The Derivative - Charting a Chinese Commodities Course with Fred Schutzman of Abingdon Global

Episode Date: August 19, 2021

What do you do when trends stop appearing for the quarter of a billion dollars you manage? Where do you go to find markets like the ‘good old days’ for trend following? Our guest for this episode, Abingdon Global’s Fred Schutzman is in a unique position to answer those questions – and much more! Listen to Fred share his background being a Chartist, working at CRB, why technical analysts have holes in their shoes, how easy it seemed to find successful trend models 20 years ago, the rise and fall of Briarwood, sleepless nights with a quarter of a billion on the line, why 10,000 trades are better than 1000, why 3 models are better than 1, and thoughts on Queens, Acid, Coke, Iron Ore, gaining exposure to China, to inflation, to dollar weakness, the perfect NY slice, and eating his own (Chinese) cooking. Chapters: 00:00-02:29=Intro 02:30-29:37= Technical Analysis = Holes in Your Shoes 29:38-39:29= Trend Following Tigers Changing their Stripes 39:30-59:06= Deep Chinese Markets, Acid, & 10,000 Trades 59:07-01:31:31= The Model, Magic Darts, and Eating your own Cooking From this Episode: Listen to the previous podcast with Fred Schutzman here: Trading Chinese Futures Markets with Abingdon Global Listen or Watch Modeling Markets and Accessing AI with Robert Rotella and Jag Prakasam Listen or Watch Asian Markets, American Investments, & Accessing (Chinese) Futures with Alvin Fan of OPIM For more information on accessing China markets, contact Matt Bradbard at RCM (312.870.1653) Don't forget to subscribe to The Derivative, and follow us on Twitter at @rcmAlts and our host Jeff at @AttainCap2,  or LinkedIn , and Facebook, and sign-up for our blog digest. And visit our sponsor, the CME Group at www.cmegroup.com to learn more about futures and options. Disclaimer: This podcast is provided for informational purposes only and should not be relied upon as legal, business, or tax advice. All opinions expressed by podcast participants are solely their own opinions and do not necessarily reflect the opinions of RCM Alternatives, their affiliates, or companies featured. Due to industry regulations, participants on this podcast are instructed not to make specific trade recommendations, nor reference past or potential profits. And listeners are reminded that managed futures, commodity trading, and other alternative investments are complex and carry a risk of substantial losses. As such, they are not suitable for all investors. For more information, visit www.rcmalternatives.com/disclaimer

Thanks for listening to The Derivative. This podcast is provided for informational purposes only and should not be relied upon as legal, business, investment, or tax advice. All opinions expressed by podcast participants are solely their own opinions and do not necessarily reflect the opinions of RCM Alternatives, their affiliates, or companies featured. Due to industry regulations, participants on this podcast are instructed not to make specific trade recommendations nor reference past or potential profits, and listeners are reminded that managed futures, commodity trading, and other alternative investments are complex and carry a risk

of substantial losses. As such, they are not suitable for all investors. Welcome to The Derivative by RCM Alternatives, where we dive into what makes alternative investments go, analyze the strategies of unique hedge fund managers, and chat with interesting guests from across the investment world. It took me a while to actually take his advice and learn how to program, but once I learned how to program, it changed my life. I was able to backtest every concept that I had learned in all the books on technical analysis and all the classes I took and all the actual work I did. And I was able to determine what worked and what didn't.

And, you know, technical analysis is a difficult, difficult process because many times everyone applies it differently. And beauty is in the eye of the beholder. So I backtested the way I personally view charts. Someone else may backtest differently than I did. But when I did it my way, I found that anywhere from 95 to 98% of technical analysis did not work, did not make money, was not tradable. All right. Hi, everyone. We're here with a guy who's been around the trend following, technical analysis, fund management business so long. He's sort of gone full circle back to the beginning, now putting his quiver of systematic models onto the emerging derivatives markets, which are Chinese futures. He's our friend, Fred Schutzman of Abington Global, back on the pod. Welcome, Fred.

Thanks for having me, Jeff. Good to see you. You at home there? Yeah, I'm at home, Forest Hills, Queens. Forest Hills, Queens. It has a little Queens vibe. And then we'll get your New York accent. I love when you say chart. Give us a chart.

Chart. We'll spell that out. So what's it been like? You guys go, you said you just got home. So are you going into the office? Are many people going into the office? You know, most people are not. If you don't have to, there's really no reason to. Yeah. And where would you go to the office if you were going? Downtown Manhattan? Downtown, the World Financial Center. So we covered your background a little bit on the pod last April, and we'll put links to that pod in the show notes so people can go back and get the extended version. But for now, if you just give us kind of the big highlights

of your career as a futures market trader and investor. Sure. I started out in 1986 as a technical market analyst, a chartist, basically. To be correct, you know, more specifically, I worked in at the Commodity Research Bureau in the chart room. I'm the guy who held the paper to make sure that the lines were printed properly. So I started off producing the chart, helping to produce the chart book back then. You know, in the old days, they produced manual chart books once a week. That was 1986. I graduated, went on to become a technical a full-fledged technical market analyst I really enjoyed what I was doing but I didn't know if it worked or not

Real quick Commodity Research Bureau that's like CRB and those books that used to come out that's not a government agency that was a private company or whatnot? Private company owned by the Gila brothers, yeah. Are they still around? I think we used to get CRB data.

The CRB index was a futures market, futures contract for a while, right? Yes, yes. And it might still be. I believe it still is, actually. Well, if neither of us really know that, that's probably not very liquid. But back then, there were 27 markets in the CRB and Bill Gila was still there, but he had just retired. He wrote a famous book, I think, in like 1962. I forget the exact name of it, had to read charts or something.

But when I worked there, John Murphy was basically taking over for Bill Giler. He was writing the front page commentary. And I had the privilege of working with John Murphy. Nice. And so you're like literally hand drawing the charts or they're not hand drawing. The machine was drawing them. I was just making sure that they plotted properly on the paper. And if, if the chart wasn't proper,

I pulled the paper out and put another piece of graph paper in. Right. Start over. We'll have to look that up where those guys are now. So sorry, then you question yourself of whether this charting stuff works. I became a full fledged technical analyst, joined the Market Technicians Association, passed the CMT exams. And I really believed it worked, but I wasn't getting any feedback. It's as if someone went to medical school to become a brain surgeon, but never did any operations. How do you know the theory that you're learning in school could actually save someone's life?

How do you know it works unless you perform an operation? Yeah. So I wanted to perform an operation. You wanted to start cutting. I wanted to trade. And I figured the only way to determine if my knowledge, you know, if what I knew actually worked and actually made money in the markets was to

buy and sell commodities. Yeah. For your own account. For my own account initially, and then for client accounts. You know, I was always skeptical of the industry because every technical analyst I spoke to called every bottom and every top in the market. Everyone selectively remembered their successes and forgot their failures. I wanted a report card. I remembered my school days and I appreciated school. I like going to school and getting a report card. I knew how I stood. I knew how well I was doing and trading, I felt would, to some extent, give me a report card. Yeah. So you would say that the ultimate report card, right?

Yes. Yes. I mean, obviously there are traders who are more skilled than others. But I felt that even if I was a mediocre trader, having these tools at my disposal, I should certainly be able to generate a profit. And so that led into Briarwood? That led into Briarwood. And it was probably a five or 10 year process. I didn't realize how difficult trading actually is. Knowing how to reach odds doesn't, you can't monetize that skill immediately. Thank God you weren't doing the brain surgery you mentioned mentioned you might have lost a few of those early patients exactly so uh first step was trying to understand how to actually apply this theoretical knowledge in the markets and how to get out if i

was wrong you know in the beginning i figured, I figured I'm always going to be right. What do I need to stop for? So first thing I had to learn was how to place a stop loss order. And then after a few years of doing it, I realized that I need to backtest these concepts. And the only way to backtest these concepts is to learn how to trade. And, and a famous, you know, I was very fortunate, early on, a famous commodity trader, Robert Rutella, was, you know, I knew him from the coffee floor. And also, we were both teaching at the New York Institute of Finance. Robert was very generous with his time and advice. And basically told me, if you want to get anywhere, you have to learn how to program. Yeah, he's been on the pod, we'll put a link to his notes in there or a link to his pod as well.

I'd forgotten about that connection. That's cool. And it took me a while to actually take his advice and learn how to program. But once I learned how to program, it changed my life. I was able to backtest every concept that I had learned in all the books on technical analysis and all the classes I took and all the actual work I did. And I was able to determine what worked and what didn't. And, you know, technical analysis is a difficult, difficult process because many times everyone applies it differently and beauty is in the eye

of the beholder. So I back-tested the way I personally view charts. Someone else may back-test differently than I did. But when I did it my way, I found that anywhere from 95 to 98% of technical analysis did not work, did not make money, was not tradable. Give us an example of a selling selling when a market's overbought um i'm sorry selling when a selling when a market's overbought or buying when it's oversold did not work actually the the opposite worked a little bit better probably better off buying when the stochastics is 90 right and some would say? Like to say 95% of technical analysis doesn't work. Like you still have to create a strategy on the analysis. So it's not that the analysis doesn't work. It's just the strategies built purely off of that might not work. Exactly. And I was going

to clarify that myself, not that it doesn't work, but for me, a concept that works is something I could, number one, objectively define. And number two, generate enough of a profit to give me a net positive return after overhead. And overhead is basically slippage in commissions. You know, for a concept, you know, it doesn't pay to trade a concept where I'm going to break even and then end up losing money after, you know, paying commissions and slippage. Not only do I have to make it a small profit or, and then some, but I have to make enough of a profit to make it worthwhile to trade. Why risk a dollar to make a dollar one if I'm taking a lot of risk? For sure. And how did you tend to tilt in your modeling towards more of like a positive skew, long volatility type models, right? Like you can

take the analysis and go either way of like nine times out of 10, this thing reverts. So I'm going to trade that. But you're saying maybe the 10th time I only have to risk a dollar and I can make $25. That seems like the better opportunity to me. For me, it has to suit your personality. That always fit my personality. I was always comfortable being a trend trader. I like the idea of being right, maybe 38, 40% of the time and making nice profits in the long run. I didn't want to be an option seller, for example, where I could be right 99% of the time. And then if my strategy is not perfect, blow up on trade number 100. That fit my personality. And when we started, I wanted to build something that, you know, I would be comfortable trading and I would be able to stick with because

a system is worthless if you're not going to trade it. Yeah. Yeah. And it's so funny to say out loud, right? Like I'm, I like being right. 38% of the time, right? Like what? Nobody, nobody, you don't actually like that, but you're comfortable being right there. In a perfect world, you could be right 98% of the time and still have the same risk profile, but that's extremely hard to do. Exactly. So once I learned how to program and I saw what didn't work and what did work and, and a lot, you know, I, a lot of other technical concepts I appreciate and I think are valuable and I think they're helpful. You know, just from my perspective, being able to objectively define and program and come up with tradable concepts,

there wasn't much I could do. For example, Elliott wave theory, I was always a big fan of Elliott wave theory. To this day, I think it has a lot of value, but it's not something I could make work objectively. So when you were just a chartist and looking at the charts, you're drawing the ones and twos and threes. And what is it? There's five waves, right? Five waves in the direction of the major trend, three waves against. Right. So you're putting those numbers on a chart and you're like, this is great. When you went to test it, not so great. Exactly. In gold recently, a few weeks ago, a friend of mine who I had worked with for many

years, I had helped build him a divergence indicator. He's very big on divergences. And gold had a positive divergence. So he goes, hey, should I buy gold? It has a positive divergence. I said, it's not something, you know, I'm not a divergence trader to begin with. But I said, one thing makes me a little uncomfortable here. And gold sold off in a five wave pattern. That was something I had noticed. And the divergence was perfect. It rallied for a few weeks and then came down afterwards. But that five wave down move sort of spooked me a little. So from a subjective

standpoint, it was something I was uncomfortable with. You know, many times I'll look at a chart and if I see a market rallies in five waves and then starts correcting, I begin to get excited because that five wave advance tells me, hey, the trend is now up. Yeah. Even though I'm a system trader, old habits are hard to break. And I still subjectively look at charts and try to form opinions. And part of the reason I do that is and I'll go into this in more detail. But, you know, that is the way I started in the industry. And that's how I developed my trading, my trading systems. Everything to me was looking at charts, coming up with concepts first, and then building trading systems from that. I used to teach a class in technical analysis and building trading systems. And I always spoke about throwing dots at a dartboard. What many people do is they'll throw 100 dots at a dartboard. And the three dots that hit the bullseye, those are the three magic

dots. Yeah. What I like to do is, in advance, say, Jeff, look, I have 100 dots here. These are your three magic dots. Here they are. In advance, before I throw them, now let me throw them at the bullseye and see how well, see if these three magic dots outperform the other 97. And maybe these are my three magic dots because they have all their feathers. They're equally weighted. You know, I mean, there's some reason, rhyme and reason behind that. Yeah. And when I you know, if I'm looking at a chart and I'm developing concepts, it has to make sense to me. I've seen systems where if it rains the third Thursday of the month in Paris, buy soybeans in Chicago. Maybe it works for the last 16, 17 years, but it's not something I would trade because it doesn't make common sense to me. Right. And so how do you weigh that? I think a lot of our listeners are going to hear you and be like,

this is so old fashioned. Who looks at charts anymore? Right. AI just crunches all this data. They don't care what the chart looks like. But to your point, that AI could easily shoot out like something nonsensical. Like if this happens, right, if it's 2.26 p.m. on a Wednesday, don't take the trade because the last 62 Wednesdays that you know occurred doesn't have any bearing on whether that's going to occur this next Wednesday but and this is what works best for me this is what I believe in you know my thought was I was a good I felt I was a good chart reader and by looking at charts I get ideas so if I look at chart after chart after chart, and I, you know, I develop certain concepts of how markets work. And then I set out to build trading systems that basically emulated the way I subjectively analyzed markets. And I felt if I could do that, then obviously, you know, the computer is doing the same thing I am, but the computer is a lot more consistent

and disciplined than a human. And it should have better results in the long run. Yeah, it's just, it's weird to me, right? Like if you said, you get some global macro guidance, like I just take my experience of analyzing sectors and this and that, and I've coded my experience into a model. I feel like people give that, if they're voting one out of 10, like, oh, that's an up with a model. These days, they're going to be like, charts? Are you kidding me? Nobody does that anymore. And I feel like they'll go on the other side. But why do you think that is, that people have kind of moved away? That certified market technician never really took off. At least to me, what I see on FinTwit, on Twitter, if people put up a chart with some lines and everything, you know, 80 percent of people come back at them like, oh, let me draw a smiley face here or whatnot. So why do you think we've moved away from charting as a legit, legit thing? A few reasons.

One, it's a skill that you can never monetize. You know, I remember in the old days, you know, being in New York, I was able to rub shoulders with the top technical analysts, you know, alive. You know, people like John Murphy and Ralph Ancompora and Alan Shore and John Tyrone. I mean, those were four of the classes I took at the New York Institute of Finance. I mean, big, big names. The problem is technical analysts never generated income for firms. And, you know, back then you were able to get a job as a technical analyst. But year after year, companies just let their technicians go because they weren't profit centers. They, you know,

they didn't consider them valuable. And now, you know, I mean, I haven't looked for a while, but my understanding is now not that many technical analysts are really employed. Yeah. Well, they'd rather have the quant, right, which is funny because they're so similar in nature, but they're able to program it right out of school. Exactly. They are similar. And a knock on technical analysis, because I would imagine a quant would probably say the same thing, that very few concepts they actually use. Yeah, I think you're in the majority there for sure. But I think most people have that feeling of like this technical analysis, it's all like you said, beauty of the beholder, or in the eye of the beholder and what you do with it matters. It doesn't just work straight out of the box.

Yeah. So, you know, the problem is technicians really couldn't get paid. So there's not many technical jobs out there anymore. Not only that, they had a bad reputation. This friend of mine, Dennis, who I worked with for many years, he gave me a job. My first job in money management was with him. And from day one, he was a big fan of technical analysis. But from day one, I'm trying to think of the exact quote. It was something to the effect that all technicians have holes in their shoes. He tried to impress upon me from day one that technicians that never trade really, you know, they don't make any money. Yeah.

They're analysts. They're not well-paid. They can't trade to save their life because they've never done it. Not because they're applying the wrong concepts. It's just a long learning curve. It took me five or 10 years to actually take my theoretical knowledge and become profitable. I think you see the same thing in the quant space today. Like when they come straight out of school and they're, they're green, they're deer in the headlights when, you know, presented with real money problems a lot of times, or, Oh,

if I'd known then what I know now, right. Of like the risk controls and all of the, you know, degrees of freedom that they don't think of in their first iterations of their code and whatnot. Exactly. Now, I always felt technical analysis was very helpful because it helped me understand how markets worked, how they traded. And if I could understand how, what is a chart? It's basically a pictorial view of human behavior. So if I could understand how people are buying and selling by looking at charts, I thought it would, you know, it's of great value. And anyone, if you could understand markets and understand how markets work, I think you have a big edge when you're trading trading systems. Whereas if you're right out of school, if you're a Kwan, if you throw 10,000 ideas at the computer and come up with two or three systems,

you know, how do you know, how do you know they're actually going to work going forward? You know, the magic starts. Exactly. Obviously, some dots are going to hit the bullseye, but that could be pure coincidence. So, you know, I mean, I remember when I started out and and I was so fortunate to spend time with Ralph Ancampora. And every time I spoke to Ralph, I was amazed at how much he knew about markets. And I, you know, from early on, I said, if you could take this knowledge and somehow objectify it, somehow program it, I strongly felt that it could do well in markets. And that has been an edge for me, understanding how markets work. When I build a trading system, I'm building a trading system

that number one is rooted in common sense and number two, backtests well. But if it doesn't make sense, if it's not something that you would expect to continue to occur in the future, there's no sense in trading it. Just because something backtests well, just because it's the magic dot,

doesn't mean anything. The object of the game is to make money on the right side of the chart, not the left side of the chart. But I went the, you know, I took the scenic route. I learned, I learned how to, I worked various jobs. I worked, you know, plotting charts. Then I worked writing commentary that, you know, then I was a full-fledged technical analyst. Then I worked with some money managers. Then I learned how to program. Then I formed my own CTA. But if I were to learn how to program early on, the 1980s, you could have been

making 100% a year. Yeah, you and John Henry. Or Richard Dennis and the Turtles. These traders, they were making 100% a year back then. Right. With models I could write in Excel in like 30 minutes today, right? Exactly. Exactly. So by the time I got started, which I was late to the party, by the time we were doing really well, the party pretty much ended. So I was fortunate. I was able to make some good money. You know, Briarwood had as much as two hundred and forty seven million dollars on the management at our peak. But if I would have started 10 years earlier, who knows?

We would have had a lot more. Yeah. And if I would have started five years later, I'd probably have no money at all. I have friends in the industry who are smarter than I am, and they really haven't been able to make money, but it's a function of markets. It's difficult to make money nowadays, whereas in the 1980s, 1990s, 2000s, anyone could have made money. When I was teaching one of my classes, I remember telling people it's easy to make money. You know, moving average system is profitable over the long run. It is not difficult. You know, back then it wasn't difficult to build a mechanical trading system that would give you a decent risk reward ratio that you could trade live. Now it's exponentially harder. I love it.

So wanted to dig into that a little bit of why, in your view, is trend, especially trend, so difficult the past 10 years in the U.S. markets? What's what's going on there? I guess the honest answer is I don't know. Perfectly honest. honest, but I suspect it has to do with the economy and the fact that markets are manipulated to a certain extent. Interest rates have been held at artificially low levels for many years now. Central banks continue to intervene in the currency markets. And historically, that's where CTAs made their money. Briarwood made most of its money in currencies and interest rates. And if those two markets aren't moving, if they're not profit centers, it's a lot harder to make money. Also, back then, you know, I remember interest rates were like 5%

in the good old days. And you could break even trading for the year and still show a 5% profit. Right. You could post margin as T-bills, you know, post the T-bills for the margin. But do you think, so which came first?? Like so those simplistic models we were talking about in the 80s, just throw one of these out there. Are we saying those stop working because the Fed was kind of suppressing the volatility of those markets? Or you think those stop working because more machines came in or because these got too big? You can argue that people were taking the edge out of the market as more professionals entered the market. And that was certainly true. It was easy to make money, say, the 1980s, 1990s.

It started getting a lot harder in the 2000s. So even if we didn't have this type of environment, if markets were allowed to trade freely, if currencies, if interest rates just traded based on market forces, I suspect CTAs will have a resurgence. They will do a lot better. But, you know, a lot of the edge may have been taken out of the market. You have more CTAs, more professionals competing. So it's not as easy as it used to be. And, you know, that could be a factor as well. But, you know, everything works in cycles. And if you remember the stock market, you know, the last decade in the stock market was the 2000s. And stocks have been roaring for the last decade, the last 12

years now. Maybe the same is true in the commodity world. And I suspect it is that, you know, it's been very difficult to make money, say, the last six years or so. I suspect the next six years or 12 years may be a lot easier that markets will trade more freely. Yeah. In my comment, I was always like, is it too big? I think that's been debunked a few places. Right. It's still a relatively small percentage of especially interest rate and stock equity markets. Maybe if you're talking something like palladium or something. But in terms of the main markets where they usually drive their profits, I don't think it's too big. And then it comes back to like, is it AI and prop firms kind of having figured out and can easily, right?

They can easily put, you know, a proxy of what all the CTAs are doing into their systems and know where the buying is going to come in, know where the selling is going to come in and get in front of that or behind it or whatnot. So I think that can kind of abbreviate some of those simplistic signals and let people get in and out a little better. Yeah. But keep thinking of what my partner, Stephen Klein, has been saying. And I agree

with him 100%. Stephen feels that a lot of people basically change their methodology. You know, if it's not working, if the system no longer works, they change the system. They're basically optimizing it to markets. And if you, you know, look at the CTA world, it was easy to make money for many years. Briarwood made money 15 years in a row from 1996 to 2010. You know, got a lot harder, say, you know, then it got choppy. But from 2015 on, it got significantly harder. Yeah, I think all our clients came in around 11. So thanks for that. Stephen's of the opinion that a lot of people who had profitable systems back in the day,

say from 1996 to 2010, when this system stopped working, instead of saying, you know, maybe it's the markets aren't trending anymore. Instead, they said, oh, now we have to modify our systems for current market conditions. So people have modified their systems to, say, the last six years or so. The problem with that is if markets revert back to the historical norm and they begin trending again, the systems won't work. And this came up because we, as you know, Abington trades China for RCM. Yeah. We're providing RCM with signals to trade the Chinese futures markets. And the signals have been very profitable. And, you know, it's not that we're doing anything magic.

It all goes back to what John Murphy told me from day one. And that was the holy grail is knowing what markets are going to trend and what aren't. Yeah. Tell me if you could develop an indicator that told you which markets were going to trend. You know, that's all you need. Yeah. You could make money hand over fist. Right.

The capturing of the trends, the easier part. And we'll discuss this more, but the Chinese markets are almost like going in a time machine back 15, 20 years. And they're easy to trade. They trend. It's easy to make money. You know,

you could throw many systems at them and they would all be profitable. So what happened was when we went into China, our attitude was we're just going to take the same exact models that we traded in the US with the same exact parameters and trade China. And it seemed like everyone else developed new and unique models for China or changed parameters or did something different. And they all changed their models. You know, what happened was their models, quote, evolved because they weren't making money in the U.S. and they felt their models were broken. So they had to fix them. And they apply, you know, and some of these people applied their

new and improved models to China and they didn't work. They didn't do well. And it seemed like Abington was doing very well in China and a lot of these other people weren't. And Stephen goes to me, you know what it is? They had these really profitable trend models, but they changed them. What they did was they optimized them for the last two or three years instead of looking at a 20 or 30 year time horizon. Right. Which this has been a common theme on this part of, I can't blame them because it was change or go out of business. Right. And if you're left with those two options, you're probably going to change. Right. I went out of business. Yeah. So there you go. We ended up closing Briarwood. I, you know, I kept, you know, I had many sleepless nights considering this, but my

attitude was the systems were built basically on data that went back as far as 100 years. They worked. If they worked over a hundred year period, I wasn't going to change it because markets stopped trending for two, three, four years. Yeah. You know, my attitude was the systems weren't broken, the markets were. And maybe the best thing to do was step aside. And, you know, it wasn't, you know, I didn't want to build counter trend models, wasn't something I was comfortable with. And it wasn't

something that I felt had a good risk reward ratio. I said, maybe it's better to stand aside till markets revert back to their historical or long-term norms. And when we started trading China, again, we're trading the same exact model, same exact parameters that we had in the US and China, and models are working perfectly. They're making a lot of money. And they would have done horribly in the US over the last few years. So are the models broken, or are the markets broken? I could argue, going back to John Murphy, I could argue just, if you could identify the markets that are going to trend, then we could do very well by applying our models, which are trend following in nature to these markets. So we let China out of the bag there. So before we dig in there, I wanted to read a piece from Prelude Capital and kind of set the stage.

They put this out on LinkedIn. The number of Chinese hedge funds managing more than $1.5 billion in assets doubled in 2020 in China to 63. China money managers currently have $578 billion under management. As compared with $3.6 trillion globally. Chinese hedge funds return more than 30% on average in 2020. The best performer surging tenfold, which I think tenfold means a thousand percent. That's a big number. This compares to an average 11.6 gain for hedge funds globally in 2020. And then the Eureka Hedge Greater China Hedge Fund Index of 88 constituent funds focusing on the region gained 35 percent in 2020. The top 10 percent of those posting an average turn of 80 percent.

So with that as the backdrop and a lot of that is not necessarily applicable, we'll into it why it isn't to what you guys are doing um but with that as a backdrop is you know tell us about and you've already hinted on it but tell us about what you see happening in china why it's become such a hotbed of hedge fund activity uh the market's trend it's easy to you know In the old days, I remember saying, oh, easy to make money. And we made money for 15 consecutive years. And every year I was amazed. I said, I can't believe how simple this is, how easy it is to get a positive return each and every year. And, that party ended. But that is how China is right now. And we'll throw out a quick past performance is not necessarily indicative of future results, disclaimer, but as you lived, right? Yeah, or at so far, so far, it's been that easy. And part of you know, I believe part of the reason is they have unique markets that are not traded anywhere else. You know, in the US, CTAs made their money in currencies and interest rates. And a lot of these other markets are not that liquid, to tell you the truth. You want to trade coffee, you know, or Kansas City wheat or bean oil, you know,

cotton, they're not the most liquid markets in the world. Outside of currencies and interest rates, it's really only a handful of really liquid markets, you know, like crude and gold and soybeans. In China, they have the most liquid markets in the world. I mean, I haven't looked for a while, but maybe out of the 12 markets with the highest volume, out of 20 markets with the highest volume, they maybe had 12 of the 20. But they have extremely liquid markets.

They don't really have extremely liquid markets. They have you know, they don't really have any currency markets. They do have some equity indices and interest rate markets. But in general, 95 percent of what we trade there is commodities. So, you know, like industrial type commodities, right? Basically, yeah. But the beauty is there, you know, you can't manipulate these markets as easily, at least, you know, I mean, the currency markets, you have central bank intervention, interest rates, governments could affect, you know, you know, yields. But in general, you know, what can you do about the soybean crop? What can you do, you know, about crude, you know, there's OPEC, there's other issues. But these commodities, I think, trade better on a technical basis because there's fewer outside influences.

And the chart really determines future price direction to a large extent. And they have unique markets that are not traded anywhere. Such as? What are some of those unique markets that are not traded anywhere. Edwin Dorsey Such as? What are some of those unique markets? David Sherman Iron ore, metallurgical coke, coking coal, steel rebar, hot roll coils. But market, thermal coal, market after market after market, like I said, with tremendous liquidity. And they move like markets moved in the old days. And they don't have as many professionals trading there. It's probably more public participation. Despite my stats I just rattled off of all those billions in hedge funds, which admittedly a lot of those are trading long only in equities, in Chinese A shares.

Yeah. And I'm trying to pick out the winners in the Chinese stock market. And I'm only talking commodities. Yeah. And what? First of all, you really can't trade the commodity markets in China unless you're a Chinese national. The you know, we're not allowed to trade Chinese markets directly. All we do is provide signals to RCM who provides the signals to the client and the client is the one who actually makes the trades. Yes. There's only you know, there's maybe 40 highly liquid Chinese futures markets, and only seven of those are internationalized, where they allow people outside of China to trade them. And internationalized doesn't really include the US. You can't trade them as a U.S. We'll get to that in a sec.

Let me back up. Is a lot of this success, just hearing you rattle off those markets, made me think, okay, but yeah, they're building these cities. The spending in China is well known. Is it all just because they're spending so much and buying all these commodities that the prices are going up, up, up? And that's why it's such a good market to trade. Like all they do is go up, up, up. Are you seeing major down spikes as well? I mean, historically, you make more money on the long side than you do the short side because of the nature of markets. Well, they can go up infinitely and they're capped on the downs. Exactly. And when they move, you know, they can go up infinitely and they're capped on the downs. Exactly. And when they move, you know, they can move exponentially many times on the upside. But I mean, we've traded

both sides. But in general, you're right. They have been going up primarily. And, you know, you're asking the wrong person. I'm a chartist. You know, I don't look at the fundamentals, but you're right. I believe the Chinese economy is the second largest in the world. Yeah, soon to be, by all accounts, soon to be number one over the US, right? Yeah. I mean, I was a speaker with CompuTrack in 1992. We did a tour of Asia. And when I went to Beijing and Hong Kong and some of these other countries, some of these other cities in China, people were riding bicycles. There weren't even that many cars back then. It was a different world.

China has advanced so dramatically over the last 30 years. Their economy is growing by leaps and bounds. And so what you're saying makes sense. There's probably a lot of demand for these commodities because of their tremendous growth and their tremendous growth potential going forward. Right. So it's sort of a way to play that growth potential without getting exposure to these equity markets there. Right. Like we saw that they came out, I think it was two weeks ago and said all these companies that do like tutoring, student tutoring are going to be government owned entities or something. Right. They basically shot all their stock prices down 80 percent in an hour by saying they're right. So that's the kind of stuff that scares people off of China.

I'd like I'd love to be exposed there, but I don't want any exposure to that kind of nonsense. Yeah, I would suspect it's harder because, again, you know, the government could enforce certain rules for companies, for example, how do you enforce a rule for copper? You know, what were you going to say? No one could buy copper. Right. Where, you know, no one could buy copper for the next 90 days. And obviously, you know, that, that would have a negative effect on price. But they they have less power to control the commodity markets than they do other markets. And but part part of me thinks my pet theory is maybe they have the ultimate control. And that's what keeps them kind of more smooth and trending versus, you know, in the global markets where there's no central control. So they're choppier and less easy to

trade. Whatever, whatever makes the markets trend. Yeah. Right. That was going to be my next question. Do you even care? Right. If it's central committeeed trends, if it's demand, infrastructure spending trends, who cares? As long as it's working, you don't care. All we care about is risk and reward. Obviously, if the price of something could go from 50 to 100 in three months and then back down to zero overnight, of course, that's something we can't trade because the risk would be too great. But we don't really care why a market's going up or why it's going down as long as we have a good risk reward ratio. Right. Or even what the market is, right? You don't care if there's enough liquidity. Let us in, let us out, let us do our thing. Exactly. And, you know, we were pleasantly surprised.

You know, at first we questioned the liquidity of the Chinese futures markets. You know, we saw big numbers on paper, but Stephen and I looked at each other and we said, are these legitimate or Chinese government just publishing them? But they're legitimate. You know, you can tell by your fills, these are thick markets and, you know, and the Chinese public seems to, you know, I had been told this early on, they like to take risk, the Chinese population in general. They're not as risk averse as they are in the US. And they seem to be a lot more open to trading commodities in China.

I love it. So let's dig into the system a little bit itself. There's kind of two elements, right? The automated buy and sell signals and the risk management overlay. So dig into that a little bit if you can. And just to take a step back, our philosophy on markets was always that, you know, markets are different. They don't all behave the same. You know,

you look at a currency chart, at least historically, it looked totally different than, say, a soybean chart. Grains trade differently than the currencies. Precious metals trade differently than crude oil. You know, the problem is, when I started backtesting,

I was fortunate enough to work for a firm early on that developed a unique system for every single market. They not only had different systems in each sector, but they had a different system for heating oil than the one they traded in crude oil. And I learned early on, I said, oh, this doesn't make any sense to me. You know, they believed the sample size was 30 trades. And when, you know, we developed systems on paper that had these great profit to risk ratios, then when you put them into play in real time,

they lost money. And I said from early on, I said, 30 trades is not a big enough sample size. I personally decided I wanted 2000 or more trades. And the only way to get 2000 or more trades is to apply the same, to apply a one size fits all approach, same model, same parameters to many different markets across a long timeframe. And when I did that, you know, more and more, I realized markets changed their stripes over time. For many years, gold was a dog. It did

absolutely nothing. Then all of a sudden, you know, I may have been in the business from, say, the late 1980s, and it took gold 13 years or 15 years to start moving nicely, all of a sudden gold started trending and gold was the hot market after, you know, after say 15 years of choppy action. So I learned that you never know what the next trending market's going to be. And you never know when a market like currencies is going to stop trending and start going sideways. So I said, hey, I like this one size fits all approach. I like building models where I could backtest and have five or 10,000 trades. And since I'm applying a one size fits all approach, doesn't matter if a market starts acting differently than it did in the past begins to trend or stops

trending uh i i have a cookie cutter approach that will work no matter what markets do as long as some of them trend yeah and but isn't that counter to your first thing you said of like that all these charts look different they do but there was no way to quantify it yeah there was no way to find exactly what made grains different than uh crude oil and even if i could i'd be developing um a model or a system say for the grain markets, that did not have enough trades. It was something I didn't have enough confidence in. I even, I had seen one of the most successful stock market models ever developed. And I, you know, in the beginning of my career, I was a programmer for hire. And I programmed this for someone and it had over 5,000

trades over a 30 year period in the stock market, trading a stock index. Then it stopped working. And I said, holy cow, here's something that worked for three decades and then stopped working. But if you build, if you apply the same exact model, one size fits all approach to 30 different markets over a 20 or 30 year time frame, it's a lot less likely to stop working. Yeah. So that particular model probably didn't work when you put it on 20 other markets. It just happened to have worked for those 30 years on that one market. It was unique to the stock market. It looked at certain indicators like an advanced decline line, certain metrics that you would not have access to normally in the commodity markets unless you built it yourself. So you were like a kid in the candy store when you got the Chinese

data of like, awesome, here's all this out of sample data that we can see our models on. And now I can get another couple thousand trades in the sample. Exactly. And at the time, Stephen and I said, hey, maybe the models have stopped working. Maybe trend following is dead. We don't know yet. But we were pleasantly surprised when we applied these models to the Chinese futures markets and the backtest was so profitable. And the beauty of it is what you see is what you get, meaning that we said these results are very reliable. They can be achieved going forward because there's no smack of optimization whatsoever because these models were built

before we even knew these markets existed. Right. And then the flip side to that is if they stopped working in the US though, they could stop working in China, right? They could, they could. But they stopped working in the U.S., though, they could stop working in China, right? They could. They could. But, you know, they stopped working in the U.S. because currency stopped trending and interest rates were no longer profitable. And I felt that, you know, at least there was a reason to explain why that was so.

Have you dusted those off? I bet they actually did pretty well in the last six months. I've actually been trading in them for the last two years. I felt markets were beginning to change in 2019. And, you know, we were early, but they've worked well, actually, for the last two years. Yeah, the CTA trends had a little bit of a resurgence with all the reflation trade and possibly inflation. Not only have they worked well, but every indication is they should continue to work well for the foreseeable future in the US.

And do you have a view on that? If inflation shows up, it's for sure going to show up in those Chinese commodity prices, right? It could seem hard to have US inflation without it showing up over there. To me, what I like about China is we could get positive absolute returns, number one. Number two, it's not correlated to really any other asset class I've seen. It's not even that highly correlated to U.S. commodity markets. Yeah. And, you know, when I look at the two, I mean, there is if China ever opens up their markets to the world, every CTA is going to start trading China, if for no other reason than diversification. Yeah.

Adding Chinese markets to your current portfolio will not only increase your absolute returns, but it'll lower your drawdown. In China, you know, I could throw a dot at the page. A magic dart or just a normal dart? Just a normal dart and say, oh, here's another trading opportunity. Yeah. So we touched on a little bit. Let's go into those. So there's the 40 or so markets that you can only access in China for Chinese investors. But to your point, they've started to open it up.

We had Alvin Fan of OPIM on the Pot of Wild Back talking through this. They're trying to get internationalized their financial markets. So part of that was saying you can invest in onshore hedge funds, which hasn't totally been approved yet, but they came out with that rule. Part of it was you can invest in these seven, I believe it is, futures markets over there, which as you said, it hasn't totally been opened up because none of the brokers over there will take U.S. investors. You know, so international doesn't include U.S. Maybe that's because of the trade war or who knows what what that is. So but you guys have looked at those seven. You've created a model just on those seven or some subset of the seven and are creating a program to access for U.S. investors through

Cayman, through a Cayman structure where they can get access to this. So what's exciting about those markets? Which markets are those and what's it look like? Sure. And what we're doing is just take the models we're trading in the U.S. from like the late 1990s on playing the same exact model, same exact parameters to these seven. There's overlap, of course. Technically, you could argue these seven markets are a subset of the 40 markets. That's true, but it's not fully true.

Four of the seven markets are identical to the ones that Chinese nationals trade. Three, they develop just for international traders. Okay. And let me just make sure I give you the right three. Fuel oil, low sulfur fuel oil. You could trade fuel oil in China, but they have a low sulfur fuel oil contract that international traders could trade. Also, rubber and copper are two heavily liquid markets in China, but you can't trade those contracts directly. They created secondary contracts that I'm not sure exactly how they differed. They may have different grade of copper for all I know,

but they're internationalized contracts. The other four contracts, Ionor is one of the most liquid markets in the entire world. It'll probably be everyone's favorite market to trade or close to it going forward. It's a great market and you get to trade the big boy contract along with everyone else. Same is true of palm oil, crude oil, and what am I missing? PTA. Don't ask me what this is, but it's an asset contract. Not the Parent Teachers Association? Ionor is a great, great contract. So is palm oil. So is crude oil.

PTA has had big moves, but I don't, you know, in my opinion, it doesn't trend as well as the other three. You know, copper obviously is a great trending market. And by your model will automatically distill those lists down to the tradable ones. What it does is, you know, we, I'll go through the models, but we basically built models to. In its simplest terms, basically to try to identify which markets are trending and trade them. Yeah. You know, the John Murphy, holy grail approach. Yeah. And, you know, I mean, easier said than done. And, you know,

the trick now with these internationalized markets, like I said, there's seven of them, four are highly liquid, the other three are becoming more liquid day by day. So, you know, our hope is all seven, you know, if, you know, if you can't trade all seven today, hopefully, you know, one month, three months, six months from now, all seven will be tradable. And as more people get into the space, they're going to be trading it. But we don't do anything different in these markets than we do elsewhere. And this is how our models basically work. Our program is based on three models. We've developed many more models, but we feel we get enough diversification trading three of them.

Adding a fourth, fifth, sixth really didn't add a lot of value. We have three that are different enough, even though all three are trend following, different enough in terms of timeframe, in terms of methodology, entry, exit, money management, where the three of them combined give us a smoother equity curve are medium term in nature. One is longer term. The basic approach is when markets go up, we want to buy. When markets are going down, we want to sell. Simple trend following. one market's a breakout system, break above resistance. For example, we buy. Another one is a pattern recognition system. We believe that's somewhat unique in this industry because we've been able to take subjective price patterns, put them into object, convert them to objective rules and actually program them. And from what I've seen, few people have been able to do that successfully.

So the patterns themselves are nothing you haven't seen, Jeff. But the fact that the computer could search all the commodities and identify them for us is somewhat unique. And it goes back to what we said earlier, beauty is in the eye of the beholder. I could show 10 technical analysts a chart and maybe five will say, yeah, that's a head and shoulders top. Four will say it's a double top. And the last one will say, I don't see anything. Yeah. Market, war check, test, right? They see what they want to see.

So it's the beauty of the chart as I see it program. The systems, you know, the way they work, they enter the market at different stages. I was always intrigued by the concept of pyramiding. I always liked reading Reminiscence of a Stock Operator or Jesse Livermore's book or Richard Dennis and learning how these great traders would put on trades. And, you know, some of them believed in the concept of pyramiding. I could never, I always liked it conceptually, but I could never take that concept and make it work objectively. Every time I tried to program, I found out that my first purchase was my best one. As I bought more and more as the market went up, the risk reward would diminish on each increase, you know,

at each higher and higher level. So what we did was build three systems and entered at different times. And each of them had filters, which I'll explain in a moment as well. So if a market is going up or down, we may have anywhere from zero to all three systems participating. Ideally, if a market's going to have a big trend, we're hoping we'll get three systems getting in getting in on the action and if a market's choppy we're hopeful that you know we don't get in or we only get in with one or two systems but if a market if gold is going to go to 3 000 an ounce for example in the future and um you know gold begins to go up we may buy our first position goes higher this you know, gold begins to go up. We may buy our first position goes higher.

You know, maybe the technical system kicks in first, then the pattern recognition system, then our third system, our long term systems, our statistical system. And that only buys not only if it's going up, but if it's going up on increasing momentum, so by the time we get the third buy, we have basically done the same thing as a pyramiding scheme, but we've done it in a safe, secure fashion. We've added to markets when they moved in our favor. And when they didn't move in our favor, we didn't have a full position on, we had less exposure. And if the market went higher and higher and higher, we'd be putting more and more on, but it made conceptual sense. And it allowed me to say, okay, now I'm happy. I like pyramiding because the concept was if a market moves more and more in your favor, you should increase your bet size. That, you know,

that made, you know, I like that idea. I like that idea because, you know, why the more it moved in my favor, the more confirmation I got, the better, you know, the higher the probability of the trade would be. So I should somehow increase my exposure. Right. The flip side of that is it every day forward, maybe, you know, one day less length of the trend. Exactly. But by having three unique systems with different timeframes, I basically was able to replicate that, but in a nice fashion where it accomplished, it gave us more exposure when markets were moving in our favor. But at the same time,

it allowed us to have less exposure on if a market failed. Did they exit on the different timeframes as well? Yes. Whereas if we only traded one system, it would put on all three units right away. And then if the market went south, we'd be losing three times as much. This way, we have less exposure early on until the market proves itself, until we have confirmation. Right. This way, you got to be wrong three times. Exactly. It's hard to do. Now, we practice something that we like to call selective

trend following. If there's 100 generic trend following signals, we may only take 35 of them. And 35 we take is going to be very much in line with what other CTAs are taking. You know, trend following is trend following, you know, you know, you could have 10 different systems. And if a market's going up, they should everyone's going to be in eventually. Exactly. Our secret sauce, if we have any, is in the 65% of the trades that we filter out. And the filters at the system level are basically asking the question, will the trend continue? If a market is going down, is the trend, are prices likely to be lower than they are now one month three months six months in the future that's what we want to know and just because prices are going to be lowered doesn't mean we could make money if we sell short it just means we're more likely to

make money you know if you look at the uh s&, for example, it's gone up over the last 12 years. And this is a trap a lot of system developers fall into. But if you develop a system on the S&P, I think the first thing you'll notice is your trades on the long side did a lot better than your trades on the short side over the last 12-year period. And of course, the trends went up over the last 12 years. So you're saying, per that concept, if you've seen this thing has mostly been going up over such and such period, you're going to be more apt to take that long signal and vice versa? Is that what you're saying on the filtering process?

Yes. The way the filters work is that filter at the system level basically tries to determine that. The stock market's been up over the last 12 years, so it's been easy to make money on the long side, a lot more difficult on the short side. So the filters at the system level say, okay, is the trend likely to continue? If the answer is yes, then we're going to be in an environment where the trade is more likely to be successful. Over the last 12 years, any trade on the long side in the S&P would have been more likely to be successful. So we feel that if the trend is going to continue, then this trade has an edge. Now, the probability, the risk management overlay, which I'll go into soon, that has its own filters. And those filters ask the question, is the trade likely to make money?

And what we're doing at that level is more assessing the risk reward potential of the trade. I don't care if the trade, if the trend is going to continue. You know, the S&P has been up over the last 12 years. But if you show me a trade on the short side, we're after risk a dollar to make $6. That's a great trade. I want to take that. That's what the second set of filters is looking at. It doesn't care which way the market's going. It just cares about the risk reward ratio of the trade. And if they're counter to one another, if filter one says yes, filter two says no, no trade. Exactly. What happens is if we have 100 generic trend following signals, at the system level, maybe 30 out of the 100 get filtered out.

The remaining 70 get fed into the probability evaluator, which we'll discuss in a moment. And about 50% of those, 35% of those get filtered out. And out of the initial 100, we're left with 35. So the 35 that we're left with are what we call higher probability trades. We're trying to find trades that are not only with the markets, not only likely to move in our favor, but where we have a good risk to reward ratio. Yeah. What is, is there a hard and fast rule for that ratio

that you can share or it's just, you want it to be good? We, I mean, we want it to be good. It's based on a lot of factors. But normally, if we're risking a dollar, we want to make $2 to $3. Okay. So $2 to $3X. And do you ever see trends where it's risk $3 to make $1? Yeah.

But that's something that gets filtered out that we don't take. There's nothing wrong with it. It might be a successful trade, but all of our backtesting shows if you do that trade a thousand times, you're not going to be happy with the results. Right. You say, no, thanks. At least not the way we trade, because the only way to make that profitable is you have to be right 75% of the time, the risk management overlay. The systems are simple. What they do is they have a concept that we're trading. Each system has an entry, two exits, money management stop, and a trailing stop.

And it has a filter. We didn't want to complicate the system. So we put that into the risk management overlay, which has two pieces, a probability evaluator, which is concerned with entries only. And it basically tries to compute a mathematical expectation of every trade, which is impossible to do, but this is, we feel, a proxy mathematical expectation. And it has a drawdown manager, which is concerned with exits. The probability evaluator looks at a number of different factors that give us a small edge or the opposite tells us we have no edge in a market. And the more factors that line up, the better. You know, consider them green, yellow, and red lights. You know, if we have seven green lights, if seven of these factors kick in, we assume there's a higher mathematical expectation than if only three green lights are kicking in. And, you know And we're looking at various factors, without giving anything away proprietary,

let's say trades that are giving signals in multiple timeframes, for example, are better. If you have a trade breaking out on a daily chart and a weekly chart, that's a stronger signal than just the daily chart. If a market is moving sideways, if you have two markets that have dropped over a six-month period. One goes sideways for the next three months, then begins going up. The other one is forming a V bottom, which one has the higher probability of success? The one that stopped going down and moved sideways for three months. We tried to find certain concepts like that that we were able to program that gave us a small edge. And we felt that, you know, sometimes they work, sometimes they didn't. But the weight of the

evidence approach seemed to work very well. Whereas if we have 18 of them, and the more that are, you know, more that you could check the box, the higher the probability of success. And I was like, it creates a don't suck model, right? Like the more things you can do to not be really bad outweighs like if you found the perfect filter to get the perfect trade every time. Exactly. Exactly. Exactly. And the higher, the more of an edge we have based on the probability evaluator, the more we want to risk on the trade. The lower our probability of success, the less we want to risk on the trade. And that's on each of the three models. Exactly. Typically, we'll start by risking 20

basis points in every trade on each model. So in a $10 million account, 20 basis points is $20,000, one fifth of 1%. So if crude oil starts going lower and we sell, we go short crude oil on all three signals, we're risking 20, 20 and 20, 60 basis points. You know, three fifths of one percent or 60,000 in a 10 million dollar account. Looking to make 180,000, three times that. Exactly. You know, anywhere from, say, 120 to 180, ideally. Yeah. We can adjust, you know, the probability evaluator, you know, dictates, you know, not, I shouldn't say dictates, instructs us to fine tune that allocation. Instead of going risking 60 basis points, maybe we're risking zero or as high as 100 or 120 on rare occasion. Typically the sailing is

100. Yeah. And that's per model? That's all three models. Yeah. Yeah. So it'll go up to 33 per model. Yeah. Yeah. I mean, typically we could go up to 40 in each model. But, you know, think about it. We're training three different systems, Jeff. You know, let's say we buy soybeans, for example. Okay. Then soybeans goes higher. We buy more soybeans. The first stop has moved up already. Now we're risking less on the first order. Now, instead of risking 20 basis points, we're risking 18 basis points. By the time we get the third buy signal, maybe the first two signals, instead of risking 40 basis points in total, they're down to 30. So now the three combined, maybe we're only risking 50. You know, we have a nice blog post I did once of like that first day, the first week, right,

for a trend follower, that's the worst, because you can take the full stop out. And then every day kind of goes somewhat in your even sideways, or in your direction, that's going to come in and you're looking better from your principle perspective. Exactly. So in a worst case scenario, we could lose 60 basis points if all three models buy and then reverse immediately. But typically by the time we get the third signal, we're tightening stops already and we're not fully exposed. So even if we do double the risk or the allocation to the market, typically it's not going from 60 to 120. When all is said and done, we're risking no more than 100 normally. Got it. I love it. Now, big trends.

We're only taking one third of all the trend following signals. So we're going to miss trades as well. It's not unusual for us to miss amongst the move. It comes with the territory. You can't filter out all the bad trades and only take the good trades. I wish we were able to. But on occasion, you know, we'll miss major moves. But when all is said and done, the 35% of the trades we take exhibit a better risk, you know, reward profile than the 100% of the trades.

Now, the final piece, the drawdown manager, that's concerned with exits. That's concerned with managing drawdown. Typically, the systems do very well managing risk. There's the money management stop. There's the trailing stop. They work 95%, 96%, 98% of the time, except when markets move exponentially. If you buy a market and it just goes straight up, gold was a good example. Gold went straight up last year and peaked in early August 2020. There was, you know, gold was going up so sharply, our trailing stop was so far away from the market. Yeah, you know, we said this drawdown is unacceptable. And early on, I said, you know, how do I, you know, oh, what do I have to modify the systems, I have to account for this. And then I said, No, no, no, Keep the system simple. I mean, I don't,

why modify the systems for something that happens no more than 5% of the time, probably more like two or 3% of the time. Why not just build a separate unit, a separate piece of code that could address a situation? So what the drawdown manager does is it looks at various metrics, but in its simplest terms, it's basically saying, where'd the market close today? And where's our stop? And if the stop's too far away from the market, take defensive action. Which means move the stop up or get out of the position? Either one. What first line of defense, it has its own logic to move the stop up. And if we can move, you know, we, you know, let the drawdown manager determine the new and improved

stop, which is closer to the market. And if it meets our stop criteria, if it falls within our risk threshold, fine, we'll take it. If it's still too far away from the market, we will take some money off the table. If, for example, I'm making this up, but if, for example, on a position, our risk threshold was 100,000 and the system stop was 280,000 away, then the might have to do then is liquidate, you know, maybe as much as half the position to get it to 80 to 100,000 of risk. And, you know, I could tell you right off the bat, the drawdown manager hurts us. It doesn't add anything to the bottom line. If all you're concerned about is absolute return, you don't need the drawdown manager. Just let the systems run. What the drawdown manager does is it very often prevents big drawdowns. So it dampens drawdowns dramatically. It also hurts on the profit side. I'll make up some numbers. Maybe the pure systems are making 20% returns with a 12% drawdown.

Now, maybe with the drawdown manager, you're only making 16% annualized percent returns. You went from 20 to 16, but you cut drawdowns from 12 to eight. So instead of risk reward profile of 20 to 12, which is, I don't know, 1.6 to one, maybe you went to two to one. Now you're 16 and eight. Right. So it improves the MAR ratio, right right so it improves the mar ratio right so it improves the absolutely it improves the mar ratio and and you have to be an old-timer like you and i to know you know that manage account report but in theory that's all anyone should care about right i'm like you should only care about that ratio exactly and and and i mean I've had some people say, hey, you know, you're not making as much money as someone else. But, you know, our response is, but, you know, preservation of capital.

We're not giving money to invest with less, you know, put less cash up and not notionally trade it. And you'll you'll make as much as you want with a better risk reward. Exactly. And that's what we target, the best more ratio. We would much prefer that 16 and 8 ratio rather than 20 and 12. Love it. And so lastly, you're so confident in this, these Chinese markets, you're putting a bunch of your own money over there to trade those markets, right? We would like to, and I wanted to all along. I haven't been able to, but I will with the seven internationalized markets. Yeah, yeah. That's what I meant. Sorry. Yeah. You're going to personally back your own model to uh to trade those absolutely yeah no i've uh always uh i've always liked to have skin in the game and i feel it makes me a better trader i uh i pay more attention it's like um you know i've read about athletes that uh uh you know some great athletes that

just can't do well in practice and And they do a lot better in the actual game. Yeah. Yeah. I mean, to me, if I have my own money at stake, it, you know, I feel it takes it to a higher level for me. Even if you write, you're not only going to eat your own cooking, you're going to eat your own Chinese food cooking. Exactly. And I've always loved Chinese food. So yeah. Have you learned any Chinese learned any Mandarin along the way? Very little. When I when I did my speaking tour in 1992, I learned a few words. You know, I mean, you know, basic words, you know, hello, good morning. Thank you. But nothing beyond that. I am back up. We might have, you might have to get over there a few times, right? Yeah. I'm your typical American. I'm terrible at languages. I really, it's

embarrassing. We have international guys on the pod and they're like, Oh, I speak six languages. I'm like, Oh my goodness yeah yeah i love it um well i hope if we have any listeners still on we've gone a little long but this has been all great info um and so we'll put in the show notes some links to this uh these internationalized markets what we're doing uh to get access to those and um best luck to you. Thank you. And thanks a lot, Jeff. I'm coming to New York one of these days when things open back up and I want you to take me to that pizza place. You took me to one day. You got to remember the name because it was so good.

Sure. I will find it. It's near, it's within walking distance of the world financial center. So we'll go there. All right. We're going to have a meeting and go get some New York slices. Sounds good to me, my friend. All right, Fred. Great talking to you. Okay. Same here. Take care. The Derivative is brought to you by CME Group. CME Group is the world's leading and most diverse

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