Episode 4: Jeff deGraaf, CMT, CFA

As the discipline of technical analysis has evolved so have the practitioners. Episode #4 of Fill the Gap features one of Wall Street’s current icons of market research – Jeff deGraaf, CMT, CFA who is the founder and Chairman of Renaissance Macro Research LLC. In this interview, Jeff dives deep into the quantifiable data-driven approach he and the RenMac team leverage towards understanding markets. Jeff reveals some of the spurious pitfalls of data science, how RenMac separates signal from noise, and why their team always returns to price before making any investment recommendation. 

Jeff has been one of Wall Street’s most influential macro-based analysts over the last 20-years, consistently ranked by I.I. magazine since 2002, and a member of Institutional Investor’s exclusive Research Hall of Fame. Prior to founding RenMac, Jeff cut his teeth at Merrill Lynch in the 1990s, then Lehman Brothers for 10 years where he served on the firm’s investment policy committee as a Managing Director. In early 2007, Jeff moved to ISI as an Executive Managing Director, also serving on the firm’s management committee and heading the firm’s investment policy committee. 

This podcast refers to several important charts which reflect the work of Jeff’s team. To better understand the concepts covered it is recommended that you download the chart pack using this link: go.cmtassociation.org/ftge4

If you’d like to go deeper there are several video clips to help guide your experience using the same link: go.cmtassociation.org/ftge4

Fill the Gap, hosted by David Lundgren, CMT, CFA and Tyler Wood, CMT brings veteran market analysts and money managers onto a monthly podcast.

For complete show notes of every episode, visit: https://cmtassociation.org/development/podcasts/

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CMT Association is the global credentialing authority committed to advancing the discipline of technical analysis in the financial services industry. We serve members in over 137 countries. Our mission is to elevate investors mastery and skill in mitigating market risk and maximizing return in capital markets through a rigorous credentialing process, professional ethics, and continuous education. CMT Association formed in the late 1960s with headquarters in lower Manhattan, NY and Mumbai, India.

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Transcript

How Fundamentally Minded Investors Use Technical Analysis Today

Connect with Jeff deGraaf on Twitter at @renmacllc

Brought to you with support from Optuma

Transcript

Tyler Wood  00:13

Welcome to Fill the Gap, the official podcast series of the CMT Association, hosted by David Lundgren and Tyler Wood. This monthly podcast will bring veteran market analysts and money managers into conversations that will explore the interviewees investment philosophy, their process and decision making tools. By learning more about their key mentors, early influences, and their long careers in financial services, Fill the Gap will highlight lessons our guests have learned over many decades and multiple market cycles. Join us in conversation with the men and women of Wall Street, who discovered, engineered, and refined the design of technical markets.

Fill the Gap is brought to you with support from Optuma, a professional charting and data analytics platform. Whether you are a professional analyst, portfolio manager or trader, Opuima provides advanced technical and quantitative software to help you discover financial opportunities. Candidates in the CMT program gain free access to these powerful tools during the course of their study. Learn more@optuma.com

Dave Lundgren  01:55

Tyler, I’m doing well. How are you?

Tyler Wood  01:56

I’m great. You know, we made it through the first quarter of 2021. It’s April now and I’m very excited for our next guest Mr. Jeff deGraaf, CMT, CFA of Renaissance Macro.

Dave Lundgren  02:09

Yeah, we’re particularly excited to have Jeff because as you know we have some pretty explicit objectives with this podcast series. And it’s kind of threefold. One is to draw attention in and shed some light on the on the value of technical analysis and how it can really augment the traditional fundamental approach through idea generation, scaling your process risk management, and things like that. So we want to really bring folks on the podcast that help with that. We want to draw attention to the resources of the CMT Association, in the many ways that it can help investors sort of round out their investing investment gain with, with the tools they need. And then And then thirdly, really to highlight either analysts or investors who are really truly thriving with technical analysis. And I think when you think about Jeff deGraaf, I mean, he checks the box boxes on all three of those things. So it was a particularly, it was a great interview. So many takeaways, and, you know, we’re just really happy to have him on on the on the podcast.

Tyler Wood  03:15

Absolutely. I think the change up for all of our future billionaires, the listeners of fill the gap. You know, we’ve really tried to honor some of the legends of Wall Street and the founders of our community and the CMT Association. But this month, we’re bringing you a current top ranked analyst from Renaissance Macro, Mr. Jeff deGraaf. And really, for me, the takeaway that I think is so important for all of our listeners, is just trying to dispel any myths that are still out there about technical analysis. I’ve heard over the years, people worried that it’s too subjective, that, you know, you’re looking at something that might have some mysticism and I think Jeff really did a great job of explaining how it is objective, data driven, and quantifiable in absolutely everything that he does, but that even with a heavy emphasis on quantitative metrics, and a lot of historical research, he still listens to price Above all, and make sure that he’s, he’s following the market. So it was just a really fantastic interview. Dave, I wanted to ask you  what’s your favorite quote from our conversation with Jeff?

Dave Lundgren  04:24

Wow, so I mean, Jeff’s a pretty revenant guy and, and definitely states his opinion and is not shy about it. So to say what my favorite was, might be a little tough because he had so many of them throughout the podcast. But I would have to say my favorite is his reference to the boulder movie and the quote in there where you have to play with fear and arrogance. You know, in order to win right and I think that his point was that technical analysis allows you to invest with fear and arrogance because when the stars align and the fundamentals and the technicals come together, that’s when you should really press your bets. But like no other style, technical analysis also has the ability to tell you relatively quickly when you’re wrong. And so technical analysis allows you to play with fear and arrogance. And I think if you know over the long term, that’s what you know, outperformance is about as being able to really press your bets when your right and take small holes when you’re wrong. I think that’s just a perfect quote to sum up the value of technicals. And once again, Jeff just did a great job bringing that to light.

Tyler Wood  05:30

He’s certainly bringing in some references from all aspects of his life. You’ll get to see a little bit of cowboy Jeff when you tune into the resources. And I wanted to make sure that everyone who is a listener to Fill The Gap understands that with each guest, we’ve referenced further reading materials, chart packs, other resources and links that are really important for those who are listening to the interviews. This episode, more importantly, even than the others reveals some of Jeff’s work and he was very generous to share some charts with us. Throughout the conversation, you’ll hear him referencing several of those pieces. So for listeners, please visit go.cmtassociation.org/ftge4, that’s Fill The Gap, Episode Four for all of those resources. We also, during the conversation, spoke a little bit about Cathie Wood. Sometimes in bull markets, both the media and the investment public tend to pick a hero of the bull market and maybe pigeonhole those very talented investors, making it difficult for them to move out of their style or change course. Dave, you commented on this, during the interview, unpack for us just a little bit about what you were driving at there.

Dave Lundgren  06:45

Yeah, thanks, Tyler. I mean, I think you did a great job summarizing. It is just this idea that as bull markets age, the media and investors broadly tend to, you know, migrate towards those that are succeeding and put them on a pedestal that, frankly, nobody should be on a pedestal. But the problem with that, and this gets back to the behavioral aspect of investing, and that is, once you get up on that pedestal, and you are, you know, labeled as the “the guru”, if you will, if the performance certainly bears that out, and assets are flowing your way. And it’s wonderful in that moment. But when things change, it’s very difficult behaviorally to change with the times because you know, that all the money that’s in there is there because those investors want to capture the future trends and things like that. And if you see the things that have driven those trends, so far, it’s starting to change, it becomes difficult because you have been labeled as that person. And when you look at the last bull market, secular bull market that ended in a bubble, the folks at Janus Funds, you know, brilliant men and women caught that trend beautifully they were put on that pedestal. And when things change, they were unable to change with the times in their complex ended up blowing up. So I’m not by any stretch of the imagination, saying that that’s going to happen to Kathy, I’m only I only brought it up as a way of highlighting that, you know, trying to figure out where we are in this cycle. Do we have something similar to that happening today? And I think what’s happening with Cathie, not by her liking or her choosing, it’s just it’s happening. You’re powerless to fight it. But what one of the great things that gives me comfort with Cathie is knowing that she’s a subscriber to Jeff’s research so there’s no question in my mind that when this is over, Jeff will pick up on it, he’ll see it. And hopefully she listens to him if and when things do change. But that was my point.

Tyler Wood  08:30

Being a client of Jeff’s gives you a significant advantage in this industry. No matter what point in the cycle we’re in. Jeff is also a great content producer and Ren Mac hosts the legends podcast. So for those of you that want to understand a lot more about Cathie’s work and the Ark Innovation ETFs and series of funds that they run, please follow those resource links. We’ll get you back to the Ren Mac legends podcast with Cathie Wood. Dave, let’s dive into the interview with Jeff deGraaf.

Dave Lundgren  08:59

Sounds great, Tyler. Thank you. Alright, welcome to Fill The Gap, the official podcast of the CMT Association where we’re especially excited to have as our guest today, Jeff deGraaf, from Renaissance Macro. Jeff has a long and storied career in the business, which we’re excited to get to. But what we really appreciate about Jeff’s perspective is his slow evolution over the years from being schooled and grounded in classical technical analysis and learning the value of that, but at the same time over the years, morphing into much more of a data scientist and really trying to meld the insights from both what the data is saying and what are the charts saying. And I think that that, honestly, any technician that’s not making some effort to at least do that themselves or follow somebody that is, I think is really missing a great opportunity. I think from that perspective, Jeff will have a lot to share with us. So Jeff Happy St Patrick’s Day and top of the afternoon to you.

Jeff deGraaf 10:02

Well, thank you. And you too, and I still have the scars on my knuckles from them dragging from the early days. Yes, you’re right.

Dave Lundgren  10:11

Right. Yeah. So I think, let’s get into a quick overview of, you know, what got you into technicals? And then, was there a catalyst along the way somewhere that got you to transition more to a data oriented technician? and then just maybe kind of help us understand how your career unfolded. You’ve ended a bunch of really important shots, had huge impact, highly ranked, institutional investor analyst and all these things. So why don’t you tell us a little bit about that?

Jeff deGraaf 10:45

Well, I started out, you know, as almost everybody does in the business, which was, you know, on the fundamental side, at least, with a fundamental background and had heard in business school and everything else about how, you know, the technical analysis was “voodoo” and “witchcraft”, you know, whatever. So I was, I certainly had drank that Kool Aid and was, was looking at the world from a fundamental side. I was actually in sales at Merrill back in the early 1980s, in a gentleman by the name of Steve Shobun, who actually ended up becoming my mentor, ran this equity options update, I think, at 1215. And I used to listen in just to sort of get an understanding of what was going on. And, you know, just listening to what he was talking about over time, you know, in comparing it to the fundamental research of the firm, and, he wasn’t shy about, he certainly wasn’t rude about he was a nice human being as you can find. But, you know, there would be a disconnect. And usually, when it came down to who was right, it ended up being Steve and technical analysis that was more right than the fundamental side. And I remember names like Syntek, which was a drug which I think peaked at, like 55 bucks. And, you know, I think Merrill turned bearish on it in the teens. You had Marlboro Friday, if you remember that, which was 1984 I believe, and, you know, this big top formation, and the animals were all balled up on it, and it just crucified people, you know, with the gap down. And so, finally, I’m just like, What the hell’s going on with this stuff? Like, what is this? What are these end trails that they’re reading? You know, let me let me be a little bit more open minded about it. And once I started really getting down the path, it just really resonated with me because I’ve always had a probabilistic mind. I enjoy playing cards I like, I just like the numbers. And as I, really thought about it more intuitively and less about, you know, the intellectual perspective of, you know, do I really want to dig through the balance sheets and figure this stuff out? Or do I want to be right? And do I want to think about the world in a very structured way a lot like a blackjack player did. And I’m like that, to me, that makes all the sense in the world. And so when it came to risk control, when it came to position sizing, when it came really to an understanding of putting the odds in your favor, technical analysis just made all the sense in the world. And that’s what drew me to it.

As I got more and more involved with it there are definitely some aspects of it that I’m like, you know, come on, what are we? What are we really doing here? And then there’s others, I’m like, look, there’s there is something here, that can be even better if we just lean into it a little bit and do the work and look at history and understand some of the data. I would say it goes for contrarian thinking as well. I mean, I have a saying, if you’re always contrarian, that makes you a cynic. If you’re always a cynic, that pretty much makes you an asshole, right? I mean, people don’t like cynics all the time, right? And so it’s the same with contrary I mean, we could all, we can all be against the crowd all the time but that doesn’t do any good. What’s really interesting, particularly as we go through and do the data in economics, is we see so many aspects of economic data that says, you want to be contrarian to it. And so if we have that history, if we have that knowledge in that context and can say, okay, well, the data supports this. I can use this technique this contrarian thinking that actually has proven to be pretty effective throughout the years. You know, that, to me is a pretty good combination. Sothat’s sort of the long history truncated. I went from Merrill, actually to work with Steve Shoban at Lehman Brothers, was there for about 10 years and left Lehman Brothers in ‘07. I would say the best trade of my life is the day of my resignation letter is the day of the highest stock price of Lehman Brothers in February of 2007. So that was a good one.

Dave Lundgren  14:49

It’d be known the technicals are all about timing, right?

Jeff deGraaf 14:53

Yeah. Yeah, exactly. And, and then I went to ISI for four years. And then started Renaissance in actually we just had our anniversary on Sunday, 10 year anniversary Pi Day 2011. So Happy Birthday RenMac.

Dave Lundgren  15:09

Happy birthday. And congratulations. You know I’m a longtime follower of your research, I followed it back in my Fidelity days and ever since then, of course up till to this very day. So you’ve always stood out as being a very thoughtful, self-aware technician, which I think is a skill set that that is essential in succeeding in the environment. It’s one thing to, to know that you have the data, and it’s one thing to have everything every decision you make backed by the data. But there’s also a practicality to technical analysis, which is always, you know, this is what the data says, but is it my seeing it in the markets and you’ve always done a great job. I think what I’ve been impressed with is that over the years, I’ve just seen you more and you get more deep, deeper into the data and trying to understand what’s happening in the markets, but I’ve never once seen you flinch from the disconnects that happened sometimes in the data in the in the charts. And can you give us an example recently, we’ve seen some pretty crazy things happen in the past few years in the markets. Are there some good examples where you can highlight, when the data says this should be happening but it’s not happening based on the charts and the charts did a good job for you of steering you out of embracing that? What otherwise should have been a trade you should have put on?

Jeff deGraaf 16:19

Yeah, I think one of the things and this is a little bit more macro in nature, but one of the things that we found, you know, there’s this old quip on wall street that the bond market is smarter than the equity markets, people have been saying that for years. And I think maybe in corporate credit, there might be something to that. I think it would be a little careful of you know, rushing into that headlong but I think there’s you know, that there’s something to that. Certainly, the bond, bond market participants are more pessimistic than equity market participants. But that’s just the nature of the security, right, you just want your money back in bonds and in equities, you’re hoping to, you know, to find the next Amazon. But one of the things that we find, which I think is really interesting, and so, you know, one of the things I would say that we do, as well as anybody, at least I hope we do, we certainly try, and that’s know the data. You know, we really sit down with the data. We try to be really critical with the data. Sometimes it doesn’t matter you know. I’ll be honest, sometimes it just doesn’t matter. And other times we find that we can create some nuance which actually has an important message for the market.

The chart that I just pulled up is one that’s through Monday which are just cyclicals leading defensive. Now we define cyclicals as industrials, technology and discretionary. We don’t just make that up. What we did is we said okay, well with within the sectors, we’ve got the data back to the sectors back to the 1950s. And we said what sectors have the highest correlation coefficient to forward GDP. We all know that the price leads the data, particularly GDP data, which can be revised, etc. We use a point in time, and you know, we do all those things that you should do. But what we found was those three sectors I gave you had the highest correlation coefficient with forward GDP. So they lead GDP up and down, and they had more variability than almost any other sectors in the marketplace or sectors in the marketplace. On the defensive end, and by the way, none had a negative coefficient, right. So they’re all they’re all positively related. They’re just less so or more.

Dave Lundgren  18:29

Before you go on with that can I ask you when you when you did this study, because another thing that you do, which I really appreciate, as your always mindful to make the distinction between cap weighted and equally weighted. So when you did the analysis, did you do that cap weighted, equal weighted or both?

Jeff deGraaf 18:45*

Those cap weighted, we usually do both and then just figure out which one’s the best but that one ended up being equal weight, right. Defensive would be healthcare, utilities and staples. I think it makes all the sense in the world. When we look at cyclicals versus defensive those three sectors divided by the other three sectors, it gives you that red line and what we find historically is that cyclicals, I think you can see it really in, you know, forget the most recent data points, but you can see it back here in 2018. Which was you know, getting into really the middle part of 2018. Both of these were in sync right cyclicals relating defensives and bond yields were going up. Then sometime in the summer the equity markets said, you know what, enough is enough and cyclicals started to massively underperform the defensive part of the market. Bond yields went on to make a new high at over 3%, about three and a quarter percent. At that time, we were like look bonds are a great buy here and you know, nothing you’re going to see those in my IRA or anything but you know. Generally speaking just from a from a practical standpoint of what type of environment are we in, it was screaming to us that something had it wrong. Either the bond market was too pessimistic or the actual equity market in their styling was too pessimistic, right with defensive rallying. And, you know it proved to be yields and yields came down and, you know, basically until we troughed out here and at 50 basis points back in the summer of 2020. And so when we went back and looked at this, you know, all the way back to the 60s, this was not an anomaly. It wasn’t an anomaly that the cyclicals versus defensive somehow sniff this out three months, six months prior to the bond market. It was very, very, very consistent. We publish those charts, you know, through time just to show people that this isn’t an anomaly. And so for you, particularly in the summer of 2020 you can see down here, it was pretty obvious to us that the bond market probably had it wrong. And you know, at the same time people were concerned about vaccines are concerned about politics are concerned about a lot of things. And cyclicals versus defensives were just screaming. And really they had been off the lows, which is what history tells us. That’s exactly what should happen. When we have growth contraction when we have inflation that’s into what we call the deflationary busts zone, that’s exactly what should happen. That’s the point in time where you hold your nose. And because history gives us the confidence, we can then become contrarians, not always contrarians but contrarians at the right spot where we think it makes the most sense. I think it’s very, very similar to having two aces, and the dealer has a six showing. What are you supposed to do there? Well, you probably want to split those, right, and you probably want to lean into it, because the odds are in your favor. And that’s exactly how we think about it.

*Almost all renmac work has found that the best signals are from an equal weight perspective

Dave Lundgren  21:41

I remember when I’m sorry, I remember when you were publishing this back, when rates were back up above three to 3%, three a quarter. And I remember at the time as well, that it just from a take out the old pencil and the ruler, and you just drew a trendline off the off the highs from the early 1980s. That was actually right at the three and a quarter mark as well. So you had here’s a good example of, you know, the data saying one thing, and then classical technicals pointing you in another direction in the same direction, I should say. So that kind of was a good example of these two things melding together perfectly, I mean, confirmation of each other,

Jeff deGraaf 22:13

I’ll tell you in my career, which is, you know, 30 years now plus that damn trendline from 1981. In the bottom. I mean, it’s unbelievable. It is unbelievable. You know, if you get through it by a week, you’re, you know, barely it’s, it’s really been been phenomenal.

Dave Lundgren  22:31

Yeah, it should, it should stand the test of time in terms of being, you know, a good example of you know, the longer the more times a trend line is touch, the more important it becomes. And these are the sort of foundation foundational thoughts that we have in technical analysis. But that’s a perfect example. But like, my question to you is like, when you when you were referring to that study, you went back to the I think you said the 1950s. And so my my recollection of how these things behave over time, is that you can have an average expectation, because this is kind of on average, when it has happened throughout history. And then you can have your standard deviation bands around that average, to give you a sense of the, the accuracy of the prediction and whatnot. But it’s also true to say that during that same 70 year span of time, there’s been certain regimes and major trend cycles. And so in some of those regimes, interest rates rising has been good for stocks and interest rates falling has been good for stocks, so it kind of changes and morphs with time. So how do you? How do you balance those two things where you have to be aware of what regime you’re in, relative to that long term, data series that you’ve studied?

Jeff Degraaf 23:33

Yeah, you know, it’s, it’s a rabbit hole, once you start really getting into data. And we’ve got about five different ways that we look at data from, you know, as I like to say, we approach the mountain from the north, from the south, from the east, in the West. And if it has roughly the same characteristics from each side, then we know what we’re dealing with, right? When it looks completely different from the north, and it does the south, then, you know, you have to ask yourself, What the hell is going on here. And so I think one of the one of the big pitfalls, and it’s easy to do, right, if you have a lot of data, and you think, okay, I’ve got a lot of data, and I’m going to use all the data, and here we go. And that’s fine, you know, you should use all the data. To us the the important part of it, though, is one of the first things and it’s really hard for the math guys that I have, right? I’m like, we need to visualize the data, just scatter plot the data, let’s just look at a scatter plot of the data. Because a lot of times that scatter plots, gonna give you information visually, that I don’t care how much AI you have, it’s, you know, it’s gonna take longer for that thing to figure it out than it is for us to look at it and go, Hey, something happens out here, right, or something happens over here. And then it’s up to us to figure out if that’s consistent enough, that we can actually use that or if it’s just, you know, a one off anomaly and you can get that you know, 2008 2009 and I guarantee you 2020, you’re gonna have a lot of data points that are just so skewed. If you’re waiting for those data points to happen again, they might not happen in your lifetime, they certainly probably won’t happen in my lifetime, right. So You know, if you think about usually the as a rough estimate, every generation goes through at least a 50% drawdown in their equity stake. So if you’re a 30 year investor, you have a, I can’t remember exactly the number, I think it’s a 99% probability might be 98% probability of experiencing a 50% drawdown in your equity exposure,

Dave Lundgren  25:23

that’s as a buy and hold investor

Jeff deGraaf 25:25

as a buy and hold, right. So if you’re 30, okay, but if you’re 60, on your way to 61, retiring, and that happens, that’s a little different. That’s a little different outcome, right. So, you know, when we go through and look at the data, we look at the data, we certainly look at the T stat, and you can see the T stat in this one here, this is our yield impact model. But you can see the T setup here, which is pretty good, right? So that any, anytime your T stat is above two or below negative two, it means there’s statistically some viability there. And so you look at the entirety of the data. And that’s what the T stat gives you. But we’ll also take the data and say, Okay, well, if I look at the T stat over that entire timeframe, right, so 50 years, if I look at 50 years of data, does that T stat remain stable, right? Is it always negative three, or something that’s statistically significant? And always contrary, right? Because the last thing I want? And I can tell you there are there are plenty of things, particularly since Oh, 809, where the T stat was meaningfully positive. And then since Oh, 809 has actually flip flopped and gone meaningfully negative, right? And you sit there and say, What the hell am I supposed to do with this? Because is, is this the new normal? Or was that the normal, and we’re now into a different norm, right, there’s like, you just don’t know. And so to me, the worst thing for an indicator that can happen is that it changes its stripes. And so if I’ve got consistency, where it’s always a contrarian indicator, such as a negative t stat, it’s it means it’s an a, it’s a contrarian indicator as a positive t stat means it’s a momentum or confirming indicator. So the worst thing you can do is change those stripes. And that, frankly, has happened with yields, yields went from being a positive t stat to a negative t stat. And you’d sort of sit there and say, Well, what what is it right is, is this the new normal? Or do I just not have enough data points from, you know, the 1570s, that would have shown me that we’re in the same exact, you know, situation that we are today. And that brings us to, you know, I think an important point, which is that everything that we do, no matter how good we we think we have a corralled, there’s always a chance for that horse to get out of the out of the ring, right. And that’s because we’re always dealing with out of sample data, we’ve got a lot of great data, we can look at it, it gives us confidence, and, you know, makes us or allows us gives us the the confidence to make calls that might be otherwise uncomfortable. But we still have to be considerate of the fact that everything that we’re doing all the variables that go into the equity markets, or the bond markets or whatever, are changing through time, right, the demographics are never the same as they were, the interest rates are never the same as they were the political environments never the same as that none of those things line up perfectly. And so you always have to get to give some, you know, some rope to these things that, you know, the dog needs to be able to run off the leash a little bit.

Dave Lundgren  28:22

Right. And I think it’s just real quick. And I know you have some questions on data, Tyler that we should get, we need to get to because they’re important observations. And I just, you know, to me, I just want to just reiterate again, that, you know, that it’s important to have an awareness of the data. And I think your observation about just taking the data that you see, even after you’ve done all your massaging of the data, drawing your conclusions, you still need to look at that scatterplot just to see if it even makes sense. And but at the end of the day, even if you do all of those important sort of failsafe measures, you’re still as the value of technical analysis is that it it? There is this this concept of, you know, the the, the checklist of trend change, or the inviolable rules of trend, and none of these data points that are forecasting some certain outcome in the markets can possibly happen unless this trend actually changes. So as your final failsafe measure, you got to wait for the trend. Right? Right.

Jeff deGraaf 29:14

if you look at this chart, right, so this is, when I show you that yield impact model, we’re in the 90th percentile. So we know the combination of the level of yields today. And the rate of change of those yields puts us in the 90th percentile back to 1965. Right, okay, well, historically, in that zone, I know that equities perform just a little bit below average, it’s not the end of the world by any means. And in the 100th percentile, it becomes you know, more problematic. So what we then do is say okay, well, if we know what should work in that 90th percentile, boom, here’s that chart, right. So if I were, you know, if I were just a data monkey and said, Hey, this is you know, this is history, and this is what we’re gonna do. Then we’d be short all these names over here, and we’d be long all these names over here, but because We have great respect for the current environment and for technical analysis and what it’s telling us. We color code the bars as an indication of to what’s happening today. So is today holding up the way that history would otherwise suggest. And this is where there’s a lot of disconnect in the market today. Because if we look particularly things like discretionary which most of these right autos, consumer durable apparel, which is a, you know, long, fancy way to say home building, retail, consumer services, all those are discretionary, those should be getting absolutely clobbered, and they’re not right. And so what tells us that look at these extraordinary events that are happening in the bond market, and this this move higher, is really probably coming from such a low level and such an extraordinary event, that it’s not yet working against the consumer and the consumer names. Now, when that happens, when we start to see that shift, I think that’s going to be an important shift for the market call overall. But generally speaking, what we do is we say, Okay, look, in terms of the data layout, this is what should be happening. And then from a colored perspective, the color bars, it tells us whether or not history is being affirmed by the marketplace. And right now it’s not, you can see some of the weakest, you know, weakest trends or things that should be the strongest, and some of the strongest or things that should actually be the weakest. So, you know, there’s a unique, there’s unique flavor to this to this environment. But it’s, it’s combining those two things to us, that gives us a lot of confidence, and, frankly, provides some nuance to the call where we can come in and say, Hey, you know, normally the data would say this, but because the markets telling us something different, we are going to lean towards the market and say, Hey, this probably, instead of being in the seventh, eighth, maybe ninth inning for the cycle, this suggests to us that it’s probably earlier innings and people are giving you credit for right, from what’s happening to interest rates and the like.

Tyler Wood  31:56

The question I wanted to ask you about data, Jeff, I mean, the name of your firm is Renaissance macro. So clearly your process is looking from a top down perspective, do you look at all data at all times? Or do you take some discretion over whether yields versus, you know, inflation data or payrolls data, do certain data sets have more impact in certain points in the cycle?

Jeff deGraaf 32:21

I mean, we can get really cute and tell you that we know the sensitivity of every macro data point to you know, to what’s important right now. And right now yields are the most important, right, sometimes it’s oil, sometimes it’s inflation sometimes. So we run sensitivity analysis to give us a sense as to what’s going on. And then we can take that and drop that down, right where we know that, you know, historically, and, in fact, it’s a really good example banks and yields, banks and yields never really had much of a relationship. I mean, I know it seems, you know, almost blasphemous to say that today. But before 2008, there really wasn’t a strong relationship, there was something but it wasn’t that strong. Today, the T stats like off the charts, it’s like six, it’s something that you know, it’s just ridiculous. So we always want to know, what is the sensitivity in the marketplace, and you know, what’s happening. And generally, you can find that that happens at different points in the cycle. So the dollar becomes more important, as you get deeper into the cycle interest rates are more important earlier in the cycle. So, you know, we we know the history of that, but we also measure the actual sensitivity to those to those variables. Now, you know, look, that’s a sort of acute exercise. And, you know, sort of lets you flex your, your muscle memory upstairs a little bit, but I don’t know if it’s, you know, I don’t I like to know it, but it’s not like I’d be lost without it. But, but you’re right. I mean, there are sensitivities that change throughout the cycles as as you go. And that’s an important thing to be cognizant of.

Dave Lundgren  33:52

Absolutely. You mentioned banks, and I guess maybe two questions on that. One is, you first you mentioned the, the, I guess, the the disconnect and understanding of the importance of rates and banks over time. So that would be like a disconnect between what people think and what actually is. So when you look at your data today, and you you know, you speak to hundreds of clients around the world, and they present to you their their conceptions or their perceptions of what’s driving price, why not? What would you say is the biggest belief in the market such shift that’s simply not borne out in the data?

Jeff deGraaf 34:30

Well, there’s a there’s a couple things right here right now. And you know, maybe this will come back to bite me. We’ll see as time goes on. But one of the things I think is really important to conceptualize and, and I have to check myself on it sometimes, too. If you look at inflation expectations, right, and the good news is we’ve got 23 years or something like that, of tips being traded. So we saw what inflation expectations were given with inflation expectations are today. And their ability to predict what inflation is going to be five years from now, or even 10 years from now. It’s the T stat is essentially zero. It’s a very, very, very poor predictor. Yet when we listen to other people talk about it there, it’s almost as if it’s a fait accompli, that inflation is right around the corner. And we look at inflation expectations where they are today. And, you know, when we do that, there’s, there’s a little trick that we use to say, okay, look, we can model this out to understand what the inflation expectations should be, where they are. If that error, if you will, is wide enough, then it becomes a sentiment model. And so I think one of the things that I would look at is, I think that the inflation expectations, right now are much more a reflection of sentiment than they are the likely reality that inflation is going to meet those expectations. And again, I know that that sounds like it’s blasphemous a little bit, but it just doesn’t have a very good track record. And, so, we use that and try to use that against the market, right, to try to position ourselves in a different way. That that could be useful. You know it’s akin to saying you’ve had a good record, for whatever reason, flipping a coin and now people are really sort of asking, hey, what’s Dave Lundgren thinking? heads or tails? And, you know, the reality is you don’t have any clue over that, right? The people are putting a lot more faith in your ability to call that than what the data would otherwise suggest. So I think that’s one thing.

The other thing that we really struggle with, is this growth value concept. Because these definitions have been so bastardized. I mean, they’re just almost beyond the point of being useful because there’s so many cross currents or crossbreeding, if you will, in terms of other factors that are really driving this thing. So, you know, as an example, the growth metric in Russell uses price momentum. And if you take price momentum out the growth, what’s left doesn’t give you anything that you should use in terms of identifying stocks. It sounds good on the chalkboard, but if you take them in you say I’m gonna apply earnings growth, and I’m gonna apply estimates, I’m gonna apply this to stocks overall. And you look at that there’s, you know, there’s nothing there. There’s nothing that’s really that interesting. The other part of the value equation is that you end up with making sector bets. And so the question is, is that really value? Or is it just energy? value? Yeah, something else? So are you really teasing out value? And what I would say, so we do it, we do it sector neutral, we do it market neutral. And we do a cap neutral, and we look at it and we do it a lot of different ways. But only in the last, maybe it’s three weeks, maybe maybe it’s a month? I don’t think it’s a month, but only in the last couple of weeks, several weeks, have we seen value across the spectrum, right? So cheap in tech versus cheap in industrials versus cheap in staples. Value generally has started to work, righ? And so okay, that’s fine. But it hasn’t been that dominant of value that people are looking at. And that’s just because, you know, energies work and financials have worked, they worked really well year to date. But you know, are those really value? Because it’s hard to associate value, specifically, when the cap structure amongst different sectors is so different? How can you compare a bank to them you know, to GM to a manufacturer, or to a software maker, right? I mean, software’s three guys and a dog in a garage, like there’s no capital investment, there never going to look cheap. So, you know, I just, we struggle with some of these, with these definitions, and particularly when people you know, stand on a pedestal and preach about the values of some of these things, and you’re sitting there just saying, you know, dude, like, you know where the stones are. I can see you’re walking on water, but I can see the stone for you.

Dave Lundgren  39:11

Right now, when you when you look at the valuation across the sector’s, do you adjust how you measure value? Do you find that some valuation metrics are more? have better forecast value in one sector versus

Jeff deGraaf 39:23

Another? Yeah, so we call it contextualize value? I don’t I don’t know made that up. I’m sure we stole it from somebody. But the idea is that I have that a bank is going to have a different value proposition than a software company, right, which will have a different value proposition than, say a utility. And that’s actually the some some of that’s been a lot of fun to do. Because I’ll give you an example. I mean, the number of questions that we’ve had, about you know, shouldn’t shouldn’t utilities be a great buy here because yields are so low, and the difference between the dividend yield the utility sector, industry and The 10 year yield to just make some screaming by if you’re, you know, if you’re like looking for yield equivalence, right. And if we go back, we have all the rustle data back to 1979. That might be one of the worst ways to value utilities and whether or not they’re going to give you a performance going forward. So and what happens and you know, people sort of scratch their head, they hit their heads against the wall on this thing. And I think it’s, it’s part of what this business has to become, which is, it’s almost absurd that it’s not that people just have these theories, and they put billions of dollars to work based on these theories that don’t hold any water. It’s just, it’s amazing to me that that actually happens. But what’s happening in that situation, is that yields when you go back, and look, yields are so low for a reason, the Fed is stimulating the economy, and the market knows it’s gonna work, right. That’s what exactly what that cyclical versus defensive chart that we just talked about shows is that it’s not that you want to own utilities, because you want to play that spread for 300 basis points, whatever it is, because you don’t want anything to do with utilities, because you can double your money in GM, you know, and so that’s, that’s what works. And but understanding that, and doing it from a contextualized basis is, you know, to us is really, really important, because it helps to see through some of those misconceptions that are out there that, frankly, you know, have the ability to bury people, if I will tell you this, if you were to use on average, it doesn’t it’s not the best for everything. But if you were to use one valuation technique across the board, so it ranks on average, the highest of all of them, it’s an earnings, yield rights, earnings, earnings yield to EBIT, is, is you know, if you had to three on an island and said, You have to be a value investor, you know, what are you gonna pick? Give me earnings yield to EBIT? Right. The best

Dave Lundgren  41:49

So, on finance in banks in particular, I you know, when when you look at the the depth of your team at Renaissance, you have I think one of the best economic strategists on the on the street, Neil data, he’s fantastic. You also have Howard Mason, who’s actually a fundamental analysts focusing on is it just banks or the financials broadly?

Jeff deGraaf 42:12

It’s really payments. He’s really, he’s really payments. Yeah. Okay. So,

Dave Lundgren  42:16

I mean, at a shop like yours, you can, you can pick and choose what sectors you’re covering, you know, I can, I can certainly appreciate why you don’t cover everything. But given given your ability to really kind of choose where you can pick and make your bets on the fundamental side where you think you can add value, what, what what drew you there? Was it? Is it some, some added value that his observations kind of feed back into your bigger picture, macro thinking? or?

Jeff deGraaf 42:40

Yeah, I mean, look, when we go through credit, such a big part of our work, right, and we we, we measure credit, we look at credit, there’s a lot of misconceptions about credit, there’s a lot of interest in the M data, and you can have it, you can have, you can have it, you can have data, good luck. God bless you good luck, I don’t ever have to see that stuff again. I mean, we look at it, but it’s just not that just not that useful. But Howard is great at a lot of things. And one of the things he’s great at is the mechanism of the way central banks work. And so understanding the swap lines, understanding interest on excess reserves, understanding, he’s got a really interesting call out right now about whether the Fed will be able to manage the reverse repo rate, because they’ve sort of inverted curves in the very short end of the of the term structure. So that those are all important things to us because that that mechanism is is super helpful. And, and so we want to understand that. And he he’s got as good of understanding of that as anybody and, and then also is very adept at the payments. So everything from visa, PayPal, and the like, which, you know, frankly, is in that sort of innovators group, right, and keeps it fresh, and he understands the tokens and the Bitcoin and the blockchain and all that stuff. So that’s sort of morphed. We hired him originally for the macroprocess. But he’s, he’s always been good with the, with the payments.

Dave Lundgren  44:18

Yeah, I mean, this conversation has been replete with examples of how important it is to tie. You know, respect the fundamentals, but observe and analyze the fundamentals, Visa v the data, and then wrap it all up in a sort of a technical wrapper, if you will. And I think that’s, that’s, that’s just a great example of how the all three of these things, I’ve always said, there’s really, there’s really no right way to invest in the you know, the the best thing to do is to find the best of all and put them all together in one process. And obviously, you’ve, you’ve spent a lot, a lot of time doing that. Well,

Jeff deGraaf 44:48

I think there’s a couple things to think about there. And I had a conversation with a good friend of mine as a growth manager the other day, and you know, he was sort of he was lamenting about not owning enough of something or you know, having sold it to her And I said, Look, there’s, you’ve got, you’ve got two bookends here. Right? The one bookend is you, you, you buy Amazon in 1997, whatever it was, and you hold on to the thing forever. Right? Okay. I mean, that’s, that’s great nine. So that was the right thing to do. The other is that you don’t trust the internet at all. And you held cash, right? Yeah. Yeah. Alright, so you get you get your two bookends. Now, there’s got to be something in between. And so, you know, I think what what fundamentals do is they give you the confidence to see the big picture, you know, as to what can happen. And, you know, I want to be careful here, because the confidence can obviously be a problem. The technicals give you really the most unbiased way to figure out where you might be wrong. Now, look, that would have forced you to sell Amazon at some point in time. But what I always tell people is there’s nothing nothing, and you have to get over this. There’s nothing to prevent you from buying it back. Right, exactly what we buy it back well said Well said. And so, you know, does that mean that you know, you you maximize your wealth as much as you could by buying and holding Amazon? No, it doesn’t. But did you? Did you do it within a within the context of the confines of being able to have some type of risk control that you felt better about where you were, and had the flexibility, the mental and, you know, frankly, the financial flexibility to be able to take advantage of the reacceleration and the in the growth and everything else? So, you know, I mean, I just I don’t know how else you you do it? I think I haven’t seen anything. On the fundamental side that controls for risk, as well as technical analysis. It’s just discipline. Mm hmm.

Tyler Wood  46:48

Jeff, I wanted to ask, we, we all have some physics envy in every department. But specifically for investors, we’re looking for one, you know, cover all equation that explains the whole world with given how much work you do, how much time and effort and energy you spend on processing data and having a quantified view? How does how does your team avoid anchoring too strongly to something that has given them conviction? any recent examples where, where you really had to throw the baby out with the bathwater in terms of your data and analysis? And what techniques do you use to to not develop such a strong anchoring bias to to the quantitative side?

Jeff deGraaf 47:34

Well, it’s a really good question. Some of it is those the sort of, we talked about the consistency of the T stat, right? If we know that it’s always been negative, and it’s, you know, still negative, obviously, we have a lot more faith in it. Than then we would if it was, you know, jittery or showed, you know, some some other type of flaw to it.

But look, I don’t, we don’t get, you know, religious about this stuff. You know, we’ll go to church on Saturday and Sunday, and even Wednesday, we have to wait goes right. So, you know, I look, I think the thing that technical analysis has done for us is, you know, really opened our eyes in terms of just a fresh look at things. And when we run into these situations where, where the history is telling us something else should be happening. But the markets telling us differently. We we absolutely, I mean, not even, you know, questioning, we will come down on the side of the market, the market is telling us something is different. And it really is on our shoulders to figure out what is that that difference, right. And I think I think it’s a really important thing to do. Because if you can figure out what the one or two things are in the cycle, and you know, really get down to it, and I’ll give you a little hint, it usually has something to do with credit, there’s usually something in the credit structure that has something to do with it. But if you can figure that out, and where it’s impacting the economy, and then where it’s impacting the asset prices, you can really cut through a lot of noise and figure out what’s going on and have the confidence to be, you know, aggressive. There’s an old Bull Durham quote, which is I might screw it up, but something about play with fear and arrogance, right. So, you know, play like you’re the best out there. But also understand that at any point in time, you know, you can get punched right in the face, right. So and that’s what technical analysis does it It allows you to play. You know, in our view, it allows you to play with that arrogance, which the fundamental can help, but you have to have the respect and the the just common sense to say hey, look, something is different. It’s not doing as I would otherwise expect, and therefore, you know, we need to take down risk or change our thesis or just think differently about the world. And that’s what this chart that it’s up is a great example of that. I mean, you know, if this were, if this were following script, we would be short, everything on the left and long everything on the right. And you can see, that’s just not what the markets telling you you want to be doing right here right now. Now, that might be the case in July. But until that happens, we’re gonna stay with what the markets telling us

Tyler Wood  50:29

timing. Do you have any critiques, anything you found in the technical toolkit, that that led you astray? When you, you’ve been at this for a long time, and you’ve met to the best technicians in the business? Where, where’s the technical community gone wrong?

Jeff deGraaf 50:45

Well, I look, this is a, this is a purse, this is a personal preference of mine. I didn’t get into technical analysis to tell the market what to do. Right, I didn’t get into I didn’t get into this business to say, market stop at 4000, on the s&p on the upside pullback to 3849. But let’s look at 3842. And then, you know, break out and go to whatever, 5000. Right, I didn’t get into business to do that.

Tyler Wood  51:12

And I am the guy who taptic the bond market when he entered a dead top take Lehman Brothers with his resignation.

Jeff deGraaf 51:19

Better lucky than good question. You know, I think you want to listen to the market. And I think what technical analysis does, you know, as I tell my kids, God gave you two ears and one mouth. So what, you know, what are you supposed to be doing? Right? Listen to the market. And, you know, fundamentals don’t listen to the market. They’re talking all the time, right. And I think when technicians talk all the time, it’s a problem. I think you want to listen, and you know, use the markets message, and really take it to heart, you know, I mean, sometimes your boss has a message for you, and you want to ignore it, or your parents have a message for you want to ignore it or whatever, your wife has a message for you or ignore it. But you probably should listen to it. Right. I mean, it was probably hard for them to say what they’re saying. And it’s probably for your own good. And it’s the same thing for the market, listen to it, don’t try to tell the market what you know what it needs to do, because it doesn’t need to, and it’s not going to and so, you know, again, have that fear about what’s out there. And, you know, absorb it.

Dave Lundgren  52:19

Really, really well said, Yeah, absolutely. I mean, totally, you want to transition to maybe some of the more current current environment, conversation?

Tyler Wood  52:29

I think all of our listeners want to know where AMC is going to be out on July 13 2021.

Jeff deGraaf 52:34

What’s the ticker?

Dave Lundgren  52:37

Let’s Let’s start with like, like the just the big picture, because the the last 20 years, it’s almost like Alice in Wonderland. And then it’s gotten even worse, the further down the rabbit hole we’ve gotten, I mean, we’ve got we had negative oil, we’ve got negative nominal rates, you know, we see the put call ratio is being depressed for so long. And it’s it’s at a, I don’t know if it’s a record low, but it’s certainly a record time in this vicinity. And I know it is very depressing. At the same time, we have what’s happening with GameStop. And now we have this onslaught of spax, I can’t even tell if those are a good thing or a bad thing. All the leverage coming into the system, modern, modern monetary theory, all these things just kind of hitting us all at once. When you step back and look at the environment that you that we’re all observing, and you do your data work, run it through the filter, the technicals, I mean, where are we I mean, we are we truly it’s such a unique place that we’ve never seen this before. And as you like to say, where, you know, investing out of sample for sure, today, then more so than, you know, perhaps ever?

Jeff deGraaf 53:38

I think from the political environment, right? I’m pretty apolitical. But I think from the political environment, we’re probably in that mid 1960s, you know, the Great Society, everybody can have everything. I mean, look, to me, to me, economics is really simple. If you want to, if you want to, if you want to still economics down, it’s about one thing, it’s about choice. You got to make a choice, right? It’s either guns, it’s butter, it’s, you know, jobs. It’s inflation. It’s about choices. And so the Stephanie Kelton to the world come on with, you know what I mean? I like Disneyland as much as anybody, but I know, I can’t live in frontier land, the whole, you know, my entire life. So, I mean, there’s an illusion here, right? And if you look at people that have, you know, really been influential, they’ve been great salespeople. Keynes was a great salesperson. I mean, read Keynes, his work. He’s a great salesperson. von nesis, who was, you know, one of the probably preeminent Austrians was not a great salesperson. He had great ideas. He wasn’t a great salesperson. Milton Friedman had pretty good ideas and was a great salesperson. Stephanie Kelton is a great salesperson. And you know that the risk is there’s nothing really monad modern about her monetary theory, I think the risk is is that she’s a great salesperson and with all deference to stuff Keep in mind too, that when you become, you know, when you become the spokesperson for a movement, you’re not going to get to a point where you say, Oh, shit, sorry, no wrong, I’m just stepping back a little bit, right, you’re going to continue to press it forward, forward, forward. So she might not even believe it anymore. I think she’s probably still does, but those, they’ll get to some point where they won’t believe it, but she doesn’t have the opportunity or the flexibility because she’s, you know, she’s the Pied Piper. And all the rats are behind her, you know.

Dave Lundgren  55:34

as some of the box today is, is Cathy wood with her Ark ETFs. I mean, she’s brilliant. And she’s done a phenomenal job, she succeeded tremendously, but she’s now become the face of the movement. And it reminds me of like, trying to think about where we are, in terms of environments, it reminds me of the Janice funds in the late 90s. I mean, those guys were brilliant. They were they were held up on a pedestal as if perhaps they were more brilliant than they were, but they became the face of the movement. And it was impossible for them to change when they really had to change. And, and I think that’s another disagreed example of behavioral impacts on what actually, you know, makes real investing just not the same thing you learn about in textbooks?

Jeff deGraaf 56:16

Yeah, I think that the, the, the political environment reminds me of the 60s, I think the market that we are in, as you know, as investors, from a policy standpoint, from a what’s working standpoint, I think we’re in the sort of mid 1999, I would view long term capital, which was Lehman Brothers at the time almost almost went bankrupt, then. But it, you know, 1999 was the point of stimulus in the market, right, long term capital was a situation that obviously impacted the financial community didn’t impact the real economy that much because it was so fast, but they’re obviously concerned about it impacting the real economy, the Fed stepped in, you know, help to sort of lubricate the mechanism, because these banks took down and put the the assets on their balance sheets to unwind it. And so they sort of gave them a gift. The Fed gave the the banking system a gift, that helped to create the liquidity environment that then started to differentiate. Well, all stocks went up, right. And then in the mid part of 1999, you started to see just tech work right at the expense of everything else. We haven’t we haven’t gotten to that point yet, right? I mean, we we’ve got the chart in here. You know, where we talk about the the 6552 week highs? And you know, what distribution Would you rather own Would you rather own the distribution in red, or the distribution in gray. And the point here is that this is the distribution of red are now this is resample. But this is the sort of what you’d expect three months after 52 week highs exceed 20% for the first time in a year. And so you can see there’s clearly a skew here to positive returns. Importantly, the distribution is more narrow than the the other distribution, which is all of the times right, all of the three month returns, which means that not only is the return higher, but my standard deviation is lower, right. So basically, I can get about 50% more in equity returns with a third of the deviation that I wouldn’t any other three month period time again, resample, there have been, there have been three month period times where you’ve been negative, but resample is telling you sort of what you should expect on average, and the highest probability of the events. So we’re, you know, to me, this is not January of 1999, the Fed committed today to you know, keeping the dots where they are Neal data, and our team has been on that for a long time, we think it’s going to be the case. So I think these eight guys the current thinking, whether it’s from the Fed, whether it’s from politicians, whether it’s from society at large, think about demographics. I mean, you’ve got the you’ve got the millennials, now the biggest demographic group on the planet, you know, so we’re looking at consumption, boom, low rates, jobs, getting into that time of your life where you’re, you know, you’re having kids, you’re, you’re getting married, you’re buying houses, you’re doing all these things. We haven’t seen a consumption boom, and probably, you know, 15 plus years in in the US in a meaningful, you know, in a meaningful way. So, there’s a lot of differences here. But I think, you know, as we try to narrow this down to where we are, yeah, I mean, Cathy wood has had a great run with growth, but I think if you look at her process, you know, she’s very process oriented. She’s got a lot of really great ideas. And she’s got the humility and the flexibility to change when she needs to. I think I think she’s gonna she’s she’s doing some great unique things that Yes, she’s helped define this bull market a little bit. But I don’t think it’s at the exclusion of everything else. And that’s usually where it becomes more problematic.

Dave Lundgren  1:00:10

What are you when on your team when you guys have discussions about about Bitcoin and sfax. And these things that are happening, I mean, these are, these have the potential to be structural changes in the finance business, but they also can be pretty good sort of leading barometers of speculation and risk on behavior. I know you actually featured, as he was, in your note this morning about how Bitcoin moving to new highs is a good indication of, you know, risk on behavior. But on the other hand, it’s also it also is it does have the potential to actually be a structural change in the financial business. How do you guys think about those two things?

Jeff deGraaf 1:00:51

I think it’s a really, really unique, unique asset. I mean, I can’t think of anything else we’ve seen that, you know, has had that disruption ability, like it has one thing I would just say about Bitcoin, which is, you know, unusual, we had a parabolic rise back in, I think it was late 17, right under 18. And, you know, than it did, what parabolic rise is do right, it went into dormancy, it lost, you know, 70% of its value. And what was unique though, is it’s come back and clearly broken out 200% ago. And that doesn’t happen, right? That’s one thing that though after you go into a parabolic state and crack it, you know, to lips Selsey bubble you name it, you know, go into it, that doesn’t happen. You don’t come back. I mean, you can you can look at Qualcomm, right? It’s taking Qualcomm 20 years to get back to where it was, it’s, you know, is micron making better chips today than they weren’t in 1999. Absolutely. And yet, the stock is only back to where it was, right. So it takes a long time, and you know, a whole new generation to work through that parabolic rise. So look, I think if I had to, if I had to make my bet, I would say Bitcoin has legitimacy, and it’s going to be with us for a while. You know, the reality is, and I’ll be the first one to tell you, no one knows. Jeff dygraf doesn’t know. Mike Novogratz doesn’t know, nobody knows. But you know, some people play it and some people decide not to, I think it’s got the ability to transform the way that people think about currency. But it’s not a store of value, it can’t be a store of value when it when it you know, loses in games, five to 10% on a daily basis. That’s just, that’s just not reasonable. So I think it’s transformative. I think it’s speculative. But I do think that you want to have some exposure there in just a, in some way to have some skin in that game, because it is something that could really be revolutionary.

Dave Lundgren  1:02:56

Yeah, that’s a really interesting point about how, how quickly it came back to the prior peak, when that presumably was a speculative bubble. That doesn’t, doesn’t happen. It hasn’t happened historically. In other cases, I just say, generations before they come back. Yeah. Now that is, that is a distinctive, wouldn’t you want to,

Tyler Wood  1:03:15

wouldn’t want explanation be that so few people were participating in, in Bitcoin or any other cryptocurrency or digital asset prior to Thanksgiving? 2017, and that there was still so much money on the sidelines for digital assets coming into 2019, that maybe there were there were just less people bruised by that crack parabolic move. Right? That? Yeah, sure.

Jeff deGraaf 1:03:39

But, but usually, when it gets to that point, there’s, you know, it, whatever it is, is just sort of moved the, the the tide of society has gone out, and something else, you know, takes us places it but i think i think you hit on a really important point, which is, it’s still not easy to buy. Right, like I you know, my exposure is not through owning Bitcoin on a, you know, zipped digital wallet. Yeah. I mean, you know, so it’s still not really where it would need to be to have that full indoctrination of the public. And so I think that’s an important, you know, an important distinction that we don’t have, yet full access, you know, in a in a meaningful way. Or a simple simple, like non friction, you know, non fictional one.

Tyler Wood  1:04:30

I think the fact that there are so many other even further speculative outlets for people who are really into mania ism and NF T’s or, or looking at, you know, non fungible digital tokens that that there’s a place for people who are extremely speculative, and maybe Bitcoin looks pretty vanilla by comparison to that.

Dave Lundgren  1:04:53

That’s a statement right there. about where we are. So Jeff, I know you have a client meeting coming up, and I want to be respectful of your time. Any any other things we haven’t touched upon yet that you wanted to make sure the CMT community heard from you while we have you?

Jeff deGraaf 1:05:12

Well, you know, one thing I would say, when you when your fundamental investor, you know, you they really bucket you into one or two things, you’re a fun, your fundamental growth investor your fundamental value investor, right. And those are very two different types of investors. You know, one tends to be more optimistic and looking to the future and growth investing is hard. and the value investor tends to be more incredulous, and, you know, thinking about the world in terms of cigar butts. And, you know, how much can I can I can I make off of this? You know, margin of safety and suppose other things. There’s, there’s not really that big a distinction between that and in, in our community in technical analysis between trend following and mean reversion. And so I think, you know, one of the things that you just need to decide as a technician, is, how am I going to approach this? Do I want to be a mean, revert? Or do do I want to be a trend follower? And that really, you know, it’s, it’s a relatively simple question, I can help you make the decision, which is, you know, if you look through time, trend following does have a lot of legitimacy, it generates alpha, it is not about that illusion of control. mean reversion at the peaks obviously becomes really, really important. But most of the time, by the, by the time you’ve hit the peak, and you’ve made the proper call, you know, was that the fifth call was at the seventh call was that the eighth call that you tried to get out of it? Would you have been better off just being in the trend, and, you know, having taken a 10, maybe 15% drawdown to see that trend, reverse and then play for the other side of it? I understand, you know, both both sides. But when it comes down to predictability when it comes down to, you know, having what appears to be the right call, you’re far better off being in all of our work that we’ve done a trend follower with a consistency that trend, and we’re always looking for wealth maximization. What does that mean? We want the most amount of money that we possibly can have, at the end of a cycle. And the best way we found to do that is through trend following. And so the illusion of control the I’m gonna buy it down here, sell it up here, there’s, you can use that stuff. Absolutely. But it needs to be within the context. And the context that we found to be most important is that of the underlying primary trend.

Dave Lundgren  1:07:46

Well said, I couldn’t agree more. I know. You’re, you’re in your spare time. You you like to ski. You like to fly. I’ve seen it a tire on your wall, but I’ve never seen you play it. Like Earth Roxanna. Anyway, exactly. But you know, when I sail, and I see a lot of similarities between sailing and investing, so when you’re skiing, I know you do quite a bit of skiing, powder, skiing and flying, do you? Is there anything you’ve learned from those things that has helped you as an investor or that you’ve learned investing that has helped you think about, like flying or managing risk while you’re flying? Or determining if you’ve got avalanche risk or anything like that?

Jeff deGraaf 1:08:29

Yeah, I mean, preparedness, right? I mean, those are, those are two really important things. You can’t You can’t prepare for every scenario. And it’s true for investing, right. But you have to have some point where you say, if things get to here, I need to think differently. Right. And that’s certainly true for flying, that is true for, you know, back country skiing, where it’s just not worth the risk. And I think that does translate into into investing. I would, I would add that you want to have that ahead of time, right? I mean, so when I’m flying, I’m you know, I’m lucky enough that I’ve got an instrument license and, you know, compliance pursuit, but there are personal limitations where your looks like I’m not, you know, that comfortable here. And so, whether it’s a three mile visibility, whether it’s a you know, one one and a half mile visibility, they call minimums in flight, you know, what are your personal What are your personal minimums? And it’s the same thing with investing is it you know, when I when I’m a momentum investor, is it a, you know, is a hard stop drawdown? Is it a volatility, drawdown? How do I want to think about that? Is it a trend change? Is it you know, what are those things because in the heat of the moment, I want to be doing things consistently. I don’t want to be playing by the seat of my pants, because that’s where I’ll let the emotions get the best of me at the point where they really get the best of you. Right? And so, by having it scripted out ahead of time, I think it’s really really important. And look, I understand Some people want to, you know, have that art of you know, just I feel it, whatever. But look, you know, can you hit blackjack with a 19? And take a card? Yes, you can. Is it a good idea? No, it’s not. Right. So just, you know, think in terms big picture, think in terms of probability things and think in terms of putting the advantage to your side. I think trends are important. And I think it’s gonna sound a little it’s gonna sound a little bit duplicitous, but and I think contrary opinion is also important when you have enough of the data to understand where there’s that vulnerability.

Dave Lundgren  1:10:41

perfect spot to wrap it up, Jeff, how can our listeners follow you or or reach you or any any contact information you want to provide?

Jeff deGraaf 1:10:50

Probably the best is our Twitter account. We post a lot of stuff, both policy economic and obviously our market stuff, which would be rent GMAC LLC at Red Mac LLC. Great way to follow us and a questions you can always get us there.

Dave Lundgren  1:11:06

Yeah, I follow you there, for sure. And to our listeners, and hopefully viewers, if we can get this on video, highly recommend it. It’s a great way to stay in touch with what Jeff is thinking in not just Jeff but his whole team. I would just maybe wrap it up with just a big thank you from the CMT Association for for your time today. And for of course, being a, you know, a great emblematic example of what modern day technical analysis looks like. well executed, very thoughtful, but also very practical. So Tyler, anything you want to you want to wrap up with,

Tyler Wood  1:11:38

really appreciate your time today, Jeff, and thank you very much for this conversation and many more in the future.

Jeff deGraaf 1:11:45

It’s a great organization, keep keep fighting the good fight, guys. It’s really, really important not only to the investment discipline, but for just the sanity check in, you know, in the world. So love what you’re doing. Keep it up.

Dave Lundgren  1:12:01

Thanks so much, Jeff.

Tyler Wood  1:12:02

Happy St. Patty’s Day. Ah,

Dave Lundgren  1:12:04

yes, thank you and you. Doug, Casey, you guys. As we mentioned at the outset, Tyler, what one of the objectives of the podcast is to keep folks abreast of what’s happening in the CMT Association. Why don’t you give us an update on what’s happening in the near future? Absolutely. Dave,

Tyler Wood  1:12:27

we’ve had a very busy spring for those members who were able to attend. earlier last month, we ran a full day seminar on behavioral finance topics in March, really high quality speakers brought together by our chapter Chair, Mr. Own cup. So you’ll see Professor john Knopf singer, the illustrious David Keller, and Brian Brogan professor at St. Joseph’s in in Philadelphia, just trying to unpack some of those investor behaviors. Obviously, at this point in the cycle and some of the pretty incredible things that we’re seeing happen in the markets. It was a very timely point to refer back to a lot of the material that’s in our CMT curriculum, trying to understand investor behavior and some of those irrationalities that exists at extremes but also the heuristics that every investor faces in terms of our own biases. So a great day great content and lucky for all of our listeners, this was recorded. It’s free and available to all members of the CMT Association. And for those of you who are just in the in the path of learning want to understand a little bit more about the the mental game of trading and investing or about technical tools really want to encourage you to join as an affiliate member of the CMT Association and have access to not only our behavioral training seminar, but about 40 years of really incredible educational content that’s in our archives. So that was a that was a great event. Dave, great feedback from all the participants. And we’re looking forward to having even more content. Here. At the end of this month, the CMT Americas summit, that conference will take place over two days, April 29, and 30th. And it will feature what technicians do best which is understanding how to take advantage of trends in this marketplace while managing risk. So we’ll we’ll divide that those two days into four segments. We’ll learn from some of the best experts in the field, Chief fix strategist from Bank of America, Mr. Paul Sienna, will bring in portfolio managers from Millennium partners that are running oil and natural gas funds will talk deep dive around the commodity space also rates and currencies, and even dive into a little bit more on the digital asset space and new emerging trends that are coming out there. So it’s a great day great chance to learn from a number of technicians, market analysts and portfolio managers. That’s April 29, and 30th, the CMT Americas summit, you can register right now at CMT. association.org and Dave, I wanted to turn it back to you because you’ve been a busy lecturer yourself I know retired from from Brandeis University recently. But still keeping, keeping the torch alive, teaching investors about the links between fundamental analysis and technical analysis. Can you tell us a little bit about what you did for the CFA society? Boston last month?

Dave Lundgren  1:15:12

Yeah, absolutely. They They asked me to give a presentation on the links between technicals and fundamentals and in how institutional investors use technical analysis today. So we did did a bit of a deep dive on that using examples and really just trying to, I guess, dig out the the the best slides from my Brandeis days that I use to help students instead, of course, investors draw that the connection between the two and how important they are. And in frankly, unbreakable they are. That discussion was moderated by Heather young over at Luma sail, she did a great job. And I think it will, you know, we’ll provide a link to it in the resources because I think, since since publishing it, we’ve gotten some great feedback on how the discussion in unique ways in ways that were under appreciated previously, to drive in those connections between technicals and fundamentals, so our listeners will be able to see that presentation in the resources.

Tyler Wood  1:16:10

That’s fantastic, Dave, really incredible job condensing 14 weeks of a semester long course to just 45 minutes and discussion for the CFA society in Boston. I really enjoyed that presentation, and we will link to the recording in the resources section. Thanks again to all of our listeners, for tuning in. We really appreciate your feedback on this podcast series.

For those of you who have ideas, topics, themes, speakers and guests, please send that feedback to podcast at CMT association.org you can reach Dave and I there and once again all of the resources for Episode 4 of Fill the Gap with Jeff deGraaf are available go.cmtassociation.org/ftge3, that’s Fill the Gap Episode Four.

Thanks again for listening and we’ll see you next time.

Fill the Gap is brought to you with support from Optuma. In addition to candidates study of the official CMT curriculum, Optuma provides a full video course on all of the material that candidates need to know for each level of the CMT exams. Each course is broken up into modules, ranging from 15 to 45 minutes, depending on the complexity and length of the topics being covered. Learn more www.optuma.com