Interview: Keith Schneider from Market Gauge

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Introduction

Jeremy: Well. Hello everybody and welcome to this very special audio interview that I had a chance to do with, uh, the great Keith Schneider co-founder of Market Gauge. Uh, some of you know, Keith, most of you probably don't, and he's one of those gems on Wall Street that it's kind of been lurking in the shadows for about 50 years and had an amazing career. And I got the opportunity to meet Keith a couple of years ago down in Florida and an event we were at together. And, uh, we just struck up a really great friendship and this idea came up to do an interview together, which is something I've wanted to do with several great traders over the years. And Keith was the first one who said he would be willing to do it. So I have Keith with me today and, uh, Keith, welcome.

Keith: Well, thanks for having me in that wonderful introduction.

Early Life As A Trader

Jeremy: Absolutely. So for people who don't know Keith Schneider, Keith has got a his entire life basically he has spent on Wall Street as a trader, a fund manager. He's one of the Co founders of a company called market gauge. He's a futures trader. Everything you can imagine, systems designer, all of this goes into this great man that we know as Keith Schneider. And today what we're going to do is we're just going to spend a little bit of time kind of talking about his career in the industry and what it has meant to him, all the discoveries he's made, and just kind of all the stuff that many of you have wondered about great traders. What are they like? Well, we're going to get the opportunity to hear some of that today from Keith. So Keith, as we kick it off, let's go way, way back when you were a child or whatever it was, how did you get your start trading in this crazy world that we call Wall Street? What brought you to it?

Keith: Actually, I was very, very fortunate. My uncle was a worldclass investor and um, at the time he had no kids. So I was sort of his Q and a from the age of seven or 10 I was being taught the principles of the financial markets from a world class expert. Wow.

Jeremy: So from the time you were a child, you were learning some of these things that people today and their fifties and sixties, you're trying to figure out. You were there from the beginning basically.

Keith: Absolutely. In fact, um, while I was in junior high school, um, uh, I used to cut school and go down to Wall Street and hang out with him and watch him, uh, trade the markets.

Jeremy: That's incredible. So do you remember your very first trade?

Keith: Um, the very first trade that I made was actually in Gulf and western options.

Jeremy: Your first trade, you went all the way, all the way to options, not to keep it simple. Everything. Yes.

Keith: And um, options were in exactly the most liquid instruments back then. But yes, I started trading a Gulf and western options.

Jeremy: So when was that? What was that year? Early Seventies. So you've been trading in the market since the early 1970s. And how did you, how did you pick that? I mean, what drove you to do something so risky as an illiquid option at that time?

Keith: Well, we were looking at the Gulf and western stock and at that time, um, the whole world was being driven by the nifty 50, like the top stocks. It's sort of like what, what Fang is today, but there were top stocks. Um, and at the time there was this really a new idea of code called conglomerates and they were the hottest thing. And Gulf and Western was considered the consummate, um, uh, conglomerate the trade. And so we like the way the chart patterns we're looking and we thought that there was some interesting news at the time. Um, I dunno, he was by Charlie Blue and Warren, uh, was the name, he was the CEO and he was buying up some companies, I think it was an insurance company or something. And we thought that it was a very good opportunity.

Jeremy: So heavily influenced by your uncle's decision making at that time?

Keith: Yes. Yes. All right. He was more of a fundamental investor, um, then a technical trader. But you know, as things progressed, you know, I went out and, um, uh, got a seat on the commodities exchange and basically 20 years old. And, um, develop my own trading methodologies, which were quite a bit different. Um, although I was introduced to charts, hand drawn bar charts, um, by my uncle. In fact, I got some originals of commodity prices back from the late forties and early fifties that he actually did by hand.

Life As A Floor Trader

Jeremy: Wow, that's incredible. That's actually a great transition. I wanted it to talk a little bit about your life as a floor trader. You, you got to see it on the exchange and once you started trading right there in the middle of all the action, you were surrounded by all these big Ivy League financial gurus, if you will. And that didn't really set well with you when we first met. You talked about how it was very early on, you started leaning towards that technical side of trading. Why was that? Talk to us a little bit about that.

Keith: Well, the floor of the commodities exchange was a very interesting melting pot in New York City that was in full world trade center. So, um, in the mid seventies, all the exchanges in New York commodity exchanges, uh, merge their trading operations. They kept the, their membership separate, but they sort of combined on one big floor in four World Trade Center. So you know, if you saw the movie like trading places, that was the place. And so, uh, when I call it a melting pot, they were guys who were brilliant from Columbia Law School or Columbia Business School, um, down there. And, um, there were some very, very smart, uh, people who, uh, were very, very well educated. What I found is that some of the guys who were highly educated, um, coming from really, uh, you know, sort of elite backgrounds, um, they tried to do fundamental analysis even though they were on the trading floor. And by the time they figured out what was going on, they were broke or should have been broke if they, um, were, you know, of normal, uh, uh, lineage. Some of these people had some very, very substantial lines of credit or family that bailed them out, but they weren't very successful, um, as traders.

Jeremy: So the idea that they could sit here and calculate from a fundamental basis, by the time they got that done, the trade had moved on. Is that what you're saying?

Keith: Total? Especially in commodities in the 70s. It was historic period where the market's movement was, you know, exacerbated. This was the hay day and probably, um, the last great mega move in commodities that floor traders experience. So remember we had, um, multiple oil shocks, massive inflation, a decoupling from the gold standard. All this was a current, so the geo political global macro scene was of historic proportions. You know, the hunt corner of the silver market was predicated on the belief that currency, you know, Thea currency from the central banks was going to go away and they tried to corner the silver market and they did a pretty good job for a while. So it was, you know, really historic times to cut your teeth as a kid trading. So either learn fast or you are out of the game.

Jeremy: And so that led you to technical trading because it was so much faster to be able to get the data, assimilate it and recognize what was happening in the marketplace.

Keith: Absolutely. Hand drawn shorts, um, technical, you know, to do the technical analysis and basically, um, you know, part of my exercise or you know, process was to be able to track 10 or 15 commodities all by hand doing it myself to get the pulse. So, you know, drawing the charts actually gave you a pulse.

Jeremy: And so this was in the 70s. This was a time when computers, like we know it today or you know, they were a dream that that wasn't going to come along for another 20 years. Certainly not like we have today. Um, but there was some similarities of what you learned back then in the 70s because the speed with which the market was moving. And like you said, you drew it by hand, but today the market moves super fast. We got all this day trading, we have this electronic markets that you didn't have a fully fleshed out back then. And how was that similar today?

Keith: Well, I the, the core principles, um, behind the floor trading techniques is not that dissimilar from, you know, what is happening today. And certainly, uh, the, the floor floor trading doesn't exist anymore. It's now high frequency trading. So basically the floor traders are, have been replaced with high frequency trading. But listen, the core principles of market behavior, there are still a things called humans that run the markets even if they're managing algorithms. So the next thing is that these core anomalies that are driven by human behavior still persist. A lot of smaller anomalies get sort of arbitrage or moved out of the market because people recognize it. But the basics of human behavior still exists. And there are some statistical anomalies, anomalies that still work and those are edges that we try to explore. And I learned something from the floor.

Jeremy: So in those early days, can you think of a time when you know all of your fundamental cohorts, if we will, you know, your, your people that you were trading with, they were all looking at one thing, but you knew in your gut based on your technical trading, they were wrong. And you are able to exploit that. Can you think of a, you remember a time when that happened?

Keith: Oh yeah, there was, um, without mentioning particular names, but there was one particular gentleman who was affiliated with one of the goal core gold bullion dealers. Um, uh, and he kept on shorting goal on the way up from 300 to 400 to 500. And this was, you know, the late seventies. And so he was literally losing millions of dollars every day and getting a margin call. And I'm like, okay. And I was young and you know, trying to figure out how that all fit in. And when I realized he was just losing his, his ass, um, and I was making money and thinking that maybe I was doing something wrong and there was really more something to it, but it wasn't, the bottom line is he just had a fundamental opinion that gold shouldn't be moving and silver shouldn't be moving at the rate that it was and got in front of a freight train of a trend. And we lost a lot of mine.

Jeremy: That's incredible. And there's a lot of people today that they do the same thing though. Just get such a personal bias maybe because if someone's opinion that they see on television or something, they read and they just keep throwing good money after bad. And here you are at a young age watching someone else sink that ship. What did you learn from that?

Keith: Number one is risk management. If you don't have risk management, um, you're, you're, you're going to fail. So to me, always knowing a number when I felt I was wrong was the key thing to self preservation. And by the way, if you control your losses, I also realize that whatever I needed to learn at that age, if I control the risk, at least I'd have the time to figure it out.

Jeremy: That's amazing advice. I want to highlight that if you control your risk, at least you can have the time and your words are, I would say you, you have the ability to survive, to go figure it out. There's so many people that just keep throwing good money after bad thinking. It's going to turn around and then they wonder why they go broke. And it's really sad because no one needs to do that. Uh, let me, let me shift just a little bit. And in that transition or that, that season of your life, you ultimately came off the floor and you transitioned over to working for millennium partners. Was that the next step for you?

Keith: Well, no, actually the sequence was this. Um, when the silver market actually, um, God stopped in it's track because of the sort of the corner of by the humps Whoa. Broken by, uh, the exchange, um, and vulgar in a, around the same time took over the Fed to brick, the back of inflation. Um, it was clear to me that the big commodity run was over. And actually one of my friends from who, who taught me from a Columbia who actually was a bit of a fundamentalist, but also blended technical trading. And he taught me a lot. He pointed out that, you know, this was now shifted. So I started looking around and I realized that the market was shifting to equities. Um, and that the, um, uh, interest rate market, um, that went from, you know, 12%, which at that point was considered low in some cases up to 20%, uh, on, depending on the duration was going to break the back of inflation and stocks. We're going to move, I actually got into technology and built a computer system that where I made a nuclear submarine colored display technology, um, windows that I called a few ports and built a technology company to be able to track the markets from off the floor.

Jeremy: Okay. So you actually were a pioneer in developing some of the first computers that even did anything in the world of trading?

Keith: Absolutely. Yeah. Well, I, I did, um, I was the first to do color graphics, high resolution terminals, multiple windows, which I call view ports technical analysis. And um, that was the product called market vision that I built in the early eighties and an integrated data feed. It wasn't so easy to get data all in one spot. So if you wanted, you know, commodity data, it was coming from seven different sources. So I also built a consolidated data feed to be able to compare and look at trends on a global basis and compare them.

Jeremy: Wow, that's incredible. The amount of work you had to go through when you think back about what you did in your early career and the tools that modern traders have, it's got to just blow your mind.

Keith: It is amazing. But the funny thing is when you look at the stuff today compared to what I was actually doing, uh, in the early eighties, it hasn't change. Uh, the basic stuff has not changed. Of course, now you have, uh, something called the Internet to get the data those days. Um, it wasn't so easy. You had to use special modems and direct, um, direct phone lines, um, to be able to drive the data cause there was no internet.

Jeremy: That is, that's just so fascinating to me. And you know, people often think about me and my career and they say, you've been in the market for a long time, which I have over 20 years, but you were literally in the market cutting teeth as I was

Life As A Fund Manager

Jeremy: being born. And you, you experienced this entire evolution, which is incredible to me. Um, I want to talk about, so somewhere in there, you moved over and you started working with Millennium Partners, uh, where, where did that come in?

Keith: Um, uh, mid nineties.

Jeremy: Okay. So it was another 10 years later,

Keith: correct? Yes.

Jeremy: And talk to us a little bit about, um, what it meant to be part of the hedge fund world. At that time, hedge funds were, you know, not, not a black sheep necessarily, but they weren't the big word that they are today. And there's a lot of missing information and kind of a lot of misunderstanding about what hedge funds are. So why don't you just in your own words, describe for our listeners what is a hedge fund and how was that different than the traditional mutual funds that they're associated with?

Keith: Well, a mutual fund is, uh, you know, an investment vehicle that goes back to, I guess the Investment Act to the thirties and forties. Um, and most mutual funds are a really buy in whole, uh, and they embrace a particular strategy and stick to it. Um, the idea of a hedge fund originated with the idea of instead of it being long only that you have long ideas, you have short ideas and different strategies to basically minimize downside risk and maximize or get Alpha because, uh, which is relative performance versus a benchmark. And so that whole industry is really got a sort of a different mission than what the original mutual fund business is.

Jeremy: Right. Which is why they require qualified investors and all these different things. It's basically an active trading philosophy, but inside of a fund,

Keith: yes. And now I, it's, it's sort of branched out because there are, I don't know, thousands probably, I dunno, 10,000 hedge funds or some number like that, although it's been shrinking because their performance is definitely not really necessarily kept up or, um, the extra fees that people pay hedge funds, um, haven't necessarily produce the outcome of outsize returns. But, um, the, what I found, um, was an different approach than what I was doing for myself or what I saw, uh, happening, uh, on the floor. So you know, when you're managing other people's money, uh, draw downs, um, and risk control, uh, and diversification become much more important. So millennium partners was a great exposure to institutional money, how they think and what they do.

Jeremy: Okay. Let's talk about that for a little bit. So you're a fund manager now, you've started to manage risks differently because you're not managing your money. You're now responsible for other people. And so talk to us about that. Now that you're having to think about other people's money, you've obviously been hired because you're the Wall Street wizkid you know, how to take a $10,000 gold account and turn it into millions, but now you're in an institution. What did you discover from an institutional perspective about risk management that our listeners can learn from?

Keith: Well, they're much more concerned about drawdowns as a percentage of the total equity. Um, so you have to be really cognizant of that. Um, I also found I didn't like a lot of the, what was considered a normal metrics. Um, so for instance, you know, a classic Sharpe ratio, which is sort of the, uh, the gold standard for looking at risk adjusted returns is a ratio that I don't particularly like. And in fact, um, when I signed my deal with Millennium Partners, um, a lot of the concepts were built around sort of these classic Nobel Prize winning economics formulas, um, that were being produced. And I didn't particularly like that sharp ratio because it penalizes you for outsize wins, um, unnecessarily. So, you know, uh, it was a learning process as well. So, uh, what I found is, uh, some of the metrics that classic hedge funds use is not necessarily, um, productive. Um, and there's more there, there's other ways to look at risk and measure it. And, um, I try to use those type of benchmarks, especially the sortino ratio, which does not penalize you for w w uh, big winners or outliers that make a multiple of what the losers do.

Jeremy: Okay. So you're talking about some high level models for risk management that most of our listeners, they have no idea what these words are. Let's talk. Let's talk about diversified risk. I'm talking about kind of, you know, most people are poorly diversified and they need to spread their risk, but they don't know how. And so what people find a lot of times is maybe they're in say for example 10 mutual funds or 10 ETFs, but 80% of those funds are all correlated. And so when you think about diversification, it's not actually there. You just have a bunch of positions that do the same thing as a hedge fund. In Layman's terms, how do you start spreading that risk out so that when one market does something, the entire portfolio doesn't go to pot?

Keith: Okay, well there's a couple ways to think about that. The first one, which I think is probably easiest to understand is that if you have strategies that are based on different principles, then you have some level of diversification. So for instance, there are certain statistical anomalies that give you an edge and there are a handful of them that even the average investor, if they are aware of it and have the right methodology to exploit, they can use them. So one way to diversify risk is to have strategies that do, that are based on different edges in the market or different concepts. So for instance, there's, you know, income based option strategies, right? Something that you actually work with. Um, then there are our momentum strategies that look at trends and trend continuation and the best ones look for trends that have huge outliers. That's a strategy.

Jeremy: So what you might consider is you might consider allocating some money, whatever that percentage is. Two a momentum strategy that's tracing the trend and it's tracking the trend. You might consider applying one percentage of your income to, for example, selling covered calls, which would be an option income strategy. And then you might apply a different portion of your overall portfolio to other strategies.

Keith: Correct. So you're not always trying to exploit the same edge that's gonna give you, um, you know, non diversified exposure. So if you're looking for momentum, um, and you're playing only momentum strategies, when that sort of subsides and every strategy goes through its inevitable cycles, um, you're not going to get killed. You're going to basically mitigate the risk. And in if you handle it appropriately, um, hopefully a smooth the returns and on average beat the market. That's the classic Multi Strategy Hedge Fund that um, is a model for a lot of people for a lot of hedge funds anyway.

Jeremy: Yeah. So the Multi Strategy Hedge Fund says we're going to have different funds within our overall management that exploit different, as you call it, edges what a lot of people would use as the term strategy. And as we diversify across this, you know, in sideways markets the income strategies might outperform, but in a strong bull market, the momentum strategies will outperform and you just balance overall so that as a whole, the portfolio and the overall equity curve is going up

Keith: correct. With the smoothest returns possible. That's exactly the goal of a diversified multi strategy hedge fund.

Jeremy: The ultimate goal is to smooth overall equity curve so that the draw downs or less and the growth is consistent

Keith: and hopefully not only consistent out before the underlying market

Jeremy: and not only consistent but also outperforming. So one let, let's just dig into that for a moment. One strategy. Yeah. I mean that that is the goal. Yeah. So one strategy, for example, a momentum strategy, a trend trading strategy, it may, it may really suffer in a sideways market. They may be getting whipsawed in and out and that that strategy may actually be losing some money, but the income strategy may have that kind of slow and steady, consistent 5% return or a 10% return. And overall your overall portfolio is smoothed out. That's what you're trying to describe. Correct.

Keith: Exactly. Right, right. In a momentum strategy, uh, in a momentum type market, then, uh, probably your incomes strategy will not do as well. Some things will get cold away because they trend very strong, et cetera. Um, so yeah, so there's a, a balance there. And like I, you know, like when you just mentioned there are cycles to different types of edges or strategies that you employ. And hopefully what you want to do is have the right smattering, will the right smorgasbord of strategies that have the lowest, you know, drawdowns on average in the best returns.

Jeremy: Do you have a number? What if someone needed to diversify over x number of strategies, what should that be? Two, four, eight, 100,000 or what's the number?

Keith: Um, I, I'm really looking at three or four different different edges and it's really determined by edges in the market that one can exploit, right? So for instance, if you're a renaissance, the hedge fund and you have the infrastructure to, um, do high frequency trading, which, you know, on a moment's notice, they could decide I need that, you know, 1000000th of a second, uh, edge and throw out their existing, um, technology and improve it. And you know, okay, that's 100 million, not a big deal to affirm that's running, you know, tens of billions or more. They'll play with that structure, um, and invest in the infrastructure to maintain the edge of that particular strategy for the average investor that doesn't exist. So you need to find strategies that have a statistical edges that work and that you can employ without any major investment in technology.

Jeremy: I think that is such a valuable thing that you just said. The statistical edge. Uh, you know, if somebody were to go to Las Vegas and play cards, what are you looking for? You're looking for the statistical edge. That's what you're, even though you're not gambling in the stock market, that's the way we approach it. We approach it by playing the odds. And what you added to that is, you know, the, the average trader at home, they can't, they can't pretend to compete with a high frequency trader, but at the same time, they're not the victim of the high frequency trader. A lot of people think cause the high frequency trading that they can't beat it. It's wrong. You just have to play a different game. They may not be able to beat them at the high frequency game, but they can still beat them in a momentum game or something that doesn't require a huge technology stack that the individual can do at home on their schedule, in a system that works for them.

Keith: Right? So the edge has to be significant enough to make it worthwhile to plan. So we've discovered, um, I dunno, maybe three to five edges that are meaningful.

Jeremy: And that's the, that's the way that you diversify it.

Keith: Yes, based on edges that we find that we research and that, um, we monitor to make sure that it's still in play.

Post Wall-Street And Market Gauge

Jeremy: Okay. I want to talk more about some of those systems in a moment. Um, but for a moment, let's, let's get a little personal. You met your wife on Wall Street, she was a floor trader as well. And the first time you and I met, you guys were sharing with me how you, you obviously met on the floor. You met your business partner, Jeff on the floor. You were so close and then nine 11 happened and you and your wife looked at each other and you said, we're done. And you left New York City and you went all the way out west. So you know, first of all, where were you on nine 11? This is an event that it shocked the world. It's forever seared and our memories and it obviously made such an impact for you that you made a distinction and you said, my life in the future is going to be different. Tell us a little bit about that.

Keith: Well, um, actually on nine 11, uh, there was a, uh, you know, I had mentioned earlier that I've always been very much involved in technology and, uh, you know, computer terminals, etc. Etc. Well, market gauge, the company that we currently have, we started in 1997. Um, so it was sort of in its infancy, but we were supplying advanced analytics to some of the top institutional firms and prime brokers, um, in the u s

Jeremy: So the stuff that you're using now for retail traders, you started providing that for the professionals on the floor?

Keith: Well, professionals at the major clearing operations for hedge funds and big institutions. So fidelity, we supplied contentment. The, they're, they're uh, institutional, a brokerage division. We supplied analytics and technology to them and other firms like that, Bank of America, etc. Yes. So we, this was when the Internet was, um, really in, still in its infancy, relatively speaking. So we, uh, we're part of a, you know, technology, Wall Street technology, um, you know, ecosystem. And I got invited to something called the waters, uh, show, which was oh, convention, which was a meeting of the top Wall Street technologists. And I was supposed to go and I'm actually one of the, um, what are the people that, that, that um, we were doing business with. Um, I was up, cause I lived up in Westchester at the time and I was supposed to pick them up and a new convertible I bought and head down to the World Trade Center. And it just turns out that I got really jam. And I told him, um, at the last minute, basically the day before that I'm Jeff and I needed to go over something and I'm going to miss that first breakfast meeting eight 30, nine, 11. Right. Um, at windows of the world.

Jeremy: So you were supposed to be at World Trade Center having breakfast at eight 30 in the morning

Jeremy: and the day before for circumstances that were out of your control. You decided I'm too busy, I'm going to cancel it.

Keith: Yes.

Jeremy: And then the next day you had that real, you realize what you had just dodged.

Keith: Yup. That's, that's a, that's the story.

Jeremy: And then obviously, I mean the event itself shook the entire country, but for people like yourself who, you know, you really escaped death. And as you told me down in Florida, when we first met you kind of took stock you for your life and it, it really changed some of your values and you decided to slow down a little bit and you decided he'd move out West. And tell us a little bit about that transition from Professional Wall Street to helping others.

Keith: Well, uh, the, the, the interesting thing is, you know, I had the publishing company, a market gauge, um, and we really, during that period transition from working with professionals, um, to directly working with individuals. Now actually, my wife, uh, Mitch who is also my partner and part of market gage has always been a teacher, special ed teacher. And in fact, uh, for many years she was doing consulting work as a special educator, uh, for children with disabilities, with the top school districts in the country. And what we realized is there's a huge need for people to understand their finances. And so we decided to, um, really focus on the retail investor, um, use the techniques that, um, Mitch knew how to modify curriculum. Um, and so we've incorporated that. And, uh, I have to say the giving back part, um, has been very, very raw. We're white because we constantly get people who thank us for our dedication and for, you know, making what is relatively esoteric, complex stuff, um, accessible in an area where the level of, uh, or the level of knowledge is extremely low because mainstream, you know, uh, schools don't teach some of this basic stuff, which is really critical to your happiness as a human being. So we feel like we're, we're definitely, um, illuminating that for a lot of people.

Jeremy: Yeah. And I can attest to that as well. You know, the thank you emails and messages that we get from customers, it really, I don't think people can appreciate how cold the corporate world is. I'm, I'm going to guess fidelity called you exactly. Never. And said, thanks for all the great trade ideas. Am I right?

Keith: Absolutely. A couple of the executives who we did business with the higher end, uh, you know, at the top level, you know, the CEOs of the division or they, you know, they were very appreciative. Um, one thing that we found with working with a big institutions was that you definitely get lost. Um, and so it was much more rewarding to work directly with the retail client who you have a relationship with.

Jeremy: Yeah. And I totally agree and people off often ask, and I'm just going to say this kind of for the record here, you know, they say, why do you do this? And I keep saying you guys don't understand the spiritually, emotionally there's a reward to giving back and contributing. And when you see lives changed, whether it's because they just stopped losing money or because they made a fortune or because you know, one of the emails we got, Hey, I'm not going to be in class for the next three weeks cause I'm taking my family to the Olympics based on what they'd learned from trade smart. It really, yeah, you can't put in words the emotional reward for that. And it's so much more than money can buy. And I know that you and Michelle and Mrs you'd like to refer to her as, um, you guys are totally in sync with that.

About the Market Gauge Products


Jeremy: I love your tools. I love your models. Uh, as soon as I saw them I knew that they could help so many people. And I think even back then when, when I met you the first time, I described it as a hedge fund in a box and we kind of laughed about it. But in a lot of ways that's really the very thing that you created with market gauge. It's kind of the tools of a hedge fund put into a box. So let's talk about that. First of all, you have three main models. Why don't you tell us about each of these models just briefly and then we can kind of go into more detail.

Keith: Okay. Well one thing is you, you would ask a question before about, you know, diversification and we talked about strategy diversification based on edges. The other one is asset class diversification as well. So now I'll go into that. The last question. So in terms of the, uh, models, we have both strategy diversification and asset class diversification built into the three models. And uh, the three models are, the following, one is called to Nasdaq old stars. It's a relative strength and momentum based model looking at the top Nasdaq 100 stocks. So as an asset class, it's equities, right? As a strategy class, it's mostly long term momentum. So one of the edges that are known to be still sound and big enough to exploit is playing long term. When I say longer term, you know, on average, um, the holding period for the monthly rotation on the all stars is 90 days. Some last a year old longer like, um, our Nydia trade don't what it does, it captures the biggest trends in the hottest internet biotech stocks that, uh, reside in the Nasdaq 100. So there's all different, um, uh, details on how the model works, but it's highly effective.

Jeremy: Cow. Want to come back to how that works a little bit. Um, let's, so let's just put it out there so people kind of have a structural idea here. You've got the three models, you had the Alpha rotation, which we'll talk about. You have the Nasdaq all stars, which you just mentioned, and you've got the ETF model. And I do want to dig into each of these. Uh, but the theory of these models all came from your hedge fund days. Is that correct?

Keith: Pretty much. Now, one thing that's been really a very, very powerful is the internet. So, uh, if you've got a passion for anything, you can easily follow it. And so one of the things I'm always doing is researching and I have all of these core ideas all came from the days on the floor but then refined to move it out. So we're not getting washed by high frequency traders. And the frequency of the trays are enough to exploit the edges, instills sidestep a lot of the, um, uh, a lot of the computer algos that are designed to defeat it.

Jeremy: Yeah. So basically it's modern technology, modern wisdom applied to a lifetime of learned lessons all wrapped up into these products that you call market gauge. So a individual sitting at home in their car, wherever they are listening to this, how could they use these tools to balance their own portfolio? Almost like a hedge fund, maybe a little bit different but, but kind of like a hedge fund. Let's start with the first one. Let's just kind of go in order here. We learned a little bit about Nasdaq. We might come back to that, but the Alpha rotation explained the theory on Alpha rotation. Just kind of the model is it's simple risk on risk off. Explain that theory to our listeners.

Keith: Okay. Well

Jeremy: the, the most basic and most important is uh, to make a determination whether the market environment from a big picture perspective favors stocks or fixed income bonds for the other possibility, which most people don't like to think about is none of them. So you could, you could be 100% in equity. You can be 100% in fixed income or treasuries as most people refer to them or you can be in cash. You mean to tell me cash as an investment?

Keith: Absolutely. There are times, um, when both stocks and bonds go down, that's not when you want to be in either one of those. And so the Alpha rotation model,

Jeremy: it exploits the best of the, of the three, which one is the best? It gives you a market edge saying hey equities or the best or fixed income as the best or cash is the best.

Keith: Correct. And that's it. It's that simple. It's that simple. But what does it incorporates a couple of their times. So we talked about edges. So there are some very classic ways to look at the big picture and look at relationships between different types of assets.

Jeremy: So you're not just following a moving average, you're looking at some inner market relationships and you're saying, okay, based on these relationships, this is where the edge is to exploit.

Keith: Yes. And the other thing that we do is like everything in life, nothing is 100% now it's up maybe for death and taxes. Right? But aside from that and pull and politicians arguing and, and, and, and, and that as well. So, so, so with that, we're not going to rely on any one relationship. So we've identified five core intermarket relationships that measure the appetite for risk. And that's what's built into the Alpha rotation model.

Jeremy: Now I know your, your models proprietary, is there any of those five

Keith: items that you can reveal to our listeners? Yeah, I mean listen, what, what's proprietary is the algorithm of how we measure it. The fine toony cause that's only one element. So we look at all those things. We have, um, a risk management built into it. Um, we have, uh, a whole bunch of other things that, uh, elements that make a model work. So there's some, a little bit of a charting and technical analysis. There's some, uh, uh, sentiment indicator that we'll use only under certain circumstances. So there, there's a bunch of different elements, but the core are looking at, um, the s and p, uh, versus the long bond. We like to look at goal versus the s and. P because that tells you a lot about geopolitics and potentially inflation. We like to look at, um, one burr versus, um, the, uh, gold market because that tells you a lot about the nature of the economy as well. Do you have inflation and is that, and the not being a positive where you know, you're getting inflation and lots of growth. And of course the lumber is very sensitive to the housing market. So that's important. And we also look at high yield debt junky dead versus safe day, right? When the safety, um, when people are less concerned about, uh, the false junk debt will tend to outperform in a risk on environment.

Jeremy: So all this stuff kind of sounds a little bit like fundamental stuff, but it's really a technical approach to some of those core pieces of intermarket relationship.

Keith: Yeah. Well, we're looking, yes. And what we've done is we've converted to a formulas and algorithms that are mechanical. These are not subjective. Well, I think this, this is not looking so good or this is looking great. There's, uh, a methodical process that we use across all of those different, uh, intermarket relationships on a consistent basis.

Jeremy: All right. So that's the Alpha model, which I personally love it. I have used it, I've been using it and applying it and helping my parents with their retirement money. Would that model, let's talk about the Nasdaq model. This is an interesting model that focuses on the Nasdaq 100 and it, it actually tells the user what are the top five Nasdaq stocks to trade right now. Talk to us about that.

Keith: Well, okay, so in essence, the edge that we spoke about this statistical anomalies that are probably the strongest is still momentum and the concept of relative. So not only do we want positive momentum, we want that momentum to be really strong. So aside from our independent, our research, if you take a look at all the white papers that are out there, that statistical anomaly shows that momentum works if you measure it appropriately. So the Tsi model has an algorithm called the trend strength indicator. That is a, a, a blend of, uh, measuring the momentum over various time frames, um, and coming up with the top five holdings.

Jeremy: So it takes, it takes momentum. It doesn't just look at one picture, it looks at multiple timeframes and it does this algorithm where it says these are the five best stocks that have the most momentum so that people can take advantage of that one of those edges. That is a known edge. It's a long standing, it's been a tried and true. But this model through the Tsi that your, your trend strength indicator, it tells you what those five most momentous stocks are going to be.

Keith: Correct. And there's a whole risk management system built into it as well.

Jeremy: So it, it meant it approaches risk management as well.

Keith: Absolutely. That's one of the big things that differentiate our models versus many other systems out there. You know, sitting through a 50 or an 80% draw down, which is entirely possible. Certainly it happened, you know, not that long ago, 2008, you know, the market was down 50, 60%, um, and took quite a while. And in fact, in 2000 to 2010, 2012, it took 10, 12 years to get your money back. So I'm not a big, you know, listen as, as a floor trader, you know, being in and out of, you know, multiple trades every day, managing risk to the tick. Um, to me, uh, a buy and hold strategy where you're hoping that something comes back during, you know, your lifetime. Um, may or may not happen. I'm not a big delete Berlin. Yeah.

Jeremy: So we kind of have an idea of the alpha rotation a that's more of a, you know, based on intermarket relationships, where's the best place to put some money right now it's a very simple model. Nasdaq is going to pull out those top five stocks. And then there's this other model that not as many people know about. It's the ETF model. It's built on exchange traded funds. Maybe it's your most complex model, but it also might be one of the best keys to diversification. So talk to us a little about the ETF model and how that fits in.

Keith: Well, they're, the ETF model, uh, when it's fully invested can go up to nine different instruments, right? Where the Alpha rotation is basically a max of, if you have diversification between three different equity indices, could be a max of three or just one and all stars is a Max of five. This is nine. And the reason for that is there a three different asset classes that it covers.

Jeremy: Okay. So let's, let's slow down. Let's slow down and bring some highlights to this. So you've got a diversification of nine ETFs when it's fully fleshed out. That basically is like a fund of funds. So it's a very heavily diversified approach. Is that correct? It is. And it diversifies all those different things that we talked about. You're talking about asset classes and you're talking about some trends, is that correct?

Keith: Correct. It's, it's, it's, it's a momentum based model, but looking at instead of individual equities, ETFs in sectors, so there's a sector component, there's a country component, right? So we look at 20 different country farms, we look at the 12 or so different market sectors and then we have something looking at global macro. So that's sort of a smattering of looking at, um, all different types of financial instruments, which include, uh, specifically, uh, metals, commodities, oil volatility, solar power, you know, all different, um, ways to look at the market as well as some exposure to, um, to equity market as well.

Jeremy: Okay. So you've got, let me just recap that. That's, that's pretty phenomenal in terms of asset class diversification, diversification. You've got equity, you have international markets with these countries and you even diversify over commodities and maybe some of the less traditional instruments to, to equities. That's correct.

Keith: Correct. And then we put three instruments from each of those three categories. Uh, and that's your portfolio.

Jeremy: So it's not just diversified over asset classes, but it's diversified within that. And that's how you come up with these nine that, uh, that the whole model is built upon. Correct. So when somebody thinks about these three models, it really gives an incredibly diverse approach to the market. Uh, and yes, like we said

Jeremy: earlier, you've actually had hedge funds and professionals using, if not these exact models, the precursors to these models. Is that correct?

Keith: Yes, absolutely.

Jeremy: So a person sitting at home, let's say they have their, their Roth IRA or whatever retirement vehicle that vehicle they've got and they want to create sustainable growth, but in a balanced way. Kind of like what you talked about with that hedge fund approach where they have the equity curve going up, but without the massive drawdowns from, you know, the occasional market hits, how might those people consider diversifying with these models?

Keith: Well, I mean, to keep it really simple, um, you, you have allocated to investing, you know, you, you can say, uh, I'm going to allocate x percent of my equity to this, uh, to these three different approaches and basically put a third, um, a third of your money equally into each month. If you get more familiar and more sophisticated, dynamically adjusting how much you're putting into each of the models, um, as a percentage is something you can do once you're a bit more familiar or sophisticated. Um, and I'm familiar with the models. So at what is a very straightforward and relatively simple approach is whatever you want to invest in this type of approach, put a third of your money and to each one of those models.

Jeremy: Okay, so that's not just, that's not just diversifying into one fund, that's like getting three different funds you're diversifying in. So the Alpha model is its own diversification. The Nasdaq model is its own diversification. The ETF model is its own diversification and as an entirety it provides that that stability for equity growth with minimize drawdown. Correct. Now, let's be clear on this market gauge models. They don't do all the work for the individual. They just kind of do some of that hard work of picking the direction and telling you how to allocate the model, tells you where the money needs to go. It tells you how it flows, but it's the individual that still has 100% of that decision making power. Is that correct? Yeah. I mean basically you're your own man, so you're giving the people the tools to manage like these big wigs on Wall Street, but for individual retail persons accessibility. Correct. Let's say that the model makes a trade alert and it says you need to go do this, is there ever a time that you might ignore that completely?

Keith: There might be times now listen, it's the models, you know, proven their track record, um, you know, is basically transparent every time. Uh, and we let people know there's a backtested part, um, and what we call, um, the actual part or simulated, which means from a legal or technical approach, we put out a recommendation or we put out, you know, a suggestion that the model as you know, uh, indicated to make a change, we'll put that out and it's up to you to execute it. Now, um, as a professional myself, there are times where I might find tune the entry using maybe some shorter term techniques, but on balance I'm pretty much trying just to replicate what the trade is at the time and the way these models where we issued the trade and it's pretty straightforward. It'll, the performance is based basically on what we tell you at the time. We do it without any finesse.

Jeremy: Okay. So Keith, what you're saying is an individual doesn't have to come in here and add additional intelligence. The model itself tells them when to buy, when to sell, how to manage the risk. It does basically everything. And even though maybe they want to, if they, if they would like to add some of their own intelligence, they don't need to. How do these models perform over time? What kind of results have you seen?

Keith: Well, if we do a blend, and remember this is not, uh, uh, audited or per se, this is a hypothetical, our results. But if you follow the signals religiously across the three models, right? The, um, the return right on the blend since 2007, right? So this was before the financial crash. And one thing I want to say is a lot of people who supplied this information, you know, do it during a period where the locker was all in an uptrend. Well, we deliberately went back and our testing, and this is, uh, an hour back test here, uh, including some, you know, since 2014 depending on the model, the actual, uh, uh, recommendations were produced without the benefit of any hindsight. The blend since the back test and set and, uh, inception, which goes to 2007 is 686% versus the s and p total return during the same period of 146%.

Jeremy: Wow. So those are astounding results. You're saying that diversified over all the models over a 10 year period, 11 year period, um, these results are giving a five or six times better performance than the s and p alone. And that includes before the financial crisis in 2008. Yes, absolutely. And some of those results were back tested results, but for the last several years, those have been actual trade results. The real triggers as the model spit them out.

Keith: Yes, they have. In other words, we put out an email alert that can be, you know, verify that everyone got who subscribed to this from depending on the model. But starting around 2014 when we started building these various models, um, that's what we call a simulation trade because it works without the benefit of any hindsight.

Jeremy: Yeah. I don't know if you realize this Keith, but according to the standard and Poor's, I think it's about 92 I'd have to go back and look at the, there was the report again, but it was 92 or 93% of professional fund managers cannot match the performance of the s and p 500 over a 15 year period of time. And some of them do it for a year or two. Some of them do it over five years, but over 15 years it's 92 or 93% cannot match the s and p 500 and what you're telling me is your model not only matches it, it is beating it and it's consistently doing it over time. It's stabilized that equity curve that fund managers worked so hard to stabilize.

Keith: Absolutely. Now the other interesting thing is, uh, our blended maximum draw down was minus 11%.

Jeremy: So if you did, if you did all of the models, your total draw down at the absolute worst was only 11%.

Keith: If you did all three together at exactly the time that we said to do the trade. Yes,

Jeremy: that is fantastic. I don't think somebody can can ever, uh, on their own come up with such a great model. I mean, it's just, it's pure genius I think. Course. I, you know, I think that your stuff is genius. Uh, let's talk about this for a moment. Your wife, um, mische short from Michelle, she's a fantastic trader and she, she does teach a lot of the discretionary trading techniques, which for those of you not as familiar with the word discretionary, discretionary just simply means individuals making their own decision at their own discretion. That's what discretionary trading is. And for

Jeremy: Mish, you know, that's what she does and that's really what we've taught at trade smart for all these years. How does a discretionary trading plan fit in with these ideas of these algorithms and overall management for your, for your money?

Keith: I think it totally fits because as part of the strategies we w we identified a couple of different edges here, right? Um, the Alpha rotation looks at him to market relationships where there's, you know, this, uh, uh, anomaly of momentum. Um, and you know, there were a couple of the others. So the, the other thing is there's something to be said for a, someone who was sick, you know, knows what they're doing as good at risk control and can put together things, um, in a way that maybe a algorithm camp, um, or that it, uh, in a discretionary system, uh, you may even get input from mechanical models or quad based models. That's just an input. So there's definitely a place, in my opinion, for discretionary trade check, the everything. Um, and even your discretionary trading should be based on tools that have some statistical edge in them and combining them in a unique ways. That's an art form and there still are.

Jeremy: Yeah, there's still art to the market, which I always say that you know the market's more art than science, but what I understood from this interview is an individual has a discretionary trader. If they take maybe 15% 20% 25% of their account, whatever they're comfortable with, and they manage that for their day trading or for their short term swing trading or they're active options that can be kind of their, their little 2020 5% corner, and then let's say they took the other 75% and they put a third of it into the Alpha model and they took a third of it and they put it into the Nasdaq model and they took a third of it and they put it into the ETF model. What you're telling me is that individual on their own, within all of their own power without having to hire a big fund manager without paying all those fees, they've got the diversification that you would have approached four or five different strategies, same kind of diversification that you would have been targeting at millennium partners. Is that right?

Keith: Absolutely. No, that's what the millennium partners was farming. So I mean they would have people, uh, with specialties, right. And each one of those would contribute. At the time when I was there, there were only there a small, uh, on a relative basis now that are running 40 or 50 billion or some crazy number. Um, uh, you know, a huge number, very successful, but they had different people doing different strategies.

Jeremy: And let's, let's also be clear to it, for the average individual retail trader, they can't call millennium partners and say, well, you do this for me. There's this weird SCC rule called qualified investor. And if people don't match that criteria, which is a certain net worth in a certain income, these hedge funds can't even take their money. That's right.

Keith: Well, they can't take their money. But guess what the biggest, I mean, this is no different. What, what's happening though in the business world is winners take all. So, you know, right? Think about what's happening with social media. You got Google, you got Facebook, Amazon is coming along and you know, these are, you know, your key players. Everyone else has crowded out, all the money goes to the winners. That's even more so in hedge funds. So all the money is being absorbed by the winners. And remember we said that most managers can't add perform over long periods of time. That's right. So what's happened is that the big fuss get bigger and they're close to the average investor and some of them are even close to the, um, to, you know, pension plans and et cetera or, or just closed period. So like for instance, renaissance is closed to outside investors. They gave back all their money and they only trade their internal thoughts, tens of billions of dollars.

Jeremy: So it's not just hard to beat the market, it's not just hard to find a fund manager who can manage your fund. When you do find them, you've got to somehow get your foot in the door and get them to take your money. And the average person that's sitting at home with a quarter million dollar or $500,000 Ira, they're just not that interesting to these big hedge funds that are actually doing these kinds of results. But with your models, with the market gauge, that's the same philosophy that you were using 20 years ago with with millennium partners adapted a little bit for modern times and here these individuals can get that kind of expertise relationship with these tools. Is that correct?

Keith: Yes, that is absolutely correct. That's, that's the objective. Okay,

Jeremy: so big picture, portfolio management, relative discretionary trading, big picture portfolio management, that's a much slower game. That's more that the long term and you're not going to get as many signals. You're not going to be moving your money as much. You know, for a day trader, they may move their money 10 times during the day, but for this bigger picture, this is a slower game. But the outcome is to smooth that equity curve to have lower draw downs and overall higher gains. Am I articulating that correctly?

Keith: Absolutely. I remember if you going to be a super active trader, um, your edge better be really strong because all of a sudden you're starting to bump up against these algos and high frequency trading operations that are designed to, you know, take a small percentage every time you trade. And so it's very difficult to beat them because you know what, it's not even that they're that all that smart. It's just that they could read the order flow before it even hits the floor or you know the electronic trading floor. So you're being game if you're super active. Yeah. So that means the whole idea of an edge has to be, unless you've got the infrastructure where you can invest in a hedge fund that has that type of infrastructure, you're going to need to maneuver at a frequency where that type of slippage is not a major piece of the profit.

Jeremy: Yeah. I think that's probably why. Maybe more on a subconscious level. I have gravitated personally away from that style of trading. I, I've just never been a day trader or haven't enjoyed it. I don't like to sit in front of a computer all the time and for me it's always been more of the swing trading two weeks to a couple of months into a trade. What I love about these models is it fits perfect with that. As an act of swing trader can be relatively active but have a life, you know, for me, coach baseball for my kids, for other people, whatever they might want to do, spend time with grandkids, have another business. And then having these market gauge models is just such a nice piece to well rounded it out and you're not paying that 2% a year of your entire portfolio for management fees. You're not having all this overhead, this solution. Uh, Keith, I really think it's, this can help so many people. It really can because it's such a practical solution, it's easy to follow and it gives such a balance, professional attention to detail, but in a way that the average retail trader can use it. Let me ask you this, how does your market, or your models, I should say, how does your models handle the bear market?

Keith: Well, in fact, what they're, you know, listen, as a floor trader going through the commodity cycles and also because you have, as a member of the exchanges, infinite leverage. There was no edge to being buy and hold and just be long. So that meant you had to figure out how to make money on the short side because let's face it, you know, it was great when silver went from five to 50, but it also went from 50 back down to five during the same period. So net net, um, these models are designed to either one take advantage of the downside. And one thing that's really nice is there's lots of ets out there, which um, the uh, short selling rule, um, can be, um, uh, Verdun and in fact an IRA accounts right, where you can't go short on if you could buy an inverse ETF, you get around it. So specifically the ETF complete, um, has um, built into it, um, the ability to take advantage on the down side and turn a profit.

Jeremy: So what's you're telling me is you have taken, well you're telling me is you have taken and built into this model, does these models an algorithm that adjusts and when the market turns substantially bearish, like 2008 it'll put your money in inverse funds that the average trader can still trade in their retirement account and they can win with it. Is that what you're saying?

Keith: Yes. Right. Because you know, even if it's in your retirement account and you want to, you know, bet on the downside. Well Hell you can definitely buy, you know, a short, you know, instruments that go up when the market goes down and they're in the mall.

Jeremy: So is it fair to say Keith, just transparently here, you know Ray Daleo, one of the great hedge fund managers, one of his core mantras is radical transparency. So in the spirit of Ray Dalio and radical transparency, is it fair to say that an individual retail trader who is not considered qualified by the SEC standards, is it fair to say that for that individual, something like market gauge is maybe the only way that they could get access to that level of fund management intelligence and actually beat the market?

Keith: Well, I hate to make statements like we're the only one, but, um, in terms of our trading models, um, I think that, um, they certainly rate, um, favorably even against the majority of money managers, professionals out there. So the answer is yes. And you know, in, in, in, uh, terms of radical transparency, um, you know, like everything else, um, there is certainly risk that things could change. Uh, the, you know, algorithms could get smarter and humans are completely outmoded. I mean, who knows. Um, you know, it's a, it's a big debate, but, um, at the moment I would say, you know, there are probably, um, I, and I'm not aware of them. They're, they're, you know, they're probably other companies that might have, uh, other approaches. Um, you know, similar, which I'm not aware of and it may not be available to um, you know, non institutional or super high net worth individuals. So we're definitely trying to do something that is not readily available to mainstream investors.

Wrap Up

Jeremy: Yeah. And I think I may have said the only way, I intended to say one of the only ways, uh, but I can verify having been in this industry for 20 years, there are just not many other options to something like market gauge and I've never seen anything like market gates that has the results that you guys have had that is so accessible, uh, for so many people. So that's why I'm a big fan. That's why I tell everybody it's a great tool. It doesn't replace your discretionary trading. It's in addition to, it's an additional piece to your overall portfolio management, your overall planning for how you take advantage of these paper assets that we call the market. So a, Keith, I appreciate your time so much. This has been an incredibly educational hour and a half that we've spent together almost an hour and a half. And, uh, I just really appreciate your time. I know our listeners appreciate your time and if people want to learn more about you, where can they go?

Keith: Oh, go to market gauge.com and there's a, that's our website and it tells you all about us. And um, some short bios about the, uh, you know, our partners.

Jeremy: Okay. So market gauge.com is where you can learn more about Keith Schneider and his wife Michelle. Uh, also known as Mitch. That's her nickname, which everybody really calls her Misch and his business partner Jeff, which we didn't talk much about today, but Jeff's a great guy as well. And of course a trade smart u.com. That's the website for Trade Smart University. And for those of you who don't know, we have all of the market gaze models integrated into our, you can actually get them directly through trade smart as well. And I would not do that if I did not believe in these models. That's how strong these are. So a, again, key. Thank you so much for the time. It's been incredibly educational, very helpful. Is there anything else you'd like to add at the end? No, thanks for um, this was great. I enjoyed it. It actually made me step back and think, uh, uh, it was nice to reminisce a little bit about the uh, the past and uh, and history, well I appreciate the trip down memory lane with you and maybe what I didn't highlight as much folks is Keith actually is like a certified genius.

Jeremy: He's like the Albert Einstein of trading and I'm not blowing smoke. If you look at him, he kind of looks like Albert Einstein. And so it's truly these people that are listening right now, they are getting to listen to a true genius and someone who I think the future in the history of Wall Street may look back and say that was uh, uh, you know, an Einstein, a genuine expert that just showed up timeline in history and contributed to the world. So thank you for your contributions and thank you for sharing with us today. Well, thank you. I'll probably next time what I'm going to need to do is brush my hair. Ah, well, fortunately as we like to say in the entertainment industry, you have the perfect face for radio. Thanks again, Keith, and thank you to everybody for listening and until next time, happy trading to all of you. We'll talk to you soon.

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