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.

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.

Rob,it is great to have

you back this week. I think actually it's the first time in 2025.

So how are things on your side? How are things in the UK?

Things are fine. It's a bit cold and damp here and I've actually

had, I've got a cold, which I've had for several weeks and isn't

going away.

So,listeners should be aware that if there's any

weird gaps in the conversation, it's because the editors

had to take out about five minutes of me coughing. My voice

sounds even sort of lower and gravelier than usual as well.

Fair enough. I'm sure we'll work our way through that.

Weare,

however, going to keep you pretty busy talking today because

we’ve got a ton of questions in for you, which is great, so we

much appreciate that. But before we even get to that, let me

just ask you the usual question and that is, since we last

spoke, lots of things have happened. Anything in particular

that stuck on your radar the last few weeks?

Yeah, I mean, something that's come up quite recently actually is

what on earth is going on with gold? Right?

Imean,so, gold's gone

up, which, you know, is one of these things that happens. And the

causes of it, we could argue about - instability and uncertainty

politically, which is interesting. But the thing that I

find interesting about this specific thing is that there's some

kind of weird technical stuff going on in the background.

So,according

to market reports, what's happening is that gold is basically

being moved from London to the US. And I'm not sure whether that's

a physical movement or the gold bars are staying in the same

place, but the kind of legal right to it is moving. I'm not completely

familiar with what's going on there. And what's happening as a

result is that…

So,when gold is a futures contract, like a lot

of futures contracts, the futures price will depend on the

spot price plus any kind of yield that you earn on it, less the

interest rates for funding the position. But because gold doesn't

earn a yield, you actually have to effectively put in essentially

a borrowing cost and a storage cost.

So,the storage cost is, you

know, if you've got a lot of gold in a warehouse, you've got to

hire people with guns and thick walls and stuff to keep it

safe, I guess, keep it underground somewhere.

Butactually,

amortized over a large amount of gold, the storage cost isn't very

much. So, what really drives the difference in the futures and

the spot price is the borrowing cost. And borrowing costs

have just exploded. I mean they're up something like they normally

follow pretty closely the sort of “risk free rates”. You'd expect

them to be about kind of 4.50%, 5%.

Likeroughly the kind

of sort of Fed dollar rate, borrowing rates, because gold is

priced in dollars of course. But actually, they've jumped up to

like 10%, 11%, 12% which is just crazy because of this weird

imbalance in inventories across warehouses.

Andif I look

at the futures price at the moment, so, for example, gold for

delivery in say December is 150 points or something like that,

which it's up to about 10% annualized over the spot price, which

is just weird. So, we have this interesting situation where,

as a futures trader, gold is going up. I want to bet on gold going

up.

Andactually, if I look at my own forecasts, I've got a long

position on gold and on silver incidentally, and on Bitcoin (which,

you know, it's digital gold, isn't it?). But the cost of carry

on that position is negative because the future is well above

the spot price.

So,it's one of those weird situations where you

are kind of getting mixed signals from the price movement and

the carry movement. And I love this sort of weird technical stuff

that goes on underneath futures markets. And this is an interesting

example of it. So, we'll see what happens over the next few weeks.

Yeah, I had not picked up on that. Well, I will say I have been

traveling for about a month, so, I guess that slipped my radar.

So, I'm glad you brought it up.

Doesit say anything about, about

who's moving their gold back to New York?

I'm looking at the article. So, there's been a few articles.

Some of them are in the less kind of accurate end of the financial

press, shall we say.

ButI'm looking at the Financial Times, which

is normally pretty accurate and, and it doesn't say so. So yeah,

it's a mystery to me exactly what's going on. I'm sure that you

can read all kinds of conspiracy theories on the Internet,

but fair enough. But for the time being, yeah, it's definitely

causing some issues.

Yeah, very interesting. Thanks for bringing that up.

Forme, what

hit my desk this week was an interesting, but maybe not sort of

surprising in some ways, article that Bloomberg had about

fees in the “hedge fund world”. And both you and I are old

enough to remember when the traditional model 2 and 20 was the

norm. Then, over the years, it was seen as being very rich and way

too high for most investors. I think a lot of institutional investors

certainly also helped push fees down in our industry.

Andinterestingly

enough, of course now, actually the 2 and 20 model can be

seen as pretty cheap and that probably needs to be explained somewhat.

And it's this article on Bloomberg that basically compares

the 2 and 20 model to the new multi strat/pod shop pass-through

model.

ImeanI have to say it's pretty scary reading if you're

an investor paying those fees. Although I do accept that the net

return has been, for the most part, very good.

Butthere are some

examples, and I'm not going to go through all of them. But there

is, for example, one quote where they estimate clients are effectively

paying something like 7 and 20 or even up to 15 and 20 - compare

that to the 2 and 20 that hedge funds was known for.

Andit

all starts out with a comparison of how much was left by

investors or for investors, I should say, from the gain of around,

was it 15.2% gain that the Balyyasny Asset Enhanced Offshore

Fund delivered in 2023. Before fees it delivered 15.2%. After fees,

what the client got was 2.8%.

Now,I have argued before that, of

course, the net return is the most important thing to some extent.

What surprises me, really, and I'm not sure it's covered by the

article as such, is that we've seen (as many know) an enormous amount

of interest and growth and money being allocated to this space.

It's kind of the new thing in our world.

Andthat, you know, leads

me to believe that this must be large institutions that can allocate

this amount of capital. Otherwise, it just wouldn't be these

numbers that we are talking about.

Andso, if that is the case,

then I will say I am surprised that some of these pension funds,

insurance companies, et cetera, et cetera, are accepting

the level of fees being put on these investments, at least compared

to what I have seen in my career in terms of pushback from

large investors, even in the low, relatively low fee world that

I've been operating in. So, that actually is something that caught

my eye. I know I sent the link to you. I don't know if you had a

chance to look at it or had any thoughts.

I was sort of aware of this discussion, and actually I think

it's interesting because I think it comes down to transparency.

I think, for right or for wrong, the old model where we were

like, “this is our management fee, this is our performance fee”,

was very clear and transparent. Whereas now it's like,

well, we have these management fee performance fees, but they're

quite low. And then there are these other fees kind of falling

out of the back door of the fund that you can't necessarily see

because everything's been charged effectively to the client's

account.

So,I think the issue might be that institutions just look

at, as you say, look at the net performance, look at the kind

of headline fees, and think, well, this seems fine without realizing

that there's all this money kind of disappearing out the back

door almost invisibly. So, yeah, I mean, it's not a new problem

in the sense that if you think about a kind of fund of funds model.

So,you know, before Mr. Madoff came along, the fund of funds

business was the way that people tended to get exposure to

lots of different hedge fund strategies at the same time. The

sort of multi strategy pod shop was less common.

Butin that

model, you had the issue where, for example, if you had managers

that were doing really well, but the overall portfolio was doing

badly, you'd have to pay performance fees to the managers

that were doing well. So that's another issue with the pods.

Imean,if you're sitting in your pod and the whole strat fund,

as a whole, is down, you're still going to want to get paid.

And the pod guys want to keep these guys sitting there in their

seats, so they're still going to pay them their bonuses even if

the fund overall is losing money. And that's another thing that

kind of ratchets up the overall expenses.

So,that specific

issue is not new, but I think the issue of the transparency of

costs, I mean, I feel like we're going backwards. Because in

the retail world, transparency costs actually improved a lot. If

you look at things like UCITS, the transparency costs is much better

for the retail investors. But it seems like these multi strategy

pods are taking a step backwards in terms of transparency,

which I don't think is a good thing, frankly.

No, neither do I actually.

AlthoughI will say someone mentioned

to me that even the UCITS space, you can now find examples

of people, if you read the perspectives close enough, where

you have the official fee. So, everybody says, oh yeah, that's great,

and they may even state a certain expense ratio. But then when

you drill down, there are some other costs, like research costs,

et cetera, et cetera, that crop up. And so that's a little bit

worrisome if we start seeing that in the UCITS space because it

really should be crystal clear, from the expense ratio, what

people are paying and what people are not paying for.

Okay,so

let's leave that aside because I do want to just very briefly mention

one other thing because it was on my radar when I saw it. It was

just this picture of Elon Musk with one of his many children on

his shoulders in the Oval Office. I don't want to make this

political, but I thought it was very telling of the times we

live in. And then people have to make up their own mind as to what

they think of it. I know we're going to come back to some of this

a little bit later, but from an economic point, of course.

Anyways,it's

too bad people can't see your face right now, Rob, because you

really want to say something. But I will now gently move on to

the trend following update that has also been very interesting.

I'm really curious to hear your thoughts on the first six, seven

weeks of the year.

Now,as far as I can tell from looking at the

indices, it's been a mixed start across the industry. Different

managers doing, you know, well, not so well in terms of performance.

The CT indices are not moving a lot, frankly, away from zero. Some

above, some, some below.

Obviouslywhen you think about the

market moves we've had so far, you would think things like equities

have done well for trend followers, coffee, even some of the

metals. You mentioned gold, for sure. And frankly, also, at least

if you have a longer term horizon, I would have thought that

fixed income had also done okay, despite the recent rally we

saw in bonds. But now it's selling off again with the latest

inflation figures.

Theonly thing I can kind of see, from my

vantage point, that has been a little bit tricky this year has been

the currency sector, and that's mostly been in February actually.

So, does this resonate with what you're seeing in your different

models?

To be honest, I've not looked at my performance. So, I'm actually

just going to do that now. From memory, my gut feeling is that

I think I'm sort of up a little bit this year. But, if you

give me a moment, I'll be able to tell you for sure.

Yeah, no, I'm just curious to see because obviously all managers

are different so these could also just be general observations

even though I'm sure you don't follow…

I'm up like 1% for the year, so, basically noise, to be honest.

And that consists of being down about 1 1/2% in January and

then, so far, in February being up like 2 1/2%.

So,not very

meaningful to be honest.

No.

Myown trend barometer finished yesterday at 30 which is

actually a weak reading. But, again, it’s a different time frame

for what I use for calculating that to what we see in the indices

will also play a role. I think yesterday, which was Wednesday, probably

was an up day for most people.

Anyways,in terms of numbers, BTOP50

is up 46 basis points as of Tuesday, up 1.68% so far this year.

So that's actually doing the best of all of the indices. SocGen

CTA index up 15 basis points in February, up 77 basis points for

the year. The Trend Index up 42 basis points so far in Feb, and

only up 57 basis points this year. And the Short Term Traders

Index down 18 basis points in Feb, and down 12 basis points in

this year so far, and continues to struggle, frankly. I

talked a little bit with Tom about that a few weeks ago. And so,

I'll probably bring that up with him next time he's on the podcast.

MSCIWorld up 30 basis points in Feb, and up 3.79 so far this year.

And the 20+ Year S&P Treasury Bond index is down 32 basis points

(it obviously was hit a bit by these new inflation numbers), but

still up 15 basis points so far this year. And the S&P 500 Total

Return is pretty flat, up about a quarter percent this month,

and up 3% so far this year.

Allright, as I mentioned, we have

a ton of questions in which is great. Now, first of all, some of

them are long to read and I'm going to stumble across them, but

I'm going to do my best. Some of it is also a little bit technical,

although I have tried to weed out at least one that I thought was

just maybe too narrow because we want something that is something

that many people can benefit from. So, we'll do our best.

Weobviously

take the questions as they come, but just bear with us and then

we'll move on to your topics which are truly very, very interesting,

Rob. So, let's do it.

So.the first question is from David, all

the way from Spain. “Thank you both for creating such a high quality

content for retail investors. I've been studying Rob's book and

working on putting the concepts into practice both for a

long only portfolio and a managed futures portfolio. Question

for Rob, I've been studying smart portfolios and am in the process

of designing my own portfolio.

Sincethe book was published, several

multi asset leverage ETFs have become available such as the WisdomTree

Efficient Core, series such as the WisdomTree EF, and a one and

a half times leveraged 60/40 US Equity Bond ETF. And there are

some return stack portfolios, as he mentions. Anyways, the question

is, do you think these products have a place in a long term

portfolio? If so, what kind of allocation would you consider reasonable?”

Now,I want to preface this, David, and to all the other questions.

Of course, we do not provide investment advice on the podcast,

and of course each of us will just voice our own opinion. So, it'll

be as much as we can say. But don't take it as investment advice.

Definitely not. Because I'm actually not regulated to give investment

advice anywhere. So, I used to be, but not anymore.

Soyeah, this

is an interesting one because actually if you do read smart portfolios

and this is a kind of good general piece of advice, leveraged

ETFs are generally a little bit dangerous, especially for holding

for long periods of time. What happens is, if they go down a lot

and then go up by the same amount, if they go down 10% and they

go up 10%, you actually end up down. So, you're not back where you

started and then that's leverage. So, instead of going down

10%, you go down 20% and then up 20% and again you're even further

back from where you started.

So,what will happen over a long

period of time, with very volatile assets, is the value of

these will tend to drift down. So, if you're underlying is something

that's already quite volatile, like say the S&P 500, or let's get

really silly and look at, say, MicroStrategy, it's called strategy

now isn't it? The strategy company, which is basically just

a bag of Bitcoin which you can buy at twice the value of the Bitcoin

plus a small software business. I would definitely not,

in a million years, buy a leveraged ETF on that because the

underlying is very volatile and the value of that's going to

end up getting sucked down to zero over time with these large volatile

movements.

Nowto get technical for a second, the appropriate

level of leverage and risk depends on something called the Kelly

criteria, which depends on the expected performance of the thing

you're investing in. And that's true for ETF, it's true for

someone targeting a futures trend following strategy or anything

like that. And so, as a rule of thumb, if you kind of say, well,

if the risk you're getting on something is more than about 20%,

25%, 30%, it's potentially quite likely that that's going to

be more than the amount of risk you should actually be taking

because it's unlikely that your performance will end up being

high enough to justify that.

Sothat's why, for example, I wouldn't

invest in say a two-times leveraged S&P 500 ETF because that's

going to have volatility of 30%, 40% a year, which I think is

too high. I’m certainly not investing in a strategy times two

ETF because that's going to have a volatility of hundreds of

percent, probably.

Nowthese particular products though, so, if

you look at say 60/40 leveraged by times 1.5, that's probably

going to have (I've not looked at the product documentation), just

off the top of my head, I would imagine that's going to have

a volatility of somewhere around the 12%, 13%, 14% level, something

like that, 15% maybe. So, on that basis, I'd say that that's probably

okay, that's probably a reasonably safe thing to invest in,

just purely from whether the leverage is appropriate or not.

Notwith

any respect as to whether 60/40 is a good investment, or whether

that particular product is a good investment, or whether the fees

on that particular product are a reasonable level because I haven't

looked at any of that stuff. The return stack stuff, again, so,

it's two times leveraged S&P plus managed futures. That's a little

bit, sounding a little bit scarier.

Idoknow and have a great

deal of respect for the people that actually launched this product.

So, you know, they're very sensible people who think very carefully

about what they're doing. So, for that I'm not going to just say,

oh, it's probably fine. I'm saying, okay, I'd want to have a

close look at the documentation, look at the volatility

of that product and look at how that's come out.

AndI would

be a little bit skeptical and a little bit concerned because it's

probably relying on the fact that, if you look at the risk of

that thing, if the correlation of managed futures and S&P stays

relatively low, then it's going to have a lowish risk, and

applying some leverage to it is going to be fairly safe. The risk

is potentially, of course, if the correlation of those two things

increases and stays increased for a long period of time, then the

volatility is going to be higher and it may potentially then

be beyond the level which I'd consider a safe level of leverage.

So,I'm reasonably comfortable with 1 1/2 times 60/40. I'd need

to think quite carefully about 2 times S&P plus anything, never

mind managed futures. And as to what allocation, you'd have those

in your portfolio. Well, I mean, you know, that's an impossible

question to answer in a short period of time because it's very

much going to depend on what's in the rest of your portfolio, to

be honest.

Next question is from Carlos and with some of the questions that

I can sort of quickly overstate oversee here, I'm going

to rephrase them and make it shorter just so we have more time

actually.

ButCarlos brings up an interesting question I thought

actually, and that is, if you start out with a trading account

where you are able to trade 10 markets but you're just using one

model for that, you know, could be, you know, one approach,

call it that. If you then suddenly have more money, would you

then rather split the money and trade, you know, equal amounts

of money but using more systems (so, say, a system 2 and

trading the same markets), or would you add more markets to your

model that you're already running?

Iknowthis is of course

completely impossible to answer without lots of research,

but philosophically I guess the question is, do you gain more

from diversifying on models than you do on markets?

I love the way you give me all these impossible questions, Niels.

I really appreciate that.

Well, Carlos actually gave it to us.

Oh Carlos. Anyway, thanks Carlos.

Okay,so the answer is it

depends, right?

So,if for example, your trend following system

was relatively undiversified and just consisted of a single trading

speed and then you were thinking about adding something to

that, well, it's quite likely you'll get more diversification from

adding more markets than by adding further trend following systems

which are fairly similar. Because it comes purely under correlation.

So,the extra markets going in are probably going to have a correlation

of 0.4, 0.5 with the ones that are in there, something like that.

Another trend following system might have a correlation of 0.8 0.9

because there are only so many ways you can do trend following,

even if you're doing it at different speeds, it's going to be

fairly similar. So, I probably instinctively go towards more markets

with my first answer.

Whenwould be a case when you wouldn't

do that? Well, if you've already got quite a lot of markets,

for example, then the additional markets going in are going

to have a very small marginal benefit to the existing portfolio.

Andif you're then adding not just under the trend flowing system,

but something that's a bit different, like say carry, which

we talked about briefly when we talk about gold earlier, then

that potentially has got a correlation of maybe only about 0.7

with the existing system. So, at that point the pendulum swings

from more markets being better to a different system being better.

Andthe other advantage of adding systems is at least if you

do it the way that I do it, you don't actually need more capital

to do that. So, adding systems is virtually free as far as capital

goes, whereas adding markets isn't.

So,my answer is yes, markets,

definitely. But given that adding systems is sort of “free”

if you're fully automated, it's just a matter of writing some

code. You know, obviously you lose a bit in terms of intuitively

and complexity of your system. I wouldn't, you know, rule out completely.

I wouldn't just add a thousand different signals to my model just

because they all might produce a tiny marginal increase. I think

there's a point at which that's not really adding any real

value.

Butyeah, markets first is my normal instinctive answer to

that question.

Yeah, that makes perfect sense.

Allright, we're going to

jump to a quick question from Chris again. I'm going to try and

summarize it.

EssentiallyChris is asking you,

Rob, whether using ETFs to backtest trend following strategies,

you know, will give an accurate representation of performance.

Of course, Chris is aware of the challenges with rolling inside

an ETF if it's based on futures, but also compared to obviously

having to roll yourself if you're using futures contracts in

your backtest. Any thoughts on this particular issue?

Well, the first question I have is what are you actually going

to trade, Chris? I mean if you're going to trade futures, then

you really probably should be using futures to actually do your

backtesting with. If, on the other hand, you are trading ETFs

then it would probably be better, if you can, to use ETFs to

do your backtesting with.

So,with that in mind, what are the

differences between, say, holding an ETF which has underlying

it some contracts like, say, the Bitcoin ETFs that have futures

underneath them and holding the actual future itself? So, what

are the differences between doing it one way or the other?

Well,one

difference is fees. So, there'll be fees applied to the ETF

product and costs. And as we've discussed already, some of

those costs may be obvious, some not be obvious, but what costs

are those people going to have to pay? I mean, obviously they're

going to have to pay some administrative costs, they want some

profits.

Andthere'll also be trading costs from rolling from one

contract to the next. And of all of those costs, the only one

that you'd have to pay in the futures space is the actual rolling

costs. So, you know, you should be able to get a rough idea

of how much it's going to cost you to roll and then compare that

with the total annual expense ratio of the ETF and then check that

does include everything that you think it includes and there's

no hidden stuff coming out of the back, and that'll give you a

fair comparison.

Andultimately, you're probably going

to end up paying a bit more for the ETF, I would imagine, because

although, in principle, a big asset manager has got economies of

scale and can actually probably end up getting lower costs

than you can potentially, because they're big they're going

to have more slippage, so they'll end up with higher costs.

And secondly, because they've got to make a profit and support

all of these, you know, various functions, they're going

to have higher costs coming in there. So, all the things being equal,

I would expect the ETF to cost more money.

Yeah, and one final thing I just want to add to that, Chris,

and that is just be aware also of liquidity. A lot of ETFs have

been issued, but they don't all have very good liquidity, frankly.

So, you know, just be aware of that.

Yeah, and the other difference, of course, between them

is that if you're looking at the futures price, then you're basically,

you have to sort of effectively add on the risk-free

rate to that because the margin that you're holding against

that futures contract, you will actually earn interest on it.

If you just look at your backtest, you won't actually see

that money coming in.

Whereasthe ETF will actually include

that interest within the price of the ETF, because the ETF is actually

earning that interest on the capital, it's got the exchange and

it can return that to the investor as well. And that might

be in the form of, you know, an outright dividend yield or it

might be imputed into the price.

Ifit's a dividend yield,

then, again, you've got to kind of add it back in. So, essentially

you want to be computing what I'd call a true total return series.

So, for the ETFs, that's going to include any dividend yields and

it's going to be less any costs that you're going to have to

pay, either implicit costs that are hidden or explicit costs

in terms of a management fee. And then you can compare that to

the futures price, back adjusted price, and that's effectively,

again, a total return series. But you need to add in the risk-free

rate or deduct it from the ETF to get a fair comparison. So, this

is why it's much simpler if you can, if you're trading ETFs to

use ETFs in your backtest, if you're trading futures to use futures

in your backtest.

Andthen a second question is, what is better?

Well, as you say, I think costs and liquidity are the two main

points definitely to consider. But the reason why you would want

to go down the ETF route would potentially be market access and

contract size.

So,if the contracts are really big in the world

of futures and you need a lot of capital to diversify, well, you

may be better off going down the ETF route where the share prices

are smaller and potentially even you can buy fractional shares.

So, as far as the decision between ETFs and futures go, it's

not straightforward.

Allof the things being equal, I'd say generally

speaking, if you've got enough capital, futures are better. But

not everyone's in that position, of course.

So, we can summarize it to test what you trade and trade what

you test.

That is a good thing to have. Definitely, always.

All right, next question that came in is from Steve, and Steve

writes, “In AFTs, (which, of course, I had to ask you, what exactly

is AFTs? Of course it's a good way to plug one of your many books,

Advanced Futures Trading Strategies), all forecasting techniques

are rules based. Any pointers on how to use predictive modeling

techniques like linear regression etc. and how could we

combine it with your forecast scaling framework? Also, can you

comment on potential objective functions?”

Ithinkagain, let's

keep it broad so that most people can get some use for it and

just allow for the rest of the questions too.

Yeah, so this is kind of a general thing which is how do we

get from what, in machine learning, they called a feature to

a forecast of a price. But, in general terms, you've done some analysis,

you've come up with something you think predicts futures prices.

How do you get from say that wiggly line on the graph to a thing

saying, right, this means we should buy X many futures contracts

in say gold, which we've already talked about in the episode.

Andthe sort of simplest way of doing that, which is what I do,

is literally to say, well I'm going to treat that wiggly line as

something that has some kind of distribution. I'm going to construct

in such a way that if it's positive then I'm bullish, if it's

negative I'm bearish. And then I'm going to kind of calculate some

scaling around it. So, I've got some way of saying is it high,

is it low?

Andthat comes down to quite simply just dividing it

by a number and producing something like, if you're familiar

with the terminology, something a bit like a Z score. Now,

that process could equally be done by, say, a linear regression.

And with a linear regression what you'd say is well, I'm trying

to predict prices.

So,on the left-hand side of my regression equation

I've got the price, or probably you want a normalized return,

actually, a volatility normalized return on the left-hand

side. And on the right-hand side of regression is the thing that

you're trying to predict it with. Well, that will be the wiggly

line on the graph. And then the alpha and the beta of that regression

will effectively be, the beta’s going to be (we won't go to

the details of calculations), it’s going to be very much the same

thing in the sense that the coefficient on the regression is

going to be something that tells you how big the wiggly line

is. You know, is this a big forecast or a small forecast? And

then the alpha, the insert on the regression, well that's just

a way of essentially removing any systematic bias from forecasts

that are systematic long or systematically short, which you may

not want to do, by the way. And that's a whole big debate we

can have on another podcast.

So,actually, there's not really

any fundamental difference between using say linear regression

and doing what I do, with the possible exception of the fact that

I don't, generally speaking, remove systematic biases because

(and we can have a big discussion about that) I just prefer

not to. But in principle I could.

So,in answer to the question

about the objective function, which just means in plain English,

what is it we're trying to forecast? Well, I would always be

trying to forecast risk adjusted returns. I think that's

the most appropriate thing because we then want to size our

positions according to risk.

Yeah, cool. Good question. Next question that came in is from

Vic.

Vicwrites, “I'm curious about limits of research in finding

new or improving systematic trading rules in the liquid mid low

frequency space. Once you've included established risk premier

rules like trend, carry, and fundamental valuations, do most research

efforts by experienced teams in big and small firms amount to

just fancy branding exercises? In a competitive environment where

everyone is working with more or less the same data, is it possible

to meaningfully move the needle? Would love to hear your views

and thanks and all the best.”

Whatare your thoughts?

Thisis obviously

super difficult because we don't know what goes on inside the

research teams, but we know they have some very clever people

working there. What are your thoughts, actually? I have my thoughts,

but what are your thoughts?

Yeah, I mean, this is an interesting one and it's quite a

cynical view, isn't it, to say that, well, everyone's just doing

the same thing. It's just fancy branding and all this sort

of stuff. So, you know, there are Indeed some CTAs that have not

changed their model for years and not done any research and are

just plugging along quite happily and that may be a very valid

way of working as well, to be honest.

So,what are they doing inside

these big shops with hundreds of PhDs? Well, they could be doing

things like, for example, implementing new markets, some of

which have issues with pricing. So, certainly when I worked

at AHL, that was something that we were pushing to do in a big

way, and don't mind me plugging it, their very successful

Evolution Fund was a result of that. And of course, there are other

funds out there like Florin Court that have also pushed big into

alt markets. And this is something we've talked about in the

podcast before. So, that's a big job.

Andgoing back to the earlier

question in terms of whether you should be adding markets or systems?

Well, actually, adding markets can often give you the biggest bang

for your buck. So maybe that's what you should be doing.

Youcan

be looking at things like improving execution as well. The

bigger that you are, the more important execution is. So, for me,

I can do a pretty decent job of execution with an algorithm that's

a few lines of code long. But if you're a big fund trading hundreds

of millions or even billions of dollars of notional a day, then

execution is something that you should definitely be thinking

about.

Thenthe other alt, of course, out there is alt data. So,

there are people looking at alternative sources of data. And

that's also quite a big growth area.

Ithinkwhere there's probably

less research effort than you might expect is in using, let's say,

alt methodologies. So, we had all the alts in this question. Alt

methodologies, so that's your neural networks, your machine learning,

your artificial intelligence. So, basically working with existing

data, but doing it in kind of fancier ways. That's an area where

I think you're less likely to get much value, although undoubtedly

people are doing it. But I'd be very wary of any sort of team

of researchers that were purely focusing exclusively on that

area of improvement, because I think the lower hanging fruit is

quite high up in the tree there. And I think there aren't many

places, with the obvious exception of Renaissance Technologies,

that are really good at that kind of stuff.

Yes. At least for their proprietary fund, I might add. But

there we are. I completely agree with what you just mentioned.

It'snot just the kind of data that I think firms are looking at.

It's actually also what to do with the data before they stick it

into their algorithms that I think is an area of interest for

these firms.

ButI tend to agree. I don't think necessarily

that, as an industry, we're coming up with many new ways of doing

trend following. Although I don't necessarily think it's a bad

thing that you use more than one approach to trend following.

Instead of saying, “Oh, I'm wedded to moving average crossover,”

well, okay, maybe you can combine that with something else

and actually get a better result. So that's kind of one small

thing.

Butthe other thing I was going to say is that I think

where I would suspect we see the most evolution still, and where

there's still room to improve, is probably risk management. I think

that, at least what I see, is that better ways of dealing with

risk, forecasting risk and all of that stuff I think is pretty interesting.

And I think, as an industry, I think we've always been risk managers,

first and foremost, and I think we've done a pretty good job.

It's rare that you hear about a trend follower blowing up unless

it's specifically because they were running like a 5x leverage version

of their strategy. That's obviously something I have seen in

the past, which is crazy.

Inone of the conversations we had

when we did the SocGen CTA Index series with all the managers,

I think some of the ones, maybe was AHL where they talked about

that probably of their research budget, 35%, 40% of that

goes to course execution - improving execution to not lose out

when they get more inflows and manage bigger amounts of money.

So,I

do think that is true and that's obviously where managers have

to be careful that they could still improve enough to increase

the capacity of the strategy. But thanks for the question.

Thenext

question is from Andrew, and Andrew writes, “Thank you very much,

Rob, for your books and your transparency in your trading. Question,

approximately about a year and a half ago or more you published

on X that you were making a discretionary trade increasing your

bond position. I'm just curious how that trade worked out

and if you think, in retrospect, that discretionary call

was correct. And are there any other learnings for the rest of us

about when to know if a discretionary call makes sense?”

Yeah, I have to say I really didn't like this question because…

Well, when you asked for it on X…

I know, I know. Well, I'm a very good systematic trader. So,

if you ask me how a particular trade works out, I can tell you with

precision because it's all in a big database.

But,the small number

of discretionary trades I make, and the last one I made was

during Covid, I'm not very good at kind of keeping records of

them and sort of saying how they did in terms of P&L.

So,I did

do that for my Covid trading because there was a lot of it in

quite a short period, and I did work out that I had actually

made some money. So, you know, that was nice.

Butthis particular

one I actually just had to quickly check while you were talking,

and have a look, and I did quite well in catching the bottom

of the bond market, the top of the market in terms of yield terms.

But I didn't do a very good job of sort of closing the position.

So, I think I actually closed the position basically flat.

So,I

made a good entry decision but a poor exit decision. I should have

had a, I mean this is ridiculous because I literally have

written books about this, but I didn't have a predefined sort of

stop loss or exit criteria for my trade which is just crazy. And

this is why I'm not a discretionary trader because I'm

rubbish at it. Absolutely rubbish.

So,the learnings from this

is don't do it, I think at least as far as I’m concerned.

All right, all right, good question. I'm glad we got that straightened

out.

Thenext question is from Paul. Paul writes, “I have a question

about incorporating value/long term mean reversion strategies. In

Advanced Futures Trading Strategies, Rob introduces a mean

reversion strategy based on past five-year performance relative

to each instrument asset class. The strategy has a negative

Sharpe ratio but improves the performance of his baseline trend

plus carry strategy. I was wondering what the benefits/drawbacks

of having an absolute strategy that just looked at if the post returns

were positive or negative rather than relative to the performance

of the asset class. In the academic paper Time Series Momentum,

Moskowitz, al, in 2012, the authors show that returns years 2

through 5 are negatively related to subsequent returns. Given

this result, it seems like applying a value approach on an absolute

basis could increase the Sharpe on the standalone value measure

while still maintaining the strategies negative correlation to

trend.”

I'm trying to, I'm really trying to dig through my mind and

I can't remember if I've ever tested an absolute momentum, an absolute

long term mean reversion, rather, which is just negative momentum.

So,this should definitely work, and actually one of the things

I want to talk about later is a paper that talks about momentum

and mean reversion behavior across different time periods. So,

this is a nice kind of preview of that. So, it should work in principle.

Idon'tthink I've tested it in like the last 10 years because

I'm quite good at blogging about things that I've researched

and I'm pretty sure I haven't blogged about it. So yeah, I'll have

a look at it. I mean it's in terms of Occam's razor, you should

always go for the simplest possible version of something.

Andobviously

this is simpler than the relative mean reversion. And even

if it's sort of similar in performance, it's probably diversifying.

It's probably going to give you something a bit different.

Soyeah.

Now, as the questioner says, there's a lot of research in it,

particularly in equities. I mean there's papers by people like

Richard Thaler and stuff on mean reversion and you know, it's

sort of related to value effect and equities. So yeah, I'm

a fan of the idea of it.

Ofcourse, as a long term signal

it's going to be quite hard to get statistical significance. So,

you know, and it's never going to be that good in terms of Sharpe

ratio because of that. And it may even be negative in the backtest.

But yeah, I'll make a note of that and have a look at it.

Okay. All right. The next question is from Samuel. It's a long

one which I'll probably butcher a few places, but I'll try

and do my best.

Hestarts out by saying, “I'm a big fan of TTU

for a number of years now, but a few concepts have made their way

into my head that would apply to the trend following universe and

yet haven't been covered on the show. (Well, there we are. Good

that you bring them up.) Namely, what does the research say,

if any, of trend following strategies that don't rely on lagging

indicators?

IfI recall correctly, EMA - exponential moving

average (that's what I was just about to say) crossovers versus

Donchian breakout strategies, if applied systematically, don't

change backtests all that much on a diversified basket. As Rob Smith

highlighted (I'm not sure who Rob Smith is but), as Rob Smith highlighted

in his May 2022 presentation, price doesn't have mass. So, using

the term momentum with stocks is more like describing a sports

team that has momentum. It's not literally applicable to the thing

being described.

Onesimply needs to look at any duration candlestick

chart to recognize that price often turns on a dime. Bright green

on one candle, bright red on the next one, changing without any

hint of a transition. To your knowledge, has anyone done any studies

using the current state of monthly, quarterly, yearly candles

for a trend following system, say reducing volatility at the beginning

of those time periods rather than on a rolling basis. Same thing

with adding to positions in addition to or in lieu of the various

channel breakouts of EMA crossovers. Why not look at the current

state of high time frame candles to increase exposure progressively?

Same thing on reducing exposure, should something that was

doing great one quarter turn around immediately be the next?”

So first a few caveats. Things I do not understand in this question

or don't know about Donchian breakouts. I'm not familiar with

the work of Rob Smith and I don't tend to look at candles.

Withall

that in mind. ultimately, all indicators are lagging because they

look at the past, right? How can we reduce lag?

Well,we can reduce

it by using less of the past and more recent periods. So, for

example, we can speed up a moving average by using shorter numbers

in the moving average. Exponential moving averages weight

more recent periods more than periods longer ago. Okay, so that's

another way of doing it.

Sobasically, to get technical for

a second, both the moving average and exponential moving average,

and indeed any indicator that takes a series of past returns, is

a weighting function over those past returns. So, a simple

moving average is literally just the last, say 20 returns equally

weighted so that the response function for that would be flat.

The exponential weighting response function, obviously, is

exponential. So, it's high for recent periods and then goes down.

So,I think, if I understand the question correctly, it seems

that he's talking about doing something weird with the most, perhaps

most recent observations, and weighting those. Either weighting

them more highly or changing your response in a more nonlinear

way to that.

So,for example, to paraphrase it might be something

like, well, the moving average says we should be long, but because

the last week or so is negative, we should actually be short

or change our position. Something like that. I'm not generally

a fan of sort of nonlinear stuff because it's not very intuitive.

And also, it's highly, potentially can be highly overfit

because you need additional parameters to do it.

So,you know,

to implement the kind of thing I've discussed, you'd need to have

a parameter saying, well, how far back do we look, what do we actually

do when this thing reverses? I mean, there's quite a few extra parameters

potentially there. It's making the system more complicated and potentially

more overfitted.

Itmight be better. A simpler way of doing that

is to say something like, well, I'm not saying this probably

isn't true, and I'll discuss why in a bit when I get to my part

of the podcast. But if you think, for example, that prices trend

over six months but then tend to mean revert, if they have been

trending for six months and they start to mean revert suddenly,

then you should go short.

Well,a better way of doing that

is to have a separate mean reversion one week signal, or to

fit some kind of response function, as we were talking about

earlier with the question about regression, between how prices

move depending on how strong your forecast is. And again, I've

done that and there are some effects there, but I've judged that

the complexity they add is not worth the tiny, tiny, insignificant

performance that they add.

Soyeah, I think this is one of those

things that kind of sounds like a good idea. Let's get rid of

lagging indicators and use indicators that don't lag. Well,

actually it's impossible to do that.

Actually, it would be better to have future indicators, right?

So, we would always know.

I mean, I would prefer to have future indicators. Unfortunately,

I've not been able to find any because, you know, time travel is

not possible.

Not yet.

Anyways,last question and then we get to your

topics. I have to preface here. First of all, it came from

Crypto Captain. Now Crypto Captain is, I think, a longtime listener,

so I really appreciate that. And Crypto Captain has also asked

questions before, as far as I recall. I do think, however, I did

mention last time, Crypto Captain, that you really should use

your own name or at least tell us who you really are because we

don't really appreciate people being anonymous on this. I will never

mention your last name, but let's make it more direct instead

of using these different names.

Anyways,you asked two questions,

Crypto Captain. We will answer question two because the first question

was simply, in our opinion, too narrow for our audience. And

so, I'm sure you will understand that. However, your second

question is something that we both felt was relevant. So here goes.

Youasked, “How to handle missing data when contracts get delisted

and then relisted. In my case, many contracts in some commodities

got delisted in June 2020 and then got relisted in February 2023.

ChatGPT suggested I use co-integration and error correction

models to fill the missing data because the larger contract

data is available. What are other things I can try out?”

So,Rob,

over to you.

Well, the easiest thing to do is to ignore any data before February

2023. So, basically ignore the period it was trading earlier and

obviously ignore the gap.

Thenext thing to do that's still

kind of okay, but more complicated is to create your trading

system so it can actually deal with missing data. So, then what

would happen is that in your backtest you'd be trading this thing

for June 2020, and then you'd go to a position of zero until the

prices started coming in again. And then once there was enough

prices to form an opinion about what the forecast should be

and what the volatility should be, et cetera, et cetera, then you'd

go back to having a position.

Iwouldreally, really not interpolate

data, price data, and then, then use that in a backtest and say,

oh yes, look at, this is great. I think it's a fundamentally

stupid thing to do, to be honest, and I'm not surprised that

ChatGPT has suggested it because, you know, I'm not a big

fan of AI, as you know. I really, really wouldn't do that,

to be honest.

Now,there are some limited cases in which it might

make sense to do this. So, for example, if you are, say, estimating

a volatility and you've got hourly data, but obviously you've

got a period where when markets are closed, then it's probably

a reasonable thing to do to get a better estimate of volatility

to actually interpolate those overnight hours. I've seen people

do that. It's a reasonable thing to do.

Interms of techniques,

I wouldn't use co-integration or an ECM. I'd use a Brownian bridge.

If you don't know what one of those is, you shouldn't be doing

this, frankly, because, you know, it's quite complicated stuff

and you need to be very careful with it. But I would use

it in that specific instance and if I think hard, I can probably

think of a few more. But 99.9% of the time, interpolating missing

prices is a fundamentally stupid thing to do, that only an

AI would suggest.

All right, let's move on to your topics. Now we're going to talk

about your most recent blog post, which is on a very interesting

topic, which has been discussed in different shapes and

forms over the years now. However, actually, there is a very

nice sort of bridge into you into this topic from the most recent,

which is Q4 2024, paper from Quantica, our friends here in Switzerland,

who write some excellent stuff. People should go and check

it out.

Now,I think, and I can't remember if I did the discussion

on this paper or maybe Alan did with Katy. I'm not entirely sure.

Anyways, maybe you could just quickly summarize what they concluded

about dynamic position sizing and so on, and so forth, and then

gently take us into your blog post and guide us through that.

Yeah, so, the Quantica paper is a really nice paper and I definitely

encourage people to read it. I'm not going to summarize it in

great detail here because that's not the main point of the

conversation, but it's about evaluating three different kinds

of position sizing framework.

One,where you enter a trade and

you take a certain number of contracts and you hold that fixed

number of contracts.

Thesecond method is fixed notional,

where you would say, all right, I want to get say $100,000

of exposure to this particular future. On day one, that might be

five contracts. On day two, maybe the price has gone up a bit,

therefore you might lower it to four contracts. Obviously with

a very small amount of capital it would be quite hard to get an

exact notional, but with large enough capital you can obviously

get pretty close to the notional you want to target.

Andthen

the third methodology is the methodology I use, which is to say

I want to get a certain amount of risk on my contract. So, you'd

say I want to have $25,000 of annualized risk on that contract.

What does that correspond to? And then that will change if the

price changes, but it will also change if the volatility changes.

So, most notably, if the volatility goes up a lot, then you'll

reduce the number of contracts that you hold. And they look at this

specific example of cocoa, because obviously cocoa was the poster

child trade of 2024.

Andthey then sort of evaluate these different

techniques. And I've done a similar work myself, and they come

to the conclusion that the volatility adjustment has the highest

Sharpe ratio. Okay.

Whatthey don't do, however, and I have done

in my own work, is look at skew. So, you know, trend followers

reduce positive skew. And it turns out that the closer to your

sort of fixed position sizing the system you're running, or even

the notional position sizing, the greater the skew you'll get.

Andthe reason for that intuitively is, well, what's happening

is that if you have something like cocoa that explodes in price

and goes up a lot, and you're just holding a fixed number of contracts,

then that's going to produce an outsize effect on your P&L and

an outsize effect, positive outlier on the upside of your P&L.

And the same thing doesn't happen on the downside because obviously,

when things move against us, we close our positions.

Sothat's

the kind of intuitive logic behind that. So that's the Quantica

paper. Go away and read it. It's very interesting.

Butthis comes

down to essentially a question we should ask whenever evaluating

any kind of strategy or asset in finance, which is what should

we be paying for risk? And we use Sharpe ratios because as futures

traders we can use leverage. And that means essentially if by

risk, if you mean volatility, well we can get any level of volatility

we like. We just need to change our leverage. And that's not

going to change our Sharpe ratio,

So,effectively, the price

of risk is basically zero for a leveraged trader. We can get any

amount of risk that we want to get. That's not true of skew though,

necessarily.

Sooften when we're evaluating different options

or, say, different hedge fund strategies, we might have a choice

between something that has a really good Sharpe ratio but negative

skew. And an example of that would be something like… An extreme

example of it would be something like an option selling

strategy. A less extreme example of that would be something

like an equity market neutral strategy. They tend to have negative

skew as well.

Andthen you might be comparing that with something

that has positive skew, like, say, a trend following strategy.

And you could also be comparing different kinds of trend

following strategies, so ones that are closer to mine, where you've

got good Sharpe ratios but the skew maybe isn't so good and then

you've got other funds that have lower Sharpe ratios but very,

very high positive skew.

So,what I wanted to do was, in a

sort of intuitive way, kind of say, well, if I'm comparing two different

assets, whether they be funds or strategies or underlying instruments,

and they've got different Sharpe ratios and different skews,

what should the kind of trade off between those two things be,

at least in theory?

AndI say in theory because in practice people

have preferences for this sort of thing. So, some people really

like positive skew and they'll, you know, happily give up

more of them, their Sharpe ratio to get it. Other people won't.

So, this sort of is like a risk neutral approach, if you like,

as far as skew goes.

Anyway,my conclusions were quite

interesting because I was surprised to find that trade off

wasn't actually that substantial. So, in other words,

the amount of Sharpe ratio you should be giving up to “buy” positive

skew was actually be very small.

Toput it another way, if

you have two strategies, one with a very good Sharpe ratio and

one with a slightly worse Sharpe ratio, but with very good

positive skew, generally speaking, you want to go for the

higher Sharpe ratio strategy because the geometric return of the

product is going to be better. And the geometric return, sometimes

called the CAGR, the Compound Annual Growth Rate, maximizing that

basically maximizes the amount of money that you have at the end

of your investment horizon. That's, I believe, the kind of main

fundamental metric that everyone should be using when they're

evaluating anything.

Sharperatio only works if everything

has the same skew. And here we're looking at a specific example

where things have different skews.

Soyeah, it was interesting,

and I guess for me it was another nail in the coffin, if you

like, of the idea of using something like a constant contract

or a constant notional, as is in the Quantica paper, because they

do have a lower Sharpe ratio. I found that. Quantica showed that

as well.

Butany improvement in skew… There's no conceivable amount

of improvement in skew that would justify that lower Sharpe ratio

and sort of pay for that lower Sharpe ratio if you like.

So first of all, people should go and read this full blog post on

your website and we'll put a link to that in the show notes, of

course. And again, because we're starting to run out of time

a little bit, I just have one general question that I think some

people might think and sit with, hearing your thoughts on this.

Andthat is, well, on many of these episodes we've had in the past

decade or so, I'm sure many people, including myself, would have

said, well, hang on, Sharpe is not really great to optimize for

when it comes to trend following falling because it penalizes

upside volatility. How should people think about that when you

say, well actually we should still optimize for Sharpe?

It penalizes upside volatility, sure.

Butthe point is

that if an investment has a high Sharpe ratio, you can sort of

leverage it up so that the benefits of getting the upside and

the downside…Yeah, this is quite a hard question to answer actually.

That's fine. It was on the fly, so don't feel like…

So, I'm trying to think of an intuitive way of explaining it, but

basically what I did was sort of simulate the effect of holding

different investments with different levels of Sharpe ratio

and skew. And I said, well, the only metric I care about is how

much money I have at the end of time.

Right.

So that simulation accounts the fact that the high skew, positive

skew, lower Sharpe ratio investments, their pattern of returns

is going to be getting all of this extra upside volatility.

Thepoint

is that, in this framework, you don't really think about volatility.

Volatility only matters in as much as it will reduce how much money

you have at the end of time if it moves against you.

So,the point

was basically that the additional benefits of having a higher

Sharpe ratio massively more than compensate for the fact that

we're not getting those big upside volatility moments. So, I

think it's quite a good framework thinking about things,

because you don't need to say, well, okay, yes, upside volatility

should be valued more than downside volatility, which Sharpe

ratio doesn't account for, but skew does.

Butactually, combining

those two things together, combining a measure of symmetry,

essentially, in your performance judgment, which is what

skew does, it still tells you that you should generally be hunting

for higher Sharpe ratio investments. Because, you know, the

benefits of positive skew are, when you actually look at how much

money you're going to end up with, you know, they're limited.

Yeah. And of course, always a warning that some very high Sharpe

strategies, I can think of one like Bernie Madoff, may not always

turn out to be that great of an investment at the end of the day.

Absolutely. Yeah.

All right.

Especially if they've got a lot of, you know… Ignoring like outright

frauds like Bernie Madoff, I mean, we should always be careful

of high Sharpe ratio strategies that require a lot of

leverage because even if they haven't got negative skew risk in,

in the backtest during the historic returns, it's something

you should always be concerned about.

Yeah, and are opaque at the same time in some cases.

Okay,all

right, the next one, we'll keep the best for last, of course.

So, we will get through this one first because you mentioned that

this is actually an interesting paper and I simply hadn't

got the time, when I came back last night from my travels, to dive

into it in any great details. But you already mentioned that it's

somewhat relevant to our previous discussion today.

So,I'd

love for you to take us through this paper that is very recent.

It came out, I think only a few days ago. I think it's called

Trends and Reversion in Financial Markets on Timescales from

Minutes to Decades.

AndI should of course have mentioned the

authors. I don't have it in front of me here. You may have it,

just to be full credit.

Yes, Sara Safari and Christof (and I'm probably going to mangle

this) Schmidhuber, both of whom are not far from you, Niels.

Exactly. That's exactly why we want to definitely give a plug for

Zurich University, which I think this is where they relate from.

Anyway,I'm going to turn it over to you, Rob. You read it much

more carefully than I did.

Yeah, I mean this is a really interesting paper.

So,we've mentioned

my previous book already, but in my previous book I say, well one

thing that's interesting is that at different timescales mean

reversion and momentum tend to do better or worse. So, as we discussed

with one of the earlier questions, if your time period is

multiple years, then generally speaking you're probably looking

at mean reversion. Momentum seems to work well, empirically,

certainly in futures, across multiple asset classes for time periods

of say a month up to a year.

Andwe also know that if we go right,

right down to kind of really small time increments, mean reversion

tends to work well because that's where the high frequency traders

are operating and their strategy is very simple. It's buying

on the bid, selling on the ask and they're relying on the prices

kind of bouncing between those two points.

Andin my book I say,

well, there's a sort of a gap between this high frequency trading

and this one week, one month time horizon where momentum or mean

reversion may be working. And I kind of, unfortunately I didn't

have the data to do an analysis and say what actually happened

in those time periods.

Ikindof waved my hands around and

came up with some suppositions that actually this paper says are

false. So that's kind of, I don't mind having my vague guesses

refuted. I'm much happier to see hard evidence because, apart

from anything else, it's a really good guide to if you're thinking

about sort of going into faster trading, whether that faster

trading should be mean reversion or momentum. I think it's

really useful to have that as a starting point.

Butanyway, what

they do is they, they look at probably the widest range of time

frequencies I've seen in any paper ever, which is fantastic. I

won't go into the technical details of what they're doing, but

basically what they do is for different time horizons, time frequencies,

they basically say, is this a time frequency where we see momentum

or is this time frequency where we see mean reversion? That's

kind of what the paper boils down to.

Andif you do nothing else,

go to page 28, figure 10 and that's the figure I'm now going to

describe to you. And that basically summarizes the paper beautifully.

Nowwhat complicates things slightly is that the way that they

analyze trends is a bit weird. They fit a cubic polynomial, which

is a slightly unusual way of doing it. And to get technical for

a second, it allows you to model both the sort of relationship

between trend strength and mean reversion and also the general

trend. But we'll not talk about trend strength because there

is some interesting stuff in there but I think it takes away from

the key idea in the paper I want to bring out, which is the relationship

between, as I said, at a given horizon, do we see trends or do we

see mean reversion?

So,they go right down to sort of minute level

data, and they basically find that, let's say for time periods

of less than an hour, mean reversion occurs. Okay. And I think

the most mean reversion occurs at roughly a five minute time window.

So,that's kind of the area where, if you're going to be a mean

reversion trader, you want to be playing in.

Anda huge caveat

here, you know, trading at those kinds of frequencies is a massive

engineering and backtesting exercise and it's not something that

you should be casually doing. You don't just now sit at your computer

and look at charts and every five minutes do mean reversion trades.

Do not do that, whatever you do. But empirically that seems to

be what's going on.

Now,if you look at trend horizons of more

than an hour, they find momentum occurring. And this is where

this sort of fills in the gaps in my previous knowledge because

I wasn't sure what would be happening at these time horizons.

But basically, if you're trading for holding positions for

an hour, or two hours, or four hours, or a day, you should probably

be trading momentum. And again, big caveats about trading

that quickly.

Sure.

Trading costs, in particular, are going to be very hard to overcome

if you were trend following in short time frequencies, so be very

careful there.

Andthen they go on to sort of two days, three

days, four days, five days, ten days. It's still momentum. You

know, three weeks, six weeks, three months, six months, one year,

it's still momentum. So that, you know, it's momentum all the way.

Thisis a great paper for our industry because it's basically saying

that as long as you're not really a really fast trader, you

should probably be a momentum trader, which of course is what most

CTOs do. And then is when the switch happens.

Thenis when the

switch happens. So, anything longer than a year is when mean reversion

kicks in.

Andas I said, they do look at ridiculous amounts of

data because they go up to 16 years. They look at data out 16 years

and they're still finding mean reversion out there. And to do that

they're looking at data from 1692. So, they're looking at, you

know, 330 years of data to do this analysis.

So,it's an incredibly

thorough job and very, very, very impressive. But yes, the bottom

line is, so we talked earlier about looking at absolute mean reversion

over multiple years. This paper supports the idea that if you're

trading, is it really trading if it's multiple years or is it just

investing? I don't know.

Yeah,but if your forecast horizon

is, you know, two, three, four years, definitely a mean reversion

strategy is more likely to make sense. If your time horizon

is anywhere between one hour and one year, you should be a momentum

trader.

Andif you're able to trade at sub one-hour frequencies,

then yeah, you could look at mean reversion. So, it's a beautiful

empirical survey of everything from right down to the tiny, tiny

subatomic structure of high frequency trading, zooming out to

the giant galactic views of multiple year holding periods.

I'm surprised, actually, that it cuts off at one year, a little

bit, because I do think that many trend followers use lookback

periods that are somewhat longer than one year.

Yeah, well actually, the cutoff point is two years. One year

has the strongest, has a very strong trend flowing performance.

Two years is pretty much flat. So, you might get away with 18 months.

Yeah, that's actually what I would have thought.

Yeah.

Without doing all the research, of course. There we are.

Okay,we've come to the last topic brought to you or brought by

you, I should say. And it's about one of your favorite persons

to talk about, Trump, but not in a political way. It is from a

economic way.

Yeah.

What does it mean?

What does it mean? What does it all mean? Yes, what is the point?

What are the economic consequences of Donald Trump?

Correct, absolutely. In your view.

There’s a paper written, by John Maynard Keynes about Winston

Churchill, almost exactly 100 years ago. Yeah, so, I've been told

I'm not allowed to be political on the podcast. It’s not

a politics podcast and I might offend some of the people listening

who are fans of the man. So, this is not political at all.

Thisis

a pure hardheaded macroeconomic analysis of the likely

consequences of Donald Trump and, of course, the implications

for any investments that you might care to make over the next

four years. So, we'll start with the big one, tariffs, of course.

Bythe way, I should preface this by saying that I'm going to

assume that he is successful in his endeavors so that he's going

to actually do the things that, A, he said he's going to do

and, B, he appears to be trying to do. So, you know, there

are some instances already of pushback from the courts, potentially

some Republican politicians. And it's going to be quite interesting

to see how the sort of conflicts between the different branches

of the US Government resolve themselves. Because there are going

to be conflicts and there are going to be arguments and discussions,

that's for sure.

Ithinka lot will depend on how much he gets done

in the next two years because I can't really see the midterms going

that well. And midterms generally don't go well. Like, for

presidents it’s sort of a stop light.

It'spretty usual that if

you start a presidential term with a majority in the House and

the Senate and the presidency, it's pretty likely you'll end up

losing one of those majorities in the midterms. That happens nearly

all the time, mainly because people just don't like sitting, you

know, they don't like sitting governments. So, the midterms are

almost a bit of a protest vote. And we see a similar thing

in the UK with sort of local council elections, but those are

far less important than the midterms, clearly.

So,yeah, it's

going to come down a lot to what he manages to get done in the

next two years before he loses, I think he'll probably lose

the Legislature.

Anyway,having said all that, let's

start with the big one which is tariffs. The tariffs are interesting

because it's probably the one of his policies that there's the

most pushback by people who, actually, he's going to listen to

to. Because most Republicans think that increasing tariffs is

a terrible idea. Trump uniquely seems to think they're a

good idea. But it's generally accepted that tariffs will increase

inflation and just generally be a bad thing.

AndI don't think

I need to talk about that in a lot of detail because a lot of ink's

been spilt on why tariffs are a terrible thing, and almost no mainstream

economist thinks that they're a good thing. So, they're going to

increase inflation, but of course they won't just increase inflation

in the US, they will increase inflation globally, I think, for

sure, due to retaliation and just generally. So, let's put that

one aside and look at other things that he's up to.

So,he's

planning to deport a lot of people, and send them back to where

they came from. What effect will that have? Okay, well, simple

supply and demand. If you reduce the amount of labor in the

market, then that will probably increase wage costs, I would

imagine, which is more inflation. Now, there'll be an effect

on the demand side as well, but I think it'll be less substantial.

But the other thing that really worries me is the likely effect

that this will have on supply chains.

Ithinkwhat Covid really

showed us is that the sort of network of supply chains in the world

is a very delicate thing, and anything that causes damage to it

can have consequences which are very problematic. And you end

up with stuff in the wrong place, and stuff not being manufactured,

and issues with that.

AndI think there are also potentially

supply chain consequences from the tariffs as well, because, for

example, I know that US cars, bits of cars, go backwards and forwards

between Canada and the US across the border. Think about where

Detroit is actually physically located for a start. So that's again,

potentially going to lead to inflation. Again, I think a lot of

these things are inflationary, I really do.

Thenwe get into something

a bit more esoteric, which is regulation. So, I think it's fair

to say that Trump doesn't like regulation. And there's a sort of

naive view that all regulation is a negative cost for businesses.

So, therefore, less regulation should be positive for share prices

because businesses will make more profits. Obviously, there is

some truth in that to an extent. But actually, what businesses

want and like is things like certainty, and the rule of law, and

a set of rules and regulations that they can kind of rely on. And

if you start messing around with things like that, then what

that's probably going to do is actually increase what economists

call, the risk premium.

So,people will demand to be paid

more to hold risky assets, because everything's getting riskier,

everything's changing, everything's all over the place.

So, I think potentially, actually things like regulation and

things like tariff policies that change every five minutes even

if they don't end up going in the wrong direction, that's going

to increase the risk premium, which would be bad for equities.

Ithinkthat zooming out a bit more, and looking at the fact that

he seems to be, how can I put this politely, making some fairly

radical changes to the way that the sort of US Government operates,

and potentially even doing things like literally, metaphorically

putting his finger (or perhaps it should be Elon Musk's finger)

on various spigots of money that are flowing and keeping the

US Economy moving and going. Just putting a finger on and saying,

what happens if I just stop this payment?

Again,what's that

going to do? Well, potentially it's going to make people unemployed,

it's going to cause supply shocks, it's going to cause demand

shocks, it's going to cause uncertainty.

Andso, I think the

fact that he's sort of breaking the contracts that the American

government has with its people, and also that the American

government has with other governments, it's going to increase

uncertainty, it's going to increase risk premium, it's going

to be bad for equities. I think there's going to be inflation,

which is going to be bad for bonds. And of course, the conclusion

of this is we should just all buy CTAs, lock ourselves in our bunkers

with our shotguns and our baked beans and hope for the best.

Well, I mean, there's also a little bit of a nuanced view on this.

I don't, I don't disagree with some of the stuff you've said.

Andactually,

you tricked me a little bit, Rob, because you sent me a link to

an article by the FT and that that was a slightly different version

of what will happen under Trump. So, you know, kudos for me

to agree to this topic.

You can still cut it out at the edit, now.

No, absolutely not. That's not how we do things here.

ButI think

there are a couple of interesting observations in the paper

or in the article in the FT, because I agree with you that there

are certainly a lot of risks in doing what's likely to happen.

But there's also this conundrum that we see the risks showing

up in only parts of the financial markets at the moment.

Right?

Sofixed income is probably showing a little bit more

concern about what's going on while equities…

So is gold of course.

And gold, as we talked about, yes. Whilst equities are not really

showing a lot of angst at the moment, if we just measure angst

by the price level on many of these indices. So, it is an interesting

time.

I'veobviously alluded to it in my previous conversations

and I will dig a little bit deeper with a very special guest

in a couple of months time, because I think what you're saying

and what I'm saying, in a slightly different way, is I think

that not just what happens right now in the White House, but

actually what's happened in the last couple of decades, is an

erosion of trust, erosion of trust in institutions. I think that's

probably also why I mentioned the picture from the Oval Office

earlier in our conversation. I do think we are losing respect and

trust in a lot of these institutions.

Andthat to me is a

serious issue. And in a world where there is definitely a disconnect

also happening between what is value and what's the price. I do

agree with you that, actually, a price-based strategy that doesn't

care about ‘is it the right value or not’, but just follows the

price. Of course, I would at all times say that that's a pretty

good strategy to have in your portfolio. And trend following is

certainly one of very few that I can think of.

So actually, if I think back to 2007, 2008, the equity markets

for a long time thought everything was fine and it was in

the bond markets, in the CDS markets and so on, the corporate

bond markets and the mortgage backed security markets that the

initial pain was and the initial foresight was.

AndI do think

that I'm reluctant to say that market X always leads market Y, but

I do think there is an argument for the fact that most of

the people trading equities are naturally, how should we say

this, optimistic people who might be slow to kind of make a judgment

about market news. And that's probably particularly true now that

I think equity trading now has got a much bigger percentage of retail

traders than it ever used to have.

Thebond market however, is

still, I think, dominated by more professional traders. And I

think bond investors also are naturally grumpier and more conservative

than equity investors. They must be to accept that kind of 4%

or 5% yield.

So,I do think that potentially this could be a

situation where the bond market could be a bit ahead of the

curve and maybe even the gold market in saying, well, look at,

there's some scary stuff going on here.

Andobviously there are

different drivers because the bond market's probably more concerned

about inflation rather than, say, the risks of a recession, whereas

the equity market. Is inflation good or bad for equities?

There is not an obvious answer to that question.

Soit may be that

it's just a more direct thing, that Trump's policies are clearly

inflationary, therefore bonds will probably react, equities, not

so sure. But I do think that as some of these other effects start,

I mean, he's not been in office that long, Right?

Youthink

about the amount of stuff he's done already, but, you know, a lot

of the things that he's doing, there'll be quite a lag before they

have an effect on the real economy and start showing up in things

like jobs numbers and even bigger lag before they show up in

equities. So, I'd say watch this space.

Yes. And I'll finish with one thing which actually I do think might

be also a little bit of the signs that we're seeing now. Many,

many years ago, I came across someone who talked about this idea

of cycles between public and private, Where sometimes the public

trust is high, sometimes it's very low, and it's the private…

AndI

will say I have been thinking about this concept a little more

recently, and I would not be surprised if what people think is

safe, i.e. government bonds, will turn out to be not so safe.

And actually, what we think of, maybe more risky normally, such

as equities, might actually turn out to be more of a safe harbor.

Thisis not a market forecast, but I just think we need to revisit

or even take out of the archives some of these concepts,

some of these cycles that come across so rare that we don't think

about them day to day. And always, at least in my mind, I always

think about the conversation we had with Neil Howe and the books

that he or the book he wrote back in the early 90s, The Fourth

Turning.

Ithinkthat is a concept that we should not ignore

at this point in time. And I fully, firmly believe that this is

what we're seeing right now. And it will turn more ugly and more

surprising before it's over. So, it will be interesting times

and there'll be lots of things for us to talk about every week on

the podcast.

Rob,thank you ever so much for doing such a thorough

job without coughing, despite having to bite your tongue at times

when we discuss certain elements on the podcast today. Great

stuff and I hope people appreciate all the preparation that

Rob put into this. If you did, by all means go and leave a rating

and review on your favorite podcast platform to show your appreciation.

Nextweek I have another interesting, super insightful guest

that used to work actually with Rob, namely Graham Robertson

from AHL. So, that’s going to be another fun and very insightful

conversation.

Ifyou have some questions for Graham, something that

you might want to challenge him about, then by all means send

your questions to info@toptradersunplugged.com and

I'll do my best to get them in front of him.

Andof course, as you

can tell from my dyslexic way of pronouncing some of these words,

by all means make them short and easy for me to put forward to

him. Anyways, this is it from Rob and me. Thanks ever so much for

listening. We do 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 the Systematic Investor podcast series.

If you enjoy 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.

Andremember, 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 is 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.