238 Systematic Investor Series ft. Rob Carver – April 8th, 2023

[00:00:00] Intro

You’re about to join Niels Kaastrup-Larsen on a raw and honest journey into the world of systematic investing and learn about the most dependable and consistent yet often overlooked investment strategy. Welcome to the Systematic Investor Series.

[00:00:23] Niels

Welcome and welcome back to this week’s edition of the Systematic Investor Series with Rob Carver and I, Niels Kaastrup Larsen, where each week we take the pulse of the global market through the lens of a rules-based investor. If you’re new to the show, I hope that today’s episode will trigger your curiosity enough to check out the back catalogue and listen to past episodes that you may have missed, like my conversation with Rich last week where we discussed the March madness that we just experienced as well as how the design of trend following strategies allow it to be “prepared” for unforeseen events without overcomplicating the investment process.

Also, if you missed the Wednesday episode, I would encourage you to listen to that one. It was a thought-provoking conversation with Barry Eichengreen, Professor of Economic and Political Science at University of California, about what we can learn from economic history in the current volatile global macro environment. Lastly, of course, I’m excited to invite you to enjoy the CTA mini-series where Alan and I have had the privilege of speaking with many of the decision-makers of most of the largest CTAs in the world. We dive deep into the most pressing topics and have gained unprecedented access to these industry leaders who share some exceptional insights really to the CTA world. So head over and check it out after you’re done listening to Rob and me today.

Rob, it is great to have you back this week. So much continues to happen in between our episodes. In fact, the last time we spoke, I just looked it up, was March 9, which turned out to be an interesting weekend for the US banking system. But anyway, how are you doing my friend?

[00:01:57] Rob

Yeah, it’s funny, isn’t it? I’m thinking that I hade the cardinal mistake of boasting about my performance at that particular podcast. In fact, it was funny, I was speaking at a conference at a French bank last week and I put up some slides that I prepared before March the 9th, and obviously, I had to say, well, after the end of this graph, things changed slightly, but the overall message is still the same. There was some people at the conference from a certain Swiss bank that is no more, shall we say. So yeah, there was a few awkward conversations going on in the corridors at that particular conference, I can tell you.

[00:02:36] Niels

Absolutely. There was a certain Swiss bank that got rebranded, let’s put it that way. All right. Good to hear. We do have a great lineup of questions and topics which of course I say every week, but I actually really mean it. So before we head over to that, let me do a quick market wrap. It’s obviously been a shortened week, but investors did experience a little bit of a roller coaster ride this week. Interest rates continuing to trend low in the face of mixed economic data.

At the start of the week, the manufacturing and service surveys both came in weaker than expected, leading some to fear that the US was heading towards a recessionary environment. This fear was compounded by weaker than expected readings in factory orders and durable goods. However, the back half of the week brought some good news as the US employment situation remains strong with March figures close to expectations. While wages were a touch softer year on year, this was largely due to a payroll mix and reflects the fact that lower-wage jobs are being added at a faster rate than higher-wage jobs.

Anyway, another bright spot in this week’s data was the strong Q1 year-on-year sales again in the US auto sector, and that was up 8% thanks to increased supplies and steady prices. While interest rates did rise slightly on Friday after the employment release, the rates market remained significantly lower than it was a month ago, as we just talked about here. The question in everybody’s minds, of course now, is whether the crisis is truly behind us or if it is yet to manifest itself in the real economy.

I’m really struggling with my words this morning, but anyway, Rob, I’m sure we’ll get through it. Next week, by the way, we have some inflation data coming out, I think, on the 12th and we have some financial sector earnings coming out on the 13th. So, no doubt, another interesting week. But anyway, let’s talk about what’s been standing out, for you, Rob, since you were last on the show. As mentioned, lots of things has happened since then, especially in a place called Silicon Valley. I was wondering whether we should be concerned when you have a place like that that consists of two words, namely “sili” and “con”, and then everything else happens from there. Anyways, that’s a bad joke on Easter Saturday. What has been standing out for you, Rob?

[00:04:53] Rob

Yeah, it’s been an interesting few weeks. Actually, another little anecdote I was teaching last week and the lady who was lecturing before me came up to me said, “What do you actually teach?” I said finance, not wanting to go into detail. “Is Deutsche Bank safe?” I said, “If Deutsche Bank goes, then we’ve got real problems.” I said, “As a depositor, your money’s probably fine. I’m sure you’ll be fine.” But yes, obviously, it’s really very much been a year of three thirds, I suppose is the most accurate way of putting it.

So the first third was the period up till when I was talking to you guys, March the 9th, March the 10th was okay, I think, and then obviously, a horrendous few days happened. Actually ignoring that, the next few weeks have been okay, actually. I’m actually up slightly since my low. I personally lost, actually, around 7.5% on that particular weekend, which I think is slightly better than average looking across the industry at other funds anyway. Where does that leave me for the year?

Well, for the year, that leaves me down, unfortunately, about 2.5%. Sorry, about 2.9% actually, so nearly 3%. Biggest losses, no surprise to hear, there’s a lot of bonds in that particular bucket. So US 20 years, German 10-year bonds, US 5 years all making an appearance there. Obviously, these are all positions where I was short bonds and got trashed when the market rallied on the back of that banking news in the US. Not all bad though. Some positive performance.

Interestingly, quite good performance in lean hogs and also in US gas and I made a little bit of money in VIX as well. So on net-net, mainly losses, unfortunately, and yeah, bonds and equities, metals, and FX actually all losing money as well, just looking at the sector split. My positioning now actually, I’ve said for quite a while now that my risk is quite low, and it’s even lower now. So having to scale back positions even further on the back of a shock, as you’d expect trend following to do. My analyzed risk now is running at around maybe a quarter or a fifth of long-term target.

My biggest risk now actually is in the Ags markets. The bond markets slipped to second place. So I’ve trimmed my position in bonds quite considerably, although I do still have a modest short in US 2 year, but I’m long. Yeah, I’ve got very few positions. Actually, I could list them all quite quickly. It does illustrate the kind of situation where we’ve really cut back our positions, as you’d expect, given that things have moved against us. So yeah, not really a huge surprise, probably in line with most people in terms of my experience for the year and the few four months we’ve had so far.

[00:08:04] Niels

Yeah. It sounds like it for sure. Of course, we know now that the SG indices, the CTA index, the Trend Index, had their biggest two-day loss on the 10th and the 13th, 14th, whenever it was. So yeah, it was an unusual period of time. I think it sounds like you did pretty well. Of course, as I briefly talked to Rich about last weekend, I think this period in particular will certainly have a lot of dispersion returns, mostly driven by just the markets and the exposure levels that people would have had towards fixed income, and that’s fine. That’s how it should be.

This week, after an exciting March month”, it has been a very quiet week performance-wise as far as I can tell, even though we got off to a little bit of a bang when the OPEC people decided to cut the production further by I think 1.1 million barrels per day. That was a bit of a surprise. We have seen some decent moves in the markets this week. But when I was briefly looking at the funds that I follow, intra-month, it looks like performance so far in April is pretty flat also from the indices. From what I can gather, there was maybe a little bit of a challenge in some of the Japanese equity markets for trend followers, but on the other hand, commodities did pretty well. So anyway, it seems to have offset each other pretty well.

When I look at the numbers as of Thursday night because of course, we don’t have the numbers for Friday, which would have been a very small change anyways because of Easter, BTOP 50 is down 4 basis points for the year, down less than 4% for the month and down for 4% for the year. SocGen CTA Index down 14 bips for the month, down 5.34 for the year. The Trend Index is flat, down 7.3% so far this year. So nothing too much. Short Term Traders are down 18 basis points in April, they’re down 2.29 for the year. Equities are doing well. Up 7.2 for the world equity markets MSCI World. For the year, the bonds are up 0.5% this month and the S&P 500 index is almost up 7% for the year.

Now, we’ll run through a few questions. I don’t think they’re that long, and then we’ll dive into the topics that we have talked about, Rob, in advance. The first one is a message for you. It even says, “Dear Robert”. It’s from Ricardo and he’s just asking, “When are we going,” he says “we”, “going to write a book on Python backtester to trade equities futures foreign exchange?”

[00:11:06] Rob

Ricardo is a good friend of mine who actually lives in the same town as I do so he’s deliberately winding me up now.

[00:11:15] Niels

You have just finished one book, so I guess it’s time to think of the next one.

[00:11:17] Rob

He’s like you need to start on another book, so yeah. The answer is truthfully, Ricardo, probably never. I don’t like the idea of writing books with code in them like about Python and stuff like that. One reason being (there are a few reasons actually), one is that programming languages and things are dynamic. They change over time, and that means you need to keep reissuing the book and rewriting the code in them or they get out of date.

Now, that’s great if you’re a publisher that does that sort of book, like Wiley, for example. They’ve got a lot of these books. But it does mean a lot of work for somebody, and that would be me. Another reason is that they’re quite complicated books to write. The books I write are pretty complicated anyway, but you’ve got to write the code, you’ve got to test it, and so on and so forth. Then you get lots of people contacting you asking for clarifications and saying this won’t run, this won’t run. Again, that happens with other books anyway. People will write to you and say, in this formula here, what do you mean by this, what do you mean by that?

But with code, it’s literally something like, I typed this in, it didn’t work. What are you going to do about it? I just don’t feel that that’s the kind of thing I want to do. Our good friend, Andreas Clenow, who talked about his reissuing of his classic book on managed futures recently, I think his third book was actually a book of this kind about backtesting equities in Python. I know he’s had some problems with the fact that it was about a particular library that’s no longer supported and he gets lots of questions coming in and so on and so forth. So yeah.

Ricardo, I think the next thing he’s going to do is like hire a plane to fly with a banner going past my house every hour saying, when you’re going to write this book? He’s very, very keen for me to write it because he personally would like to read it.

[00:13:12] Niels

He should write it of course then.

[00:13:15] Rob

Well, yes.

[00:13:15] Niels

Exactly. I thought another reason why you wouldn’t want to do that was it would be an interesting challenge to do the audio version of it.

[00:13:27] Rob

Quite.

[00:13:28] Niels

All right. Well, let’s jump to a question from Bruno. Bruno writes, “Let me express my gratitude and admiration for your podcast and you and your roster of impressive guests.” So that would be you, Rob, and everyone else, of course. “I would like to ask Rob a question on dynamic position sizing and the need for volatility forecast. One thing that isn’t addressed in great detail, in my opinion, is the apparent contradiction of using historical volatility as a predictor of future market conditions when defining position size. This is a bit like the critique many people move to VaR, value at risk, which is like driving while looking in the rearview mirror. Does Rob advocate using a model of any kind to produce a volatility forecast and let this risk budget fluctuate according to market conditions or does he see more value in having a more empirical approach and using a blend of historical volatility perhaps using different lookback periods? What would be the main reason for his choice of one paradigm and the other and what would be the most important features of Rob’s volatility model should he develop one?” Okay, good question.

[00:14:39] Rob

Yeah, that’s a good question. This is kind of one of those unspoken assumptions that we use historic vol, but actually, what we really want of course is future volatility, but we don’t have access to that. Now, the good news is that the single best predictor of future volatility is actually historic volatility. To be more precise, if I measure the volatility using standard deviation over a number of different lookbacks, so if I look at vol over the last few days, vol over the last few weeks, vol over the last six months or the last year, and then I use that to predict what volatility will be in the near future. Again, I can look at a number of different holding periods for my assets.

What I will find is that the single best predictor of future volatility, regardless of your horizon actually, is the volatility with a lookback of around a month. That’s true whether I use a simple standard deviation that just takes and equally weights all the returns from the last 20, 25 business days, or whether you do something more sophisticated and use an exponential weighting, which is what I use myself. If you do a regression, which is a measure of how well y predicts x if you like, you get an R squared of about 0.4, which actually is extremely good.

If I try and do regression like that and try and predict correlations, I’ll get an R squared of about 0.2. If I try and predict means or Sharpe ratios, I get a very, very weak R squared indeed, because it’s much harder to predict those. Now, you can improve that volatility model in a number of different ways. So one obvious thing you can do is to use implied volatility. The implied volatility of an options price is actually mainly driven by the market’s forecast of what volatility is going to be in the period up to when the option expires. But there is a caveat there which is that options are systematically overpriced.

We can earn this thing called a variance premium by selling gamma (as they say in the options world) and delta hedging it. We’d expect to earn a positive return over time, occasionally losing money if the market moves a lot. So it’s a classic kind of negative skew, a trading strategy selling gamma. But putting that to one side, yeah, we can use implied vol from options data. I don’t do that personally, although when I was at AHL, we did do that and I assume that they still do that. Because there’s a fair bit of work because you’ve got to bring in the volatility and do some calculations and then back out the effect of the variance premium.

There are other things you can do in terms of getting more and more sophisticated. The academic literature is littered with various volatility models. You’ve got things like GARCH, for example, which… (Let me see if I can get this right because people are wondering why both Niels and I are stumbling a bit this morning, is we’re actually recording quite a bit earlier than we normally do because of Niels’ his travel schedule. So I think we’re both a bit tired.) But GARCH I think stands for generalized autoregressive conditional heteroskedasticity.

[00:18:02] Niels

The good news, Rob, is I wouldn’t know so I can’t even correct you here.

[00:18:06] Rob

Yes, but I know for sure there’s at least a couple of people listening who will know whether I got that right or not, but hopefully I did. But these are basically ways of weighting and modeling the volatility in various different ways. So I do something like that, and Bruno actually kind of talks about as well, and that’s that I use a mixture of a blend of a very slow estimate of volatility on this one month one I’ve already talked about. The reason I do that is because volatility is a process that is predictable in the short term, in a sort of stationary way. In other words, if vol has been high recently, it’ll stay high. If it’s been low recently, it will stay low. But it also mean reverts as well at longer timeframes.

If equity market vol is currently very high, so above, say, 40% annualized standard deviation, it’s unlikely to stay that high for more than a few months. So to account for that, I include a very slow estimate of volatility that kind of pulls in my quick moving estimate. One implication of that, which is very important for someone who’s in a sort of CTA business because we size our positions inversely according to volatility. So if volatility is very low, we’ll increase our positions dramatically and have more leverage.

So if volatility is very low, we’ll have a lot of leverage on and will be very exposed to potential market shocks. By combining a short and a long-term estimate of volatility, that means that I won’t be putting quite as much leverage on in those low vol periods and I’ll be less exposed to the market shocks that are happening.

One more thing you can do, just before I finish, is you can include intraday data. So even though I’m running my system mainly at daily frequency, one good estimate of improving vol is to bring in just your vol estimates from last couple of days of say hourly data. That allows you to pick up early on something happening in the market that the daily returns aren’t showing up yet in a big way.

So yeah, a simple one-month lookback of vol does a really, really good job and will get you 90% of the way there. There are all these refinements you can throw in that will do a slightly better job of improving your estimate of volatility. That R squared number would maybe go from 0.4 to 0.5. That’s not necessarily going to improve your returns, but it will make your distribution a little bit more stable. If you’ve got the time and you want to put the effort in, it might be worth doing. It’s a kind of marginal gain, I would say.

[00:20:44] Niels

Sure. Great stuff. Thanks very much for that, Rob.

All right. The last question or set of questions is from Skip. Skip writes “Hello, Niels, I would like to ask Rob a few questions.” The first question, and pardon the pun here, I’m going to skip, because we already talked about it. It’s about performance. We’ve already done that. But the other one will be, “I know that Rob is not a pure trend follower. How is the overall performance of the portfolio affected? Is there any comparison when using only trend versus his other trading rules, carry, mean reversion based on backtests, for example?” So I’m not sure, you may understand this better question than what I do and where Skip is going with this.

[00:21:29] Rob

Yeah, I’m just trying to see if I’ve got an up-to-date report that will answer Skip’s question. I’m not sure I do, sadly. Just bear with me.

[00:21:38] Niels

Just general terms, obviously.

[00:21:40] Rob

No, actually, I do have an up-to-date report. So I think what Skip’s asking is over the last few months, clearly, trend following would have suffered in March, but did other trading rules that I run like, for example, carry most famously, would they also have suffered or would they have provided diversification? So I’m just quickly scrolling through a very, very long report, which actually has the performance for all my different trading rules in it. I’m not yet seeing any good news, fair to say, but just bear with me.

[00:22:17] Niels

Hope it’s not that long then.

[00:22:20] Rob

Exactly. Yeah. Well, it includes performance going back for various periods. So there’s a year-to-date report, but also longer timeframes as well, and it breaks it down by every single type of trading rule I have. There’s a few, to say the least. I’ll just talk while that without reports loading. The reason for including lots of different trading rules, just to take you back to basics, is of course we would hope that that would provide us with diversification in the same way that adding more instruments to our portfolio also provides us with some diversification effect.

I now have the spinning wheel on the computer that indicates that the computer is like no, this report is too big. I’m not going to load anymore. What I can say to you, Skip, is a couple of things. From a theoretical perspective, just to look at bonds and look at carry, I probably would have expected carry to potentially have been in a similar situation to trend because the yield curve was actually pretty flat, I think, going into the crisis that happened. Actually, that’s one of the reasons for banks being in trouble because banks like steep yield curves. They want to be able to essentially borrow money at the front of the yield curve from depositors for low-interest rates and then put it into long-maturity bonds and mortgages and other investments like that with higher interest rates and make money.

The situation they’ve been in recently means they’ve had trouble doing that. People who have been listening for a while remember from Cam Harvey, who we interviewed for the macro series, that a flatter inverted yield curve actually is potentially a sign of bad economic times to come as well. So there’s something there. In theory, it’s quite likely that carry and bonds would also have been short and wouldn’t have, specifically in bonds, been much help in that particular episode. But the other thing I will say, Skip, is I’m going to, in the next few weeks, do some analysis of my performance last 12 months, which I do every year. It aligns with the UK tax year, which goes into April. That analysis will include a full analysis of all the different trading rules that I run. So you can check in on my blog, and maybe next time I’m on, I’ll talk about that topic again.

[00:24:54] Niels

Okay, cool. Final question before we dive into your topics or our topics, I should say, if you had to pick one trading rule, trend or something else, what’s kind of your… You have to choose between your children here.

[00:25:09] Rob

Exactly. I was going to say exactly the same thing. It’s the choose between your children question. In the backtest, carry has a better Sharpe ratio but not as good skew as trend following and vice versa. I’d probably pick trend following. I don’t see how I could pick something else.

[00:25:28] Niels

There was only one real correct answer, I should say, on this so I’m glad you picked the right one.

All right. Thanks for the questions and thanks for your kind comments, Skip. Let’s jump into some topics. Now, the first topic, when you raised it to me, Rob, I thought, is this really interesting, just being completely transparent here? But then you just gave me like 30 seconds and I thought, yeah, this is probably relevant for us to spend a couple of minutes talking about. So can you reveal what this mystery topic is?

[00:26:02] Rob

Well, I can. Niels, do you know what April the 14th is this year? It’s a special day.

[00:26:05] Niels

April the 14th this year?

[00:26:10] Rob

No, it’s not my birthday either in case you’re wondering and haven’t gotten me a present.

[00:26:13] Niels

If it’s related to this topic, I’ll kind of guess. But maybe the last trading day of something.

[00:26:19] Rob

It is. Yeah. So April the 14th is the day that if you own a Eurodollar future, which obviously is a US interest rate future based on the LIBOR rate, it will convert into a different kind of future. It will convert into an SOFR future, which is secured overnight financing rate future. I think this is an interesting topic for a number of different reasons actually. The first is as a futures trader, it’s quite unusual for this to happen. It’s quite unusual for the market to say, okay, that future that you own, we’re going to take that away and replace it with a different future.

Futures delist from time to time. Futures often become more abundant. No one trades them anymore and the CME or whoever decides it’s just not worth the hassle of keeping them on the books so they they delist them. It does happen. A recent example would be the big S&P contract which delisted I think about a year, a year and a half ago, and now we’ve just got the micro and the mini because everyone just switched to trading the micro and the mini. They’re like we don’t need the big contracts anymore.

Another example actually would be in lumber. They changed the definition of the lumber contracts, the old lumber contract stopped trading. There’s now a new lumber contract which is defined in a different way. But it’s really unusual for a big, high-volume contract like the Eurodollar future, which is one of the largest volume contracts in the world, to be replaced like this. Of course it all ties back into LIBOR itself. I’m speaking from close personal experience here with this, but LIBOR was a measure of interest rates based on a survey of banks that was done every morning.

So literally in the olden days, someone rung up all these banks and said, where can you borrow or lend for three months today. That survey clearly is open to potential manipulation, and indeed, several people have gone to jail and been prosecuted with that manipulation, including some people I know quite well because I used to work with them. At the start of my career in investment bank trading, I was sitting a few meters away from people who, unbeknownst to me, were fixing LIBOR and have subsequently served jail time for it.

This is not the place for a discussion about whether that was really illegal or whether the law was effectively changed and applied retrospectively. I’ve blogged about that if people want to know. To me, this is one of these once-in-a-lifetime things. I don’t think that this is going to happen again. It feels like quite a compelling thing. So yeah, if you happen to own any Eurodollar futures, then something weird and magical is going to happen to them. On a more kind of pragmatic level, if you’re like me and your system is fully automated, a lot of things are probably going to break. So just be aware of that.

One thing, for example, that will happen is the price will actually jump by I think it’s 26 basis points off the top of my head, but basically because these things are not quite the same thing. One is a secured rate, one is an unsecured rate. The S in SOFR stands for secured. So there’s going to be a difference in price and there’s a difference in the credit. SOFR is actually based on real market trades rather than on a survey which is of course the reason why they’re replacing LIBOR.

The whole LIBOR saga has been a very long and turgid one. I think the issues of LIBOR potentially being fixed were first raised somewhere in late 2007 if my memory is correct, so it’s been 16 years to get to this point. But yeah, it feels like an important day that’s worth marking, and yes, it’s a bit nerdy and it’s a bit kind of fixed income nerdy, but to me personally, it means quite a lot. So I would have felt bad if I hadn’t mentioned it.

[00:30:32] Niels

No, I’m glad you did. Absolutely. It was not on my radar, per se, except that I’ve seen obviously that we also stopped trading Eurodollar a while back, but anyways. Now, you wrote a blog post about another topic, which may on the surface seem also a little bit nerdy, but you assured me that it’s not. So let’s run with that. It’s about the wonderful topic of estimating standard deviation.

[00:30:57] Rob

Which we’ve touched already, so yes.

[00:30:59] Niels

Right, exactly.

[00:31:01] Rob

Yeah. This is actually about a kind of either/or question. Actually, this is something that happens a lot because often you’ll see in the headlines in the news, they’ll say that the S&P dropped by 100 points today. Actually, that’s one of the things I really hate seeing in newspaper headlines because unless you have in your head a mental model of what 100 points means, it’s completely meaningless. So what people really ought to do is convert that into a percentage and say the S&P dropped by 2.5% today. That’s not a massive loss, is it? It’s kind of a bad day, but it’s not a terrible day.

But obviously, in the newspaper, the S&P dropped 100 whole points today. Mentally, you’re thinking, wow, that sounds like a lot. But really, it’s really not. They never do that with something that has a small dollar on it. So they wouldn’t ever say, oh, yeah, the price of this went up by just this. They would report the percentage to make it seem bigger. I guess that’s what being a journalist is all about, sadly, grabbing headlines. So I personally prefer often when looking and thinking about price changes to do them in percentages. It’s the same when I’m reporting my P&L to you guys every week and I said I’m down just under 3% for the year. I didn’t say I’m down…

[00:32:36] Niels

Fifty million.

[00:32:39] Rob

Fifty million. I wish. I wish, Niels. Yes, I wish. I don’t think so. Yeah, a lot less than that. But it wouldn’t mean anything. If I reported to you a dollar amount, it wouldn’t mean anything. In terms of thinking about price changes, I think percentages are important. In terms of reporting standard deviation, so saying my long-term standard deviation target is 25% a year and that would translate on the S&P to 1000 points or something. But actually, in terms of calculating standard deviation, there are actually good reasons why you should not use the percentages.

So when you’re actually sitting down and saying, right, I’m going to get say the last 25, 30 days of returns and I’m going to put that into a calculation to estimate what my risk should be, which is what we were talking about earlier, you shouldn’t use percentage standard deviations. There are a few reasons why not. The first is that prices can actually sometimes go negative. We’ve seen that in the last, well, actually, almost exactly three years ago. The price of front crude oil went negative.

Clearly, it’s nonsensical to divide something by a negative number because unless you do something about it, you’re going to end up with a negative number for your standard deviation, which doesn’t make any sense. The issue isn’t so much the going negative, it’s when things get really close to zero. So if you imagine something like crude oil which three years ago, was probably moving about an average of $5 or $10 a day, $10 divided by $50 is 20%. But $10 divided by $1 is 1,000%.

What you’ll see happen if you’re using percentage standard deviations, if a price starts to go towards zero, then the percentage returns will get bigger and bigger and bigger even though in reality, the market volatility is still the same. It’s not like the market regimes change. We’ve just done it with these ridiculously huge return numbers. You might say, well, Rob, how often do prices really go negative? You can only think of one example in the last three years. But because of the way that most people build their futures backtesting systems, we do this thing called generating a back-adjusted price, which means essentially, we join together the prices of lots of different contracts that are traded through history.

If you do that with a contract that has a positive carry, like for example, bonds, as we discussed, normally you’re in a positive carry on bonds, what you’ll find is that the adjusted price if you go back into history, it gets lower and lower and lower, and at some point, quite possibly will turn negative. So if I pull up the price of US 10 year bonds in my system, it’s going to go from maybe about 100 now and about 30 years ago, it’ll be zero. Before that, it’ll be negative. So this issue with calculating percentages on very, very small numbers will be another issue.

So what will happen is my standard deviation estimates, even if nothing’s really happened to the market, will get bigger and bigger and bigger as that price approaches zero, and then they’ll get smaller and smaller again, so they’ll just be really strange numbers. There is a way of getting around that which is to use the actual price of the contract as it was trading, then run the back-adjusted price as the denominator in your calculation, which I prefer to do. But again, that won’t get you away from the issue of things going to zero.

The final reason for doing this, which may not be that obvious, is actually it is the price change that you care about in terms of actually scaling your positions because if you think about a basic idea of how you’re scaling your positions, let’s say you want to take a million dollars of risk in something, wouldn’t you want to know what the dollar risk is of trading that thing? That’s going to be equal to the standard deviation measured in price terms multiplied by the value of each contract. So for Eurodollars, as we’ve been discussing, that’d be $2,500 a point. For 10-year futures, it would be $1,000 a point and so on.

So yeah, it is a bit of a nerdy and geeky conversation but it’s an example of something that’s kind of going on under the hood of a lot of systems that people may not properly appreciate. It’s an example of when, if market conditions change and your system is not sufficiently robust. So for example, if you were using percentage standard deviations and a price suddenly went negative, your whole system would just go whoa, hang on a second. The best thing that would happen is it would just throw an exception and crash. The worst thing that would happen is it would just carry on but produce really weird results, which you wouldn’t necessarily pick up on straight away.

So this business isn’t that complicated but it really helps sometimes to have a real focus on attention to detail on some of the small things going on. Again, it may seem a bit nerdy, it may seem a bit uninteresting, but I think it’s something that people should be aware of.

[00:38:01] Niels

Well, we’re going to shift gears now and we’re going to pull some punches, because there was an article called Trend Following: Rolling with the Punches from our friends over at Man AHL that, yeah, again on the topic of trend following naturally but also in relationship to what we’ve just been through and crisis periods. I know you had a quick chance to look it through. What were your main takeaways, Rob, from the article?

[00:38:30] Rob

Yeah, it’s an interesting article. I think the important caveat is that these pieces are written by the sales side of the business really. They’re not necessarily super serious pieces of research. I think we should always have in mind that Man, although they’re a great firm, and as I often say, they paid for my house, so I have a sort of legacy of appreciation towards them. They are high quality pieces, but we should always bear in mind that the motivation is like ours to a degree, to say trend following is good. When we have these periods like March, we know basically don’t panic. That’s the message and that’s the motivation, and that should always be borne in mind.

But having said that, as I said, it’s a pretty high-quality piece. They say, well, what actually happened? Well, as we’ve discussed, SVB, Silicon Valley Bank happened, and then UBS Credit Suisse and another US Bank as well. Us two-year treasury yields specifically moved by the most of moves since Black Monday, October ‘87. But it wasn’t just that. There’s quite a few markets that saw reversals in their prices. The US Treasuries were the most dramatic, but quite a few equity markets also showed sharp reversals, FX markets showed sharp reversals, even nat gas actually showed a sharp reversal.

So it wasn’t just that single market that caused those sharp losses. It was because a lot of things switched direction on the same day. Because obviously, as trend followers, we normally try and be diversified. We wouldn’t have had that big an exposure to just one US fixed-income market necessarily. But then they said, well, okay, that’s kind of the bad news but can we kind of look at history and have an opinion about generally how trend following behaves around these crisis periods when we see sharp reversals?

They’ve taken a bunch of historic periods when these reversals happened. For example, July 2007 was one, November 2001 was another. They looked at the performance in three periods, so before the reversal, the reversal itself, and then after the reversal. The first thing to say is March was bad, but actually interesting, March of ‘07 was worse, because the stock market had been going up and then the news about the credit crisis, initial credit crisis, you start to filter it and things reverse quite sharply. So that kind of puts it in historical context.

But the other thing that they do say well, you know what? If we take an average of all these periods in which trend following saw a sharp reversal, how does trend following do after that. The good news is that on average, it actually pretty much makes up the reversal, and if anything, within 12 months actually has a small profit. So we know it does seem that after a sharp reversal, there is a kind of, technical term, negative autocorrelation returns or less technically a bounce back in improvement. Now, of course, we should say that this hasn’t always happened.

For example, in February 2018, or in the 12 months following February 2018, we basically went sideways for 12 months. It didn’t recover any of its previous performance. So that’s an average. So yeah, it’s quite an interesting piece and with the usual caveats that, yeah, it’s a bit of a sales piece. It has a motivation to encourage people to look into trend following.

Generally speaking, I’m of the view that they always say, when’s the best time to buy stocks? The answer is, well, if you believe stocks are going to go up in the long run, the answer is today. Trying to get out of stocks after they’ve done badly or getting into them when they’ve done well, unless you’re running some kind of systematic trend following model on stocks, it’s a bad idea. Similarly, if you’re going to have an investment in a risk premia type strategy like trend following, I believe you should try and stay exposed to that as much as you can and not panic and get out when things have gone badly.

I’m not sure that there’s enough evidence in his article to say that the best time to get into trend following is now because the markets suffered a reversal, and after a reversal, things are always going to come back. I’m not sure that they kind of spin that tail. But I think the message is if you are invested in trend following, there’s no reason why you should be particularly concerned about further poor performance from here. But yeah, it is what it is.

[00:43:18] Niels

That’s what it is. Of course, there’s absolutely nothing wrong with being a little bit biased toward trend following on this particular podcast, I would say. It reminds me of a quote that our founder Bill Dunn would say, and that is, “The best time to invest in trend following is at the bottom of a drawdown, the second best is today.” Alrighty, well, of course, we talk about trend following in terms of during a crisis period, but that kind of nicely leads another topic, which was an article that was published in Bloomberg this week.

Of course, ideally, a lot of people really want to have protection of their portfolio, ideally, protection that doesn’t cost them anything, and we can certainly think of one strategy that does that over time. But of course, when we talk about tail hedge and we talk about protection, there’s one particular individual that often is associated with some strong opinions, both his own and of others, and that is, of course, Nassim Nicholas Taleb, who is the author of a number of important books, I guess. Also, he’s an adviser to a firm, I guess you would call them a hedge fund called Universa.

Universa made some headlines back in 2020 because of the way they quoted their returns during COVID, thousands of percent they quoted that they had made. I think there was a lot of discussion on social media about the way that they approached this. Now, there is again this article came up. I kind of forget the details of the article, I have to say. There’s just so many things going on right now. But I did read it and I did listen to a podcast actually with Nassim Taleb this week. He did come across much more mellow, I have to say. Maybe it was just because the two hosts were more in agreement with him I guess than in disagreement. But it is an interesting topic of course.

I know you only had a few minutes to kind of glaze over the article but this thing about tail hedge, this thing about how to quote your returns without them being eye-catching and controversial, kind of goes a little bit to this thing you talked about before of small denominators can lead to very high numbers.

[00:45:43] Rob

This is quite nerdy as well, right?

[00:45:45] Niels

Maybe let’s not make it too nerdy because there’s another controversial topic coming up after this one.

[00:45:50] Rob

Yeah, I think actually, I’m going to listen to that podcast you mentioned because I obviously never listen to rival podcasts, Niels, unless you give me permission to. But I think one thing about Nassim Taleb and indeed, like a lot of people, I mostly see him on Twitter where of course he comes across as this very aggressive personality. In real life, I’ve never met him, but I have met people who have met him if that makes sense, so I’ve got a kind of second-degree connection to Nassim Taleb.

They say he’s much nicer in real life than Twitter, and that’s true probably of nearly everyone, including me, I would say. I hopefully come across even on this podcast as much nicer than on Twitter, because on Twitter, of course, sometimes you haven’t got time to be nice. You just have to say what you got to say. I think that’s an accepted part of the medium.

So tail hedging, it’s a fascinating topic. There are better people than me to talk about the mechanics of tail hedging and how you do it, but the basic idea is this, that you’re essentially buying insurance against a market downturn without it costing you a net amount of money. We talked about this already. If you systematically buy options and delta hedge them, you will systematically lose money because of this thing called the volatility premium.

Essentially, the market makes you pay for insurance and that cost gets worse if you buy massively out of the money options because of this thing called smile. So basically, post October ’87, the market has said there’s a possibility of this massive outside move happening, and therefore, we’re going to charge you a lot more money for say 20 delta out of the money put options, which would be the sort of thing you’d use to insure against a market catastrophe.

The other thing is that the bid-ask spreads on those out of the money options tend to be quite wide as well. So that combined with the volatility smile means it’s a very expensive way of protecting yourself. But it is the only sure way of protecting yourself. Trend following empirically has protected you against certain kinds of market crashes, but not always. It wasn’t much help in March 2020 either, but it was a big help last year, over the course of the year when the classic 60/40 portfolio got absolutely smashed and trend following did very well. But it’s not a guarantee of that protection. So it’s not really a true crisis alpha insurance product shall we say.

The only true crisis alpha insurance product is either keeping all the money in cash, in which case, inflation will stuff you or yes, buying these out of the money options that are very expensive. What tail hedging funds try and do is to do that insurance buying in a more selective way. Without going into details because apart from everything else, I’m not an expert, what they’re trying to do is buy insurance when it’s relatively cheap, and buy certain kinds of insurance that’s cheaper than others, and potentially pay for their insurance by selling other options that are rich and all these kinds of tricks. That means they will never be a perfect hedge, but it means if they do their job well, they can still be a hedge against crashes without costing you a net amount of money in the long run and potentially even making you money in the long run.

So let’s switch away from the specifics and just think of an analogy which most people may be more comfortable with. Let’s say you want to insure your house. So let’s say your house is worth, I don’t know, half a million euros and the insurance company says to you, okay, we’re going to insure your house for, I don’t know, 500 euros a year, which is 0.1% or 10 basis points of the value of the house. On average, this insurance company is kind of making profits and stuff on average when you’d expect over the lifetime of that house insurance that they would make money.

So you might be paying 500 euros a year over, say, 20 years of ownership, which adds up to 10,000 euros, I think, and you make maybe one claim for if something happens to that house, you make one claim for 5000 euros. So you’re a net loser of 5000 euros on that. That’s basically what will happen if you’re a naive tail hedger who just buys out of the money options. That’s essentially what’s happening. You’re going to lose money in the long run on that deal.

Now, let’s suppose that you managed to find a tail hedging manager or in this analogy, an insurance company that’s not very good. It’d be an insurance company that’s not very good. Or maybe you’re a really smart person who really knows how to buy really cheap insurance policy so you’re the equivalent of a smart tail hedger. So you’re paying your 500 euros a year in premium, but instead of getting 5000 back in claims, you actually get 12,000 back in claims. You make a 2000 euro profit over the life of your policy. Over 20 years, that’s 100 euros a year of gain effectively. Now, Niels, the question is this. This is the question the article arises. That 2000 euros in profit (and this comes back to what we were talking about earlier), what is that as a percentage?

[00:51:30] Niels

Yeah, that’s the question.

[00:51:35] Rob

Yeah. So you’re going to try and answer or?

[00:51:38] Niels

I’ll leave you to do all the answering today, Rob.

[00:51:40] Rob

It’s too early for both of us. I’m lining up these clues and Niels is trying to keep his eyes open. Okay, so there’s two ways of thinking about this. One way is to say, well, my house is worth half a million euros. That 2000 euros of profit, I should divide that 2000 divided by 500,000, which is obviously going to give me 0.25%, I think, or something like that. It’s going to give me a small number, a small percentage number.

But another way of thinking about this is to say, well, actually, your 10,000 euros of premium, you should divide by that. So you’ve made 2000 euros profit on 10,000 euros of premiums, so you’ve actually made 20% profit. Or you could even say on the money you’ve paid in this year, the 500 euros you’ve paid in this year, you’ve made 12,000 back. So you could say it’s 12,000 divided by 500, which obviously is going to be a big four-figure percentage return, which looks amazing.

Now, it’s not going to be too difficult to guess, given the choice, which of the three options you would quote. You’re not going to say yeah, we make our clients 0.25% a year because they’ll go, okay, that’s not really particularly impressive. But if you say we make our clients 11,000% a year or some other big number, then they’re going to be like, wow, that’s incredible, and that’s obviously going to be in the news, it’ going to be on Bloomberg, and people are going to be very impressed by it.

The question is whether that’s really a valid number or not. It’s a very difficult one, because these tail protect funds, although we call them hedge funds, they’re very different from a normal hedge fund. With a normal hedge fund you hand over your investment. the gains and losses come, and it’s quite easy to say what the percentage gains and losses are. With these tail protect funds, what you do is you hand over your premium, you hand over your insurance premium and they do what they do.

If you make an outsized gain, then obviously, you hand over your premium, but you also say you have a bigger amount of money, which is the amount you’re insuring, right? That’s the 500,000 euros, the value of your house. They don’t have control of the full 500, 000. They say, well, we’re not going to use that as our denominator in our percentage calculation, we’re going to use the premium, and that’s where these big numbers come from. So in a way, what they’re doing is kind of correct in one sense of the word, except maybe in an accounting sense of the word when there’s perhaps one right way of doing this.

[00:54:21] Niels

Which seems important.

[00:54:22] Rob

Well, yeah, but we all know a good accountant will say to you, what would you like the number to be? But in terms of tax and stuff like that, I guess there’s an important number to come in there. But actually, in terms of kind of economic value, I think these guys should be… Quoting these big numbers is unnecessary. Any tail protect fund that makes money in the long run should be proud of themselves because it’s not an easy thing to do. They’re fighting against this variance premium. They’re providing insurance against market crashes.

I think they should be more honest and say, yeah, we cost you money in insurance, but in the long run, you’ll get it back and some more. It’s not a lot more but it pays you off. The important thing to say here is that we shouldn’t really be judging these funds on the returns anyway, we should be judging them on the package of returns they produce when combined with a portfolio, with a long only portfolio, because that’s the reason you’re buying them. You’re not buying a tail protect fund as your only investment because that’s a pretty rubbish investment where you pay out money year after year after year, and every now and then, this huge money comes back into your account. Most people don’t want that sort of return profile. You’re buying it as insurance to hold with another asset.

So what they really should be doing is saying, and this is kind of what the CTA industry tends to do as well, because in isolation, a CTA performance might not look that great, but combined with 60/40, with the diversification you get, all of a sudden, it looks really good, and that’s the marketing these guys should be doing as well. They should be saying, this is your equity line. Okay, now what happens when we add tail protect? This is your equity line. The drawdowns are much reduced and the overall return is unchanged. Brilliant. That’s fantastic. They don’t need to do this headline grabbing stuff or quoting return in thousands of percent. I think it’s unnecessary, frankly.

[00:56:23] Niels

Thank you for that.

Now, we had two more topics that we had discussed. Luckily, we only have room for one in terms of time. Even more stroke of luck, we don’t have much time. But the topic, speaking about headline grabbing content, is something you came up with called “reasons not to trend follow.” I can hardly say the words. It’s very hard for me to express that sentiment. But Rob, as always, I’m sure there is a very good reason why you would even consider bringing this up as a topic and I have no idea where we’re going to go with this. So let’s spend a few minutes on this as our final topic for today, because of course, I’m sure there’s a good reason for it.

[00:57:16] Rob

Well, one reason is just to make the podcast more interesting, Niels, because week after week…

[00:57:22] Niels

So you’re doing the Universa, you’re coming up with headline grabbing stuff.

[00:57:26] Rob

Well, yeah, exactly.

[00:57:28] Niels

I like your thinking.

[00:57:29] Rob

Week after week, people tune in and listen to people agreeing with each other so I feel like we should put the other side of the story in.

[00:57:36] Niels

I think we should.

[00:57:37] Rob

Yeah, absolutely. Okay, so reasons not to trend follow. Here we go. Controversial. I guess the main reason you wouldn’t necessarily do trend following is that you just don’t believe in it. I think one thing that trend following lacks, personally, is a single compelling narrative as to why it works. We’ve got lots of theories. I’ve got my own personal favorite theories around things like behavioral biases, and Prospect Theory, and you can google all this stuff if you’re interested, and loss aversion and so on and so forth. Other people have theories around when information comes in that people are slow to react and underreact to information and that produces trends.

But yeah, at the end of the day, and this is true of a lot of kind of circled risk premium type strategies, the same is true for things like equity value, the same is true of carry, there’s not a reason why they should work. In the absence of an obvious single compelling reasons as to why something should work, you’re kind of left with empirical evidence. As we’ve discussed right at the start, that’s backward looking.

Something appearing to work in the past doesn’t necessarily mean it’s going to work in the future for a number of different reasons. It could be that your backtest is overfitted for example, it could be that you’ve forgotten to take something into account, and this isn’t so important for trading costs, but things like trading costs, for example, or survivorship bias and all these problems you get with backtests. But the most obvious reason why something could have worked in the past and not future is that things change.

So if it is a behavioral based narrative, you could argue that as more and more investors use systematic methods or indeed are replaced by computers entirely, maybe people will just learn not to have these biases anymore. So yeah, that’s the first potential reason. Niels, I think the way we should do this section is I’m going to say these reasons and I think you should be the defender of trend following and tell me why I’m wrong on each of these points.

[01:00:03] Niels

I think I might have a little surprise for you coming up, Rob, so let’s continue a little while longer.

[01:00:09] Rob

Okay, I’ll bring up my next point then, shall I? It’s a surprise, Niels, that you’re secretly not a trend follower and this whole time you’ve been like a Soviet sleeper agent waiting to…

[01:00:21] Niels

I think I can reveal that’s not the case.

[01:00:23] Rob

Okay. The second reason why you wouldn’t necessarily invest in trend following is on a standalone basis actually, it’s not that compelling an investment. We kind of briefly talked about that. It’s not the kind of Sharpe ratio 1, 1.5, 2 that you can get in certain other types of strategy. One of the reasons for that is those other strategies have other unpleasant attributes in terms of risks. So for example, a solidly negative skew strategy. Option selling, for example, can be a very good strategy looked at in terms of Sharpe ratio, but it has really ugly, sharp drawdowns because of that negative skew profile.

With trend following, you’re kind of, to an extent, paying off some of your return to get some positive skew. It’s just a question of how much you value that positive skew. You can also say, well, it does well when combined with 60/40 because it provides diversification but again, this is a weak empirical result rather than a mathematical certainty like tail hedging. So it’s not guaranteed that you’ll make money in a market crisis with trend following whereas that is guaranteed with a tail hedge strategy, although a pure tail strategy will cost you money.

So a lot of it depends on your preferences around Sharpe, around skew, around tail protection. Trend following kind of sits in the middle on these things. So if you really want tail protection, trend following is probably not for you. You should buy a tail protection fund or just buy out the money puts. If you really want positive skew, then again, there are other assets. There are other types of investments like for example, buying the money puts again is a very positive skewed strategy.

If you really want good solid high Sharpe ratio returns, then you’re better off probably with a negative skewed strategy that has a high Sharpe ratio but really ugly Sharpe drawdowns. Trend following kind of sits in the middle of these. So it comes down to preferences really.

The other thing about trend following is that on an individual asset basis, it really is rubbish. It’s got very low Sharpes on an individual asset basis. It’s only when you diversify across a number of different instruments that you really get the benefit and the Sharpe sort of shoots up to the level where it becomes a sort of attractive investment in its own right.

So, if you want to do your own trend following and if you haven’t got a massive account, and we talked about this before, then trend following is probably not for you as an individual investor. So that means you’re stuck with things like for example trading, doing it but with just single equities and maybe not being able to short. So you’ll get some of the benefits but you’re losing a lot of it because you haven’t got the diversification across asset classes. You can’t short which means you can’t benefit from markets going down.

Alternatively, you can invest in a fund. There are UCITS funds. There are retail friendly funds that do this stuff for small account sizes but they’ve got fees, which means you’ll be net-net a loser compared to if you could do it yourself, of course.

[01:03:45] Niels

Any more left?

[01:03:48] Rob

I could go on all day, Niels. There are so many.

[01:03:50] Niels

I hope you can’t, but anyway, let’s do one more.

[01:03:52] Rob

I’ve only got one more left. Trend following is hard. It’s a very difficult strategy to stick to the discipline that’s required, unless you run it on an automated way like I do. Because you’ve got to sit there and take all those small losses on, and then when the big win comes, kind of hold on to the position and not close it early and take that kind of early profit. So it’s a very emotionally hard strategy to run. This, of course, is again why I think it’ll work. This is inconsistent with my first point because the harder it is, the fewer people are going to be able to do it.

It is interesting actually that the size of the CTA industry, which isn’t exactly the same as trend following, but, as a percentage of total hedge fund assets, has remained at about the same level for probably 25 years. I think that’s a really interesting result. It does indicate there’s kind of a ceiling on the level of how much money people are willing to put into the strategy or how many people there are out there willing to put money into this strategy.

This isn’t a reason not to do trend following, but it’s a reason why you maybe shouldn’t do trend following, which is that it’s really, really difficult. Especially if you trade manually, you need to be sure that you can cope with the psychological knockbacks that come with it. Okay, that’s the case for the prosecution, Niels.

[01:05:26] Niels

Exactly. Of course, we already now have the title for this episode I’m sure, something like why not to trend follow. People will think that we mistyped it.

[01:05:36] Rob

That will generate a few clicks.

[01:05:37] Niels

Exactly. Yeah, absolutely. I think your list is fair, not all of it. I certainly don’t agree with all of it. Before I reveal my little surprise, I will say probably the one I disagree with the most is this thing about the low Sharpe because as we know, we’re having a low Sharpe because a lot of the volatility comes to the upside. So low Sharpe in itself is obviously for a single line item, less meaningful, but that’s not why we’re here today right now. Because I thought when I heard your topic the other day, and I thought, what the hell is he talking about here? There was only one thing I could do and that was to go to Chat GPT and type give me five reasons or give me any reasons why not to trend follow.

[01:06:23] Rob

Brilliant.

[01:06:23] Niels

Yeah. So of course, you probably did the same because Chat GPT and you tend to agree a lot. So let me reveal what our little AI friend thought about it. Of course, it’s very diplomatic, it’s very well trained. “While systematic trend following can be a valuable investment strategy for many investors, there are maybe several reasons why some investors may choose not to allocate a portion of their portfolio to this strategy. Here are five potential reasons.” Okay.

So the first one it lists as risk tolerance. It says, “It can be highly volatile and may not be appropriate for investors with a low-risk tolerance seeking stable returns.” I think that’s a fair point actually. Good on you, Chat GPT. The other one I didn’t kind of agree with, it headlines it as diversification and it talks about, “While systematic trend following can offer diversification benefits to a portfolio, it may not be the most effective way to achieve diversification depending on an investor’s existing portfolio composition.” I guess that’s true. Although I will say it does seem to have a pretty good diversifying effect on most portfolios, but fair enough. We’ll let that slide.

Then something you also mentioned, and I think it is important should be mentioned is, “fees, that some systematic trend following programs can be expensive with high management fees and trading costs, which may reduce their attractiveness to investors who focus on minimizing expenses.” I can’t really argue with that, because of course, you should always be concerned about fees and you should never invest in a fund that has excessive fees anyways regardless of what it is doing.

The fourth reason is investor preference, it lists. “Some investors may prefer other investment strategies such as buy and hold or value investing, or may have ethical or personal reasons for avoiding certain types of investment.” Okay, you can’t really argue with that either as such. The one thing where you certainly agreed was your first point, it’s number five on the Chat GPT list, and that is just,”Lack of conviction that some investors may not fully be convinced of its effectiveness and benefits and may prefer to ask to allocate their assets to other types of investment strategies that they perceive to be more reliable or better aligned with their investment goals.” So I think you were kind of in agreement with our little AI friend.

[01:09:09] Rob

One thing as I listen to that list, frankly, that’s a very generic list of points you can make about any investment strategy. I’m not sure whether that reflects badly on me or well on Chat GPT. If this is a competition with me in Chat GPT, I really hope that you’ll say it’s clear from my answers that I know a hell of a lot more about trend following the Chat GPT does, which is just jotted out some engineered notes.

[01:09:37] Niels

I think we can say that is affirmative.

[01:09:39] Rob

Thank goodness, because I’m now starting to get very concerned about my position on this podcast, Niels. I’ll be honest with you.

[01:09:45] Niels

After you brought up this topic about why not to trend follow, maybe you shouldn be a little bit concerned. There we are, Rob.

Anyways, you’ll be back in a few weeks and I’m sure there will be no talk about why not to trend follow. In fact, there will be lots of good topics as usual, lots of education, lots of value and that’s why you are indeed very popular every time you come on. So with that, Rob, thanks for the flexibility because as you rightly say, I’m about to jump on a plane to Asia so I appreciate you coming on early today and I appreciate everyone listening to our conversation today.

If you enjoy them, please go to toptradersunplugged.com/review if you don’t know already how to leave a rating and review on any of the podcast platforms because they do really help. You can of course send questions to info@toptraders unplugged.com. You might even start thinking about questions for Rob in a few weeks. Next week, I am joined by Andrew who was meant to come last week but unfortunately, couldn’t make it. So this will be an interesting conversation. There’s been quite a few articles out about replication of CTAs managed futures.

Rich and I talked last week about whether there was a decoupling between what Andrew is doing in his fund replication of the SocGen CTA index and the CTA index itself. We’ll hear his opinions. We can talk about flows, how investors are reacting and so on and so forth. So lots of great and interesting topics coming up next week, provided of course, I can get the technology to work all the way out from Asia, which I’m sure will not be a problem.

Anyways, thank you so much for listening. From Rob and me, we look forward to being back with you next week. In the meantime, as usual, take care of yourself and take care of each other.

[01:11:39] Ending

Thanks for listening to the Systematic Investor podcast series. If you enjoyed this series, go on over to iTunes and leave an honest rating and review and be sure to listen to all the other episodes from Top Traders Unplugged. If you have questions about systematic investing, send us an email with the word “question” in the subject line to info@toptradersunplugged.com, and we’ll try to get it on the show.

Remember, all the discussion that we 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 products before you make investment decisions.

Thanks for spending some of your valuable time with us and we’ll see you on the next episode of the Systematic Investor.