Jay: Today’s show guest is John P. Reese, who is an ex-tech entrepreneur turned quant investor. John has developed computer models that are based on the published strategies of several world-famous financial investors including Warren Buffett, Peter Lynch, and Benjamin Graham. He’s also a frequent speaker, writer, columnist, and the founder of Validea Capital Management and also of Validea.com, a research website that allows visitors to use his screening tools to invest based off those same strategies used by Wall Street’s most successful investors.

John, welcome to the show.

John: Thanks very much, Jay.

Jay: I’m very excited to speak with you today because we run in some of the same circles. I’ve heard a lot about what you do, and I’ve listened to some of your prior interviews, and I’ve checked out your website multiple times. So, maybe you can give us a little bit of background because this is a podcast of both entrepreneurship and investing, so I think you have a unique background that the audience would appreciate and enjoy to hear.

John: Thank you. It starts, basically, I went to MIT to study computers and electronics. While I was there, I worked at MIT’s artificial intelligence laboratory. The key project that I was working on was taking human wisdom and knowledge that was in books and interpreting that so that computers could understand and actually process that information and come to the same decisions and conclusions. Many, many years later I would come back to use that key technology and technique.

I then went on to work in industry as an engineer. I was probably one of the first 100 engineers in the country to work with something called a microprocessor. This was back in the days of the Intel 4004 microprocessor. Of course, you know where that went.

I then went back for my MBA at Harvard Business School, specializing in finance and strategic planning and went out in the birth of the personal computer industries. This was happening right at that very time. We had the original TRS-80 and the Altair computer. I joined Texas Instruments for a secret project on their personal computers. Spent some time there. Then went on to GTE, a big telephone telecommunications firm which has now become Verizon. Then back into the personal computer field and electronic fields with Calico Electronics.

After that, I had the idea that “Hey, it would be possible to connect computers together, these little, unexpected computers.” If you tie enough of them together you can equal the power of a mainframe for 1/1000 of the price. So, I founded a company that specialized in networking at the very, very beginning of that, of connecting computers together. Grew that over nine years and sold them out to GE Capital.

That describes my time in the industry, my first round with entrepreneurship. Then I was looking at “How do I invest money?” I’ve always been interested, for a long time, in the stock market. I started reading and more reading and more reading until I was going through about 50 different periodicals and publications from Forbes, Fortune, Businessweek, and Wall Street Journal, and Money, and Smart Money, and many others researching, “Who should I listen to? How should I best make the decisions for investing the stock market?”

I went through almost a five-year research project on that. Along the way doing that, I was starting to read many of the great books by legendary investors, and one really stood out to me. There’s a light bulb that went off when I read Peter Lynch’s One Up on Wall Street.

Jay: Right. Classic.

John: So, here was somebody who basically, he grew his mutual funds to be the #1 biggest in the entire world, Magellan fund. He had a track record, and in the book, he was very descriptive of how he went about making the decisions of what stocks to invest in. Furthermore, that’s when that MIT Artificial Intelligence training came in. I was able to use those techniques and algorithms for interpreting the book and coming up with a computer model of how Peter Lynch basically says he goes about picking stocks.

I tried that, and that actually worked successfully over a very short period of time which is very, very encouraging. Although, as I’ve learned over the years, you can’t just use a short-term method, if it works over a short testing period, and believe that that will work successfully forever. But what I was kind of lucky about is I picked a strategy that already had a long-term successful track record to it.

That proved successful. So, I went on to another book that really impressed me which was The Intelligent Investor by Benjamin Graham. Benjamin Graham is considered the father of Value Investing. I was able to interpret his models, put that into a computer program. I then started publishing research of what I was doing on the internet. This is the time when the internet was just starting to take off. That caught on and eventually became the basis for a website, Validea.com, that offered an x-ray from 12 different legendary investors or investing techniques of any particular ticker symbol that you want to type in. And you would get my best interpretation of what the legendary guru said they used to figure out whether you should invest in a particular stock or not. It was highly educational and highly valuable as an investment tool. That’s where I came from.

My first attempt at networking as an entrepreneur resulted in the networking company, but then this accidental research in investing the stock market led to the launching of the second company or set of companies, Validea, as they exist today.

Jay: That’s an awesome background. Thank you for giving that. I think it’s pretty fascinating. There’s a couple of guys I’ve met that used to be tech entrepreneurs that are now full-time investors. I think from a challenged standpoint it’s probably one of the only other fields or areas that someone can just dive in and do a lot of self-study without having to go through necessarily formal schooling or education and get involved and probably have the same sort of challenges that tech gave you.

I think it’s pretty interesting how you came along in your journey to become an investor. I’m just curious. So, all the models that you—you mentioned that you were using some of your early AI models. That’s all proprietary stuff that you built and you adjusted based on the various books and methodologies that you read about from these gurus?

John: Yes. When I first did this at MIT there were techniques that we used to capture the wisdom within books. That’s what I essentially used as I read these books by the legendary guru investors.

Jay: Right. Okay. Those two books that you mentioned are obviously classics. I find it very interesting because I think many investors share the same journey that you did without the robustness and analytics behind it. It’s very easy for anyone to go and pick up a book from the bookstore and start their education that way. But, to actually aggregate all that together into a system, I don’t think many people have done it.

John: That’s true. By the way, I’ve met many people who have read quite a number of these books, but often that’s as far as they can take it. They’re very, very impressed when they find out that I’ve actually created a computer program that then implements the idea of that particular book so that they can apply that to any stock in the stock market that they want.

Jay: Yeah, that’s right. That exactly would be the same case for me because I’ve read many, many investing books and it’s kind of like when you read a book you try to pick one or two things that you can extract from it. You try to apply it, but there’s no methodology really when you’re implementing these things. So, I think it’s exciting.

Maybe we could just start with a little bit of an overview for those in the audience that aren’t familiar with quant investing or factor-based investing. How would you describe like a quant strategy or factor-based investing strategy versus a very simple fundamental-based investing strategy which, I think, a lot of equity investors lean towards?

John: There are some overlaps. Let me start by saying that quant or factor investing looks to identify groups of stocks that have certain characteristics. Some of those characteristics are technical or categorical in nature, such as if they’re a small-cap stock or momentum, but there are other factors that look at value.

Now, it’s interesting there are many ways of judging value, and that’s where there’s some overlap with fundamental-based investing. Fundamental-based investors may look at the income statement and balance sheet of particular companies and say that this particular company is priced to book ratio or priced to earnings ratio are very lowly valued compared to the overall market. They’re unpopular.

So, fundamental-based investing looks at a lot of accounting data over—well, it depends upon a period of time. It could be just quarterly, or it could be over several years and interprets that in particular ways and uses certain rules.

Quant or factor-based investing in some ways is simpler, but it looks to apply that to the entire stock market at any one time and find the best of those stocks according to that factor and the worst of those stocks according to factor. It will then buy those stocks long that are approved and, in many cases, they’ll sell the stocks short that are the worst over the list.

Basically, it’s based on some academic research for factor-based investing that have shown where the long-term pockets of outperformance of the markets can be found. Those are the factors, and that’s how I would describe the difference in the types of styles.

Jay: Part of it also, I think is a bit of a smoothing for the human emotion element, I think. We’ll talk about some of the qualitative criteria in a bit. I’m curious if you could explain what is your process in finding or identifying these gurus? You mentioned Peter Lynch and Benjamin Graham, and Warren Buffett. You have a handful of others. What was the process in which you identified and selected the gurus to model your data off of?

John: Sure. I had a few major criteria.

1.    I wanted to see a track record of outperforming the market. The actual tracker to be the person’s money-management background, or it could be an academic paper on it.
2.    The strategy had to be quantifiable in some nature. You couldn’t just say “You should hire good managers” and [inaudible] needs to be a good person.” There needs to be some detailed numbers that could be analyzed within that.
3.    The book had to be very clear in terms of how to actually apply the principles. Simply saying “buy low-P/E stocks,” which it makes a lot of sense, but what is meant by the… How low is low to cut off and qualify? And, earnings. Are you talking about future earnings? Past earnings? Earnings over one year? Earnings over 12 months? Earnings over the prior three years? Some authors and legendary investors were much more detailed and considerate than others when they came to actually spelling what they did and often included examples that illustrated that or further refined the points. Those were the three key criteria that I needed to identify somebody as qualified as a guru investor for us.

Jay: Is there one in particular that is your “favorite”? I know that’s kind of a loaded question.

John: Yeah. You’re asking me if I have like a favorite child, when I have kids of my own. There are different things about each that I like. One is I use a Warren Buffet model. I like him because he uses the longest data set. Of course, he has a great track record, a very patient investor. I also like the Graham model, again, because in some ways, it’s a very simple approach, and he finds really good values. But it’s hard to pick or identify just one as truly my favorite.

Jay: Yeah, that’s difficult. The criteria you were talking about, about track record, I think that’s so important, especially these days. A lot of fund managers nowadays, they’ll spin off from, say, another pedigreed firm, and then they’ll get seeded by a larger institutional investor or the likes of that. It’s hard because they’re in this position where they’re expected to outperform based off of their past performance, but you don’t necessarily know.

Then, a lot of times there’s—I think there’s a quote or some sort of saying in investing where it’s actually bad if you get everything right in the beginning because you end up growing this confidence and it’s less sustainable.

Let’s talk a little bit about the qualitative side of things. Some of the gurus that you follow and emulate have qualitative investment criteria. Can you give me an example of how you handle that aspect of some of their strategies in your quant models?

John: Sure. Maybe we can use Buffet as an example. Buffet likes to find companies with a competitive advantage. Or, one way of explaining that is that he wants to see a moat around a business. So, that is something that is actually hard to qualitatively judge. You could just look and subjectively say, “Such-and-such firm has a moat or competitive advantage” or the brand.

What we’ve actually found is that if this is true, these things actually show up in the numbers. Buffet handles this by using 10 years of, for instance, earnings. He likes to see 10 years of pretty much steadily increasing earnings with very few exceptions to that. So, that’s one of the signs that the company actually does have an identifiable moat or some sort of brand differentiation. He looks to see that the return on equity of the company is high. Again, if a company can return a higher capital than its peers, that is also an indication that there’s some sort of moat or protection that it has. So, a lot of these qualitative criteria actually come out within the financial criteria that they are known for. They actually go together.

Jay: Right. That’s pretty interesting as well. By just listening to the first part of this interview, it’s pretty clear that stocks selection is very, very difficult. It’s very involved. Screening, you know, people talk about stock screens. I do. I’m guilty of this as well. I’ll throw up some screens on Bloomberg and try to just screen out for X, Y, Z criteria. Then, see if I’ve found the next big winner and that sort of thing.

But it goes much deeper than that and I think that there is this sort of naivety in some investors or early/beginning investors that think that they can simply just pull up a couple of screens and be able to be a successful investor.

John: Yes, and I would add onto that—it’s very interesting, but many people start by something they hear. Like, “Buy low-P/Es…” How do they know that that is actually a successful strategy? They start with a disadvantage because they don’t really know. They start with some assumptions.

Second of all, how do they know that the strategy is one that will last for a long time through different kinds of stock market cycles? Again, most don’t know that, so they’re throwing little facts against the walls. They come up with a screen. It sounds good, but it’s not necessarily based on a long-term track record. If anything, I’ve found it’s very, very important to base this on long-term track records or long-term academic studies to identify where the key success factors in the market are.

Jay: That’s right. Absolutely right. When it comes to modeling your portfolios and they’re based off of the various gurus and the strategies, how do you deal with diversification, number of stocks, portfolio concentration, because people have different views on that as well?

John: Well, I think the research shows that an absolute minimum, you need 16 stocks to have a diversified portfolio, and that assumes that you intentionally select the stocks to be diversified with different industry groups. Typically, 20 to 30 is defined as the minimum. So, we like to see, at a minimum, portfolio sizes of 20 in order to receive diversification. But, even then, it’s very, very interesting. Since the main stock market average S&P 500 consists of 500 stocks, by definition, it is entirely possible and likely that there will be substantial periods of time where any 20-stock portfolio you have will be at variance, out of sync with the market. Now, hopefully, that’s out of sync in a positive way, but it could also be in a negative way, but there will be plenty of periods of time that way. One of the big problems with only a 20-stock portfolio is that the vast majority of people will then interpret when it’s underperforming as they’re doing something wrong and will exit the portfolio strategy. This is assuming they’ve chosen one that has a good long-term track record. That’s a very difficult human emotion to overcome.

Even though technically 16 to 20 is the minimum number you need for diversification, in reality, people need many, many more to avoid doing something very different than the index which will get them into emotional trouble.

 

Jay: Right. So, I think that’s also a very good point because even as you’re following—let’s say you were to follow these strategies, the DIY investor who basically doesn’t follow it widely, but basically thinks “Oh, I could trim this or I could add this, or I can rebalance this,” they actually end up hurting themselves. Right?

John: Very true because they don’t really know. They’re making some assumptions that it’s right, and the stock market, or what the stocks are invested in then, could turn and go down relative to their expectations. Or, the entire market could go down. The vast majority will react in the emotional manner, and at some point, they will exit from the market — usually at the worst point of time — and be afraid to actually get back in the market until the market is not only recovered, but it’s gone up by 100%.

Jay: Right. Let’s walk through some of the offers that you have at Validea. I’ve studied your website a bit. You obviously have the various portfolios. How many portfolios do you have now based on the gurus?

John: I have 12 public-facing portfolios and a number that I also maintain that’s private in my Capital Management Firm.

Jay: Right. Okay, so, you have the model portfolios and that’s—if I was just an investor that wanted to follow this model portfolio, is that just a subscription-based thing that I can access on your website?

John: Yes. That’s exactly what it is, a subscription-based thing. That’s the easiest way to follow it. Here, you’ve got a strategy with a good long-term track record and, assuming that you’re looking for long-term strategies, one could simply just follow the model. But, the other tool that’s also available by subscription is what I call Guru Analysis, which is the x-ray by 12 guru strategies for a  particular stock that you’re thinking about.  So, if you want to learn how to become a better stock picker or why we’re not Peter Lynch would like a particular stock that you’re thinking about, it’s extremely easy to get an answer that’s very easy to understand.

Jay: Right. So, in addition to that—actually, before we move on from that, is there one—which one of the strategies is the best performing?

John: As of the current time, interesting enough, it’s the one based on the Motley Fool small-capitalization stock strategy, has been outperforming, that looks at high-relative performance and looks for high-quality firms that are increasing its earnings, has quite a lot of other astringent criteria that it looks for. That has been blowing the doors off of many of the other strategies.

Jay: Wow, that’s pretty interesting. If I were an investor that would sign up for this service, it would basically be—I mean, you would basically lay out exactly the stocks that we need to be in and the rebalancing schedule. Is that right?

John: Yes, that’s correct.

Jay: That’s awesome. In addition to that, you mentioned you are running a fund as well that is emulating some of these strategies?

John: Well, two things. I do run, for higher-net-worth clients, private money that I’m able to blend the strategies together in a custom portfolio for them following an equity strategy. For clients or interested people who have a smaller amount of money to invest, I now have what’s known as a Digital Advisor or Robo-Advisor that is able to allocate not just in these stock market strategies but across several different assets, depending upon how aggressive or conservative they want to be. That’s an excellent way of managing money with very low fee structure.

Then, finally — what you’re sort of getting to — is an ETF, Electronically Retradeable Fund, that basically has 10 guru strategies, each picking 10 stocks. That’s available for somebody for as low as $30. They can buy one share of that and still get the guru-type of wisdom and advice.

Jay: Right. Okay. So, for the Robo-Advisor fund are there minimums there as well for an investor?

John: Yeah. The Robo, it’s about 25,000. That compares to—we have 250,000 minimum on a client’s side for asset management. But the Robo has a much lower minimum.

Jay: As far as just the DIY investor that wants to just follow one of your models with a subscription base, is there sort of an optimal, minimal portfolio size that you would recommend?

John: It can be done with even as little as $1,000 because, don’t forget, you are diversifying into at least 10, if not 20, different stocks. Now, there are different institutions or brokerage firms you can go where you can trade that low of stocks very economically, but you also have to allow for the cost of commissions and trading, so that makes it impractical for most people to have a smaller portfolio size than let’s say $1,000 in terms of following that. It would be much better in that case just to buy 1 share, or 10 shares, or 100 shares of the ETF.

Jay: That’s right. Yeah. That’s right. Okay. Cool. So, thanks for outlining that. So, the audience listening in, you have various levels of offering from John and his company. Depending on your amount that you want to invest and how hands-on you want to get… I would think that it would benefit anyway to try the DIY and following some of these strategies. I just think it’s interesting because you could learn a lot about the various gurus and how they model their strategies. But, I guess if you’re a lazier investor and just want to give John your money, he’ll take it too.

Great. So, John, I just have a couple of other bigger-picture questions for you as we look to wrap up. Thank you for your time. It’s been really interesting to hear about the work you’re doing there. My first question is based on me being based in Asia and looking at emerging markets. The U.S. markets are quite overvalued by a lot of metrics, by a lot of measures. How do you feel about international stocks, EM? Are there any of your portfolios that actually include them at this point?

John: Yes, we do. We agree there are a number of influential investors, including Jeremy Grantham that are really making a case for international stocks right now, particularly emerging markets. The CAPE ratios which is one very long-term measurement that we use for indicating over evaluation shows the U.S. market has been overvalued for some time now, but the international markets are undervalued. So yeah, we’re big believers that there are opportunities now in international.

Yes, the models do find international stocks. Basically, they use the stocks that are listed as ADRs on U.S. Stock Exchange. We’ve done that so it has the best financial data, but there are many hundreds of stocks that go through these same models that get compared to American stocks. So, when they show great evaluation characteristics and pass the models of gurus, they are also selected. They come out as part of the models.

Jay: Yeah, I think I just saw that. Grantham put out his seven-year outlook or something. It was a little bit bearish on U.S. and definitely more bullish on EM. Second to the last-ish question for you, John: as someone with a deep background in tech and AI, you seem to be the pioneer because AI now is very buzzy. You hear about it all the time, but you were working on AI decades ago. Is there anything in that space, the tech world, that really excites you right now, whether it’s AI or blockchain or any of these emerging technologies?

John: So, you’re asking for technologies as compared to stocks. No, actually I may be in the minority. I’m not impressed by blockchain. To me, it is another form of database that has particular characteristics with some advantages and disadvantages. One of the advantages at the current time, if you can process five transactions a second and out in the real world you need 100,000 transactions a second, it still has quite a way to go.

AI, particularly the recent learning modules as technologies have a lot of breakthroughs. Even just a few years ago, there was no belief that even with AI, computers would be able to autonomously drive cars. Now, look. Truly, they can. So, there’s a lot of excitement around that. At the same time, I’m not over-optimistic when you specifically apply it to the stock market, because there’s a lot of variability that it still can’t play against. The best thing it’s got going for it is its still unemotional and disciplined, investing in it the same mental patterns that humans do.

Obviously, in the biotechnology areas, there are a lot of exciting things that are coming through. They still have 10-year life cycles to go  through to prove them out for their safety and efficacy. But, a lot of things are coming out on the horizon to improve people’s comfort and quality of life and length of life.

Jay: Right. Those are great insights. Finally, as far as your goals for Validea or personally or profession, is there anything that you’re working on that you’re excited about that you want to share with the audience? Is the guru list locked, or is there constant search for potentially adding more to that list?

John: I have added more and kept track of more behind-the-curtain, and we’re up to over 40 different models. So, we do keep our eyes out for it, and as academics come up with new factors and ways of combining those factors, we do keep our eyes on those particular models. But, our particular goals for this year are to continue to really get out and educate people on what we’ve developed and created here and what we believe in and how to become the best and most successful long-term investors and how to use these key, proven factors in disciplined and unemotional manners. Those are our goals that we continue to put forth and to innovate on.

Jay: Fantastic. It’s been an engaging discussion, John. Thank you so much for your time and walking us through the exciting stuff that you’re doing over at Validea. Where is the best place that people can find you or follow you or connect with you or maybe learn a little bit more about what you guys are working on there?

John: I’m on Twitter at @GuruInvestor. Our research website is at Validea.com spelled v-a-l-i-d-e-a.com. From there, you can also link to the money management site at ValideaCapital.com.

Jay: Right. Got it. So, we’ll get that all linked up in the show notes. Thanks again, John. It was great catching up with you and we look forward to following your work in the future.

John: Jay, thanks for having me on.

Jay: All right. Take care.