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Welcome and welcome back to this week's edition of the Systematic Investor series with Rob Carver and I, Nils Castor Larsen, where each week we take the polls of the global market through the lens of a rules based investor.

Rob, it is wonderful to have you back this week.

Hope you're doing well.

How are things in the uk?

Is summer finally there?

Summer is finally here.

The sun is shining.

England won their first football game last night.

I'm not an especially big follower of the football or a huge football fan, but it's the World cup so I guess I should at least pretend to take an interest.

So, yeah, there's a general mood of optimism in the country at the moment.

You know, having lived in, in the UK for many years, I always remember every time there was like some kind of European cup or World cup, it's always this strong belief that this time it's coming home.

Right.

We're still, we're still waiting 60 years on.

You know, I do statistical analysis for a living and I'd say the odds are not great, to be honest.

We'll see.

I have a feeling we might talk a little bit more about this in a second.

But anyways, I just wanted to say we've got a wonderful lineup of topics today.

Probably more than we expected because I didn't see all of the ones you had sent me.

We also have a question that we'll be tackling today.

So, yeah, strap in and you know, hopefully it'll be a fun and educational one.

Anyways, before we get into all of that, as usual, I will ask you what's been, wouldn't say keeping you busy necessarily, but what's kind of come across your desk that you found interesting?

I mean, there's, there's been a lot going on the last week, couple of weeks, obviously.

We hopefully have some kind of peace deal in the Middle east which the terms and conditions of which are being debated as to whether it's a good deal on, on both sides or very weighted towards one side, whether it's better the deal that they had before.

But we'll leave that to one side.

So that does mean, I guess, that hopefully there'll be some crude flowing out the Straits of Hummus, and that will then have an impact on markets.

Although it does feel like markets have been pricing that optimistic scenario for a while yet.

So we'll see.

I guess the other thing in markets that's kind of interesting has been the SpaceX.

Oh, yeah.

And in particular there's been some debate about whether SpaceX should be allowed into the index club because these indices have quite strict rules.

And we'll touch on that, actually, later in the talk today, because I think we're going to have a talk about indexing in the CTA space.

But in the olden days, you couldn't get into an index unless you were profitable and they made adjustments for things like the free float of your shares.

So, for example, Tesla wasn't in the S&P 500 for quite a while, even though it was a big enough company because it just wasn't profitable.

But in their desperate urge to get SpaceX into their indices, most index companies, apart from S and P, in fact, who have held out have torn up the rules and they're like, open the door and please come in.

And yeah, I'm not sure it's an entirely responsible move.

I'm not a fan of SpaceX, not a fan of the man that runs it, and we shall see how that works out.

And then I guess, finally, the other thing we must mention, I suppose, is that the change at the top of the Fed has finally happened and there is now a new chairman.

But with the current inflation environment, there doesn't seem to be much appetite for cutting rates.

So maybe we won't see the true colors of that gentleman just yet.

So, yeah, been busy, actually.

I mean, all of those points could have been on my list and they probably were until I realized they were on.

No, no, that's fine, but just maybe to add a few comments to it.

So, yeah, actually, you know, let's start in reverse.

Kevin Walsh is now, you know, had his first meeting as FOMC chair, and you're absolutely right.

Kind of interesting that the tone was a lot more hawkish than what he has been, you know, saying before getting the job, so to speak.

No surprise in terms of some of the things he had mentioned in the press conference about shrinking the balance sheet and so on and so forth.

But maybe something I was thinking of, he does mention that he wants to kind of revamp the way the Fed communicates.

And for example, forward guidance is not a business that the Fed should be in according to him.

But then there was something else and that was this thing about reworking kind of the data the central bank releases as far as I can tell and maybe getting rid of some of the old fashioned survey methods.

And, and I was kind of thinking, when I, when I saw that I thought kind of interesting because we do have strategies in our world that has come more recently that are economic trend or we have systematic global macro.

Now they do rely on this kind of data as far as I can tell.

And so I thought it could be interesting to see if, if they are affected in some ways if suddenly you don't have access to, to this kind of information.

Of course for the pure price based trend followers we don't care.

But I don't know any, any thoughts?

Yeah, I mean I find it quite disappointing to be honest because there's already been quite a serious degradation of the quality of statistical data in the US partly as a result of the, the Doge cuts frankly.

I know we're not, we're trying to avoid politics but you know they, that's one of the departments.

One of the effects of those kind of fairly indiscriminate cuts to government spending also a sort of culture of secrecy and sort of lack of transparency which I find really worrying.

But also what really didn't help was the government shutdown last year because that, that resulted in a lot of statistics being late or delayed or not collected at all for quite some time.

So as with my sort of economist hat on, it really worries me.

I mean there's been a debate in the UK as well about the quality of government statistics.

You know, if you're trying to run the country and you're looking at your economic indicators and they suddenly go blank, well that's like a pilot flying with, you know, in his instru disappear.

And for us it's kind of a problem if, yeah, if you're using those indicators to sort of as inputs into any kind of process to you know, forecast prices.

I mean there are third party services.

In fact this was one run by a good friend of mine.

I won't mention the company because I don't want to advertise but said if you're listening, thumbs up to you.

So there are third party services that collect data and kind of forecast what the government statistics will be if you like and that will work if that raw data is still out there.

And in this area of big data and AI maybe arguably the need for that sort of old fashioned statistic is Gone.

But I'm of the general belief that more data is always better.

And deliberately getting rid of data or collecting data strikes me as potentially dangerous, both for the economy and also quite irritating.

If.

Sure, if you're trading on it.

Now you did mention the football, so let me just add a little comment to that, Rob.

First of all, full disclosure, I did not watch England play Croatia last night.

But you know what to me was the most surprising thing about the game.

And I have a feeling you may have watched it.

You're completely quiet.

People watching on YouTube will know this is my poker face.

Okay?

So I wasn't surprised by the result.

I was surprised that there was not a single yellow card given out during the game because usually those teams are, you know, they go at it.

So anyways, the most fun comment I saw, not about that game, but about the first round of games was the Turkish commentator who has been suspended because he, he, he mistook the two teams he was commenting on and that was Iran and New Zealand.

He switched the teams and he switched for four whole minutes, basically referring to them as the opposite team and opposite players.

I thought that was kind of funny.

But anyways, probably not.

We've all made mistakes.

Made mistakes, absolutely.

I mean, I sometimes get my kids names mixed up so you know.

Okay, I wouldn't want to make that mistake.

Okay.

All right.

Okay.

So let's move on to a quick trend following update here.

My trend barometer finished at 36 yesterday, so it's weak for sure.

And I think that kind of ties in with what we see in the numbers so far in June.

If I just from my vantage point see where there might be a little bit of headwind at the moment.

You know, clearly some of the equity markets have been somewhat weaker.

We've also seen some of the precious metals or the metals markets, I should say, I'm not entirely sure.

It could be aluminum that I'm thinking of here that's been a little bit weaker.

And also some of the grains has been.

What seems to work right now is perhaps some of the short rates in particular after the hawkish stance from the Fed because I think CTA generally have a, a short stance on the, in terms of exposure and then actually some of the currencies could have worked out well.

And I see the dollar has gotten a little bit of new wind under its wings more recently.

Any observations from your point of view in terms of markets from a trend following viewpoint?

Yeah, I mean, I'm just, just having a quick look at my, my sort of performance and Risk and numbers and you know it's fairly, the last few weeks have been a little bit positive which is nice.

Not quite up to the levels I was at earlier in the year.

And in terms of the sort of risk I'm running, yeah, quite low.

So 9% analyzed risk which kind of equates to your trend barometer numbers I suppose.

The biggest risk I have actually is in equities.

I've got a long equity position and that I guess is pro deal if you like.

Although actually, and I'm actually flat in energies and oil and gas so there's you know, I'm not really positioned for, for anything going on there I would say.

So yeah, it does feel very much like the world is still waiting.

You know both, both if we just look at the quantitative numbers but also kind of just assess the feeling in the markets, you know, this deal's on the table but it's been priced in probably anyway.

So maybe this is one of those classic cases of you know, buy the rumor, sell the sell the fact.

And then now, you know, now it's actually happened.

People will say well okay, is this really as good news as we hope it is or is it still going to be a long time before the things normalize and there'll be supply shortages of oil and potential kind of knock on economic effects to that.

Yeah, yeah, very true.

I mean looking at kind of the portfolio of markets that tend to resemble I think most of the liquid markets that CTAs trade I think the big market move so far in June has really been in the oil complex where we've seen kind of 15% drops in price.

But you know, even some of the precious metals market silver was down 9% so far.

This month's platinum also down about 9%.

But you know, to offset that as you pointed out, equities 7% up so far in June for the Nikkei, at least on the futures contract.

So not a bad start to June if you're long that market.

Yeah, that's actually my biggest long.

So yeah, okay.

Yeah, yeah, I think performance wise.

I'll run through it now as usual.

I think yesterday was a mildly positive day for CTAs.

But you know, again probably not, not, not much of a of a day so to speak.

But anyways, the beta 50 index as of Tuesday is down 85 basis points for the month, up 8.76% so far this this year sucgen CTA index down 81 basis points for the month, up 9 and a half ish for the year.

Suction trend down a bit more one and a quarter, but up 9% for the year.

And the Short Term Traders Index down only a quarter percent and still up 5% so far this year in the traditional world.

MSCI world is down about 1% for the month as of last night, still up 9 and change for the year.

The US Aggregate Bond Index is pretty flat in June, down slightly and up pretty very modestly I should say half a percent so far this year.

And the S&P 500, despite all the excitement around SpaceX, it didn't lift the index.

Of course, it's not part of the index, but it's down 2% so far this month and up 9% so far this year.

Now I did mention, I think that we have one question that came in from Ghana to you came in a couple of days ago and Ghana writes, when deciding whether to add size or remove a strategy, how do you balance Sharpe against path risk like drawdown depth, drawdown duration, loss, clustering, and whether losses happen when the rest of the portfolio is also losing?

Love the show.

I look forward to every episode and listen as soon as they drop.

Now obviously that line had to be included and we're very grateful for that.

Garner, thanks so much.

But over to you, Rob, on the question.

So this is essentially a question about portfolio optimization.

So one thing I should say up front is that I rarely drop a strategy, as I'd only do so if there was very strong statistical evidence that it stopped working.

And actually, I'm currently in the midst of writing a whole bunch of research about optimization.

And the blog post I was literally working on this morning before starting this podcast is actually about finding structural breaks, which is a fancy way of saying working out systematically if X or Y is no longer working.

So to get into the sort of meat of the question, the answer is, to be honest, I tend not to look at much beyond sharp.

Well, so let's take drawdowns, for example, Drawdown depth and draw duration.

And actually, we're going to be talking later in the pod about a nice paper from Mangrove about drawdowns, but I'm not a big fan of drawdowns as a sort of statistic for evaluating performance.

You know, generally speaking, if you sort of ignore autocorrelation effects, then your drawdown is going to scale with the performance of your strategy and how long you've been running it for.

So you know, the more history you have, the bigger drawdown will be.

The better a strategy is.

The higher its Sharpe ratio, the smaller the drawdown will be.

So you know, I don't think including the drawdown really has any meaningful information.

And you know, I just, I'm a big fan of keeping things simple and things looking at things like path risk and loss clustering and stuff like that.

Maybe that's interesting and useful at sort of the whole portfolio level.

But to sort of get into that on every individual component of your strategy for me feels like really overcomplicating things and sort of, you know, potentially even going down the route of overfitting as well.

So the answer is no, I don't really look at that in the sense of using it to decide how much risk I should allocated to a given sort of component of my overall strategy.

Is there anything like one thing, like kind of your favorite thing you look at when you, if you want to say add a, or remove part of your strategy.

I'm, I'm referring to different strategies.

I may, you, you may have built it as one and you don't really look at it, it's as separate components.

But let's just say in many instances, actually managers probably have a few different types of trend following perhaps or types of strategies inside the overall program.

And if you were in their shoes and you had to kind of pick one, go to thing to look at, to evaluate, would that be anything that springs to mind?

I mean, probably skew to be honest.

Because obviously I think that the issue becomes more when you're combining trend following with other things like carry, because, you know, virtually every CTO out there is not a pure trend follower.

Yeah, they'll have, you know, a 20 or a 30% allocation to what you might call divergent strategies, sorry, convergence strategies which aren't trend following.

My own allocation to Those is a 40% which is higher than CTAs because I don't have an end client pool to worry about.

I don't have to fit into a, you know, an allocator's box.

I can do what I think will give me the best performance.

So, you know, it could be quite useful to look at, to use skew as a proxy for deciding which of those two buckets something could sit in.

Because actually it's not always obvious.

So, you know, there are very obviously sort of negative skewed strategies.

Things like for example, if you had a systematic short volume strategy or any volume trading strategy which has a bias towards being short volume, that's going to have negative skew, you know, so that's fairly clear and obvious.

But you know, does Carry have negative skew?

Well, actually it depends on the asset class.

So carry in emerging markets, FX definitely has negative skew.

Carry in developed government bonds has actually mildly positive skew.

So it's not necessarily obvious which of those two buckets things should sit inside.

So that's the only one I'd sort of bring in.

But even then I wouldn't use that formally.

I wouldn't have like a, what economists would call a utility function that combines say the skew and the Sharpe ratio to come up with a single metric as to how much a strategy should have.

But, but I might use a classification mechanism to say, well, you know, I want to limit say 30% of my portfolio to negative skew strategies and no more.

Therefore I'm going to just categorize things and then do my allocation within that side.

I'd use it in that way.

You know, again you get into issues around statistical robustness around skew estimates, which is not a conversation to have today.

But it does mean I'm wary of using skew in of itself in sort of very constitutive way as a mechanism, in the same way I've already said I'm wary of using drawdown for the same reason.

Fair enough.

Good stuff.

All right, let's move on.

So the first thing we're going to do is we're going to kind of talk briefly about two papers that you sent to me that I completely missed and therefore I don't know what's in them, but I do know where they came from.

And the first one came from an article in Alpha Architect, it's called the Factor Zoo, has hundreds of animals but only a handful of species.

So over to you.

Yeah, so for those who don't know this, and anyone who's listened to me talk for more than about 10 seconds will know it because it's one of the first things I usually talk about.

A factor, you can call it a risk factor or a return factor, essentially is a sort of source of return.

So you know, classically in the equities world you had so called value factors and they were based on simple things like price book ratios and dividend yields and price earnings ratios.

And then the factor universe expanded and they brought in things like momentum, which is different from trend following because it's a relative factor, not an absolute factor, and quality and so on and so forth.

And then, you know, people like AQR started talking about macro factors.

And then we, you know, we, in our own universe we could think of say trend following and carry as factors themselves as well.

So essentially there's all these explanations for, for, you know, for where returns come from.

And you know, if you're an academic, you view these as risk factors and you say well, these explain why you're earning so much money because you're exposed to all these risks.

And if you're a practitioner, you just say, well just give me the money, then I'm happy to be, you know, I'm just, just, just, you know.

And they call this sort of earning a risk premium, if you like.

So there are lots and lots of these things and some of them are very correlated.

And, and the, the exercise that they've done in this nice little paper that's been linked to, in the, in the Alpha Architect website is, is essentially as a classifying group and, and sort of say, well actually if you look at this vast universe of factors, there's actually only a few that really explain, explain what's going on.

And you know, it's an interesting piece.

You could argue it's perhaps of.

Only of purely theoretical value.

But actually, you know, one of the conversations we have a lot is about diversification and you know, the more that these sort of, the, the fewer kind of real things that are driving the world, the less help diversification is going to be for you.

So it is a useful and interesting thing for, for someone to think about, even though you may think it's only a kind of, you know, purely an intellectual debate in one sense.

Sure.

No, excellent, good stuff.

And the other article or post I should say that, that you send over is from a substack beyond passive investing.

It's to.

With trend following.

Trend following actually adds to a risk premia or what trend following actually adds to a risk premier core.

Not entirely sure if there's a name of who wrote this, but that's a very good question.

I'm just clicking through.

It's fine.

I think we referenced someone.

All I can tell you is it's someone who's got a physics PhD, but, but it doesn't look like they're sort of outing themselves if you like.

So I would imagine it's someone who works in the industry, in the quant industry and doesn't want everyone to know.

That's fine.

Which is fair enough.

It's a very nice substack and it's a very nice series of posts actually they're doing about, about trend following specifically.

This is actually the, the third in a, in a series of, of four posts that they're doing.

So it's well worth looking at the whole series.

I'm just picking on this one, because it came out quite recently.

So one thing, the sort of source of this post really is this fact.

If you say trend follow equities, you will be on average net long equities because equities tend to go up.

So that means that again, putting my economist hat on, you can kind of say that, well, actually a big source of your returns is your exposure to equity, the equity risk premium, getting back to his idea of factors and premia.

And then you'll be earning some additional return above and beyond that due to the fact that you're, you're trend following.

Because you're trend following sometimes you'll, you'll actually be short the market when it's, you know, going down, hopefully, fingers crossed.

And therefore you're earning some extra return during those periods when you know and, and when the, the market isn't just, just going up and you're just being long the market.

So that means that.

We talked about this before on the podcast.

When you think about how you're designing your trend following portfolio, you need to ask yourself what your actual end goal is.

So if you're, if all of your money is in a single portfolio of trend following and you've got no money doing anything else anywhere else, then absolutely this is a good thing.

Because if you believe there's an equity risk premium, and most people seem to believe there is, then absolutely it's good to have a portfolio that's got some exposure to that and you can earn that as a source of return.

However, if your trend following portfolio is say 20% of a bigger portfolio and that bigger portfolio is say 60, 40 mixture of equities and bonds, then you're already earning the equity risk premium in spades elsewhere in your portfolio.

So you could say, well, maybe what I should do is sort of, sort of change, modify, tweak, adjust by trend following portfolio so that it has more of a kind of a neutral character.

So what that would mean in practice is rather than being long the market when it's going up, you'd probably be only long the market when it's going up a lot.

And that would bring down your average exposure to equities, your average beta.

And the same would apply in bonds, obviously in any other asset classes you're trading to a lower level or even to zero.

So that's the topic and we've talked about it before and I just thought it was worth mentioning this paper because it kind of, I'm certainly not going to go into in detail.

It's quite a complex paper and quite detailed, but it does give another interesting twist on that particular idea.

So it really caught my attention because that, that's something we talked about in the podcast before a length.

As I mentioned, I haven't read the paper so I should be very cautious in saying something, although I will just say I'm not a big fan of these people who say, oh, you need to adjust your trend following strategy because it's going to fit with something else you have in your portfolio.

I think if you feel you have too much equity, you sell the equity, you let the trend following program run because at least for many people, the, the, the interaction with other markets in the portfolio will be affected if you start reducing certain sectors artificially.

So that, that's just my gut feel.

But, and before you jump in, I can see you're almost jumping out of your chair here.

But the other thing, and this is just from quickly, quickly looking at the, a conclusion where it says what trends ads.

Precisely.

And the one thing I can see is that it says that it, it adds the market, you don't trade yourself.

And I think that's a great point actually because we know that there are so many wonderful markets that you can, that you can trade but most people find them difficult to access or risky and they've, you know.

So actually I think that's probably one of the key contributions in addition, of course, to also being usually unbiased whether to be long or short.

And again, if there is a prolonged crisis, why wouldn't you want to be, you know, fully short equities, for example, whatever.

Anyways, yeah, you can't contain yourself anymore.

Yeah, I guess that's an argument for sort of, you know, not necessarily changing your strategy, but tilting your sector allocation within your CTA away from financials that most people already have exposure to and towards things like commodities.

And actually again, looking forward, one of the papers we'll talk about today gets into that.

I do agree with that.

I do agree with it.

Having a large allocation commodities.

I think what we've got to bear in mind, Niels, is for most people the choice isn't between say having 60, 40, you know, most people don't have that option necessarily or for whatever reason of reducing their equity allocation and putting more into the CTA and getting the risk premium that way.

You know, if you are limited in what you can put into the CTA sleeve, if it's only say a 20% allocation or even a 5% allocation, then at least from a theoretical perspective it does make sense to try and you know, you'll get a better portfolio Overall if that 5 or 10 or 15 or 20% has less exposure overall to equities and bonds than otherwise.

But I agree the best thing to do, if you can, is to increase, is not to do that, but then to have more in the CTA bucket.

But as I said that unfortunately that's not always an option.

Yeah, I mean, just one final comment here.

If you only have 5% to trend, I don't think you would need to worry about the equity allocation within that trend, honestly.

But there we are.

I will leave it at that because we need to move on very conveniently to something that caught my attention and that you and I agreed that we should just maybe touch on, and that is that the CFTC, which is the regulator for all CTAs and CPOs in the US and even outside the US, if you're in this business, you're probably most likely registered with the cftc, they just came out this week and they approved, or maybe it was last month.

It could have been last month they approved what we could refer to as a perpetual futures contract.

So what is that?

Well, first of all, it's the first of its kind and secondly, it's.

It's basically a futures contract that unlike every futures contract so far that has an expiration date, has no expiration date.

So that makes it very different.

Do you have any thoughts on this?

And I should say maybe that the first one they've approved is linked to crypto.

Of course, of course.

Because this is the, you know that this is where this idea came from.

Right?

I mean, of course, actually, in fairness, the idea has been around for a long time, longer than crypto has, but the first place it's been implemented in any science is in the crypto universe.

But you are a crypto advisor, as far as I remember.

I mean, I am, I hasten to say, I'm not a crypto expert though, but yeah, yeah.

So perpetual futures are very interesting.

So let's start with a normal future.

So I just rolled some futures today because it's kind of mid June and a lot of futures are expiring because they expire on IMM date.

So we just had an IMM date.

So I'm rolling from say June to September.

So, you know, you've got futures that say a quarterly and you know, that means every three months, if you like, the bet settles Right.

So that the bet I've made through an exchange with somebody who's on the other side of that bet, at that point we settle that bet and let's keep it simple and assume it's a cash settled future.

So at that point we look at the prices and we see, you know, who was right, who did the thing go up or down, and we, and we sort of settle our bets.

So that's kind of, sort of in a simple, very simple way, the way that features work.

Now, of course, they don't actually work like that because of this thing called margin, a variation margin specifically.

So what that means in practice is that if you and I made a bet about, say, the price of bitcoin and I believed it would go up and you believed it would go down, then what would actually happen every single day is that the, you know, so let's assume we're doing this through the CME rather than through a weird crypto exchange.

We're betting on the sort of standard bitcoin future, which I think is monthly but not quarterly.

But let's ignore that for a second.

So even though the, the future doesn't expire for a few months, in practice, if the price goes up, I, you would have to pay me some money every day that actually goes via the exchange.

You don't sort of send me a check directly and, and, and vice versa.

And that, that sort of variation margin, that, that's how, that protects us from the fact that we don't want to get into a situation where the future is expiring and I've won and you've lost, and you suddenly turn around and say, well, actually, Rob, I'm not going to pay you.

Tough.

You know, there's not enough money in my brokerage account to cover it.

So that's what variation margin does.

Now, I want you to imagine the same bet, but let's compress the timescale.

So instead of doing it every three months, we're going to do that, we're going to bring the expiry of the bet down to one, one day.

So the future now no longer is in three months away, it's in one day.

So what that means is that rather than kind of quote unquote, settling our little bet every few months, we're going to settle our bet every single day.

So every single day we'll look at the price and we'll do the sort of bet settling.

And this means that the margin payment, rather than being a kind of gradual flow over the period of settling of the bet is a thing that just happens once every time the bet settled.

So although these are called perpetual futures, what they really are in the sense is daily futures, the futures that settle effectively every single day.

And in fact if you look at sort of thing about cash flow, it's going to be identical to the cash flow variation margin and the sort of two fundamental important differences are whereas with the kind of quarterly bets every few months I need to decide if I want to continue having that bet.

If I do, I need to make a new bet starting for the next expiry.

Same thing on the other side because it's a perpetual future, it's always on.

So basically, unless you say something otherwise to the contrary, when that daily bet settles, a new daily bet will be opened up automatically for the following day.

And the important key thing about that is whereas at the moment there can be a big difference between the price of the future and the spot of the underlying thing, with these perpetual futures, O2 things will always be the same, basically pretty under some kind of hand waving, no arbitrage argument.

Essentially every time the bet settles, which could be daily or could even be more frequently than daily, the prices must be identical in the same way that when a normal future expires, it will expire at or settle at the cash price.

That's the technical side.

Yeah.

Can I ask questions or we can move on to discuss why.

Just a question before we do that.

And I'm not an expert in the all the mechanics and the pricing of futures in terms of the theory here, but if I'm not mistaken.

I'm sure you are.

If I'm not mistaken, for example, interest rates play a role in the pricing of a futures contract.

And so in a sense you can think about the perpetual one as being oh, so how do I do this with the interest?

How does that, you know, what, what do I use?

But are you suggesting that because it's looked upon as a daily future settlement that maybe that is not an issue?

To get very technical, you the, the interest will be in there, but it's going to be such a tiny, tiny component, it'll probably be.

You can pretty much ignore it.

There may be scope for very, very smart people to do some kind of, you know, arbitrage.

Arbitrage and I guess if you're market making this stuff, you probably, you might have that in your model.

But to all intents and purposes you can pretty much ignore, ignore that in the same way you cannot all the other factors that affect the difference in futures and spot like you know, for equities, the dividend yield for bonds, the, you know, the yield on the, on the sort of cheapest to deliver bond for commodities, you know, the storage costs, the insurance costs and so on and so forth.

You know, to all intents and purposes the futures price will equal the spot price.

And that's the sim, that's a simplification for people who don't, for whatever reason, you know.

Well, so as to why you would do this.

Well, you know, so I.

There is actually a corner of the financial world where something similar already happens and I'm going to be in a preface this with a lot of legal stuff because it's in spread bets and contracts are different which are not legal in a lot of jurisdictions.

They are in the UK but are not in the US and a lot of other places.

So everything I'm about to say now is certainly not financial advice if you don't live in a jurisdiction where those are legal.

But in the spread betting in CFD world you have the option of trading what's called a dated bet, which is basically like your future and actually the spread bet provider will hedge their own exposure with futures.

Or you have the option of doing what's called a daily bet, which settles every single day.

And that's going to look a lot like the sort of cash flow future.

And the reason why people would do the daily bet is well for starters, a lot of the people, the customers of these firms, for good reasons or bad, and I believe it's bad reasons in most cases they aren't keeping bets open overnight, they're closing them during the day, they're day trading.

And if you're day trading it's cheaper to do it with a bet that closes today because you don't have to worry about overnight funding costs which because these brokers are not peer to peer, they charging massive spreads basically and it's a very expensive way of doing things.

Whereas of course if it's done through an exchange then it's effectively a peer to peer trade.

So the only spread you pay is difference in bid and ask.

So it's a bit of a nice environment.

So I think it's a com.

A, you know, it's, it sort of simplifies things.

But also frankly, if you're someone who's trading, you know, multiple times a day then it's, it's an easier sort of, sort of structure and way to work out yourself and you don't need to worry about rolling, you know.

Well, that brings me to the next point.

And that is clearly if, if, if this became the thing that many more and the types of futures that we would trade become perpetual futures.

Clearly that has some massive implications for firms involved in the futures industry that rely on volume because I imagine the volume would go down significantly.

There would be no roles, for example.

And so not surprising the CME Group and maybe other futures exchanges are not too happy about it.

So they have essentially, as I picked up this morning yesterday, sued the CFTC over this decision to approve a perpetual futures in the US And I'm not going to get into the technicals, but they apparently argue that this should be classified as a swap.

So there's an important point here which is to ask ourselves, well, why do futures exist originally?

Well, originally they existed.

I mean it's the first futures were in the commodity markets.

They originally started in the commodities markets because they were there purely initially as a hedging instrument.

And if you're a farmer hedging your crop, well, you absolutely want a dated future.

You don't necessarily want a perpetual future.

It's not necessarily a lot of good for you.

Now I do appreciate that the vast majority of trading in, even in commodity markets is not of, you know, is not done by hedges or by physical producers and is, or physical consumers as well.

It is done by, you know, by speculators, people like us, if you like.

But you know, it's still, you know, there's still an argument to be made that there has to be some kind of real price discovery going in on in the market.

And for that to happen there needs to be a place for producers and consumers of the underlying commodities to go to hedge their exposure.

And you know, where, I don't know where that's going to go.

I mean, will it go to, we talk about swaps briefly.

Will it go to, you know, will it start going to banks and doing OTC swaps instead?

You know, that would be not great for spreads in either market because there'll be, you know, the capacity and the liquidity will be split Apart.

So although as a person who trades futures and has to go through a painful process, you know, every few days of checking whether I need to roll stuff and rolling it and that's a lot of code I wouldn't need, I think sort of for the futures market generally.

I'm not sure it's a great development, to be honest.

I wonder if it's all going to end up with these massive market maker houses, quasi hedge funds or whatever we call them, platforms, who seem to have been taking on a lot of volume in many areas of finance.

But we'll leave that for that.

You know, I was thinking while you were talking about this thing about farmers, maybe it starts in crypto because there are no more of these yield farmers.

Didn't you have yield farmers back in the early days of crypto?

20% Risk free and all of that good stuff.

They're gone, I think now.

So now we can have perpetual futures.

Okay, let's make move on to some something very important because every time our friends over at Quantica publishes the paper, we pay attention.

And the Q1 paper came out very recently, only to sword this morning.

It's called Chasing Trends or Chasing Performance and is of course a very appropriate topic.

And as usual they've done a good job in writing about it.

Could I ask you to talk a little bit about some of the things that they address in the paper?

People should go and read it themselves, but we will address some of the key topics because I do think it's something that a lot of people, I would say a lot, some people think about this idea of maybe we should just trade the trends that are the strongest or whatever best performing market.

Let's leave Coco out because it didn't perform for 15 years and bang, you miss the biggest trend it's ever had.

Things like that.

Yeah.

There's sort of two ways I think you could think about, let's say dynamically changing allocations.

You can talk about it over time.

So I've done research and other people have done research on, for example, whether you should get out of trend following or get into trend following after drawdowns.

Winton did some piece on it a few years ago, it was quite, quite, quite interesting.

My conclusion is probably not.

And the reason is that the sort of pattern of, you know, to get 10 mill per second, the autocorrelation returns is not statistically strong enough to suggest that you would generally get either very good returns after a, you know, prolonged drawdown or very bad returns, you know, so the drawdowns persist or do they continue essentially?

Now that's.

By the way, there is an important caveat there, which is if you are paying performance fees, then you absolutely want to invest in a, in a fund when it's in a drawdown because you'll, you'll get the first bunch of returns for free, essentially without performance.

I have to correct you here.

Okay.

Necessarily, not necessarily.

If you get your own individual share class, I just want to make sure then you get your own individual high watermark.

So just be careful.

That's not.

Okay.

Yeah, yeah, yeah.

Okay.

Thank you for correcting me there.

So it may be, you know, in a specific case it may be beneficial.

But otherwise, if you are still, you know, if the performance fees are linked to your share class, as you say, then we're back to the original statement,.

Which is, yeah, if it's linked to the nav of the share class, it's different.

You can get a free ride.

You're right.

Yeah.

Okay.

Now and the other way.

So that's sort of time based predictability and the other is sort of cross sectional predictability.

So can we say that particular instruments or particular asset classes will trend better than other assets or instruments?

And you know, for example, Yoav and myself have had some debates about, about that subject because, you know, he has a fixed income only fund and he, he's a big fan of fixed income.

Given that we both used to be head of fixed income at ahl, although not at the same time, we weren't co heads and that's not really a surprise.

But you know, that's, that's another kind of interesting debate.

Now what's interesting about the Quantica paper is it takes both of those dimensions simultaneously.

So what it says is say, well, if we look at the performance of trend following in different asset classes over time, we see some very interesting patterns.

So if you look at the last 30, not quite the last 30 years, but basically the first decade of the century, the second decade of the century, and then the seven years since then, which sort of actually, interestingly is not too dissimilar from my own career in the industry.

It sort of spans similar periods.

So in that first decade, about a third of the performance comes from equities, about a third comes from currencies, and about a third comes from commodities.

Fixed income actually detracts slightly in that first 10 year period.

And I note that that is also the period in which I was head of fixed income for ahl, followed by the period in which you have for.

So maybe, you know, is this correlation or causation?

I couldn't say.

Anyway, so we were lucky in our timing there and commodities and currencies detracted and equities provided almost nothing.

And we talked about cocoa, but it's not just Coco.

I mean the last time we spoke or the time before we were talking about, about silver I think it was obviously we've been talking about crude oil.

So it's very much been.

Not about the financial assets.

So going back to the conversation we were just having, you know, the last seven years, if there were, if the commodities futures market ceased to exist, that would have been a very, very sad thing indeed.

Anyway, so what they say is, well, these patterns are very interesting and I think if you're a quant, whenever you see an interesting pattern, your immediate thought is, well, you know, for two things really.

First of all, is there a reason why this is happening?

Are there different explanations for why this is happening?

And secondly, can I exploit this apparent predictability in some way?

So could I say, well, you know what, it looks like we're currently in a phase or a regime where commodities are doing really well.

Can I shift my portfolio away from fixed income and equities that are kind of sad at the moment and instead put them into other buckets?

So that's basically what the paper is about.

It's a long paper, it's a detailed paper, it's from Quantico, they never do anything by halves.

There's a page full of equations, this lovely graphs.

So I'm not going to go through the sort of results in a lot of detail, but I am going to sort of point to a couple of interesting results.

So one, the first thing to say is that whenever you see good performance, there's kind of broadly speaking, two possible explanations for it.

One is that you've got good diversification, so you've got a lot of things doing reasonably well.

And the other is, and this goes back to our early discussion about the risk factor paper.

The other thing is that the whole you haven't got good Diversification, but everything is doing well.

So it's not just that you've got one or two markets all moving the same direction.

Everything's moving in the same direction.

It's not a diversification story.

It's basically if it's fixed income, then the Fed's just cut interest rates very predictably.

They've gone down to zero and we've made a lot of money in that period followed by rates rising again in a very predictable way.

It's just been beautiful.

So it's not been that you've got done well by being exposed to, you know, random things like Korean bonds or, or Swiss bonds or anything like that.

It's just a big one picture story.

So they look at this in detail and they find that the, in these periods when one asset class is dominating, it's very much about a sort of single factor that's driving everything.

It's not a diversification story.

It, you know, it's, it's the fact that you're getting in fact less correlation.

But it just so happens that everything's moving up.

So it's wonderful.

And now that, that means that, that you know, you, if you're someone who like me, likes to allocate your portfolio in the most diversified way possible.

Well actually this is bad news because you know, if you want to shift your portfolio into, into asset classes that, that are less diversified, that, that goes against a lot of, a lot of, a lot of things which is, you know, a bit of a potential issue.

The other thing they, they say is, well actually if you adjust your signals according to the strength of your trend.

So you're right, I'd call a continuous run the binary trader.

Actually that, that factor in of itself kind of already positions your portfolio to take, make money out of these.

So basically if you were to look at your trend strength parameter niels by asset class and don't if you do this, but you'd see that your trend strength parameter in the last seven years was much better in commodities on average than it was in equities or in fixed income for the previous decade.

It would have been very much about a fixed income.

So in a sense, by allocating to things with stronger trends, which is what you do naturally, if you've got a continuous system, that allocation is already happening.

You don't need to do anything extra on top of that.

It's just unnecessary.

So yeah, it's an interesting paper and I quite like it and I've done it myself recently.

When people publish a paper and say, well here's something interesting.

Oh, by the way, if you're wondering if you can make extra money out of it, the answer is no, it doesn't work.

But it's still a very interesting thing to talk about.

And I think a hallmark of a good research team is they look at things that don't work as, as well as things that work and they publish both because it's just as valuable to find out that something isn't working as to find out that something is working.

So that's not for me.

I like that.

I like to get to the end of papers and for people to say, yeah, nothing to see here, but I hope you've enjoyed the ride.

Yeah, no, I think I'm completely with you on that.

And I think this is, I mean, I would have loved if they had even included some of the previous decades like the 90s and the 80s.

And the reason I say say that is I remember so clearly what took place towards, I mean, interestingly enough, right.

What.

Okay.

So my, you know, the conversations we were having towards the end of that period, which of course coincides with what people call the CTA winter, things were talking about, people were talking about, oh, have things changed, has trend following, stop working, etc, etc, and I always felt that what had changed was we just had a period of time where central banks were very, very good or very, very lucky to keep inflation down, interest rates pretty much at zero for part of that time.

And that also meant that, you know, some of the economies weren't really moving kind of in a, in a, in a natural form.

It's the odd one out.

I remember another paper, and I don't have the date of that, but, and I don't know that I can disclose who wrote it, but there was a paper out a few years ago where they had looked also at attributions by sector during crisis periods and what they concluded, and this is a very reputable firm, was that the most consistent sector in a crisis is the commodity sector.

And so I know it's been very popular to focus more and more of the portfolio towards financial markets because they are more liquid usually and therefore you can manage more money and especially if you are being paid by just how much you manage, that's a very strong incentive.

But in my view, and there's nothing new in this, in my view, that's never been the best solution.

The best solution is to build your portfolio of, you know, as diversified with as many truly uncorrelated markets, so to speak, meaning more commodities, which is also a philosophy we share certainly at Don.

So I think this is really great paper to, to highlight some of the things in that area and, and hopefully it'll open up the eyes to many more investors in terms of the importance of quote, unquote, true diversification.

Acknowledging full well, of course there's going to be periods where say a sector like fixed income, maybe even a sector like equities will do, will be by far the best one.

But interestingly enough, if you go back and I was just looking at some data that I had access to, I mean if you go back 20, 25 years, I mean even through this bull market of equities, equities for from a trend following perspective hasn't been firing on all cylinders.

So, so yeah, no, I think the, the paper is great and people should definitely read it.

Yeah, I mean I, I was trying to find some statistics while you were talking because I think I've done this analysis myself.

It was just, just, you know, and it's just amazing.

So, so that was definitely true back then for sure.

The 80s and the 90s, I'd have to check.

But yeah, but you know, it's also.

What's great about it.

It's a perfect segue to the next and final topic we have because as you rightly said, people could be tempted at saying, oh, let's just move into the things that had just worked.

Well, the same is actually true when you design your system and you start looking for things that seems to work better based on historical data.

This is of course your domain, Rob, not mine, but it is a blog post from Wisdom Trading that you found about overfitting, especially in the new era of AI.

So I'd love for you to to talk people through, through this one.

Yeah, this.

I don't know about you, Niels, but whenever I go on LinkedIn or even Twitter, about 40% of my feed is people with producing back tests of strategies that are obviously been generated by, by AI, which is kind of depressing.

So.

And actually I'm.

This is a very early book book plug.

Very early book plug.

Because, because my, I was just waiting for it.

I mean it took you about 56 minutes for the first book.

Well, you know, so, so my, my, my, my fifth book is coming out in December, but that, that which is, you know, is what it is.

But my, my sixth book, which I haven't even started writing yet.

I've not signed a contract, the publisher or anything, but I started thinking about, it is going to be about back.

Back testing and fitting.

So I'm doing a lot of, as I said earlier, doing a lot of research and thinking about this and I do think certainly in the age of AI, that, that, you know, this, this is, I mean back testing and overfitting was an endemic problem before, but now we've got AI, we can, we can do it automatically.

It's great.

So, so yeah, the wisdom, the wisdom article is full of wisdom, as you would hope.

And the, the basic premise is one I kind of agree with myself, which is that, you know, it's fine to use AI essentially to generate ideas, to generate strategy ideas.

That's absolutely fine.

It's not, you know, it's a sort of, I think AI is quite good as a sort of a creativity assistant tool, you know, so I think it's quite good at say, drawing silly pictures, for example.

That's what I mostly use it for, to be honest.

Occasionally I use it to write little bits of code.

I've never used it to write any more than about 10 lines of code because I just don't trust it enough and I spend more time checking and rewriting it and I certainly never trusted to do a back test of a trading strategy.

But these guys like, well, it's fine to use it to generate ideas essentially, but the important thing is that, is that once that idea has been generated is that it's then tested in a robust fashion away from the AI.

So basically you need to have a process and it's more about.

People think that fitting and portfolio optimization is about maths.

It is to a degree, but actually the most important thing is the process that you follow.

And you know, the sort of.

One of the main point about this book, when I get around to finishing, you know, Starting it will be about the process rather than about the math.

There are lots of books full of maths about portfolio optimization and fitting that you can feel free to read.

But it's about the process that you follow once you have an idea.

And it doesn't really matter whether that idea has been generated by an AI model or by you by looking at a novel source of data.

By looking at this, you know, say this Quantica paper and think, well, that looks interesting, or whether it's been generated by more of a kind of old fashioned data mining exercise where, you know, you've gone and sat and looked at charts and said, well, it looks like, well, you've got this wick of this candle engulfing this Ichimuku cloud near that Fibonacci level.

That looks like a bicycle to me.

It doesn't matter where it comes from.

But ultimately you then have an idea which you need to be able to robustly test, bearing in mind that that idea will almost certainly have been conceptualized using future information that you wouldn't have had at the start of your backtest.

So that is the key point.

Your backtest process needs to be able to handle that in a robust and sensible manner.

And the end output of that backtest, it will essentially not be a yes or no.

Going back to the very first question at the start of the pod, near the start of the podcast, when you decide to add or delete strategies, actually it's not really a yes or no question as to whether an idea works or survives in your overall portfolio of ideas or strategies.

It's going to be a percentage, it's going to be a probability that it's good and that will translate then into a portfolio weight, you know, so if an idea is outstanding, it may end up with 10 or 15% of your portfolio because I'm sort of assuming you've got a fairly decent one already.

And if it's rubbish, it may be 0.01% but you know, it's still in there because like, like Coco, that the chance it could work, you know, you know, there's no, never 100% chance that something doesn't work.

So that, that's kind of, you know, that's my.

If people want to start using AI for backtesting and then that's really the safest way of doing it.

Otherwise, yeah, you're basically back to the bad old world of overfitting, except that now you've got a nice tool to do it for you that's using up lots of water and you know, tokens and generally being a very wasteful resource.

So the interesting thing will also be because we do know that some managers already use AI, right?

And some, obviously you should be completely transparent about it.

But it will be interesting to see how, how do you as a due diligence person actually evaluate that?

I mean for some things is probably pretty easy to understand how the AI is used, but there will be, I'm sure, things where, well, you don't really know what goes behind the scene, goes on behind the scene of the AI.

And so how do you, how do you, how do you evaluate that?

And.

Yeah, I mean, it's an excellent question, Niels, but actually I, I, my, I've never, I haven't, I've never been on that side of a due diligence.

I've, I've been always been on the other side.

You know, back, back when I was managing money, I'd have had people come to me and say, right, you know, we've, we've got this allocator, this, this sovereign wealth fund, this pension fund who wants to invest in us.

You know, Here is the 50 page question here we have, you know, the ref, the ref that we have to fill in at the rfi, you know, and we're stuck on question seven, can you help?

Sort of thing.

That's been my exposure to that process.

So, but, but you know, I, I probably think I could do a reasonable job of designing a questionnaire for a CTA investment because having been on that side, you know, poacher term, gamekeeper, I, I know what questions to ask.

And the questions I would ask now would be exactly the same questions I'd have asked 20 years ago before AI became this big thing.

And they're down to, again, they're really down to the understanding the research process, you know.

So tell me what happens from, through that process, from idea to live trading.

What are the steps in that process?

What are the checks and balances, you know, what the robustness, what's the peer review and so on, you know, and so on and so forth.

And the fact that at the beginning of that process it is typing into ChatGPT or you know, other AI models are available, you know, analyze this data, come up with a trading strategy that works.

To be honest, that's no different from, you know, 20 years ago that might have been, you know, a researcher, a junior researcher sitting at their Bloomberg terminal, other terminals that are available and looking at lines and saying, well, it looks like this predicts that.

I think I'll, I'll see if that works.

You know, there's not really from, from the point, you know, of actually coming up with the idea, almost certainly using forward information to actually putting it into your portfolio.

That process shouldn't really be fundamentally different.

So I wouldn't necessarily have to create a whole custom load of sheets about AI unless it was being done wrong.

So if I started not liking the answers to those questions, then I would be circling back and saying, well, okay, you need to tell me things like for example, this AA model, is it an external or an internal model?

And if it's an internal model which you trained yourself, did you train it on say, data before a certain date and therefore have a pure out of sample period?

You know, you'd have to start asking questions like that.

But that would only be the case if, as I said, the process was effectively flawed.

Because ideally, you know, you wouldn't be trusting the AIs sort of evaluation of itself, which, you know, which means you don't need to worry too much about whether it does have, you know, kind of forward information plugged into its learning set.

Now if it's a public AI model, then you all bets are off.

You know, you've no idea what, you know, where the data is coming from, whether the data is real.

You know, it's be a lot more of a concern in that case.

Yeah.

And to that point I imagine that a lot of these AI trading strategies that are being offered not by CTAs but on the Internet at large, of course probably do make use of public AI.

So that is definitely a dangerous place to be spending your time and your money.

In, in, in my guess would be my guess.

Anyways, I think we've come up against time limit today, even though there was one more paper that we kind of briefly touched on last week and we never really got around to it.

Maybe it's kind of a little bit the same.

And it's a paper from another group of our friends, namely the people over at man.

I mentioned it last time, it's called Don't look down because I thought it was kind of an interesting summary reminder as to how drawdowns show up in different types of assets, how frequently they show up, how deep they, they are.

And I think some people might be surprised by, by some of the findings.

And I mean, unless you want to say something about it, I think people should just go and read it themselves.

It's obviously on the MAN group's website under Insights, but anything new?

Yeah, it's an interesting paper.

I mean one Thing it gets into quite early, which most people don't bother with is actually what is a drawdown.

Yeah.

You know, because you kind of have a very pure definition, which is, which would mean that you're essentially, you'd be in a drawdown almost all the time because unless you're literally making a high water mark that day, you know, then, then technically you're in a drawdown.

So he does actually definitely find drawdowns which is, which is quite useful.

And then yeah, he looks at them across a number of different asset classes, but also you know, risk, premium, seller.

Yeah.

As we mentioned before, things like trend value, momentum and quality.

So he looks at the sort of distinctive characteristics of different asset classes in terms of, you know, you know, how big their drawdowns are, how often they occur and things like that.

You know, I'm, I'm not sure how sort of statistically significant these results are because by definition drawdowns are episodic.

You know, they're not happening all the time.

And this, you know, if you apply a strict definition to them then, then in your data set you're probably not going to get more than say 10, 15 or maybe 20 of them in a, say a 50 year back test.

And that does mean I'd be, I'm not sure you can draw too many firm conclusions about whether equity drawdowns are you know, substantially different from say bond drawdowns on that basis.

But the more interesting part of the paper for me is the second half where he looks at the, the interaction of drawdowns.

So we know what drawdowns tend to happen at the same time.

And you know, that that's quite a nice take because I think one thing that people do a lot is, is, is what I call the sort of crisis alpha test.

So they, you know, the classic thing is you, you say, well you know, this is your standards sort of.

If you look at any deck from any cta, you'll see this slide in there.

It'll be, these are the periods when the S P did badly or when 60, 40, dead badly or when there were recessions.

And look how well our trend following portfolio performed in these, in these episodes.

Aren't we great?

And you know, sometimes they're a bit naughty and they cherry pick a bit and they don't put in there the ones where trend following didn't do quite so well.

Like for example, Covid.

Anyway, so that, that's, you know, that sort of classic thing, this is a bit more of a rigorous way of doing it and it's a bit more of a sort of a different take on it, if you like.

Because, you know, they're not just saying, well, when the S and P was in a drawdown, how well did trend following do?

They're taking a much more holistic view and saying, well, when these assets are in a drawdown, what other assets tend to be in a drawdown and not in a drawdown?

So it's a different way, if you like, of identifying what could be a good diversifying asset.

Although, as I said, caveats.

You know, there aren't that many drawdowns in most data sets and therefore it's a, you need to be wary about drawing firm conclusions from, from, from those figures.

But, but yeah, it's an interesting paper and you know, like, I think it's quite interesting to contrast the Quantica papers and the MAN papers.

The MAN papers are a little bit friendlier to read, I should say a bit less technical, a few more pictures, a bit shorter.

So they're more your kind of light, light reading over your coffee in the morning.

Whereas for the Quantica paper you, you normally want to have a couple more cups of coffee and get your head down before you read those.

But both great papers.

Yeah.

Although I will say I think MAN also produces the, the long deep dives, but they produce a lot more.

So you're right, some of them are a little bit shorter and that's also great.

Sometimes you, you need that.

So it's kind of interesting enough.

It's kind of like drawdown diversification.

How can I get stuff in my portfolio that does not draw down at the same time?

So yeah, good stuff.

Rob.

This was, this was perfect.

Thanks so much for, for preparing yourself for, for all these topics and I'm sure people enjoyed kind of this buffet of different types of trend following related stuff.

And if you did, please head over to your favorite podcast platform and leave a nice rating and review for Rob and of course for all the other co hosts that we have every single week.

Next week I'll be joined by another one great one, Mark, and he also has usually some really interesting topics that he brings along, but it'll also be your chance to send some, some questions for Mark.

You can as usual send them to info toptraders unplugged.com and I will do my best to bring them up.

That's it for now.

I'm off to celebrate my children graduating both with a bachelor and a master's different one.

So a big family moment for me.

So I'm gonna leave it at that, yeah.

And say, from Rob and me, thanks so much for listening.

We look forward to being back with you next week.

And in the meantime, as usual, take care of yourself and take care of each other.

Thanks for listening to Top Traders Unplugged.

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