#44 - Jeff deGraaf: Technical Analysis

26:32You might have a pullback down to this level, which is X deviations, et cetera. But when we really look for our opportunities, it's what the market's giving us, not what we want to project on the market. What do I mean by that? Somebody might say, well, what do you think about NVIDIA? and say, okay, well, it's okay, the trend's up and the relative performance is breaking out, that should be all right. But maybe you should be looking at this because we know that it's oversold, it's in an uptrend, it's got these characteristics that we look for. And when we go back and look, these are high probability long-term winners.

27:07Well, you didn't come to me with that name. I'm just giving you that name. And I think that's one of the things that we're very good at, which is sort of being receptive to ideas. is we're not trying to force what we want to happen on the market. We're listening to what the market's giving us and trying to use that. And I think about it exactly the same way as trying to make a living in New York City, walking around looking for$100 bills in the street. You might find one, and if you do, you're going to pick it up. And absolutely, you should pick it up. But you're probably going to go hungry pretty quickly, right?

27:38Instead, we're just saying, look, we're not trying to force that somebody's going to drop that bill on 42nd Street. Like it's just, it's just not how we think about it. Right. So we're looking for ideas as they come to us. When we see a dollar bill, we're going to pick it up. But we're not going around saying this, you know, somebody drop a dollar bill for us, please, for God's sakes, we need a bowl of soup. And so that's one of the things that I think is really important. And if you want to use this discipline to really make good money, you have to be willing to not say, we're going to have X percentage in semiconductors and X percentage in energy.

28:18You're just going to have to do what the market tells you is the high probability events. And that might not be as much fun. I mean, I know that there's a certain utility, you know, to ripping apart balance sheets and going through it and understanding what the company does and having management meetings. I get all that. We just think about it differently, you know, in terms of finding those opportunities. Yeah, you made a very important distinction, which is it's not about predicting the future with certainty. It's about putting the probabilities in your favor. And technical analysis is a great way to do that.

28:51Without question. It's, you know, we are essentially trying to find the coin that is going to come up heads two thirds of the time. That's it. And even in the cases where it's less than half the time, if there's asymmetry in the payoff, that can be very valuable as well. Absolutely. Yep. And those are more of our behavioral elements. We had a great example. We had a capitulation signal in China back in the end of January of this year. and we just know that there's a high probability that it's going to bounce. After about six months, we frankly have no idea. Sometimes it continues, sometimes it doesn't.

29:31We just got the reaffirmation of that, which was nice and supportive. But what we really know is that the downside versus upside is absolutely skewed positively. So even if it's just a 50-50 bet, which in this case is actually better than that. But even if it's just a 50-50 or less, we know that the upside is substantially different than the downside. Now, the hard part, and this is where narrative is important, the hard part is nobody is thinking about owning those names at that point in time. That's one of the reasons why you have capitulation, right? So the narrative is it's uninvestable. I can't invest in Chinese communism.

30:09I can't, you know, blah, blah, blah, sanctions, et cetera. You have to be able to put that aside. It's not easy to do, but we've just got enough iterations of this that we've seen it time and time again. And I think that's an important part of one of the things that we do when we go back and look at these things. We pull the news sources, right? We pull what was the New York Times saying about this the week before and the week after? What was the Wall Street Journal saying about this around the point of the lows? And we do that because we want to construct what was happening. So when we talk to clients, they can see this was not, you know, some guru out there saying, buy it.

30:45This was not the data was getting better. This is not fundamentally based. This is a behavioral nuance that we recognized and is likely to move in our favor. But with that, you have to have the intestinal fortitude to be able to stand against the crowd. And that's challenging. There's no doubt about it. So, you know, we've put our hands over our ears enough times that it's easier. It's easier for us to do it. And we've kind of become I'm tone deaf to those concerns, but it's certainly behaviorally, mentally a challenge. Are there other behavioral aspects that you found to be persistent through time that don't generally get discounted by markets?

31:25Well, overconfidence is one, right? I think that illusion of control, people believe they're better at predicting the future than they really are. And so the overconfidence is one that we find a lot, particularly with indicators. And there's a lot of time spent on Wall Street, digesting earnings, earnings estimates, a ton of time. And if you look at the return per unit of time invested in that, it's not very good. So what we really try to focus on is where do we get the most bang for our buck, if you will, in terms of return on invested time and look for those. So we see a lot of that. We see it in some of the economic figures.

32:12We see it in some of the fundamental data that people are really, really focused on. And maybe that focus has taken the edge away. You know, maybe it worked 40 years ago. And as you pointed out earlier, with technology, it's, you know, kind of become too easy to do and it gets arbitraged away. That might be part of it. I don't know. But we have ways that we measure that through time to see if these indications are still holding up, if they're getting better, if they're getting worse, and how we should think about it. You've emphasized the importance of credit markets. Would you expand on that?

32:46Credit just makes the world go round, and the availability of credit makes the world go round. And there are a lot of different ways that you can look at that. I think, one, we're just talking about kind of overemphasized indicators. M2 is a highly overemphasized indicator in terms of its actual predictive power on markets. There are some ways that we look at the balance sheets and some other things that are certainly helpful, but even those are supportive, you know, we call conditional factors. Their conditions are supportive of a bull market or maybe a bear market, depending on where they are.

33:22But credit for us in the availability of credit, and by the way, that's always changing. And so that's kind of one of the fun aspects of this business where, 15 years ago, hardly anybody knew what a credit basis swap was. And I'm sure that's still a pretty esoteric term. But it essentially showed us what the stress in the system, the foreign lending markets were to dollar funding. In other words, I need dollars because my loans are being paid in dollars and I'm not getting access to dollars. And that was a big problem back in the great financial crisis. And lo and behold, the Fed waved their magic wand and We created these direct swap facilities with the ECB and others that needed them.

34:00So we had to figure that one out, right? So we could see the stress building, and then all of a sudden that stress went away. We're like, well, how did that happen? And then we saw these new facilities that the Fed put in place. So that's always changing, right? You've got the reverse repo agreements now that are in place. So the credit markets are always kind of evolving to try to bypass, if you will, maybe the cardiac arrest that's happening in the markets. And they're looking for different ways to be able to get around that. So we measure the price. We measure the availability. We measure all those things.

34:34And we have about 35 different indicators that we look at on a daily basis just to see where the stresses might be percolating. And right now, actually, I think it's one of the things that the bears missed in this 2022-23 transition as we started to move higher. I mean, our work got bullish in the fall of 22. And then we got trend confirmations in January of 23. So pretty quickly. And we've been riding it really ever since then. And there was a lot of concern about the yield curve. There was a lot of concern about all these other things that had been predictive factors historically. But I think there were a few things that were missing from that.

35:15And one of them was just the relentless improvement that we're seeing in credit. And if you're going into a recession, credit is going to be at the forefront of showing the stress in that system. It just wasn't. So, again, that was something that the narrative was built around that wasn't being corroborated by the markets. And that, for us, provided an opportunity to be substantially more bullish than the crowd because, again, we were listening versus trying to tell the market what it needed to do. And that's a perfect example because I remember very clearly the beginning of 23 that nearly every economist was predicting a recession because they look at the interest rate hikes that were the fastest pace in 40 years, the inverted yield curve.

35:59All these things are very predictive of a recession. So everybody was expecting a recession. And what you're saying is by just looking at what the market is telling you, you saw almost the opposite of that. Yeah, yeah, absolutely. And it's not always going to be right. I mean, that one really stands out because your point being there is a predominant narrative around that, right? That was really infectious in the street. And, you know, we were kind of looking at each other saying, well, if that's the case, why is this happening? Why is that? Maybe that's not the case. Maybe this consensus has it wrong and the market is telling us that.

36:31Or, you know, maybe whatever the recession was really had played itself out and discounted in the middle of 22. And now things are incrementally just going to get better. And that's what we find. And I think that's an important point, which is there's a lot of interest in recessions in our business. Recessions don't do you much good in terms of making money. because by the time the recession is called, the market is usually troughing out, bottoming out, and actually potentially going higher by then. Certainly, it's not recession, then bear market. It's bear market, then recession, then bull market, then six months later, they say the recession has ended.

37:15But if you're waiting for that, you're going to have below average returns almost guaranteed. The market is this discounting mechanism That is anticipating all those things taking place and really reacting at the margin. There's a saying, I wish I coined it. I didn't. I don't know who did. But there's a saying, which is the market cares about better or worse than good or bad. And that is 100 % true. So you and we saw this a lot with inflation. Well, inflation is six down from nine, but it's still high. Like market doesn't care. Market cares that it's down from six and it's probably going to go to four.

37:56And yet four is still high, but it doesn't care. The market cares about the trajectory, the rate of change better versus bad. And that ends up being, I think, a really important lesson in this business that it's really about the first or second derivative, not the level. And is your sense that's the case because the market is discounting the future and it has some expectations, which is basically what the consensus view is. And what really matters is how the future transpires relative to what that base case is. Yeah. So now you're getting into the three-dimensional chest, right? So if you know and I know that Apple is going to grow 25 % over the next two years, well, 25 % is not going to do it.

38:45That's already priced in. So it's going to have to be substantially better than that or showing a trajectory to be better than that. Now, maybe if people aren't positioned for that yet, there's still an opportunity. But if that's very well discounted and in the marketplace, then you know they come out with 26 or 27 probably doesn't matter right it probably isn't good enough because it's fully saturated there you know everybody or quote-unquote close to everybody who wanted to have a position in apple will will be there and we saw some of that with nvidia this summer i mean that was no doubt in the spring in the summer um that expectation game was just so high that it was almost going to be impossible for NVIDIA to put up in the short term, put up the kind of numbers that was going to allow the stock to do substantially better than what those expectations were.

39:39And I think the other part of this, keep in mind that historically speaking, news tends to be pretty equally distributed, right? So if you've got this confluence of just great news that's kind of just fallen upon the market or the security, the opportunity for just a mediocre or maybe a little bit of an outlier bad news can have a tremendous impact, right? Where if it's not extended, if it's just kind of humming along and the news has been equally distributed, that news might not have made any difference whatsoever. But if people are positioned for this just constant onslaught of great news that they've had, and you get this kind of mediocre data, all of a sudden that has an outsized impact.

40:22So that 3D chess is not only is it important to understand what the expectations are, but are people positioned for those expectations? Because that has an awful lot to do with the profit potential or loss potential of that security. And I feel like this is one of the main reasons why it's so difficult to predict the future, because not only do you have to guess what's going to happen, but your view has to be different from the consensus and it has to be correct. Correct. Yep. That's exactly right. So what would you consider the main limitations of technical analysis? Well, it's a faith-based system, right?

40:59I mean, everything is, if you really kind of think about it, you have faith in, I think management's going to execute. And I think all those end up being faith-based. They might not be as explicitly faith-based. But, you know, if we say, hey, this looks like a great opportunity and here are the reasons why based on this analysis, you know, a lot of people don't want to or can't invest from their own internal constituency in a sort of non-narrative type of way. So I think that's something that you have to overcome. And look, I think 95 % of our clients are fundamental investors. They rely on us because they know that we're very good at detaching ourselves from whatever that narrative is and just providing that pure stream of consciousness, if you will, of what the market is telling us.

41:52So when they get that and then they can attach a narrative to it, they love it, right? That's exactly what they want to see. And knowing that the market's telling us something that they think from a narrative perspective actually makes a ton of sense. So it's that disconnect of believing that that$100 bill that's lying on the street is actually a$100 bill. You have to believe it every single time and you have to go down and pick it up. And how do you address the potential for widely known technical indicators, potentially losing effectiveness over time as it becomes more broadly understood that that's an indicator?

42:31Yeah, I think all these indicators, I mean, and we're talking about earnings estimates, so let's throw fundamentals in there too, right? So let's look, price to book has been a disaster for the last 30 years. And earnings expectations has been pretty poor for the last 15 years. There's been fits and starts. You can see a lot of this on Bloomberg. It'll tell you kind of what's got the hot hand. So one of the things that we do is we always look at a rolling T-stat of the efficacy of the indicator to the forward returns. And so we can see what's actually improving, what's getting better, and what's getting worse.

43:09Now, if that goes from, you know, over a period of time, plus two to negative two, and in the middle of the T-stat zero, then what's, you know, what's the point? Like that it's just not reliable enough to work. If it ebbs and flows between significance but is getting better, then we'll start to use it. And that does happen. You can get trend-following techniques that are improving or the sensitivity starts to go down or up. And you can get mean reversion techniques that do the same. Now, one of the ways that we do that is we measure it through time to understand. So instead of just using something static, we'll use what we call dynamic moving averages.

43:46So we understand kind of what the sensitivity of the marketplace is and we'll adjust the moving averages for that sensitivity. And what that allows us to do is kind of capture the big waves and then adjust. And this is slowly happening. It doesn't happen on a day-to-day, hour-to-hour basis. But then as the markets become maybe more volatile, then it allows us to readjust for those so that we're capturing that volatility as well. So I think for everything, you should be doing that to know that, hey, if I went back and looked and said, free cash flow to enterprise value is the bomb. That's it. That's like, you don't need to use anything else.

44:29And I just happened to pick the point in time where that hadn't worked over the last 20 years. And then suddenly it didn't work going forward. You know, that's just a mistake on my part for, you know, kind of buying into something and hoping I stay in business for the next 20 years where it didn't work, right, and didn't do any good. By measuring that through time, you can see that degradation. In fact, the Fed was the original generator of, or I should say probably the biggest marketer, of the earnings yield for equities versus the 10-year yield back in the early 1980s. And that had worked great for the last 30 years or whatever the data was that they published it.

45:11And going from that point forward, it was systemically wrong. and it really hasn't worked as well from that point. So that's a very easy, not just for technical analysis, such for all the indicators, that's a very easy trap to fall into. And so we make sure that we're looking at this through a dynamic process that at least if we don't adjust for it, it at least measures the efficacy and we can, as we see it degrade, we can start to say, hey, this is less effective. In fact, we did this for the yield curve. And when I got in the business in the early 1990s, 1990, the yield curve was kind of the end-all be-all.

45:49Like that was it. And if you looked at it, the T-stat was extraordinarily good. You almost didn't need anything else. And by using that rolling T-stat that we talk about, you can see that that has degraded to the point of actually practically worthlessness over the last 10 years. It's really started with a great financial crisis when they pegged yields. But if you looked at that, you would not have made the kind of, I think, emphatic statements that people did around the yield curve, because you could just see that the deterioration of its efficacy was just blatantly obvious. Yeah, I think it's a really important insight, because what I've learned by talking to great investors who've been in the market for a very long time is one of the keys to long-term success is being adaptable.

46:40and you can't have a dogmatic approach to investing because the market learns and improves with time. And what you just described is you have some indicator that's worked for a long period of time. Once that becomes more widely appreciated, then you really have to pay attention to almost the trend of that metric working. And when that trend starts to turn negative, then you don't use it very much because its predictive value has significantly degraded. Yeah, that's absolutely right. And look, there are just like a basketball player, there are indicators that will have hot hands and then, you know, and the cold hands.

47:17And, you know, look, if it's over a long enough period of time, that hot hand might be worth, you know, incorporating or at least having some input into your models. But without knowing where those are, I think, and just kind of hope and guessing, that's a recipe for disappointment. It may be helpful to provide a few examples. If we go back and look at stock market history, What were some extreme periods for some of your key indicators? Well, clearly COVID, right? And I will say, if I were to raise my hand and say, hey, where are you not going to be as strong as what you would like? Within the elements of a crash, it's very hard, right?

48:03And I think that really is as lucky as it is good. so most of our indicators in 1987 there were a few that were hey you know some caution but not not this is going to be a crash caution i mean you know you probably had 15 of those you know kind of similar events that didn't result in the crash so you have to always think about that way um so you know if you're going to say hey we're going to have a crash i'm going to say okay i don't know if that we're going to be great at that right that's going to be tougher particularly if it's an exogenous event. We were good. I would say a lot of our reputation was built around the great financial crisis.

48:39We saw that with a lot of foresight. In fact, we saw it with so much foresight that it was getting to the point where I was getting tired of being bearish. Even though the market was going our way, it was such a slow rolling train wreck that when you come in day in and day out, it was taking a long... I mean, we saw it. I mean, just to give you some sense here, we started seeing it in the credit markets and the swap markets in particular in the late spring of 2007. That then translated into the Bear Stearns, which had a hedge fund that blew up. It was part of a mortgage book. So, it's kind of the first indication that there was that problem.

49:17And then it just kept kind of slowly seeping its way in. And we saw it in the banks first with the big top formations. And then as we get into 2008, we saw it with obviously the deterioration in some of these more industrial names that you wouldn't have expected to be a problem. GE is a great example. AIG is a good example, obviously not an industrial, that you wouldn't expect to be a problem to kind of the housing market and what was going on. Again, remember the narrative at the time, right? It was mostly housing related. But we started seeing these big top formations in bad charts in what later became obvious that it was the financing arms of these corporations that was then causing the problem for those corporations, right?

50:01And to create an existential threat, right? Which at that point, you would never have thought that that would be the case for some of these big bellwethers, if you will. So that was a long-term – we saw it coming in the credit markets. We saw it coming in trends. We saw it just kind of slowly evolving. And then in 2009, we saw kind of the extreme oversold condition. And again, one of those capitulation signals. And then what we call this momentum surge, this acceleration wall. Very similar to what we're seeing in China today, by the way. So that was very important to us. And we rode that for an extended period of time for years.

50:43COVID was just kind of out of the blue and disastrous. And a friend of mine has a great saying, which says, if you're going to panic, panic early, which was absolutely true at that point in time. We had some positions on that were extraordinarily helpful, but I don't feel like we were high-fiving each other about that call. We were at the bottom. We absolutely saw the other indications and said, hey, that was a disaster, but this is not going to be a disaster going forward. We had a very strong call looking for the market to double out of that at the time. So that worked out great. So the crash type of stuff is really, really tricky, particularly when it's exogenous like that.

51:28It just doesn't kind of line up. Or if it does, it would have lined up 50 other times that didn't crash. So how should you really think about that? And I think that's an important philosophical thing that we think about, which is there are two types of errors in this business. There are errors of omission and there are errors of commission. I'll explain each one. Errors of commission are the ones that everybody talks about, right? I bought NVIDIA and NVIDIA went down. I made a mistake. I sold NVIDIA. Okay, fine. That's an error of commission. I acted on it and it didn't work out. But should you also take into consideration or account the error of omission, which is you saw NVIDIA in 2015 and you didn't buy it and it did what it did, right?

52:10So even though that didn't maybe directly impact your portfolio because it didn't feel like a loss because you didn't have one, it was certainly a lost opportunity. And so, you know, when we look at things, we actually look at things both from an era of omission standpoint and an era of commission standpoint. Because I think if you blend those two and you start looking and saying, hey, I had a bite at the Apple of NVIDIA and I took it. Well, that's going to go a long ways to helping to nullify some of those small errors of commission that you might actually employ or have. So that for us is super, super important.

52:47and gets back to, you know, you're not going to find us talking about crashes much. We'll talk about bear markets for sure. But to say, hey, we think this is, you know, those are sensational for headlines. And the reason that we don't is, one, they're very hard to predict. And two, if we were really being intellectually honest, we wouldn't call it a victory to say we got that one right and we missed 100 others before that because it didn't happen. I mean, that to us is just as painful, if not more, than getting it right. So that's how we think about it in kind of full intellectual honesty of how we want to manage this process.

53:21When I look back at the crashes we've experienced the last several decades, I agree calling the crash is difficult. Is your sense that calling the rebound is a lot easier? Because what I've noticed is you have complete capitulation at the bottom and you have the government stepping in, providing massive stimulus. And I think if you put those two together, it seems like those are the points where you tend to get the recovery. We just saw recently with China. And you can see it being persistent, at least conceptually, because there's just so much pessimism and the outlook is so bad. And behaviorally, it's really hard to buy at that point that it seems like that type of indicator may be more persistent through time.

54:06Well, yes, I would say recently. But keep in mind, that's kind of a new phenomenon, right? The Greenspan put. That has not been – certainly, it's not ubiquitous globally. It's become a little bit more so, but not entirely. You know, and I think for good reason. I mean, you don't want the government to pick winners and losers necessarily. And so, you know, backstopping. And look, they tried to do it. they tried to do it in around the 20th of November, 2008, with the first TARP program and inject liquidity into the balance sheet of banks. It didn't prove to be big enough. Right. And then they did it again in early March of 2009.

54:48Nobody was talking about it, but that did help to spark the equity market rally. And part of that was because people thought it was inefficient, right? It just wasn't going to really work. The problem was too big is what the expectations were. I think that's the environment that you want, where I like to hear that the government's out of bullets, the central bank's out of bullets, the authorities are out of bullets, and they're not going to be able to save the system. That, to me, is good news because that does create that concern that's out there. And then you get the Mario Draghi moments, we'll do whatever it takes, and they end up backstopping it.

55:22Now, maybe they backstop it incrementally, right, which is probably better than just here's a trillion dollars, let's see what happens. You know, it's kind of making sure that you're backstopping it through time. I'm sure there's, you know, some type of unintended consequences to that, too. But building, you know, allowing that confidence to come in, allowing that money to kind of find its way through and be productively used, I think, is super important. So we'll see. I mean, I don't I understand the reluctance in China right now is because, you know, people don't believe in communism. They don't trust Xi Jinping.

55:56I understand all those things, but I do see this, again, sort of putting our hands over our ears and looking at what the market is telling us today is very similar to some of these other points in time that were pretty meaningful moves. And even if this one proves to be wrong, again, the idea is that if it's wrong, it's wrong by that much. And if it's right, it's right by a lot. That makes a big difference. It's a very fair point because what I said earlier has this assumption that the government or the Fed has significant credibility when they come in and say, okay, we're going to, you know, not on our watch is this going to happen.

56:31We're going to do something to recover economically. They have to have the credibility for the market to react to that. And you shouldn't assume that's always the case. Yeah. And if you think about it, right, I mean, we've seen some mission creep, if you will, Right. Every time, like in the charter, they were only allowed to buy public debt. Right. Now it's private debt. Now it's not even limited to investment grade debt. Right. At what point does that start to flow into equity ETFs? Right. So as that mission creep gets larger and larger, I think the concerns as kind of the free market become higher and higher.

57:11Right. That you can't just save the system for itself, but it has to be done in a way that, you know, it's going to reallocate capital in the most efficient ways. And that means, you know, some people are going to go to zero, right? But that is going to clear the way for the others who have been, you know, more prudent and stronger and, you know, maybe less reckless way gives them the opportunity to step in and reap those rewards. So how do you incorporate political and policy uncertainties that we just talked about into your analysis? Yeah, it's a really good question. The first thing I would say is they're almost always overblown.

57:49They're almost always, there's a lot more emotion to them than there is reality in terms of whatever the rhetoric may be. It just doesn't, you know, I think that's part of the beauty of our system, which is divided government. And what you really want is kind of gridlock where neither one of them can screw it up too bad. to be blunt. We actually have an indicator that we use called the policy uncertainty index. And what you would normally expect is the higher the policy uncertainty, the worse it must be for the equity markets. And it's actually just the opposite. Statistically meaningful that the higher the policy uncertainty, the better it is for equities because the equity markets kind of understand that there's not really much to it in terms of there's uncertainty, but it's not going to derail anything.

58:37So if anything, we use policy uncertainty, hopefully to our advantage and contrary to what most would think, which is the higher the uncertainty, the more bullish that is, particularly on certain aspects of the market. And I think you're seeing part of that right now, less than a month before the election. And you can see that volatility, the equity market volatility is relatively high, particularly as it's measured against the fixed income spreads or or credit concerns. And when we look at that through time, we see that when that spread is high, and we have to do some mathematical transformation there.

59:14But when we see it, when that spread is high, historically, that's very good for equity markets out the next quarter. And so, you know, I think you're seeing part of that with the election right now is that equity markets are uncertain. They tend to be a little bit more emotional around these things. The credit markets are just, am I going to get paid back or not? Right? That's all they really care about. And so they're much more stoic about it. And as that spread rises, it actually tends to be bullish for stocks because that premium that's in the equity risk of volatility starts to go down after the election, regardless of who wins, right?

59:49So to us, that's an opportunity as we see it for the markets, at least in the very near term, but also plays into how we think about the political ramifications. More times than not, when you look at seasonality in presidential years, the market bottoms about three weeks prior to the presidential election. So a few things there. One, again, the election ramifications are hardly ever a problem. Two, the market hasn't figured out pretty efficiently weeks before the actual election. That wasn't the case in 2016. That was probably the biggest outlier, but actually proved to be bullish, not bearish.

1:00:29But all the other ones are pretty good. The downside skew is very, very tiny around elections. So we saw it at Merrill. We've seen it all the time, particularly on the retail side. People, I'm not going to do anything until after the election. And that actually ends up being a mistake historically. Which market participants do you monitor most closely? The Fed, institutions, retail investors, or others? You know, I don't listen to Fed speak. That's what Neil does for us. We look at the numbers. We look at the balance sheet. We look at those inputs. We look at positioning from ETF flows. We look at positioning from the futures market.

1:01:06We look at positioning in the options market. But we don't break that out between institutions or retail. We just kind of want to know overall sentiment. So for us, it's not about who's on what side of the boat. It really ends up being about, is everybody on the same side of the boat? And if everybody's on the same side of the boat, then we'll fish from the other side. So I don't – and honestly, we have the data that shows that sometimes the institutions or the commercials, the informed investors are actually the worst investors. And sometimes the small investor, who people kind of pick on as dumb money, actually ends up being the best investors.

1:01:49So we look at that data. We understand who's who, where, and when. But we find historically it's best that everybody's thinking consistently and then you use that as the opportunity to take the other side and be a contrarian. What would you say is the significance of market regimes and identifying them and potentially anticipating major market shifts? Yeah, that's a good one. I mean, for us, a market regime is an uptrend, right? So within our trend model, if the trends are positive, things act differently in uptrends and they do downtrends. From there, well, what tends to drive that uptrend or downtrend?

1:02:30And we'll use our market cycle clock to identify the regime or one input to that regime. We'll use sentiment to know where we are within the context of that cycle or that trend. So in other words, at the beginning of a trend, you're going to have a lot of skepticism. At the end of the trend, you're going to have a lot of enthusiasm. And so we'll measure that through time. The Fed, is the Fed in an easing cycle, in a tightening cycle, how frequently and how aggressive? That's an important regime. I think people use valuation as a regime. We haven't found it to be terribly useful. Valuation is, I would say, useful at the extremes.

1:03:11And so you're talking about maybe 15 % of the time. but there's a lot of energy spent on people getting into fistfights over 20 times versus 17 times, whatever. And that doesn't matter. It just doesn't matter. There's a lot more things that are more important than that. So we think about the kind of holistically in these big picture environments, but we're always picking around the regimes. There's no doubt. I mean, When we're doing research, we're always looking for, you know, is there a big picture kind of regime cycle that will help us to redefine or further define some of these other regimes that are in place?

1:03:51No doubt about it. That's fun, interesting, and pretty rewarding work when we come up with it. So one question related to that is one thing that we've seen happen recently is inflation all of a sudden has become a concern and hadn't really been a concern for 40 years. And we had this inflation spike and the Fed's reaction function changed. Has that affected your approach? No, because things actually acted very consistently with what we would have expected. Again, that's part of our market cycle clock framework. And I would say that according to that, the Fed should have been hiking rates in the middle of 2021.

1:04:32And obviously, they didn't. they waited way too long in our respects for that. So to see that that was kind of out of control for longer than what they wanted wasn't a huge surprise for us or to us. At the same time, they've been very aggressive at tamping that down. And so I think that's putting things back in a normalized phase. We haven't changed anything because it actually reacted very similarly to what the previous constructs were. Um, so no, I mean, if anything, that was more affirmation for our work as we've used it because it kind of held up, uh, from an out of sample set, if you will.

1:05:14Um, so again, that better or worse on the inflation side, better or worse on the growth side, uh, really fell in line. And our market cycle clock moved bullishly into the bullish zone back in, uh, November of 22. Uh, so almost exactly two years ago now. And, you know, at the time that was, you know, that was absolutely a hundred percent contrarian. And then we got the trend confirmation in January. So yeah, that actually held up very, very well for an out-of-sample set. Are any of your primary technical indicators signaling notable trends or patterns in their current market environment? The China call is probably our biggest one right here, just because that is just so kind of stars aligning, if you will.

1:05:57I would say I think the tops that we're seeing in global yields is more pervasive and probably more telling than what the consensus is. In other words, it looks like we have a top in 10-year U.S. yields, but that's also happening in gilts. It's also happening in buns and oats and the like in Europe. So I think there's more of probably a stabilization to lower rates of a long end of the curve than what the consensus is expecting. But from that point, we're, what, two years into a bull market, and things are kind of humming along as we'd expect. I would say the credit markets have held up better than even we would have imagined on the corporate side.

1:06:44that that's probably the one outlier that I'm like, wow, that that was much, much better than even I would have expected. You know, had you had you asked me to predict the future, we would have likely gotten that one. One topic that has come up recently is the market concentration. For example, the US as a percentage of global market cap, and also the dominance of the magnificent seven stocks. How do you think about those? Yeah, we don't. It kind of is what it is. We look at equal weight and we look at cap weight. There's a distinction, but it's not like equal weight's going down at the expense of cap weight.

1:07:20It just hasn't kept up, but that's not that unusual. Breadth has been okay. I get that it's frustrating if you're a portfolio manager with individual securities and you have to have kind of a concentration effect there. but you know we don't view it holistically as uh again an existential threat or problem to uh to markets um you just kind of have to play along i mean the the the idea is that they they're dominant companies right and they're uh they're growing and um they're still an uptrend so as long as that's the case we'll we'll stay with them um you know i think what you end up with and you can see this through time with Home Depot, even Apple, and some of these other just historically strong growth companies, is they'll have these advances.

1:08:08They'll go into these 18-month consolidations. The drawdowns of those consolidations will be as much as a third. I mean, they're not comfortable to be in, but they end up being just these big consolidations that then break out and go on another run. And I think that's probably what we're looking at with these names for an extended period of time. But if they fail, if they change trend, then we'll definitely start to pare back on some of those. But until they really show their colors to us, we continue to believe that the trends are persistent there. The last question I'm going to ask you today, Jeff, is are there other major market risks that you're currently monitoring?

1:08:51Well, I think there's two. And this gets back to credit liquidity. The first one is what happens when the Japanese central bank, the BOJ, Bank of Japan, starts to normalize their curve and terminate this quantitative easing. And I say it because it's been going on for so long that I don't think anybody really has a good handle on how much global liquidity has been provided by the BOJ. And so if they're changing that, I just want to be very, very aware that this is something that's so big that it's happening right under our noses without us even really fully appreciating what kind of impact it might have.

1:09:36So that's important. I think that will continue to be important. I think that's a big risk that we call lottery ticket risks, right? It's a very, very low probability of it having an impact. But if it does, it could be very large. So we want to think about it that way. And then the other is the Fed, right? The Fed is embarking on this quantitative tightening program as they're lowering rates, right? And they're trying to reduce the size of the balance sheet. They're trying to get rid of some of these facilities. So again, the plumbing, they're fixing the plumbing or reconfiguring the plumbing as all the bathrooms in the house are still active and working, right?

1:10:12So we'll see. I mean, I'm not sure how that plays out. Hopefully, they've got a good handle on it. We don't see anything yet. So I don't want this to sound like we're hitting the panic button on anything, but those are, I think, two big risks that are relatively complicated, but in essence are fairly simple, which is liquidity up or liquidity down. And obviously, that can have a huge impact on asset pricing, asset volatility, et cetera. So those are two things that are definitely worth monitoring as we go forward. Well, Jeff, this has been great. I appreciate you sharing your insights. And I know our audience did as well.

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