, most ads you have are generated by some form of AI. Spam filters have been using AI for decades. I think the fact that it's there and you might not even notice it is a testament to its power. But what I think is changing is that up until a little while ago, it was very hard to do those things for an amateur, and you're pretty much limited to simple statistics. Recently I think many amateurs can do it. You can download software, scikit-learn, or MATLAB has all sorts of packages. There's lots of different ways to use AI as an amateur, either for free or very close to free. Until a few months ago, I think they were pretty sophisticated relative to most of the other things that we've heard about in the news. There might be some secret things going on in government laboratories and hedge funds and things, but in terms of what was known in the public media, the free software was pretty powerful. But that's changing.

Open AI is becoming not open. There's all sorts of private models by Microsoft and all the other big companies. I'm sure the hedge funds have all their own secrets. At the university, I work with research partners who use these enormous computers, just the size of large buildings and quantum computers and all this technology that's absolutely not accessible to individuals. I think we are moving through a golden age of AI where amateurs can really do some very sophisticated stuff. This is kind of going the way of high-frequency trading where average people just can't compete and there'll only be a few entities with even the possibility of competing with each other. Every once in a while there'll be a tremendous breakthrough which can happen outside of those organizations and amateur could create a mathematical proof that just turns everything on its head. But that's really rare and hard to do. I think this idea of producing Alpha, this idea of outperforming the market is going to get further and further away from the average person. Even these little niches, these little opportunities that a lot of people don't look at, are going to be hoovered up by these machines that are so capable of doing so many things at once. It's a little bit dystopic but it's the way it seems to me right now.

Deidre Woollard: Is there still value for people to try to learn and try to understand investing with this idea that you've got this AI threat looming over us.

Michael Robbins: Well, yeah. I think there's still a lot of time before that happens from a personal standpoint. It's not going to happen overnight. But maybe in a generation, maybe the people in high school now won't have the opportunities we have to create investment returns. But right now there's a lot being left on the table. A lot of these machines are making some very obvious mistakes. I read an article about that game, Go with the Little Rocks, little board game and someone used AI not to create a strategy that beats the game but to identify the weaknesses in the other AI's strategy. It wasn't trying to find a way to win, it was trying to find a way to expose the obvious errors the competitor was making. It's a cat-and-mouse game. As we know from high-frequency trading, it really hasn't worked out like a lot of people would have thought it was. These high-frequency trading machines are not so brilliant because they're focusing on speed. They do some very simple trades but they do them very quickly. If you can think of something a little smarter, maybe that's another dimension where you can beat them even though they are faster than you. The same may be true with AI, at least for the next five or 10 years. Don't quote me on the time, I don't know, I'm not a futurist, but they're making plenty of mistakes now. Anybody who uses voice recognition on their phone knows how many mistakes their text messages have in them. There will be errors to capitalize on and in a lot of ways that's easier than finding investment opportunities. I'd rather find mistakes in an algorithm than try to find a good trade. There's less noise and randomness in it if you can identify a pattern. There are things that we can do. It's not going to turn overnight.

Deidre Woollard: Well, fantastic. Thank you. This was great. Really appreciate your time. The book is Quantitative Asset Management. As always, people on the program may have interest in the stocks they talk about and the Motley Fool may have formal recommendations for or against, so don't buy or sell stocks based solely on what you hear. I'm Deidre Woollard. Thanks for listening. We'll see you tomorrow.