TTU121: Trend Following...from Optional to Essential? ft. Nick Baltas

[00:00:00] Nick

At the beginning of the year it was like a cataclysmic confirmation of those trends. Call it fear of missing out, call it confirmation of trends, call it uncertainty resolution, call it whatever you want to call it. We had what we had been observing until this day. I think that’s the pivotal shift. That is what made, in my view, the substantial regime shift in the market and trend.

[00:00:35] Intro

Imagine spending an hour with the world’s greatest traders. Imagine learning from their experiences, their successes, and their failures. Imagine no more welcome to Top Traders Unplugged, the place where you can learn from the best hedge fund managers in the world so you can take your manager due diligence or investment career to the next level.

Before we begin today’s conversation, remember to keep two things in mind. All the discussion we’ll have about investment performance is about the past and past performance does not guarantee or even infer anything about future performance. Also understand that there’s a significant risk of financial loss with all investment strategies, and you need to request and understand the specific risks from the investment manager about their product before you make investment decisions.

Here’s your host, veteran hedge fund manager, Niels Kaastrup-Larsen.

[00:01:30] Niels

Hey everyone, and welcome back to another edition of Top Traders Unplugged, where today Robert Carver and I are joined by Nick Baltas, who is a managing director at Goldman Sachs and who has done a lot of research and practical work in the systematic investment space. First off, Nick, thanks so much for joining us today.

We’ve very much been looking forward to this conversation. How are you doing? How are things where you are? I understand there’s a little bit of turbulence where you are today. 

[00:01:55] Nick

There is indeed. The day is the 20th of October and we just had the Prime Minister resign, I think in record time.

It’s definitely, let’s call it an eventful day more than anything else. I’m setting that aside. It’s a great pleasure to be here. I’m a fan and it’s a great pleasure. Thanks for having me. 

[00:02:16] Niels

It’s definitely wonderful to have you. 

Rob, I know you’re in the same place, so I imagine you’ve also been preoccupied today with following what’s going on.

[00:02:25] Rob

Yeah, I was starting to think that still, technically, our Prime minister was going to drag it out all afternoon. I was sitting in front of the television thinking, really? Come on Liz, get on with it. I’ve got a podcast to do at three o’clock, so, come on, just crack on.

She obviously heard me because she came out at 1:30 and resigned. I was able to watch a bit of the analysis before starting today. That’s probably the only thing that she’s done right in her 44 days empowered to be honest. There we go.

[00:02:55] Niels

Great stuff. All right we have other juicy topics on the agenda today for sure to discuss.

I thought Nick, maybe just for the audience to get to know you and your background, perhaps you can just share a few of the highlights of your path to where you are today. 

[00:03:13] Nick

Sure. I’m happy to do that. I’m Greek, born and raised in Athens in a beautiful place with great weather. I spent 24 years of my life there. I basically did electrical and computer engineering in the National Technical University over there. Then, I wanted to do a masters and I came to London. I did a masters in signal processing communications. I was still an engineer at the time.

Then I had to do military service. I went back home and worked for a year with my father, but then came back, and that was 2007 (around the time when Northern Rock blew up), for a PhD in finance, that was the time. I spent those four years, again, at Imperial College. That was at the business school doing work primarily in equity momentum, correlation, risk, and trend following. Those were also the days for trend following, if you remember, obviously, more than I do, the growth that this space had during those years.

I spent a few more years, after that, continuing academic research in the same space, having an academic career, lecturing, doing all sorts of things in the business school. Then I decided to move to the industry. That was 2013, I believe.  

About 10 years ago I moved to UBS. I spent another five years doing sales side research on quantitative quality assets. Over the last five years I’ve been within the Goldman Sachs ecosystem as a part of structuring, within the markets division. My team is basically responsible for building systematic strategies that we make available to institutional investors globally.

We can go into more specifics, but that’s a quick path through time. It was partly coincidental kinds of moves; partly I would also call it luck; partly it was some sort of longer term strategic thinking as to what the next step should be. There you are. 

[00:05:02] Niels

I think a lot of people end up, in our industry, a little bit coincidentally and by luck. I’m not sure people wake up, in their youth, saying, “Yeah, I really want to do trend following.”

[00:05:10] Rob

That’s certainly true I’d have to say. Although curiously, I was just thinking, I actually left the industry as an employee in 2013, just as Nick was coming in. Amongst other things, now, I am a part-time academic, so we’ve almost reversed roles. I didn’t get a chance to say at the beginning, Nick, I’m a huge fan of your work and I’m really looking forward to this talk. 

[00:05:31] Nick

That’s a great pleasure. I only moved eventually (just because you mentioned), it was 2013, when I moved to UBS. That was the time that one of the more kind of senior professors at Imperial at the time (he was part-time, he wasn’t full-time) was working at UBS. He decided to move back and it’s almost as if we swapped places. That was James Sefton, a great guy and a great mentor. 

[00:05:57] Niels

Yeah, absolutely. Now, as you rightly suggest, you’ve written a lot of research and I would add you’ve written a lot of great research on various systematic trading strategies. Of course our focus today may gravitate towards trend following since we all love to be in that space. Even if there are different articles, from this year, that really triggered my wish for having you on the podcast, I wouldn’t mind if we could go back to your UBS days and dig into the archives a little bit. 

You wrote something, maybe 6, 7, 8 years ago, in 2015 or ‘16 (correct me on that), on a topic that actually comes up quite often. I have a feeling it might come up very soon again, because often when markets go south, especially if there’s a little bit of volatility, media and other participants have a habit (let’s put it that way) of blaming CTAs for magnifying the negative price action, especially if it’s happening in stocks and bonds. 

Do you mind taking us a little bit back into those days before we catch up on time, and share what you found to be true or not true about these things? 

[00:07:17] Nick

Yeah, sure. I guess that all goes back to the market turning south, in whatever form or fashion. Then you have some sort of market commentary talking about trend followers and risk parity fans, and volatility targeting. [In addition], broadly speaking, [you have] whatever type of allocation models that would start selling in some form or fashion, trying to go hand in hand with those market price moves.

I guess my point (at the time) was more about, let’s just look into the numbers and let’s try to understand exactly what is happening here, because it’s easy to say, “Well, if I’m following a trend and the trend is negative, and guess what? I’m just going to go with it for a particular reason.” Obviously the question is how much supply and demand is out there, to make my move more substantial than the aggregate supply. Basically what I started from is let’s look into trend. 

Trend is not anticipatory. It’s a price taker. We’re just expecting things to move and should they move and confirm a direction, then we’re going to deploy the exposure. First things first, they cannot create a downturn. It’s purely exogenous. We’re not going to talk about what is actually causing it. All we’re going to talk about now is that, suppose that this turn did turn, and it did happen, and we have a negative move, then there’s a few mechanical things that happen and are not, in my view, special to trend following.

Trend following would say, “Here’s a negative trend,” to the extent that I have conviction upon it, based on my rules, based on whatever the market is doing, I’m going to start selling to effectively benefit from the move in some form or fashion. That’s what gives convexity to those strategies.

If we look into risk parity fans, they say, “I want to allocate inversely proportional to my volatility.” If the market is falling and the volatility is going up – the lever effect (which by the way, this dual causality; risk can drive price – setting that aside), I’m going to reduce my exposure. By the way, it’s the same thing that a stop-loss rule would do. So, I say, “I’m hitting my stop loss, I’m going to sell.” There’s some form of risk management that comes into play, even for long-only investors, that would start reducing the exposure to whatever asset they hold if they have either some stop-losses in place or some sort of rules to just stop the bleeding. If I were to quote your guest from two weeks back, basically you need to be a quitter and you need to be confident about quitting at times and have a rule that you’re going to follow, because that brings discipline. 

So that was the initial point. The point was that there are so many mechanical (either systematic or discretionary) features that can create a selling pressure in the market. Then let’s look more carefully as to how impactful that can be. In reality, what we have to look at is what’s the positioning? How are risk models calculated? And at the end of the day, what is the (specifically equities, because people talk about mainly equities) equity exposure of all those types of investments? Then what’s the delta on that equity that has to be sold? 

Once you just try to carve out what that portion is (with the work that we did back then), you end up realizing that it’s just a very small portion. Given some assumptions about risk models, assets, and so on and so forth, it’s a small proportion of what the overall market really is. I think there’s also a very subtle point, which was highlighted to me on the backend of all this work by one of the founders of one of the largest CTAs. Basically, the claim goes as follows: trend followers scale by volatility or by risk.

If you’re in a down market (like in the present moment), and you have a significant reduction in the price that comes together with a volatility spike, what you’re actually doing is reducing your growth. You’re buying back. If anything, not only do you not intensify the down move, you’re actually acting as a support to the market.

Again, to cut a long story short, (I can go on forever on this topic), but to cut a long story short, my point was, let’s take a step back. Yes, mechanically it can be the case, you have to really look into the idiosyncrasies of all those different features and then claim that they orchestratedly (if that word even exists), they work as an orchestra to effectively start selling, to create a substantial down move. So, I was basically trying to defend the space. I just wanted to bring another type of a voice into this dialogue. 

[00:12:08] Rob

Yeah, I guess if you widen that research out beyond equities, because, obviously, if you look at the equities and what percentage of equity free-float, or volume, is CTAs, it’s going to be a pretty small number. Even if you do a look through from equity indices to underlying equities, it’s going to be a pretty small number. 

I do wonder, in some of the less liquid futures markets, whether there is some mileage in this story. We, all CTAs, especially big ones, worry about being too big a part in the market. So, crowding is a concern. I think it would be irresponsible not to be concerned about it. Is the CTA industry just not big enough to have this effect? Or is it to do with the dynamics? Or is it because you looked only at equities? What do you think?

[00:12:57] Nick

Certainly when we look into the space more broadly we can always claim that you can get into a stage whereby the assets have grown so much to allow for quick rebalancing. Therefore, you can have a market impact purely from the perspective of the mechanics of it.

Now again, I think we can run the analysis in various ways, and I can go into a few more specifics, and I could also quote Andrew that was on the show recently. He also claimed that we don’t seem to be getting close to those capacity levels. If anything, we’re running analysis on a very regular basis, especially where we are here looking into how deep the market is, and also how we can inform the allocation to any strategy (trend following is one of them) to avoid having substantial consumption of the available liquidity. 

When we talk about crowding, I think there’s a range of different ways that we can talk about crowding. We can think about crowding at the industry level. That’s more about how margins and leverage can affect the system turning point. That is more of liquidity crises and fire sales. 

We can look into crowding from the perspective of a manager. That it’s more about how do I deploy my new capital, and is it now, for me, the time to just deploy that capital to be more liquid? In the grand scheme of things it is about lower expected return opportunity. Therefore, being in this position of having to split my exposure and possibly have diminishing returns to scale, that’s another way of thinking about it. 

Then we can also look at it in isolation, how a particular strategy can react in a period that is experiencing inflows. I think that’s also a very different story. 

I’ve done some work back in the day, that was in the early days at Goldman Sachs, really looking into how crowding is impacting systematic investing. I think there’s some very nice features. I was trying to defend, again, the space saying, “Listen, crowding can have an impact, but that impact is not necessarily a negative impact.” If anything, any systematic premium almost requires systematic flows into it to justify the existence and the presence of it. If I do something and nobody else does it, guess what? It’s not going to be rewarded in one way or the other. 

I guess I’m going longer here, but there’s many ways we can look into crowding. There’s liquidity consumption, there is diminishing returns of scale, but there’s also strategy mechanics. Different answers would have different questions. So, I think we should, more broadly, be careful and look at it in isolation. 

[00:15:48] Rob

Yeah. Personally, I’m always more worried about crowding in a relative value strategy with leverage, for example. Obviously, very recently in the UK, we’ve had this LDI pensions hedging issue. In fact, I’m going to use the LDI thing in my slides for my students next semester. I’m going to replace my old examples, and say, “Here’s a brand new example for you guys of crowding and relative value trade with leverage, which results in these so-called ‘doom loops’. 

[00:16:16] Nick

A fair example. It’s a pure liquidity fire sale, in my view. 

[00:16:21] Rob

Yeah. It’s definitely more of a problem when it’s relative value, and therefore that means you need higher leverage. Obviously not for a pure hedging structure at LDI, but if you’re trying to reduce a few basis points of return into a decent size return by using leverage because you think you’ve got a pure arbitrage, you think you’re doing a purely correlated hedge. 

Why do you think, (this is not a research question, this is a question I’m asking you because you are in the business of being at the sharpe end of trying to sell these kinds of strategies to people, and you’ve probably got a better idea than I have), one thing that’s always mystified me, I would bet you any money that if you think about crowding, or if you think about market moves being amplified and turned into big pushes by something happening, it’s almost certainly more likely to be something like option hedging.

If the market’s plunging downwards rapidly, you’re right, it’s not going to be CTAs selling. They’re just not big enough and they don’t react fast enough. It’s more likely just somebody who’s sold something out of their money and the strikes creeping really close and they’re panicking. Or, if that’s not strictly true, their models are telling them to hedge, and that’s the hedging that’s required. 

Why do you think the kind of media or interest out there, or the kind of popular financial opinion out there, is, “Oh yes, these horrible risk parity and trend following people?” No one ever seems to mention the option hedges. I think the only time anyone’s ever mentioned them was in the whole GameStop story about blowing out the short squeezes. That’s the only time in the popular imagination I’ve heard that story. Why do you think that is? 

[00:18:07] Nick

I think it’s immediate misinformation. I think that’s what it is. I think it’s more behavioral than actually looking into the specifics. I don’t think I have a better answer. I just genuinely think, following 30, 40 years of Goldilocks, the 60/40 portfolios, and we know how they’re performing the year to date, and eventually giving rise to disparity portfolios, and benefiting possibly from this kind of vol scaling, and then taking that and expanding it in a multi-asset case. Then the popularity of all those multi-asset allocation schemes just happened to be, mechanically, the first (should I call it) resort? Certainly that’s the first thing that came to mind in some respect – possibly because it’s more systematic. I think it’s the fact that it’s systematic, and this is rules based more so than anything else, and that sometimes can make some people uncomfortable. 

[00:19:03] Niels

I think it’s a combination of things. I don’t disagree with any of the things you’ve said. I also think there is just generally, perhaps, a lack of understanding of what we really do, by journalists. I’ll share an example, and this is a very recent example where we were contacted by a journalist asking us, “Oh, so did you sell a lot of sterling because of what’s going on with the Prime Minister, and the tech, and the mini budget?” They were really surprised to learn that we went short sterling. I can’t remember if it was sterling or gilts, doesn’t really matter, but like in Q4 of last year. 

Going back to your point, I think we, as an industry, maybe we push prices a little bit around the entries. If the entries are very clear and you know that a lot of trend following approaches will be more or less getting in at the same time. This is at a time where there’s no big hoo-ha and there’s no big trend at the time. This is like the little breakout that we see, but most of the world doesn’t see.

All the press and all the popularity, as you rightly said, Nick, that comes towards the end of the trend when it gets painful and it’s maybe at an extreme point, and you need to find someone to blame or something to explain it by. I think then, because we don’t have any story or narrative to share, I think we are an easy victim of that.

[00:20:43] Nick

It’s in the news as well. Once you do that well, the mechanical nature talks about, obviously it’s definitely crowded. I agree with you and I think you have this point with Richard about I guess you enter in a similar region once you enter a trend, more or less.

The reality is, as you say, it’s just a formation that just crosses a threshold and just makes it more reasonable for anyone to enter. Again, what I’m going to stress is the point I made earlier on, in the presence of very strong trends on either side, what you end up doing is cutting down. We saw it this year. 

[00:21:22] Niels

Yeah. I think that is another point. Of course on this podcast, we have a lot of debate about whether that’s a good thing or a bad thing. I agree with you. I think most managers, today, have some kind of dynamic position sizing, and therefore we would actually act completely opposite of what most people think during those times, definitely. 

I want to stay on this point a little bit. I think this is from your most cited paper, which is part of your PhD (as far as I recall). It’s related to what I’m hoping will happen, namely, that finally 2022 will be the year where people realize that having trend following in their portfolio is not optional anymore. It’s essential, as Andrew said on the podcast last week. I think in that paper, one of the things you looked at was capacity constraints. 

This is a fair question that people should be aware of, and certainly I hope managers are aware of in their own ability to navigate these markets with their own size and the liquidity. We hear people talk about how the open interest (for example), in the oil markets have gone down a lot, and does that impact the “liquidity” that we benefit from as managers? Talk to us a little bit about what you found out about capacity and how to even measure it, and just anything you really want to talk about. 

[00:23:03] Nick

Yeah, I think, there’s a very nice story about this work. If we go back to 2009, or possibly early 2010, I was doing all the work on equity single stock momentum and whether those kinds of equity factors somehow correlated with correlation risk premium. There was another world that was, obviously, unrelated to my work, and that was the trend following world that had done extremely well in 2008 – taking all those short positions in equities and long positions in bonds throughout 2007-’08, and when the big heat came they were extremely well positioned, obviously, attracting a lot of interest. I think that was the big exponential growth in the assets. 

Then in 2009, 2010, it came through with performance, and started becoming a bit more mediocre. Then, after the fact (with the benefit of hindsight), we know that it was the early days of the Fed put, but at the time there was a lot of publicity, in all financial media, that the CTA space, the trend following space, it has grown so much and, therefore, we have some sort of possibly capacity issues. I happened to cross paths, at the time, with an incredible guy. He’s still in the CTA industry. He’s been part of the two or three of the largest CTAs. I could possibly name him. Anyway, he came to me as an informal advisor.

He told me, “Listen, look at this paper.” He basically gave me the working (at the time) version of Toby Moskowitz and Pedersen paper on time series momentum. “Listen, this is a way that some of those trend following strategies work.” What is more interesting for us, these days, is can you just do an analysis on capacity? Can you just have some sort of a thing as to how we could look into this space, given the AUMs – following it, whether we are hitting capacity? 

Two things, I was working back then with my advisor Robert Kosowski, we still are very close in contact and we still can try to do some work from time to time. So, we said, “Okay, there are two ways we can do it. The first way is more like the academic way, which basically says let’s run a regression – the so-called performance flow regression.” So, you look into flows at t-minus 1; you look at the return at time-t; we can call t-minus 1 last month, last three months, last year, whatever and then let’s look into the return the month after, and the three months after. 

Basically, the story here is that if the flows have an impact on performance, you should expect some sort of negative exposure between the two variables – statistically significant. We found nothing.

We looked into the flows. We took a CTA database, we took the returns of the CTA, we took the assets, and then you can back out (the net of return chains, in AUM, is the flows), so, we isolated the flows for the last (at the time) 20, 30 years and we did this analysis. We didn’t find anything. 

There was no statistical relationship. There was no significant relationship. There was not even a point estimate that was either negative through time. If you were to run it on a rolling basis, it was going positive and negative. There was no information whatsoever.

The second thing we did, which I think was even nicer, was the following. We basically said, “Let’s assume, for the sake of illustration, that the entire industry is following the same model.” This same model says I have those 50, 60 markets; I have a lookback window of X months; I’m sizing my exposure, using historical volatility by that level; I have a price path of the strategy. Then from the ‘70s onwards, I also have the AUM growth. So, at the end of every month, I can assume that this level of AUM is invested in that strategy. I can literally break down the dollar amount into how many contracts I would require for each and every constituent. Then I can compare that, month on month, with the open interest. I have 80 assets, or 60 assets, or whatever number of assets per month through time, to find how many times do I actually go past, or do I become more than a small fraction of the open interest? 

[00:27:34] Rob

Just for clarity, you’re effectively pretending that there’s only one CTA? That has all the AUM and it’s investing in this one strategy? 

[00:27:41] Nick

Yes, precisely. It’s an oversimplifying assumption. I think that on this show it has been mentioned many times that a trend follower is a CTA, but not all CTAs are trend followers. I think it’s very important to make this clarification.

In this regard, we basically said, let’s get the AUM through time. I cannot recall if it was just for CTAs or systematic CTAs, but anyway, it’s 90%, 92%, systematic. Let’s assume that they’re following a simplistic formulaic trend following strategy. Then let’s look at the asset level and how many times you would have crossed a proportion of the open interest. 

We found little to none. It was a minuscule proportion per market. There were some markets, lumber for example, that you would find, potentially, some months that you would cross (again, in a theoretical sense) the open interest.

Back to your point, Rob, these are liquidity assumptions that would enhance the models when we run them. 

[00:28:44] Rob

Yeah. I guess you are assuming equal weighting across markets in your hypothetical CTA? 

[00:28:50] Nick

When you say markets, in the same asset class or across the board?

[00:28:54] Rob

In this hypothetical CTA how did you allocate the risk between say, lumber, platinum, gold, and so on?

[00:29:02] Nick

It was done on an inverse vol basis. 

[00:29:04] Rob

So, equally weighted? So, you’re basically saying if a CTA was stupid enough to put the same amount of money in super liquid euro/dollars and not very liquid lumber, then surprise, surprise, they would have too much money in lumber and they be exceeding the open interest, which is not a huge surprise. 

When I think about these capacity constraints, the interesting thing for me is that if I imagine that there’s some kind of idealized portfolio I’d like to run, (This is no longer true for me now, I’m running retail money and I’m at the opposite end of the spectrum where I don’t have enough cash to actually trade futures properly.) If you go back 10 years when I was trading real money, proper money, 10 figures, the way I think about it as well, there’s an idealized portfolio I’d like to hold that’s going to be not that dissimilar from what you’ve described. It’s going to be roughly, assuming an homogenous correlation structure and blah, blah blah, and an equal sharpe ratio and equal cost, blah, blah, blah. It’s not going to be that different from that – from just inverse vols, same risk allocation to everything. How far do I have to depart from that given that I do have this huge pile of money? So, I was trading fixed income. Our smallest market might be something like five year Indian swaps. Clearly we couldn’t put as much money into that as we could into T-bills. That’s the kind of way to think about this capacity issue. 

[00:30:40] Nick

Completely, and I cannot recall, but there’s a couple of academic papers that look into the impact of costs.

I think what they do is they say, “Okay, what is my ideal portfolio X costs? Let me include my costs and let me minimize the tracking error to what I want to be close to after accounting obviously for those dynamics.” I completely agree with you.

[00:31:02] Niels

I don’t know if we can do this, actually, we can try. Let’s just say, for argument’s sake, that the official CTA AUM, as tracked by Barkley Hedge (they probably have the best, even though a lot of that is Bridgewater, which I’ve never really considered as a CTA, but be that as it may), let’s just say that we are at, whatever, $375 billion, which hasn’t really moved for 10 years, frankly. 

Given where the markets are, (and you may know this much better than I do), but given where the size of the underlying markets are today… and I know that there will be people like yourself, Nick, who obviously also do trend following, but don’t appear in these statistics. I’m fully aware that the real AUM that does trend following will be bigger than what Barkley Hedge is tracking. 

At current market liquidity levels, can we even say how big that we think the trend following community could be without having any impact on markets? 

[00:32:07] Nick

That’s a good question. Just to put some numbers in perspective, and I agree with you. 

[00:32:16] Niels

You may have better numbers than I do, frankly. 

[00:32:19] Nick

Some numbers in the sense, I think in the CTA at least whatever Barclay Hedge is reporting, I think it’s about $350 – the systematic, and then $375 is basically the whole space.

[00:32:30] Niels

Yeah, $200 of that, or something like that, is Bridgewater or close to it.

[00:32:35] Nick

Again, but it’s all adding up in those numbers. If I look into other places that you can have some form of trend following capacity in this way or the other, I would possibly just round this number to $400, give or take. I don’t think it’s just larger than that. When we think about the hedge fund industry as a whole, which is about what, like $34 trillion at the moment? Probably. We’re talking about like 10% of that. 

I don’t think it’s the easiest thing for us to just put out a number. Also, if we take into account the cross sectional differences between all those CTAs, they’re not all doing the same thing. Some are much shorter term. Some are longer term. I think that also should be fed into how much of that we could potentially see as a multiple.

I would not suggest that we are, in any way, approaching any problematic levels. Again, I don’t think it’s a straightforward answer. It’s more about market sense, looking into liquidity numbers, looking into how liquidity profiles change from day to day, month to month, or year on year. I do not think we’re anywhere approaching [that point]. 

I’m not sure. What’s your opinion? 

[00:33:51] Niels

Yeah, I’d love to hear Rob’s thoughts as well, but I just want to add something. Actually, our good colleague at Top Traders, CEO Alan Dunne, when he worked for Abbey, they did a really good paper on the CTA industry a few years back.

I think, from memory, that they adjusted for some of those things you mentioned about that then there are managers doing something completely different. How much is real trend following? I think they got the number down to about $125 billion, was the real number even within the CTA community.

Now, I will say I think the industry was a little bit smaller back then because it was a difficult period we went through. Obviously AUM has increased in the last 18 months just from performance and inflows. Still, it was a lot less in terms of what we see the official number is, to what they estimated the real trend following number was. I don’t think it matters too much anyways. There’s obviously always going to be some constraints in smaller markets and then it’s going to be easier in the bigger markets. What are your thoughts? 

[00:35:02] Rob

Yeah, it’s an unanswerable question really, because you could take the extreme view and say let’s stick with futures. Let’s not talk about Indian five year swaps. You could take something like, I’ve just added whey to my data set which barely trends a couple of contracts a week or something ridiculous like that. It’s just ridiculous and tiny. 

Let’s go back to Nick’s paper – a highly realistic paper, we’ve agreed and that’s fine. It’s a cool paper. I’m not going to disagree. If you concluded whey in his list of markets, and you gave that the same allocation as euro/dollar or S&P 500 or something, then you said I’m going to think that the hedge fund industry is at capacity. If any single market goes above 10%, in whey you’d be well above 10% you’d be well over 100%. In fact, there’s probably dozens and dozens of futures markets I could name where, if the entire CTA industry tried to invest in those, there wouldn’t be enough capacity for them to do that. 

Clearly, if you take that very extreme version of the capacity argument. Which is to say that because the entire CTA industry can’t invest in an idealized portfolio where there’s no constraints on capacity. Therefore the industry’s almost by definition always going to be at capacity because there are always going to be futures contracts that aren’t liquid enough. 

What I’m trying to say is it’s a really hard question to answer, because you can either say it’s always true, it’s always not true. Clearly if fund firms adapt to market conditions and put no money at all in whey, or their money in S&P 500 or in euro/dollars, then they’re going to be nowhere near capacity, of course. 

[00:37:01] Nick

You make a nice point. It just reminds me of this lumber thing. The point that I made with lumber, when we looked into the stats, I remember it was like, okay, if you actually remove lumber from the universe, it would look nicer. But that was not the point of the exercise.

The point of the exercise was to actually look and report whatever data we had, and do a look through, and understand exactly what we’re crossing from an open interest standpoint in the simplified formulation. To your point, had we removed lumber, it would look nicer. That wasn’t the point – to over fit, it was the point to report something. 

[00:37:38] Rob

Exactly. I’ve just checked, by the way, and last week I think lumber traded did an average of nine contracts a day and whey traded six. There’s not really much in it.

[00:37:53] Niels

I’m working my way slowly down to the article you wrote, which was published in Financial Times that caught my attention. Nick, I want to get to that, but before we do, because we are just talking about liquidity in markets and trends, et cetera, et cetera. One topic that I’m coming across quite a lot is this debate when investors want to select a manager. 

Ideally maybe they should select more than one manager, frankly. It’s this thing about alternative markets, which is somewhat related to liquidity and capacity, et cetera, et cetera. I’d love to hear your thoughts on the difference, or the pros and cons, the way you see it between managers who choose the 300, 400 market universe, or funds like the firm I work for, where we’ve stayed to the classical 60ish markets. How do you see it from where you sit? 

[00:38:47] Nick

We also get a good amount of questions as to more (we call it) exotic markets, like alternative markets. Yeah, let’s call it alternative markets. 

[00:38:56] Niels

I just call it alternative markets.

[00:39:00] Nick

Do we put crypto on this? Possibly we do. I don’t know. 

[00:39:01] Niels

Could be, I guess.

[00:39:02] Nick

These days there are so many markets we can possibly trade in a futures format. There are a few prevailing principles. Principle number one is the diversification we’ll talk about. Principle number two is liquidity which I think we’ve discussed quite at length already. Now, principle number three, which is becoming a bit harder now to nail, is probability – both from a statistical sense, but also from an economic standpoint of observing trends in the respective markets. If we add markets that don’t show trendiness, (and we can discuss as to whether there is or is not trendiness), then we’re only adding diversification but not performance. The only benefit is in sharpe ratio terms. 

If we’re adding markets that still don’t perform, but they’re also less liquid, in a liquidity informed optimization allocation framework it’s almost as if you’re adding nothing. I think what is more important is to say is it more likely that those markets will exhibit stronger trends?

I think here we can have a conversation because when I start thinking about trends and prolonged moves, from an academic standpoint, and I’m not necessarily just going to stick to it, why do trends exist? 

In an efficient market scenario then there shouldn’t be any forecasting ability of the past move to the future move. For whatever reason, there are so many reasons why trends exist. The one that I like the most is that markets typically digest information in a more non-instantaneous way.

It takes some time for news to come in. That piece of news is digested to the extent that this underreaction ends up forming a trend. You end up having fear of missing out and overreaction that comes along with it. There is a point to be made, which I think is a fair point, that more alternative markets probably have (I won’t call it less efficiency but) slower speed of news transmission. Therefore, one can make a case for trendiness. I think that’s also the claim that exists out there for some of the exotic commodities. I think Gresham has a very nice paper, as of two, three years ago, talking about those commodities.

Ultimately, I think what becomes important is what is the room, from a liquidity standpoint, to make those trends (to the extent that they exist) meaningful for the overall portfolio? I think that’s the challenge at the end of the day. 

[00:41:55] Niels

Yeah, I don’t want to disagree with anything you said there, Nick, but I will say my practitioner’s point of view.

I just want to say that, from a practitioner’s point of view, I don’t really see any evidence of that. Meaning when I look at managers who trade the $300, $400 market portfolios, and if I look at our own performance, I don’t see them performing better. I see them performing at different times, but not better in the long run. That’s just my observation.

[00:42:27] Nick

Which might go down to the fact that there’s not too much liquidity to make the addition as apparent in the short term. It could be that. 

[00:42:36] Rob

To that point, there’s obviously, for example, Florin Court, which pivoted to trading just alternative markets and have done pretty well. Although I should obviously disclaim my interest in that I know all of the guys who run that fund and they’re all friends of mine. So, I would say that, wouldn’t I? 

I do like your story, and it’s a story I’ve heard before. I guess I’m more with Niels, not so much looking at evidence in terms of looking at fund level returns and saying, “Oh, there’s no evidence there.” If I actually look at market level returns, and I look at the returns of exotic versus non exotic markets… We can debate for ages about where you draw the line. Is lumber exotic, for example. Probably not. I, myself, don’t see statistically significant evidence. There might be something there, but it’s not really of a statistically significant level. I think I know the guy that did the regression paper, actually, and I’m not sure he found statistically significant evidence there either.

Part of the problem, of course, is that a lot of these markets have quite short data history, compared to that we’ve been trading cable, in futures, since before I was born, for example, and before you were born, maybe not before Niels was born.  

[00:43:57] Niels

I’m afraid not.

 [00:44:00] Rob

Whereas, for a lot of these – let’s take crypto, let’s take Bitcoin – you could only meaningfully trade Bitcoin for maybe the last 10 years or so – perhaps Bitcoin spot. Bitcoin futures have only got, I think, three and a half years of history on the CME, something like that. It’s not many years. I don’t think it’s enough to say… I rarely see evidence that a market is trendier than another in terms of statistically significant evidence.

Personally, if I’m going to allocate risk amongst markets, I will include those exotic markets in there, but purely because of the diversification. I believe the diversification story, because I believe they are relatively uncorrelated. I’m certainly, personally, not going to be putting more money into them and tilting towards them a bit more because I believe they’ve got higher X anti-sharpe. 

For me, I don’t buy that story, but we’ll see.

[00:44:51] Nick

It’s fair. By the way, without digressing the discussion, I think one of the interesting challenges that I have seen in the literature for trend (I think it’s also good to keep open eyes and ears as to what comes along as a challenge), there is this story talking about: is it actually serial correlation that is driving trends, or is it just assets that (for the longer term) are rewarded or possibly penalized (in the opposite sense), that end up consistently going long because it’s been going short?

I buy the argument. I think, econometrically, it’s very hard to get a straight answer. You’re talking about markets that are trending, and the point is that, is it to reward the risk stream in the longer term? Probably not. Anyhow, but I buy the diversity. 

[00:45:41] Niels

Okay, I know you want to jump in here, Rob, but I want to gravitate for the last 15 minutes we have, Nick, towards the present and the future, for that matter. As I said, you wrote a really great paper that got featured, I think, in the Financial Times. I think there are several points that I think are really interesting to discuss. Before we jump into that, Rob, what’s on your mind?

[00:46:08] Rob

Thank you. I just really want to squeeze in if I can, just as a bit of a temporary change of subject. That’s the work you’ve done on the skew, as a predictor of future returns. It’s a strategy that I really like. I really like the story it tells in terms of it’s almost a pure risk premium.

Everyone hates skew, so go buy it. It’s a really pure story and also quite interestingly for me, at least within my own strategies. If I look at my returns year to date, trend following has done very well. Carry, interestingly, hasn’t done that well. Somewhat curiously, skew has done really well as well.

If Niels doesn’t mind me squeezing in five minutes of non trend following content, I’d really appreciate you giving us your findings, because I think it’s a nice story. 

[00:47:01] Nick

For sure. By the way, if you want to stay around for some time, I’m happy to do so. This came along, we did some work with the US public pension. The paper is now published in the Journal of Portfolio Management. Everything is in the public domain. 

The story was that there was some nice research done for commodities basically showing that negatively skewed commodities outperform less negatively or positively skewed commodities. By the way, I’m talking about realized skewness, as in, if I look back a year, six months, or nine months, some recent period, and I estimate realized skewness (simply talking about how asymmetric the distribution of daily returns are), if I buy those that have the most negative skew (which I can explain by saying they have had more regular negative tales than positive ones), I end up outperforming. Now, mechanically, if we think about it, what is actually happening here is that there is a tendency, if it’s a rewarded premium, to avoid buying the assets that have had historically more negative tails.

Conversely or symmetrically, there has been more appetite for those that have had a positive tail. Now, how do we explain that from a theoretical economic standpoint? There is a lot of literature coming from the single stock space talking about preference for stocks that look like a lottery ticket.

Basically when there’s an occasional up move, but happens rarely, I’m still willing to pay a small premium for it. What I end up doing, if there is excess demand for that, (which has been related more to the retail market as in retailers looking into these types of stocks with those characteristics), you end up overbuying them.

So in equilibrium their price goes up, the expected return is lower. You can actually claim, if we’re sophisticated enough, we can easily just take advantage of that. However, short sale constraints can be an explanation for that phenomenon. 

Now, obviously you might say, “Wait a second, now we’re talking about futures. We can easily go short. How about that?” Here you have a few other kinds of behavioral stories, which I very much agree with. There’s a cumulative prospect theory that basically says, that’s from Amos Tversky, which basically says that human beings tend to associate small probability events with a high probability of occurrence. As in, if something big (either positive or negative) happens very rarely, somehow I perceive it as happening more regularly. 

Okay. What is the consequence of that? The consequence is that I would want to go long, whatever happens to go up more frequently than what it actually does. But because I perceive it to go up more regularly I’m going to go into it, like a Tesla equivalent in some respect. Whatever happens to tank irregularly, but I perceive it to tank more regularly. I’m going to avoid it. In equilibrium, this can give rise to over-priced positively skewed, and under-priced negatively skewed.

There are also some other ways you can justify the skewness. It’s called selective hedging. Basically that means that, when I estimate my hedging ratio, I do not want just to reduce overall volatility, but I take into account higher moments. Let’s say I’m a commodity producer and I do not want the price to go down, so, I’m going to short in futures. I would not want to short the entire exposure if the asset I’m going to hedge typically happens to go up more often than going down in a tail scenario. Therefore, I would prefer to be under hedged. Conversely, if I’m a consumer, I’m going to be over hedged, and so on and so forth.

There are some tendencies, from a risk management standpoint, from a behavioral standpoint, to give rise to those patterns. To cut a long story short, that was the idea, and we said, “Listen, if that is the case, then possibly we should look into the entire landscape of futures markets, if we have evidence that works in single stocks, and there’s evidence in commodity futures, then surely we should look into other markets.”

By the way, there’s so much beta, for example, for the foreign exchange market and downside beta exposures. There was some sort of reasoning to look into the broader space. Low-and-behold we do get statistically strong results for bonds and for equity indices.

FX, I must say, is the least (from a statistical standpoint) contributor. Certainly diversification helps out (Rob, back to your point), but only freelance probably. Overall, when we look into a cross asset skew strategy, or a cross asset skew dynamic, we can possibly look at it as a certain reversal, even though it’s not really a reversal.

We can basically look at it as an intertemporal risk transfer between participants willing to continue holding negatively skewed assets versus those that are not willing to do so. I think there’s an economic theoretic support of the premium itself, and it blends nicely with trend (to your point).

[00:52:55] Niels

I do want just to spend the last few minutes on your most recent article, at least that I’ve seen. It’s about the present. It’s a little bit into what you think, why this time may be different. Even though those words are always tricky to use. I’m just going to give you the floor.

Nick, talk to us a little bit about what you wanted to express with the paper, the article, and we’ll take it from there. 

[00:53:26] Nick

Yeah, sure. How did this all start? The start of the year was very strong for trend followers. It was very strong, partly because some of the Q4 dynamics around inflation (I’m going to go back to that in a second) started playing out. Obviously, you had geopolitics (for whatever reason) giving fuel to those trends. Then, the months that followed, until March or so, was kind of different. It felt different for a trend follower. It started feeling a bit different.

There was obviously more publicity coming through. The market was not in good shape more broadly, but then CTAs started helping out. The point that started being raised with some of our discussions with investors was more about is it performing? Is that the right time? Should we go into it? 

My point was, listen, I think just judging on a three, four, or five month period, to allocate or not allocate, I think it’s wrong. The first thing we need to do is to look back, in the years between 2010 and 2020, because I think there’s a big elephant there.

That was a period, setting aside some sporadic yet very strong events like 2014, possibly 2019, broadly speaking, it was not an easy period. I think it’s very important to fundamentally address what was happening back then. Then look into the shift, the paradigm shift (possibly if there is one) that can justify the performance and (subject to us having some conviction upon that continuing) then we can talk about an allocation.

I think I just wanted to completely change the dials and say, “No, it’s not performing because it just happens to perform.” There were reasons why it didn’t. There are reasons why it does, and there’s possibly conviction around will it continue. 

That was the objective, or that was the inception of all this work (It’s more opinion based in some respect.) Then, what I tried to do is to basically say that the market this year has been so challenging. By the way, eventually (as you said) it went to the Financial Times in July, but I think it still applies to what we’re observing.

I was looking into some stats just before the call. If I look into 60/40, and you’ve discussed 60/40 so many times in these shows. I don’t want to spend too much time on the 60/40, but 60/40 or any risk parity combination of even including tips together with equities and bonds, or anything even more economic, risk balance type of an allocation; any multi-asset diversified portfolio this year is about 20% down, assuming a 10 vol annualized. It is really, really, really hard. By all means, the inflation dynamics suggest that, had you done short rates, short equities, long commods (give or take), given also the historical relationship with those asset classes to inflation, you would’ve done amazingly well yet to date.

The point that I want to make, is that really a sustainable inflation hedge? You cannot maintain that, right? You cannot maintain that portfolio forever. Because guess what? You’re basically shorting the two well regarded, rewarded premiem. You’re shorting equities and a term premium, and then you’re basically going long what has historically been primarily in contango, so commodity markets.

Sustaining that exposure just to play the inflation theme, I think it’s quite stretched. What I want to highlight here is that probably we would require more active, more dynamic location schemes. Probably trend following starts becoming a way to dynamically adjust exposures as a function of the recent move.

If you want to look into resume indicators, possibly the price is one indicator. Then if that is the claim, then why does it work? Why was it challenging for 10 years, or whatever those periods? You can basically look into whatever period you would want. But, broadly speaking, in those 10 years it was challenging. 

Here’s the story, you’ve talked about the Fed put, you’ve talked about quantitative easing, you’ve talked about all those features that were prevalent in those 10 years. I think it’s more important for our discussion just to mention a few claims that have been made for the underperformance, that in my view, and also based on the research, are not valid.

Crowding wasn’t the case. Crowding, as we mentioned at the beginning of the show, was the first reason that came through. It wasn’t crowding that led to under performance. It wasn’t even reduced diversification. That was also another claim. Back to Rob’s point, diversification did the job.

It wasn’t even an efficacy of signals to pick the moves, should the moves happen. None of those, even though they have been put forward as explanations, seem to hold. What happens to hold, mechanically speaking, is that while markets were not in a trendy fashion, broadly speaking, when they were trending, you had more frequent breaks.

Even when they were trending, the magnitude was not very big. Now, all of that is very mechanical. All I’m saying is that if something doesn’t trend, it’s not going to perform. There’s a fundamental reason underneath, and that is the Fed put. 

Why the Fed put? I think that’s the important point, the Fed put was in some respect, an element of fundamental certainty. There was either action or anticipation of an action if things go south. 

Now, in this environment, basically all I’m saying is that I have a price target of 100, but we kind of all agree about this 100. Rob might say 99, Niels, you might say 101, but guess what? The distribution of our forecast of an asset price is pretty tight in terms of disagreement (in this particular case, there’s a lot of agreement). In this environment, if the price moves for whatever reason (VIX spike in 2018), it’s more likely to come back. If you think about it in the bayesian world, this is our view, there’s news coming to it, but the only action that really happens in the market is that something’s going to come in.

Either they do come in or I anticipate them to come in pushing the price back to my conviction. I think 2018 was a great example. The market starts at an all time high, has the big spike, then by June’s all time high you have the Q4, spot down, vol down, 2019, another all time high. It’s this wiggling around that you always keep on hitting higher and higher points.

Whereas conversely, what we see today, or these days, is a complete shift to fundamental uncertainty. I don’t think any pair of us three or possibly even more agree whether we’re currently with high inflation risk, low inflation risk, soft landing, hard landing, no landing, whatever landing.

I think there’s so much uncertainty, and by all means this uncertainty, it can create price moves that contain information. Now, we might still agree 100 is a price target, but Rob might say no, I think it’s 80, and Niels might say it’s 120. What happens here is that, if you have a price move, it’s more likely that the distribution flows with it.

The price becomes sustained and this sustained move becomes more likely to be prolonged. Guess what? Systematically harvesting those moves is what makes trend work. The fundamentals are, certainty, in my view, is fundamental for trends to exist – macro uncertainty, micro volatility. 

We did some workback in my previous days that I think really hits the nail on the head on this one. We were looking into single stock reversal strategies. You buy the short-term losers and you sell the short-term winners. It’s a high turnover strategy, expensive on costs. We’re thinking, okay, how can we make this strategy better? My colleagues know, if and when they listen the show, they’re going to remember that.

We made this hypothesis along the following line. If you want reversal in the short-term, surely you need volatility (mechanically speaking). Okay, fine. Why don’t we pick the most volatile stocks and do a reversal strategy? We failed, big time. Like big time. Then obviously, because it’s a zero sum game, once you get the low volatility stocks and the low beta stocks, then you make it work. They’re like, “How is that possible?”

Then we made this hypothesis, which we tested. If low price volatility somehow proxies high fundamental uncertainty, how about we build a reversal strategy with stocks that have low analyst forecast dispersion? Stocks that the professional analysts kind of agree on, and the dispersion around the price is pretty much tight.

Then that was exactly a reversal strategy that was much better than just a plain vanilla one. That was the link again (from a bayesian standpoint) of conviction, agreement, consensus, lack of dispersion, giving more confidence that any price deviation (from whatever consensus we have) becomes more likely to bring it back. You can extrapolate and say, “Obviously when we go to the other side, high volatility relates to high momentum.” That was a fundamental shift that, in my view, has been established. 

The last thing I’m going to say, which I think is also relevant to why trends exist and why trends continue. Last year we spent the whole year debating on a single word: transitory. That was it. Is it here to stay? Is it not here to stay? Was it early, late, was it a base effect? Later on it became a concern, but then it was transitory, central banks were waiting back because no, it’s going to normalize.

In the article, a nice chart inspiration came from a CIO in the UK (asset manager). Basically the idea was if you go to Google Trends. For those that don’t know, Google Trends basically gives you a service whereby you can ask about any word or a sentence and Google will give you some sort of normalized search interest.

I basically searched for inflation and then transitory inflation. It’s so obvious, even though it’s so simplistic, that people were just Googling transitory inflation for the whole of 2021. Then suddenly December came, Powell came out saying, “Let’s forget about the word, please. That’s it. Let’s move on. Let’s fix it.” 

If that debate was happening, debate by itself suggests disagreement. We had started seeing some activity in the commodity market. some rallies started behaving in a particular fashion. Rates started moving in anticipation of rate hikes.

We had seen this underreaction. That’s precisely what we saw, underreaction by some part of the market. Then, obviously, at the beginning of the year it was a cataclysmic confirmation of those trends. Call it fear of missing out. Call it confirmation of trends. Call it uncertainty resolution. Call it whatever you want to call it.

We had what we have been observing until this day. I think that’s the pivotal shift. That is what made, in my view, the substantial regime shift in the market and trend. It’s just systematically harvesting that.

[01:05:45] Niels

It’s quite interesting, because I completely agree with you on the fact that we’ve lost the Fed put. To some extent, thank God for that. Markets, maybe, will be allowed to find their own path. Actually only a few days ago, which I don’t know if both of you are aware of that, we now have an oil put because the US had been out saying that when we get between $67 and $72, they’re going to fill up the SPR.

I know it’s not quite the same, but there is still a put out there. 

Another thing I wanted to say is that I’m definitely going to go to Google Trends after our recording and search trend following to see if there’s any hope. My real question to you, Nick, was when you talk to your clients, for example, do they sense, do they see that maybe this strategy – trend following (going back to where we started) is not optional anymore. It’s essential. Or for those who know it, do they see the difference and kind of agree with you and therefore also concluding (at least this is my view as well, I talk about it as globalization being over, and things like that), that we may be in a period where opportunities, at least for these divergent strategies, will be better (famous last words, of course), so much better than what we’ve seen in the last 10, possibly 20 years, where we had this extreme carrier regime? Is there any hope? 

[01:07:43] Nick

Certainly, right? I think testament to that is how difficult and challenging past allocation has been this year. I think another reason for asking your question, which is sometimes what we hear from some of the investors, is it too late?

I think my answer here is that’s not the right question. First of all, we know we have no crystal ball, certainly for the short-term. The short-term, again, as we said in the beginning, it’s not anticipatory, it’s reacting. It’s a price taker. That becomes a challenge to foresee. In the medium term, it’s a regime shift. I think allocating into some defensive components, or at least, call it Crisis Alpha, and then we can have a long conversation as to how Crisis Alpha is defined by Katie. Anyway, I think it’s a good term, and I think you’d agree with that. It should not be an act of regret. I genuinely should not think that this is an act of regret. We should not necessarily be in a place to foresee what’s going to happen next month. By all means, it’s almost like a broken phone. Every month this thing is hitting a new all time high over the course of the year. We could have had the same conversation six months ago. We could not necessarily foresee the next six months, but at least, from a regime standpoint, we could foresee.

The way that I’m going to answer the question, and I’m going to go back to whatever Andrew says, which resonates pretty well with me. The point is, for those that haven’t had Andrew recently, his point is that historically we have seen those strategies being part of an alternatives bucket, being part of a diversifying bucket, being part of a good to have, or possibly a good compliment, or possibly diversifying source.

We can have all sorts of different characterizations. It starts feeling more essential. Now if it’s essential, we should not be asking whether it’s late or not. If it’s essential, we should not be asking, is it too late or is it not too late. If it’s essential, we should not be thinking about an act of regret, rather, it’s more about how we strategically incorporate it into a portfolio.

By all means, to the extent that model portfolios and policy portfolios are more about a balance allocation between equities and bonds, it’s a good question – how much do you want to deviate? There’s a good amount of career risk deviating from the benchmark, whatever the benchmark is. Possibly it’s the time that the benchmark starts shifting.

I think this is a discussion to be had, but also a consideration, for us allocators, and that’s how I see it. My answer to, “Is it late?” It’s more about should it possibly be a strategic location and, therefore, when you enter it shouldn’t really matter? 

[01:10:39] Niels

I completely agree. I just want to give you, if you want, any final thoughts, Nick, you want to leave the audience with as we round this up?

[01:10:52] Nick

Final thoughts? My only final thought on the trend topic would be that there’s multiple ways we can look into an asset allocation problem. Ultimately an asset allocation problem should have short term risk management capacities and long term capital appreciation.

I think these are the two primary, in my view, features that we should be considering. The period is quite unique, certainly not in my lifetime. I was born in September, 1981. That was when it was raised for 15% and then started going down. That’s the math.

The regime is shifting. It feels that it has been shifting. It’s probably going to be here for some time. I cannot see how we can easily go back to what we had two years back. My last thoughts would be let’s be open minded about what more dynamic and active allocation schemes can bring to total portfolios.

I think that’s what I’m going to leave the audience with.

[01:11:55] Niels

I think that’s a good place to wrap up. Absolutely. 

With that said, to all of you listening today, if you like these episodes, feel free to go and leave a rating and review and share the episodes with your friends and colleagues. 

From Nick, Rob, and me. Thank you so much for listening. We look forward to being back with you on the next episode of Top Traders Unplugged. In the meantime you can always go and check out the show notes and find more resources on the website, and not least, take care of yourself and take care of each other. 

[01:12:27] Ending

Thanks for listening to Top Traders Unplugged. If you feel you learned something of value from today’s episode, the best way to stay updated is to go on over to iTunes and subscribe to the show so that you’ll be sure to get all the new episodes as they’re released. We have some amazing guests lined up for you and to ensure our show continues to grow, please leave us an honest rating and review in iTunes. It only takes a minute and it’s the best way to show us you love the podcast. We’ll see you next time on Top Traders Unplugged.