Episodes

Dan Ferris:                 Hello and welcome to the Stansberry Investor Hour. I'm Dan Ferris. I'm the editor of Extreme Value and The Ferris Report, both published by Stansberry Research.

Corey McLaughlin:    And I’m Corey McLaughlin, editor of the Stansberry Daily Digest. Today we talk with Keith Kaplan, CEO of our corporate affiliate, TradeSmith.

Dan Ferris:                 Keith is our finance-technology guru. He's forgotten more about this than I will ever know. Normally we talk about TradeStops, trailing stops, and how TradeStops helps you use trailing stops. But this time we're going to talk about something completely different − a tool that Keith's firm has recently upgraded and he has a lot to say about it. And there's a lot of technical stuff here. So get out your pen and paper and take some notes, all right? So let's do it right now. Let's talk with Keith Kaplan. Let's do it right now.

Corey McLaughlin:    For the last 25 years, Dan Ferris has predicted nearly every financial and political crisis in America, including the collapse of Lehman Brothers in 2008 And the peak of the Nasdaq in 2021. Now he has a new major announcement about a crisis that could soon threaten the U.S. economy and could soon bankrupt millions of citizens. As he puts it, "There is something happening in this country, something much bigger than you may yet realize, and millions are about to be blindsided unless they take the right steps now."

Find out what's coming and how to protect your portfolio by going to www.americandarkday.com and sign up for his free report. The last time the U.S. economy looked like this, stocks didn't move for 16 years and many investors lost 80% of their wealth. Learn the steps you can take right away to protect and potentially grow your holdings many times over at www.americandarkday.com.

[music plays and stops]

Dan Ferris:                 Keith, welcome back to the show. Good to see you again, as always.

Keith Kaplan:             Great to see you. Thank you so much.

Dan Ferris:                 So lot’s changed since May of 2022, the last time we spoke with you. Including that I have a cohost now [laughs].

Corey McLaughlin:    Howdy.

Keith Kaplan:             Hi, Corey.

Dan Ferris:                 That's right.

                                    So, you know, we're going to tag team here. But usually when you come on, of course we talk about TradeStops. Right? This is, you know, an automated way to use trailing stops – and much more, of course. And I recommend most people use it, not because trailing stops are going to help your returns so much over time – because they're not.

But what they're going to help you do is avoid selling out at bottoms in a sort of catastrophic, you know, panicky – in a panic leading to a catastrophic loss is what I mean to say. But today – and Keith, you're one of the few people – the list is growing but it's still a very small list of people who can call me up and say, "There's something I need to talk about so please let me come on the podcast," and I’ll say, "Oh, OK."

But you have something specific on your mind. And it sounds pretty interesting because it's a type of trading tool based on seasonality, which is not something I know or do. But I know lots of folks who keep statistics and have strategies based on this. And I am – I know nothing about this, this new tool that you've developed. I can't wait to find out, though. It sounds fascinating to me. So maybe we can just dive in and start there.

Keith Kaplan:             Yes, let's do it. You know, it's funny because when I think back to the past couple of years, at TradeSmith, we’ve been building a lot of different software. We have analysts that have joined our teams and they partner with the software as well to help our customers really succeed. And we've been thinking back, you know, over the years and sort of realized that a lot of us have taken an approach where we get worried about the market in the short term, don't want to go long, you know, baskets of stocks, and we want to figure out ways to generate income as we go.

Typically, we're looking at income with selling puts and selling covered calls, you know, to generate that income. And what we have started to coin over the past couple of years is that there's ways to leverage stocks and short-term moves as long as there are a lot they are a lot more predictable to trade in and out of stocks – especially stocks that are great stocks to own anyway – and generate income. And so a lot of people think, "Oh, you know, short-term gains – you know, capital gains and all that."

And that's exactly what we're doing. But we're trying to totally outpace the market when doing that. And a couple years ago, we started to really get heavy into seasonality. And it was a fascination my thinking about things like that Santa Claus rally that we hear so much. You know? We know about the January effect when all these funds and retail investors are buying in.

We know that Black Friday helps us to fuel hopefully really good sales that gets people euphoric about the stock market and future returns. We know that a lot of times we see sales dip in different companies in January, February, and March, and that impacts the earnings releases that you see in late April to May and hear "Sell in May, go away." We think about the time – it’s always sometime in August. I always feel people get very bearish and we see a lot of drops when you historically look back.

And I always jokingly say, "That’s because parents are sending their kids back to school. There's routines that have to come into play. They have to get up early. It's not fun − or they've got to pay for college. So they're selling their stocks." But we have these patterns that just happen over and over in the markets. And about two years ago, we started to really focus on those repeatable patterns and figure out the ways that we want to visualize those patterns on individual stocks and ETFs out there.

And so, we were buying a ton of data. We're going through all this data and we're figuring out there are certain times you can look at this and say, "I think I'm going to buy that stock." And a good example of that was mid-May last year, in 2024. I was walking around the office, and I was saying, "Who's going to buy Tesla with me?" And every person that would analyze Tesla would say, "Not me." Because fundamentally it was not and it still is not – it gets a whole lot of benefit from, you know, what’s happened with the election but it’s fundamentally a terrible stock for you to buy.

And so, I was one of the only people that bought Tesla mid-May and then sold it in the beginning of July and I had a 50% return because I just looked at the seasonality window that 100% of the time the last 14 years Tesla has gone up. And so, that's sort of like a simple way to think about seasonality, is we have the market seasonality and then we have individual stocks and ETFs that behave in a certain way. We don’t always know why but they repeatedly behave in a certain way. So that was just sort of the beginning of the whole seasonality journey.

Dan Ferris:                 You know, the effects that you describe are so simple one would have thought they'd have been arbed out a long time ago. I mean, it's fascinating that they're not.

Keith Kaplan:             Yeah. And a lot of people will sell you seasonality type of data. But the thing is that you're talking about stocks that change multiple times a day. I mean, infinitely – an infinite amount of times a day, but have closing prices. You have tons of stocks. I think we have 50,000 different securities in our systems − so that's stocks, bonds – everything. And they have all these movements.

But then you have to go and you have to have massive data warehouses and be able to program in a way to determine the patterns that are repeating every year. And by the way, those patterns will change over time. And so, you have to keep continually updating that data and patterns and reprogram them to make sure you're always nailing true seasonality periods for a stock or a fund.

Dan Ferris:                 That's interesting. So there may be an effect associated with a particular month or season, you know, time of the year but the effect could change over time, you're telling me. That is fascinating –

Keith Kaplan:             Absolutely.

Dan Ferris:                 And yet you’re implying to me that you can still – let's say we're looking at, you know, Tesla in May and June as you described. You know, what you're telling me sounds like, "Well, one day the effect might become, you know, neutral or bearish, but for right now it's bullish." That's what I'm hearing.

Keith Kaplan:             Correct. Correct. And so – and there's even – with U.S. presidential elections, certain stocks behave differently leading up to [the] election or postelection than they would during the other three years. So we pick up those sorts of seasonality periods. We look at stocks since their inception. So Johnson & Johnson I think is 60 or 70 years, and we'll look at it since its inception and find seasonality periods that go all the way back.

But then we might want to just look at what I call the modern era, which is after, you know, really the Y2K sort of time frame and look at how stocks are performing then. And so, with our system we do a generic 15-year look-back on every stock, but you can customize that to any sort of look-back you would like. All of its history, part of its history, whatever. Or election years.

And we've learned that over time, you have a nice, significant edge when you have an 80% pattern repetition over time. So earlier this year, I think it was February, I had presented to one of our private meetings – you guys have – oh, it's the Stansberry Editor Conference. We have what we call as our big idea conference. So it's pretty much the same thing. And to be honest, we learned it from you. Because I’ve attended many of yours that have been great.

And so, one of the things that I presented to our team was, "I want to build a portfolio that has stocks – just stocks – rotating in and out. I want them to be high-quality stocks. And I want them to rotate in and out during their seasonality periods, the optimal period. And I want to see us have a win rate of at least 80% and I want them to be very short-term gains, I want to target 5% gains but I want to win at least 80% of the time."

Dan Ferris:                 Wow. I’m going to stop you right there because folks who – you know, like market wizards, serious traders would say, "Eighty-percent? You're nuts." So that's ambitious. I mean, some of those guys are like 40% and they're crushing it, you know, less than half the time and they're still winning because they, you know they stick to their winners and they cut their losers short. But, you know, please continue, but wow.

Keith Kaplan:             Yes. So as you would expect, lots of laughs. Lots of people saying, “That's not possible.” But multiple people saying, “Hey. Something a lot lower. You know, 50% to 60%, you can have an incredible edge if you position size right, if you manage the entries and exits right, and so forth." And it's like, yes, I know all this. But what you guys don’t realize is we have the most sophisticated data-research team that you could possibly have for any retail shop out there.

I would put our team against any retail shop. Maybe not the hedge funds but any retail shop. And so, you know, to me it's like I love that sort of challenge. And we went to the drawing board and my initial thought was, “Let's pick the best stocks in the universe of stocks, the highest-quality companies, and let's go back 15 years. Any stock that has had a 100% win rate over any period of time will go into this portfolio. And we're going to test that.”

Now, here’s the key about our testing. A lot of people do what I call curve-fit testing. They already know what happened and they start to study what’s happened and they start to pick the stocks that have had returns and then they look at those and they say, “OK. This is my win rate. This is how I performed,” and so forth. What we did was wildly different.

We went all the way back and started at 2006. And then we looked at 15 years of data prior. And we judged those 15 years, and we automated the entire process, and we asked it to tell us which stocks to trade to trade in and out of the next year based on a 100% historical win rates. Then we said, “Now it’s 2007. Go back 15 years, do the same thing.” And we built this portfolio over 18 years with a starting look back of 15 years prior. That portfolio won just above 60% of the time.

And I’ll be honest with you. It took us five weeks to get the testing and get all of that set up, and I could not have been more deflated. Because I wanted to win four out of five times, not three out of five. And the key with that – you guys know how customers behave. People, they don't take every trade you would make; they cherry pick. And that's fine, but if they cherry pick only winners, that's great. But if they cherry pick only losers, that’s awful.

Dan Ferris:                 And they'll blame your system. It's crazy. They'll blame your system even though you're doing like 60% winners or something. It's crazy.

Keith Kaplan:             Exactly. And I was so excited about this product I wanted to release it early last summer. And so, here I'm thinking to myself, “I feel so let down but we're not going to do it. Let's figure this out.” So I worked with the team. We basically had all hands on deck for about four months of time. And we started to run testing after testing. The first test that was finally starting to get significant only took us one day. In the end, we ran something like 2.24 quintillion tests. Now, remember, this is six months ago.

So what did we do as a software company? We built software to go and look at optimal seasonality periods, we built the software in a way where it could continually just test permutation after permutation, factor after factor, and tied that along with seasonality, to find the optimal windows to trade in. And we got to the point where we were running 50,000 tests in a day, then 100,000 tests in a day. And all we had to do was write a program to interpret the results of the test to figure out which results we were looking at.

And so, we tried to pull out all human bias. We pulled out all bias on the back testing. There was no curve fitting. And we looked at, “How can we get this thing to above 80%? And we're not stopping until we figure it out.” And the craziest thing was it ended up just being two different things we had to look at. No. 1 is, for every stock in our system, we had to build an algorithm – and we automated all of this. We had to build an algorithm to find what we call the most optimal seasonality period out there.

So it's not always going to be 80%. It might not be 100%. Maybe it's 92%. We were asking the system to tailor this for every stock and find when seasonality has X-percent of a win rate over historical 15 years prior for the next year, “How did it perform where was the place where it won the most?” Then we looked at every technical factor you can imagine, and it turned out that there was a custom RSI (relative strength index) value that we can associate with each one of those stocks.

But again, it’s custom for every stock. Apple − RSI might need to be above 60. Tesla − RSI might need to be below 40. And so we figured out, “What is the optimal combination over 15 prior years to get us to a much more successful win rate?” In the end – I'm going to pull up numbers so I don't misquote this. The team gets upset, and they should, if I misquote these numbers. In the end we got to an 82.83% win rate. So more than 4 out of 5 winners.

Our median trade was about 6%. Our days held was, on average, 15 trading days. So that's about 3 weeks to get that. And we turned $10,000 into $85,700 over 18 years. So that's an 857% return over 18 years. Now, here's a really important point about that. Most portfolios are managed in what we call rolling gains. If you start out with $100,000 and you get to $200,000, you don't go back to 100.

Because we wanted to make sure we were as conservative as possible with the testing, our legal folks were happy – you guys know what that's like – we actually kept starting with just $10,000 every year. We never – when we won – rolled it. We always started with the same amount to get to our win. So the bucket of wins was a lot higher if you would have done even normal portfolio management and just managed your capital as you typically would than what we even put out. And so, you know, for us it was just a – I mean, it was such a magical moment −

Dan Ferris:                 Wait a minute. Wait a minute, Keith. I want to make sure I understand that point about –

Keith Kaplan:             I know. I get so excited –

Dan Ferris:                 No, it's OK. It's OK. So are you saying that you started with $10,000 15 times and the total gains were 80-something?

Keith Kaplan:             We start basically started with – I should have clarified. I'm sorry. We started with $10,000. We never added more money to it. So we basically started with $10,000, we did equal-weighted positions across the board, throughout the year, and we had typically 30 to 50 trades. It depended on how much movement we got and what the algorithm said. And we turned that initial $10,000 into $85,700.

Dan Ferris:                 OK. But I don't understand the point about rolling. And not rolling. I mean, if you start with $10,000 and you make, you know, 10% then, you know, you've got 10,000 plus – $11,000 at the end of the first year.

Keith Kaplan:             Right, you have $11,000. We then don't use $11,000, we keep using only $10,000. We put all the winnings into a bucket and we never touch them.

Dan Ferris:                 OK. I see. And you wind up at the end of 15 years with...?

Keith Kaplan:             We start with $10,000. We end up with $85,700.

Dan Ferris:                 OK.

Corey McLaughlin:    So you're not compounding the gains.

Keith Kaplan:             We're not compounding the gains. Correct.

Dan Ferris:                 Interesting. So if you did compound, you'd be through the roof.

Keith Kaplan:             Yeah. I forget what the chart was when we first looked at it − when I first saw it. And actually, when I first saw it just winning 60% of the time, it was incredible. But it didn't meet what our criteria was for the seasonality piece, for the portfolio. And so, you know, when we kind of started going further and we started working with legal and “How are we going to tell our customers about this? What is OK to say, what's not OK to say?” You know, they were like, “We don't want you compounding gains. We don't want you rolling those gains into further gains.”

You know, my argument is that “Hey, that's portfolio management.” But at the same time, I didn't care. Because this system was so phenomenal in the way we built it and how hard we worked on it and the results, that it was like, “These gains are great. Who wouldn't want to take these gains?”

Dan Ferris:                 It sounds to me though – when you say you started with $10,000 at the beginning of 15 years, I mean, it sounds like you're investing $150,000 and making $80,000. It doesn't sound to me like – you know what I'm saying?

Keith Kaplan:             No. Yeah, I see what you're saying. So you start with $10,000. Let's say it ends up being $20,000. You take – you use that same $10,000 but the other $10,000 goes away into a bucket. You've never put in more capital out of your bucket than $10,000 initially.

Dan Ferris:                 No, I get it. You’re starting with the same – it's the same $10,000 is the reason I'm wrong.

Keith Kaplan:             Correct.

Dan Ferris:                 OK. Wow. OK [laughs]. You know, now that we got all that taken care of, wow.

Corey McLaughlin:    Yeah. But I mean 80%-plus win rate. And I think what people – we've talk about this with the market-wizards people and technology too. Just having to keep up with the advances in technology and I think – and tools that people need, or feel like they need. And for like a short-term trader that seems like, you know, “Why would you not want to try this?”

Keith Kaplan:             Yeah, absolutely.

Dan Ferris:                 So, I have to ask certain questions. One of them is, testing is great – and you've obviously done more testing than, you know − you're just doing quadrillions of tests. I mean, that's a lot of testing. Testing is great but it is not trading is it, Keith? I mean, it is –

Keith Kaplan:             Correct.

Dan Ferris:                 Trading involves – whether you like it or not − it involves human emotion. And you’ve really got to stick to that system and just treat it like a machine to be able to expect a similar result, right?

Keith Kaplan:             Exactly. So what we do in our system yes, we start with 50 top stocks that our system has identified for the year. We have optimal entry and exit points that you can see on a , that are predictable, and the only thing that tells you whether you've entered it or not is that custom RSI feature that says enter or not. Then we have a very specific exit date that you will get an alert for.

So you get the alert to enter, you get the alert to exit. And then we have an analyst who does a write-up on why the system picked that and tells you to stick to the entry and exit no matter what happens. And so, that's where the human bias has to totally be, throwing out the window, is you can't break the way the system is going to tell you to trade it.

Every time we tried, by the way – when people say, “Oh, we should put this certain trailing stop up. Could we get 10% average gains,” and it's like, “No. The system couldn't find that.” You know? We can get 6% average gains. That's wins and losses. And so, you have to follow the system. You have to trade it the way the system is telling you to trade. The whole reason it’s optimal is because that's what the system has identified.

Dan Ferris:                 Right. And to be clear you're talking about an average of 6% in three weeks, right?

Keith Kaplan:             Correct. Correct.

Dan Ferris:                 So it's kind of – you know, annualized it's through the roof. It's enormous.

Keith Kaplan:             Correct. It was well over 100% annualized.

Dan Ferris:                 So wow. You know, again. And it sounds like – so, you know, with the typical newsletter, like what I write and like what a lot of people do – I basically send you a story, a write-up, a report, with all the reasons why I think, you know, company XYZ is a good bet. At the end I say, “buy company XYZ,” and that's what you get each month. What you get here sounds different. It sounds – I’m not totally clear on it but is there a level of interactivity or are you just being told – or is there just lots of information about when a trade comes in? Like, what's my interaction as the consumer of this tool?

Keith Kaplan:             All right, great question. So, there’s a couple different sort of interactions. There is the "let the tool fish for you," which includes an analyst behind the scenes who we really, you know, think of it as a sort of – he's your Sherpa to get you through it, right? Or do you want to fish for yourself, or do you want a combination of both? So for starters, this seasonality portfolio and all of the seasonality – all the different screens that we have in the system – are all part of our product that we call Trade Cycles.

And we have an analyst that's sort of at the helm of that. And he is looking at broad market things that are happening with seasonality and cycles, and also other, you know, different factors that he tracks, and giving you write-ups weekly about that. He then has trades that he favors personally. Kind of what you guys would typically have but not from a fundamental perspective − he's looking at short-term gains based on different cyclical patterns, based on different technical factors and so forth.

But then he's helping us to sort of Sherpa through this portfolio of trades where he's telling you why this system picked the trade and the entry point and an exit point once you've entered. And so, you sort of get it all, or you can go into the system and find your own and develop your own portfolio of trades based on this trading in and out. So somebody could even look at your portfolio, Dan, and say, “OK. Do I want to get into that stock now? Is this an optimal time seasonality wise? Because I'm not ready to buy a stock for the long term that Dan recommended, but I like it fundamentally because of Dan.”

So you can sort of do everything with this. You can wait for the analyst to do the write-up and tell you exactly which stocks to enter and why, which will all be technical reasons, and when to exit them, which will be technical reasons. You can look at his specific trades over the whole market. He does a lot with the QQQs, SPY and so forth. Or you can sort of dive in and look in the system and develop your own type of trades. You can look at Apple and say, “Is this the time of year I should be buying Apple?”

Corey McLaughlin:    Cool. Yeah I was going to ask you about the overall market too, applying this to the overall market. It seems like that would be something you can do and maybe you should do as well. What have you found in terms of seasonality in say the S&P 500 or the QQQs, just like something that – I don't know, an observation that you guys have discovered?

Keith Kaplan:             Yeah.  It's funny. When I was looking at these sort of patterns about a year ago with our analysts, it was so obvious. Like, the whole – every single August he's looking at the market, comparing its seasonality to the August before, and it was very specifically around August 15. And he’s seeing, “Is it the same setup every single year?” And almost always has been. And so, he'll do these write-ups that talk about 93% of the time over the last 85 years – I just made up those two numbers but it's something like that – the QQQs have dropped 5% or more August 15 through whatever the time frame is.

Right? And so, he'll then issue you a trade. You could – you know, you can just basically buy the inverse of the QQQs or you could do an options trade. You could buy a put on QQQs and so forth. And so, he'll issue a trade with all of this fascinating explanation. He does way better than I could ever do explaining that.

Talking about that sort of cyclicality in the QQQs mid-August. And we saw it for the election. He had a really cool write-up for the election around the S&P 500, Dow, and Nasdaq. He did a great piece in December talking about why we're going to be in a rally. So it's really fascinating the way he pulls everything together at a high level.

Dan Ferris:                 Yeah, that is cool.

Corey McLaughlin:    And do you care about the reason why, you know, in August? Or were you able to link anything together or does it not matter?

Keith Kaplan:             It really doesn't matter. A pattern is a pattern. You know? And so, if the market is sort of overbought at that time frame and it does the same thing every year when it's overbought, you can sort of bet that it's going to go down.

Dan Ferris:                 Keith, to what extent – obviously a lot of people do this sort of thing. The folks at Renaissance Technologies who made like 80% a year for 20 years do a lot of this type of stuff too. To what extent do you think it's a valid observation or not? I don't know because I'm not in the data the way you are. But do you think that there's a chance that, like, looking at this history and imputing these probabilities, something feels a little bit odd about that to me.

It feels to me like, “Well, this happened for the last 15 years 100% of the time.” And the first thing I started to think of was, “Well, 15 years doesn't seem like a long period of time to me.” And the second thing is just, well – because it has happened several times over the last 15, 20, 30 years and we're admitting we don't know, like – we don't know why these things happen. It feels like – it's like we have faith in markets or something. You know? We have a belief that they just behave a certain way because, you know – we don't really know. I'm having trouble formulating a question but it all feels a little funny to me.

Keith Kaplan:             Yeah, I totally get it. Let me tell you why it feels funny to me too. When we first started to hop into this all of this data, it seemed so obvious that if something happens repeatedly, it's likely to happen again. And we found it's only true 6 out of 10 times. And that to me felt like a failure. And so, you're basically saying, “OK. This happened 100% of the time,” but then going forward it only happened 60% of the time this year.

And that right in and of itself says exactly what you're saying, Dan. It feels really odd to me that we would trust 15 years of data to say something's going to happen, why would it happen again? When you start to study every single individual factor that's out there and combinations of all – and that's how we got to the 2.24 quintillion tests. When you start to study all that, which was automated, just wanted to remind you – because we can’t physically study all that.

Dan Ferris:                 Quintillion – I said merely quadrillion. Quintillion, sorry.

Keith Kaplan:             Yeah. And you would tell you which one’s higher.

Dan Ferris:                 I know.

Corey McLaughlin:    Me neither.

Keith Kaplan:             Once we got to a billion I said, “I'm sort of set. You know, I think we've done enough.” And the best result was way earlier. You just have to go through all the permutations to figure out what's the right way to do it. What we found was that the RSI was the simplest way – the 14-day relative strength index was the simplest way to understand if you should confirm a seasonality period for an individual stock, any fund, the market, whatever it might be.

And it was rare. You know, 1 out of 5 times rare. Maybe that's not the right word. But it wasn't often that it would buck the trend. And so, when you think about something like the QQQs dropping mid-August every single year, you can look at the other technical factors to say, “Why was it that they were dropping in that period Of time?” It's not just that there's a seasonal thing. There’s got to be something about August. I don't know if people are in a funk at the end of August. I don’t know what it is. There's something about August that causes that – just like people are excited in December. It causes that. Right?

But the reality is, were more people are buying stocks or selling stocks at that period of time and what was the rate of change? We look at that rate of change. So if you're "overbought," you know – everybody's bought the stocks and people start selling and they're going to be selling more aggressively – you're just pushing the stock prices down. You're pushing the index down. And so, it's really the combination of factors. It’s not just seasonality but it's that combination of factors that gives us the confidence to say, “OK. Is this a period of time that we want to write about where we want to make a trade?"

Dan Ferris:                 So it ultimately – I think the – whatever my question was I couldn't formulate it. But whatever [laughs] it is, it's just a funny feeling. Ultimately what you're telling me is that you’ve just studied enough data and run so many, you know, quintillion of tests that you are very comfortable imputing these probabilities and, gosh darn it, they’ve worked during the periods you've tested. So why wouldn't you trade them? Why wouldn't we?

Keith Kaplan:             Exactly.

Dan Ferris:                 And I'm not saying I know anything, by the way. I'm just admitting ignorance here because I don't operate in this quant world that you guys operate in. I mean, I use various mathematics of some sort – you know, arithmetic mostly, but it's in a different way. It's about fundamentals. It’s not about, you know, price action and time as it is with you.

So it fascinates me when people like you – when I get someone like you, it's like I've got to hit you from every angle so I can try to understand what the hell's going on. But I want to get back – I'm going to get back to the interaction between me as a consumer of the tool and what – you know, what I get – how often – If I am a Trade Cycles subscriber, how often do I − I can interact with this tool anytime I want or do I hear from you periodically, like weekly or something?

Keith Kaplan:             All right. The answer is all of the above.

Dan Ferris:                 I thought so.

Keith Kaplan:             Yeah. You can log into our system, you can look at every single stock and fund that we cover that we have – well, you can look at every stock that we cover. But you can then drill down to see which ones have seasonality data, which is most. And then, you can go and look at each of these periods of time and just select them. And you can see what's happened in the past.

And if the system is saying this is an optimal time to trade – because it's not always optimal as I was telling you guys earlier. So you can do all of that on your own. You can set up what we call watch lists and you can get alerts on those stocks. You can get alerts to trade in and out, you can do all of that on your own.

You can take the total opposite approach, or a hybrid approach, and you can just wait for us to send you weekly updates. [In] those weekly updates, we’ll talk about the markets, what's happening in the markets, why it's happening. And it'll be mostly from a technical perspective but with some flavor about what's impacting and driving those technical factors.

Dan Ferris:                 OK. My next question –

Keith Kaplan:             From there –

Dan Ferris:                 Before you go any further I just wanted to ask you, Keith. Whether I'm, you know, just sort of self-directed or, you know, waiting for you or hybrid as you're describing, is that all the same subscription or am I at different levels?

Keith Kaplan:             All the same – this is what I think is probably going to be the most confusing for people. This is all the same subscription. No levels. We wanted this to cover everything. This is our cycles, trading product that's focused heavily on seasonality.

Dan Ferris:                 So like one price, one subscription and this – I can do it any way I want? That is cool.

Keith Kaplan:             Exactly.

Dan Ferris:                 I like that.

Keith Kaplan:             And I think – I would bet the majority of people would do the hybrid. We’re going to be issuing trades. Sometimes those trades will be more broad-market-type trades. Like, “Buy this put on the QQQs,” or “Go long on this QQQ fund in August.” Right? A lot of times it'll be a very specific trade. Our analyst loves oil trades. He does very specific trades on oil based on its cyclicality and what's happening in the oil markets. But then he will be telling you about the automated trades that the portfolio is spitting out. My only role for him is, you don't mess with the automated trades. We did so much testing –

Dan Ferris:                 Very good.

Keith Kaplan:             He’s not allowed to mess with the automated trades. So if you think about – maybe we should break it down into three ways. We have the analyst focused on weekly updates and his own specific trades with information that you can make. Sometimes it’s one trade a month, sometimes it's four. It depends on that month and what's happening.

Then there's the automated portfolio of trades that his job is to relay to you everything that's happening and why and tell you what the system is telling you what to do − but not alter it, no matter what he thinks. Then the third way is, you can log in, you can look at any stock or fund you want, you can build your own portfolio of these things and you can get your own alerts and do it however you want. And what people I think will do is a combination of all three.

Dan Ferris:                 Yeah. I think that sounds – I think you're right. Everybody wants to tinker with the system themselves but they want to know what the guy who created the system has to say.

Keith Kaplan:             Exactly.

Dan Ferris:                 And the point about making darn sure that this guy does not mess with the system – “Don't mess with the system” – that’s so important. Every now and then tell the story about this is one of the TurtleTraders and having them show me one of the outputs. You know, a trade that was output by their system and having them say, “But I don't really want to do it.” I thought, “What? You don't really want to do it?” So, you know, I was like, “So they told me there was no discretion but there is discretion.” But you're saying no discretion, trade the system, period. And I love that, because that makes sense. Because once you get to the discretion, you get to the emotion, right?

Keith Kaplan:             Yes. And we have one more layer of this big Thanksgiving dinner that I haven't told you about. This is the gravy. For probably 20 years I've been one of those people that – I wouldn't say I'm scared, but I didn't believe in buying calls and buying puts. I believed in selling them for income. I believe most of them expire worthless. I think there's a whole – you know, incredible time-value principle that you can sell very short-term puts that expire worthless – let's say in a week to two – and make a lot of money over time.

We developed an entire system around this called the Options 360 that’s been live for four years with a 95% win rate. So I know, tried and true, the way that you collect income or trade options is by shooting for income. When we got to the point where we had an 82-point whatever – hold on. We had an 82.83% win rate. The head of my research team who has worked at funds before said, “I think it's time for us to build a call buying strategy.”

And I said, “No way.” And he said “Keith.” He said, “Listen. When you have a short-term gain like that and your average returns are even just 2% or 3%, if we can get you the call at the right strike price for the right amount of money, you can make 100% to 200% to 300% in that short 15-day period of time. We have to time the entries and exits of the call buying to that stock seasonality period and we have to have a certain window of time post the seasonality period where the actual option would expire.”

And so, I sent him on a mission to prove that he was right and I was wrong. What he came back with was – he developed an algorithm. We have 16 years of options data that we could test through. And as you guys can imagine, one stock can have a billion rows of options data for 60 years because we have every – you know, we have every price interval… it's crazy.

Dan Ferris:                 Every strike, every expiration. It's just – it's insane.

Keith Kaplan:             Oh, my gosh. Yeah. And the interval changes so much during the day. You can't even take averages. You can't even sit there and say, “This was $1 this day, it was $2 this day.” I mean, it’s like it could be –

Corey McLaughlin:    You could spend your whole life doing that, yeah.

Keith Kaplan:             It could be $1 at 10 a.m., it could be $5 at 11, and then like pennies at, you know, the close. So he was able to develop an algorithm – and again, this is custom for every single stock – to find the most optimal call to buy. He had a 60% win rate. Now, that does not mean that 40% of them expired worthless. Even if they lost 1%, it's still a loss. Sixty percent win rate turning turned $1000 into quarter of a million dollars over 16 years.

So I don't know what the – I think it's like 25,000% return or something like that. He started with just $1,000 and never once dipped back into his pockets to get money. He started with just $1,000, put all the winnings into a bucket. If he ever lost that money he pulled it out of the bucket of wins. No rolling. $1,000 into one quarter of a million over 16 years. So what we do in our system is, every time we trigger a buy of a stock based on the optimal seasonality period with the optimal RSI for that stock, we will tell you a call option you could buy as well.

And these call options hopefully are just, you know, $100 less than a couple hundred bucks. And it's a way for you to get some serious sort of alpha out of those stocks if you want to buy that call option. We're currently working on the opposite of that, which is selling puts for income. That would be a lot closer to the money versus our normal Options 360 program that goes a lot further out of the money to get the 95% win rate.

Dan Ferris:                 I see.

Keith Kaplan:             So, that's gravy. That's part of the product as well.

Dan Ferris:                 Well, if that succeeds, it'll be a first in our business. Like, the only – it was basically a revolution in our business when whoever it was that started it, you know, just started selling puts and saying, “Don't ever buy them. You know, don't ever buy calls, don't ever buy puts.” Because everyone before – all the options-trading products before that, you know, they'd get a streak and then they'd claim that that streak was representative of the system and then they'd sell a bunch of subscriptions.

And of course the streak isn't representative of shit and you'd get killed [laughs] and everybody would cancel their subscription and be extremely unhappy with you. And then people discovered income and that that's the only way to do it consistently. People like to make a little bit consistently and not lose. You know? When it comes to –

Keith Kaplan:             I agree.

Dan Ferris:                 So if you do this, Keith – I mean, I've got to have you back just to talk with you about that and nothing else. Because that will be a major – that'll be a revolution in our industry. It really will.

Keith Kaplan:             I would love to.

Dan Ferris:                 And I wish you well with it. And you're right, it's like – if the rest of that is the Thanksgiving dinner I don't know, that is some serious gravy [laughs]. That is serious gravy if you can pull that off.

Keith Kaplan:             Yeah. And what I want for people – I want to make sure this is clear too. Because it's all about position sizing. What I want for people to do is take the tiniest, less than 1% of their portfolio to play with that. And I want them to do it consistently. And I want them to start with something like $1,000 and never pull back from their wallet. If you – first of all, if you can afford a product like this, you can afford to take $1,000 and speculate with it.

And if that $1,000 can turn into $5,000 by the end of the year, that is the most wild success you'll ever see with options buying. Most people will put $1,000 in, then $5,000, and then $10,000 and then they just watch it all vaporize. And so, I want people to position size this right according to their risk tolerance and so forth. But honestly, I want you to put less than 1% of your portfolio into something like this and I want you to be very regimented about it.

Dan Ferris:                 Yeah. And even 1% might be a lot for some people depending on how much money they have. And you're right. And I'm glad you got here, because this is extremely – an extremely important point. I mentioned earlier in our conversation those market-wizards traders who, you know – some of them win less than 50% of the time and they still make plenty of money compounded over many years. They always get here. They always – in the conversation they're always like, “Yeah. You know, position sizing and management of the position, like the stops when you exit.”

And they all said, “That's far more important than the entry.” But what you've done is, you know, whatever it is − 2 quintillion or 3 quintillion tests – before making really great entries. So if you add that discipline, that trading discipline, to really great entries, it sounds like – and stick to it with an absolute iron discipline about – iron discipline about the system signals and iron discipline about your position size, it sounds to me like you've got something really cool there. Potentially super cool.

Keith Kaplan:             Yeah. And that’s the key. I'll tell you, if we didn't have those limits on the call buying, it probably would win 10% of the time, 20% of the time and we'd be lucky to be even get close to breakeven at that point. And so, I think that's the wild difference when it comes to a lot of these different services out there, is they say, “OK. Let's go ahead and buy this.” And then you got to wait and then they say, “Oh, we're down 90%. Let’s sell it.” And so, this is a very regimented, automated way to tag team with the stock buying and selling an optimal option − that's a call option − to buy and sell alongside of it.

Dan Ferris:                 Well, I can't – OK. So let me ask you a question. I'm not clear. Is Trade Cycles out there? Is it ready? Can I subscribe right this minute?

Keith Kaplan:             It's out there. You can subscribe right this minute. I'm sure that our team will get you a link for it. It’s out there and it’s ready to go. It has technically been a product that we've had for about five years now. It's just taken many different twists and turns, and then we redeveloped the entire thing from the ground up, starting about a year ago.

Dan Ferris:                 OK.

Keith Kaplan:             So it has a lot of really rich history. The software side of it, the website you log in, is fully complete. The portfolio management is there. It's built on top of all of our TradeSmith sort of engines that care about all this sophistication and making it very easy for the consumer to consume once they log in. So it's what I call a mature, redone product.

Dan Ferris:                 OK. Good. I mean, obviously I can't keep up – like, under the MarketWise umbrella, there's a million products and it's just like... absolutely. The fact that I didn’t know it existed for five years, it sounds like I'm stupid but I just wanted the listener to know there's no way I can know all of this. You know? Nobody knows all this [laughs].

Keith Kaplan:             I would expect Greg Diamond to know about this system.

Dan Ferris:                 Oh, I bet he does. Yeah, I'm getting a powerful whiff of Greg Diamond in this. Yeah.

Keith Kaplan:             Yeah.

Dan Ferris:                 Yeah.

Corey McLaughlin:    So if you're into Greg's stuff, I mean, it's right in that ballpark. Like, that's – but the difference – I think one of the differences being here is just the system involved and staying regimented with that system. I'm glad you came at that point too because that's really – like, when you're able to have the entry/exit points within a broad portfolio where it's all doing the same thing all the time, where your computers are running in the background all the time, that is really – that's doing all the risk management for you to get to those tested returns that you were talking about.

Dan Ferris:                 It’s so inhuman though to have that kind of discipline.

Corey McLaughlin:    It’s totally inhuman. Yeah, it’s like opposite of what you should do [laughs]. How many times do we – even if you have conviction on a trade and it's down 10%, it's like, "Oh" – it's gut-wrenching. Right? But this is how you overcome that I suppose.

Keith Kaplan:             I mean, look. I've been using TradeStops for forever. And TradeStops is the only reason I can even think about that and really model a new product that has smart entries, exits, and position sizing because it's just been ingrained in me that I am a terrible investor and trader if I'm not regimented. Terrible, awful. You can give me the best piece of advice ever and I will screw it up if I don't have that sort of regimented approach that I've learned over the years.

Dan Ferris:                 And really what we're saying is, [laughs] – like, Keith says he's a terrible trader. Like, we all are – humans are, human beings. That's the point. The point isn't that Keith is brain damaged, because we all are brain damaged in that way, we human beings. We all want to sell at the bottom and buy at the top. Like you said, Keith. You know, people who have that mentality – we were talking earlier I think before we hit the "record" button.

And we were talking about, you know, people who ask you for tips and I admitted that my father, you know, had periodically over the years said, “How can I make a quick $5,000 bucks?” And we agreed like, “That mentality buys at the top and sells at the bottom. Just don't do it.” But a lot of people, you know – I mentioned market wizards and Keith's system does this.

They have found a way to just sort of extract that human emotion – I mean, humans build these systems but therefore extracting that emotional element that, you know, gets you scared at the bottom and euphoric at the top and replaced it with a disciplined system of entry and exit and position sizing. In this case, based largely on seasonality. Entirely on seasonality, Keith, or just largely?

Keith Kaplan:             Seasonality and RSI, and then custom views of that per stock and fund. It's different for every – No two stocks or funds are the same. So no two algorithms ended up being the same for them

Dan Ferris:                 Wow. Yeah, so it's very sophisticated obviously. And I guess good traders – a lot of good traders have a lot of this stuff in their head. But, you know, nowadays computers are doing a lot of work. And even – I told my story about visiting the TurtleTrader many years ago, 20-plus years ago. Even they had like – the floor we were on had the trading – you know, the trading floor.

But then the floor below that was a whole team of like mathematics and computer science Ph.D.'s working on the system, creating the system. So this is how you do it. You do 2 quintillion  or 3 quintillion tests [laughs] on a lot of data, and then you stick to what it tells you and like with iron discipline. And it's just that easy, isn't it, Keith?

Keith Kaplan:             It’s funny. Because we'll be total opposites in this. I can look at numbers of a company and I can take things that I've learned from you, Dan, or from other people around the industry and I can look at something and say, “Oh, this feels fundamentally good or bad.” Right? I can even program that based on numbers. I could never in a million years do the type of research you do on a company to figure out, “Should I buy that company or not?” And just that's just like the reality of how our jobs go. Right? Like, this is what I do from a quant perspective, but I can't do that research like you would do.

Dan Ferris:                 Well, you could but it's just not you. That’s not Keith. That’s a Dan thing. It's not the Keith thing. Right. And that's important. Because finding out what – I've made this point a lot in the Digest. Corey and I have talked about it on the show. Your investing is very personal to you. And having all these tools like – you know, TradeStops, just all the products that you sell generally, are a pretty decent way to help figure out what kind of investor you really are.

So if you are – and this obviously when you combine seasonality, RSI, three-week trades with an average of 6%, you get that – that gives you a feel for what you're in for. And if that sounds like you and feels like you – and I'm sure a lot of people listening will say it feels like them [laughs]… Then that’s how you know what you want to do. And if learning about companies with wide moats and good fundamentals that I believe you can hold for the long term – you know, that’s what we do in Extreme Value.

And I do some of it – a little bit of that, not a lot – in The Ferris Report. In other words, I guess I'm saying what we say often about MarketWise generally… is that no matter what kind of investor you are, you will find your style represented by somebody who really knows what they're doing. And if you're a trader – and we've said this a lot. If you're a trader, like, you need something TradeStops has to offer. If you’re a trader – TradeStops is selling something you have to have. I'm sure of it. And this sounds pretty cool. It's amazing that you've done this. It really is.

Keith Kaplan:             Thank you. It was an incredible feat. I could not have done it without our team. We have over 70 people on the team just dedicated to our software research and data.

Dan Ferris:                 Wow.

Keith Kaplan:             I mean, yeah, it's great. People don’t realize how big we've gotten over the years.

Dan Ferris:                 Yeah, I didn't.

Keith Kaplan:             And it wasn't until about four years ago. Wait, we’re in 2025? Yeah, four years ago, early 2021. It started in 2020 where we started building the options program and realizing that processing billions and billions and billions of rows of data, that we needed a much more sophisticated team. We started hiring people. We started hiring, you know, Ph.D. level researchers, all these sorts of things.

And what happens is, you achieve something you thought was never achievable. And then it's like “Well, what do we do now?” And so it just starts to snowball and compound and that's how we got to a point where we could do this. We couldn't have done this – a year and a half ago we couldn't have even done it. You know?

It was pretty hard to do it a year ago, and it wasn't until the summer that we had the big breakthroughs. You know, got new team members that really helped us use some machine learning. Although that didn't end up being a part of this. But we had to use some machine learning to start to put us on the right stage of, “How do we even test this better?”

Dan Ferris:                 Wow. So how long has this new, improved Trade Cycles been available?

Keith Kaplan:             So the seasonality part of it's been available for about a year. But then this new portfolio version of it has been available for probably about three months internally. We've been beta testing it, and then about a month for our subscribers that already had Trade Cycles.

Dan Ferris:                 OK. I see. So, you know, even a year, I mean, is still pretty new. Do you have – do you have data on, you know, how well folks are doing with it or how well – trades you're putting out maybe or...?

Keith Kaplan:             Yes. Absolutely. So we have – with the gentleman, his name is William McCanless, who is the analyst for this service. He does this incredible job of every time he puts out a trade – whether it's a win or a loss – he asks for feedback. And he wants that feedback and then he shares the feedback with others. So, the overwhelming majority of the feedback has been, “I won this. I made $13,000 on this. I did this. I had a 212% return here.”

I mean, we have more feedback for William's work in this service that I think we have for all of our other services maybe combined over the same period of time. And William has been doing this for I think maybe a year and a half of us, maybe closer to two years with us. And he's had that sort of style in his editorial where he's just constantly telling you about something and asking you for the feedback.

Dan Ferris:                 Interesting. That's really cool. Yeah. Especially with something that's like, you know, short-term oriented, you can get a lot more feedback. Right? That makes sense, in other words, for a short-term trading product to constantly be, you know, asking for feedback. Whereas I'm like, with Extreme Value, I'm like, “OK. Basically expect nothing for at least three years and then tell me what you think.” You know? [laughs].

Because, you know, it can take a while. You find something that's undervalued. But different conversation. OK, Keith. We are actually to the point where it's time to ask our final question. And our final question is the same for every guest. You actually answered it before. I hope you don't remember, because it works better that way in my opinion [laughs].

Keith Kaplan:             Yeah, I don't quite remember.

Dan Ferris:                 OK. Good. Same question for every guest, no matter what the topic, even if it's not financial. If you’ve already said the answer, by all means feel free to repeat it. And the question simply, "If you could leave our listeners with a single thought today, what would it be?"

Keith Kaplan:             Oh, a single thought. And then, you know, just thinking about this – so this would be my one single thought that's very broad and it would cover every type of person out there. But a lot of people hopefully are well past this. But still I want them to pass it on to other people they know that aren't. Maybe it’s kids or grandkids. This is the thing that's the most important to me, especially because of the journey I personally went through that I was lucky enough to end probably about 15 years ago when it came to managing my own finances.

No. 1, get out of debt. Do not be somebody else's interest. Don't be their – don't let them be an investor off of you. No. 2 is, build up your savings. Start with some level of a rainy-day savings so that you can cover things − make sure you have somewhere to live, eat, and take care of your family. And then get to step three, which is investing.

So it goes debt, get your savings, and start investing. And when you get to that investing, you have to be regimented. You have got to care about how much you're putting into every single stock or fund you buy, why you’re even buying that in the first place. Please have a reputable reason to buy it in the first place. And you need to know when you're going to sell it before you ever even buy it, typically a trailing stop is the best way.

So you’ve got to be disciplined when you get to the investing stage. But the ultimate discipline starts with not being the leverage that somebody else gets to make money off of you by carrying ungodly amounts of debt throughout your life because you will never, ever, ever get ahead if you’re carrying that debt.

Dan Ferris:                 Brilliant. Perfect. Excellent message.

Keith Kaplan:             Thank you.

Dan Ferris:                 Listen, Keith. Thanks so much for being here. It was really – it's always a pleasure to talk with you but this was really kind of an exciting and informative conversation. I hope folks were taking notes because you give us a lot of information. And of course, they can all go to – we'll get them a link but you can go to TradeStops.com to find out about Trade Cycles. Thanks a lot, Keith.

Keith Kaplan:             All right. Thank you both. Really appreciate it.

Dan Ferris:                 You bet [music plays and stops].

I've been chatting with Keith Kaplan, a genius in the world of financial technology, and he's got a fascinating prediction. January 16 will open the biggest "Green Day" moneymaking opportunity of his 20-year career, he says. In short, he's developed a breakthrough new way to spot the biggest jumps on 5,000 stocks, to the day, weeks before they occur and with 83% backtested accuracy.

And it could double your portfolio this year, he says. Frankly, I wouldn't doubt him. His firm has been on the Wall Street Journal and on CNN and CNBC. His breakthrough new "Green Day" strategy would've already pointed to 15 stocks that could have doubled your money in under 50 days in a backtest. Go to www.2025boost.com for details on what Keith calls a chance to boost your gains by 100% to 500% or more this year. A new way of investing by using his "Green Day" system every single trading day.

He's offering one free year of access to all of our listeners. But you must get positioned by January 16, Keith says. Again, that’s www.2025boost.com. www.2025boost.com.

So this was Keith's fourth appearance on the show over the years. And he never fails to disappoint, does he? He's always full of this, you know, financial-technology stuff that I know absolutely nothing about [laughs]. It's fascinating to hear him talk about it. And, boy, did he get technical. He got into a lot of details. It was a lot. It was cool.

Corey McLaughlin:    Yeah. Yeah, I’m glad he did because some of this stuff can – when you mention technicals, it can go over the heads of some people or you just choose to ignore it. But when you really get into the details of it and understand how to get the results that he's talking about, that's important. So I'm glad we got into that. And yeah. I mean, that's what TradeSmith has been known for over the years. I mean, I remember when I got into this industry too. I mean, one of the first things I checked out was all of the trailing-stop stuff and it was – it did help me figure things out a little bit in the beginning, like you said.

So, you know, it's one of those tools that I feel like a lot of people are looking for these days to help them trade. I mean, and you have to understand. Like, what we also said is – talking about 1% of your portfolio here. You’re not talking about, you know – I wouldn't be risking your whole, you know the majority of your portfolio here. I mean, you have to know what you're getting into. But if you're in short-term trading and if you're into that, I mean, this is the kind of thing for a retail investor that I think you would want.

Dan Ferris:                 And just – it makes – trading is so difficult and emotionally just really demanding. And having like – automation is the perfect tool. An automated tool is the perfect thing for trading. Because human beings aren't automated and they're constantly being bombarded with their own emotions. And if this machine is constantly spitting out what you really ought to do if you have the discipline – you know, “If you had the discipline, you would do this,” is what the machine is telling you.

And it's nice to have a lot of different ways of doing that and, you know, TradeSmith definitely has that. If you want to find out more about this you can go to www.2025boost.com – 2025boost.com – and find out more about all the stuff Keith was talking about in this episode. The Trade Cycles product and how it works and what it does. So that was fascinating. I hope you were taking notes. We should have told you – we told you to take notes in the beginning, actually, and I hope you did it because there was a lot there.

All right. That was another interview and that was another episode of the Stansberry Investor Hour. I hope you enjoyed it and learned as much as we did. We do provide a transcript for every episode. Just go to www.investorhour.com, click on the episode you want, scroll all the way down, click on the word transcript and enjoy. If you liked this episode and know anyone else who might like it, tell them to check it out on their podcast app or at investorhour.com please.

And also, do me a favor. Subscribe to this show on iTunes, Google Play, or wherever you listen to podcasts. And while you're there, help us grow with a rate and a review. Follow us on Facebook and Instagram. Our handle is @InvestorHour. On Twitter our handle is @investor_hour. Have a guest you want us to interview? Drop us a note at [email protected] or call our listener-feedback line, 800-381-2357. Tell us what's on your mind and hear your voice on the show. For my co-host, Corey McLaughlin, until next week. I'm Dan Ferris. Thanks for listening.

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