Episode Transcript
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You're about to join NielsKaastrup-Larsen on a raw and honest
journey into the world ofsystematic investing and learn about
the most dependable andconsistent, yet often overlooked
investment strategy. Welcometo the Systematic Investor Series.
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Welcome and welcome back tothis week's edition of the Systematic
Investor series with KatyKaminski and I, Niels Kaastrup-Larsen,
where each week we take thepolls of the global market through
the lens of a rules basedinvestor. Katy, it is really great
to be back with you this week.How are you doing? What's going on
where you are?
Things are good. It's, youknow, good weather here in Boston.
Enjoying the summer, chillingin the Boston sun, hopefully. We've
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got a great lineup today. Wegot a few talking points. We're going
to focus on your latest paperon the current state of the CTA and
trend following space, butwith a little bit of a difference,
I feel, compared to the otherpapers that have been coming out
lately. So that's alwaysgreat. We've got a few other things
we want to talk about whichare highly relevant for where we
are right now. And so, youknow, super excited about our conversation.
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But of course, as always,before we even get to that, I would
love to hear what's been onyour radar the last few weeks, the
last few days, whatever.
I mean, it's been fun. It'ssummer. I mean, I think you and I
talk about this a lot. Like Iusually spend some time in Scandinavia
in the summer and recently Iwas actually here for the fourth
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of July, which I haven't donein a long time. And I was, it was
so fun, so exciting, but Ijust couldn't believe I forgot how
much fireworks are likethey're everywhere. Like everybody's
obsessed. And there wereexplosions and lots of things happening
that were bad as well too. SoI was like really, I had forgotten,
like sort of remembering whenI was a kid and really loving that
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fourth of July. So I thinkthat that's been an interesting thing.
Just kind of enjoying, youknow, U.S. holidays celebration.
Exactly, exactly. Good stuff.Well, I've got a few fireworks myself
on my radar, but these aremore from our industry. One thing
that actually caught my eye,which I thought that I didn't. I
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wouldn't say I didn't expectit. I didn't even think about it.
But I saw yesterday for thefirst time. Now it's a little bit
more out in the news that theold floor traders of the CME are
suing the CME group because ofloss of their quote, unquote the
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privilege they had to, youknow, to own a seat on the floor
before the electronic trading.I'm not going to go into the detail
of the case as such.
I thought you were saying lossof hearing, right?
No, no, no. I mean this is a$2 billion suit. I'm probably a little
bit more than hearing losshere. But it's kind of interesting,
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right that they, that there isthis case where you could say it's,
it's almost a case againsttechnological advancement. Now of
course, if there wereagreements in place and blah, blah,
blah, that has to be upheld,of course. But I find it interesting.
Didn't expect to see somethinglike this because it's been a while
since we went to electronictrading. Right. But I think I will
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keep a little eye on this tosee how it all pans out. Even though
a lot of these cases probablyend up in some kind of settlement.
But yeah, I thought that was interesting.
Not sure I forgot about that.
Yeah, yeah. The other thingthat I noticed was this is actually
related to our little worldand that is that CTA programs that
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are focused on China marketsactually had somewhat of a different
experience in June doingsomewhat worse than the traditional
CTA programs. Now we don't atDunn trade any Chinese market. So
I have no idea what went onthere. So I'm kind of curious if,
you know, if there wasanything unusual about Chinese markets
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last month or.
I haven't looked at it. Butwhat I would guess, I mean this is
just my first guess is theChinese markets are a lot of commodity
focused, particularly thefutures. So I guess, you know, you
did see big moves related togeopolitical conflict related to
different commodities. So someof the metals, the lead, like it's
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likely that that was aninteresting trending environment.
Although energies were muchmore shocked. Some of these more
sort of supply chain metalsprobably could have been interesting
from a trend basis or in themonth of June, which we didn't see
in other markets.
Yeah, no, absolutely,absolutely. Now I'm going to keep
the best news for last just tokeep the suspense. So one more thing
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that I noticed before we getto the last one and that is that
the Euro is getting bigger. Isaw a headline that Bulgaria has
now been given the green lightto introduce the euro as of January
1, 2026. I don't know if itmeans they're going to adopt the
Euro. I don't know if theyneed to approve some things domestically.
But yeah, I mean, interestingto have another member of the.
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Is Denmark next?
Oh, oh, that's a really?That's a really sorry. You know what?
You know what? The thing is,I'll be very transparent here because
I was living in Denmark backwhen we had this big debate and vote
about it. And of course a lotof people tried to get Denmark in
the euro. I will say I wasskeptical then. And I will also go
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as far as saying I actuallythink Denmark has done better than
the Eurozone because theystand outside and can still determine
their own interest rates andso on and so forth. So personally,
I would like to keep theDanish kroner. Frankly, it's strong.
I'm sure you must feel thesame because you go to Sweden a lot
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and you have your kroner.
Swedish kroner is a lotweaker. So it's not quite the same
story.
You know what, they actuallyuse that as an argument. You know,
some Danish politicians in thelast election, they said, oh, just
look at Sweden, how bad thekroner is doing as an argument for
Denmark having to go into theeuro. I'm thinking, haven't you looked
at the Danish kroner? It'sdoing pretty well.
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Exactly. I mean, andcurrencies are exciting these days.
I mean, there's. That's whatI've been interested in. I mean,
it's not very fun when youtravel abroad because obviously your
dollar just doesn't go quiteas far recently, especially this
year. And it's the only trendthat's really worked. And trend following
too.
That is true, that issue. Doyou want to have the best news? For
last you mentioned traveling.Do you want to have the very best?
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And I really mean, this isgreat news. The TSA is ending the
shoes off policy for airportsecurity screening. I mean, that's
fantastic news.
Everybody's going to smellbetter now. It's going to be great.
You know, I hate to yell my shoes.
No, but it's like. I mean,it's taken like 20 years to change
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that policy. So, you know, wecan't say that nothing good comes
out of the new policies in theUS Even though I'm not sure who actually
decides these things. But it'sgreat news for those of us who still
go to the U.S.
I'M going to Google when it starts.
Because, you know, well, Ithink it has started actually. So
you might be traveling soonand you might report back and saying,
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shoes off, shoes on. We'll see.
Sounds good.
Sounds good. All right, well,let's move on to more traditional
programming here. What's goingon in trend following right now?
And one thing that you couldalso I could have put this on what's
been on my radar, actually.And that is what happened yesterday
in copper, but not copper,broadly speaking, Comex copper specifically.
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That is the US traded copperbecause that had a big move. And
as far as I remember, this isthe largest single day price surge
in records going back to 1968.I say as far as I remember. I mean,
of course I read this like anhour ago. So that's a pretty sizable
move. I think it was up 13% ina day. And this time I actually think
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that that kind of surpriseCTAs were on the right side of that
move. I have a feeling, can'tspeak for everyone, of course this
is tariffs related. I thinkTrump came out with some tariffs
on copper and people thoughtthis is a great idea to make sure
we get more copper on thebooks because copper traded elsewhere
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in London, in China, as far asI think that they also traded there
is unaffected as such by thismove. So was that some good news
on your side yesterday?
Yeah, I'd say so. I mean, Ithink positioning probably small,
but you know, it kind of, itshows how isolated incidents can
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actually directly link totrends that extend. I mean, obviously
copper and a lot of the metalshave been directly linked to the
trade discussions. So we'veseen sort of some long signaling
starting to build in the metalsector just because of tensions and
potential tariffs. So not justcopper, you've seen some interesting
moves in other metals as well,like platinum as well. Last month
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was positive, you know, so Imean, it just shows the diversification
of the commodity sector that,you know, a lot of investors don't
really have exposure to directly.
Yeah, no, absolutely. It's oneof those value adds we certainly
provide for sure. Other thanthat, so far this month actually
has a little bit of a betterfeeling to it as far as I can see
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on my side the first week orso. I think CTA is generally positive
for the month long. Equitiesof course playing out well. Metals
you just mentioned also someshort exposure and fixed income.
US fixed income, I should sayprobably doing okay for, for managers
and we're also getting alittle bit of support for those who
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trade livestocks and grains.That seems to be working out okay.
One thing, one area of theportfolio that I think might still
be a little bit tricky isEuropean fixed income. So what are
your thoughts at the momentbased on sort of what's going on
in the CTA space, CTA world?
Well, I think the two assetclasses that have actually trended
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the most this year has beenequities recently and also all year
it's been sort of a weakdollar but that has actually been
reverting a little bit thismonth the dollar. So there's been
a little bit of support forthe dollar this month. What has been
really tricky to me has beenfixed income. I mean fixed income
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has been very mixed. You'veseen sort of steepening, flattening,
you know, posturing with theFed back forth, back forth. I mean
it has been a little dance andwith really. So I think fixed income
is definitely underweighted bytrend following signals. The interesting
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one is going to be thecommodities I think because I think
energies were really trickylast month because they shocked big
and then they came back downand now they're back up again. But
I think metals and otherthings linked to this trade policy
as it slowly comes out couldbe interesting. And we're just kind
of waiting to see if there istruth to the pivot to positivity
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for equities or not. I thinkthat's the theme that most investors
are interested in. I've seen apretty large shift in sentiment in
the last two weeks or so wherethe world is kind of saying actually
growth looks a little betterthan we thought. And we also saw
some pivoting to small cap inthe US versus large cap. So it's
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kind of a tentative, you know,environment for equities or people
are regaining some, someconviction I think and that's, we'll
see if that holds outthroughout the rest of the year.
You know, for those of us whoare systematic, of course it doesn't
really matter. But I think fora lot of people who have to make
the decisions on adiscretionary basis, having to probably
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reduce exposure in equities,long exposure quite heavily only
like three months ago wherethere was a lot of angst I think
in the markets to now havingto suddenly consider buying back
at all time highs. I meanthese are psychologically very difficult
decisions to make. So yeah, Ithink you're right. I mean the jury
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is a little bit out in termsof how much, you know, how many people
will follow along on the, onthese new. But I am actually as we
record today a little bitearly this week, the DAX is making
new all time highs for exampleso there could still be some, some,
some upside I would say. We'llsee, we'll see. Anyways on the positive
news, B top 50 index is up 27basis points so far in July. It's
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down 3.19% so far this yearbut that's really not a big deal.
Soc Gen CT Index up 22 basispoints, down 7.4% so far for this
year. SOC Gen Trend flat forthe month so far, down 10% for the
year. The short term tradersindex up 20 basis points for the
month, but down 5.11% so farthis year. MSCI World as of last
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night up 9 basis points forJuly, up 8.7% for the year. The S&P
US aggregate bond index isdown 68 basis points in July and
up 3.17% for the year. Andfinally the S&P 500 total return
up 33 basis points for themonth and 5.85% for the year. Now
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I can't remember exactly thedate you and I last recorded on,
but I think it would have beenaround the aftermath of the Liberation
Day. So this feels, feels verydifferent when you read positive
numbers for equity suddenly.
Yeah, it's, it's been, it,it's been a long year already. Already.
Well, at least we are morethan halfway, Katie. So, you know,
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and it's something foreign.The good news is that you have been
busy with one of yourcolleagues trying to put some words
on what's going on with alittle bit of a spin in terms of
how we should think about thecurrent performance, obviously the
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current drawdowns for theindustry and so on and so forth.
So I think I'm going to letyou dive into it initially. I'll
try and see if I can add alittle bit of color or do some follow
up questions. But why don'tyou talk a little bit about not just
what inspired you to writebecause I'm sure everybody knows
that, but actually why youtook maybe a little bit of a different
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angle on this.
Yeah, I mean I love anythingwe write about is always about like
what am I thinking about rightnow and how am I feeling about a
particular environment. Andthat's why I wrote a paper on Liberation
Day. I wrote a paper nowbecause, you know, anytime you're
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in the middle of something,you always kind of see just your
nose in front of your face.And so it's kind of like trying to
think about, okay, if I stepback and I sort of think more like
an institutional investor andI try and think about the long term
and sort of all history andsort of what is typical across different
environments. It always helpsme to get some perspective of what
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paths we might have goingforward. So I think this paper was
a very interesting and fun onethat kind of looks at market cycles
and managed futures, drawdownsand it's really thinking about both,
not just the drawdownsthemselves, but recovery from the
drawdown. So if we're standinghere in a difficult place, like many
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strategies have, what kind ofthings happen in the past to get
us there and what kind ofthings happen in the future for us
to kind of understand howstrategies adapt and change and recover
from drawdown. And so in thepaper, why this is important is if
you look at the top five orsix, or we actually list the top
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any drawdown for a managedfutures that's greater than 10%,
the largest drawdown wasactually between 2015 and 2019. So
that's an example of sort ofpart of it was a little bit during
Trump's first presidency. Butwe also know the longest, which is,
I guess we would call that theCTA winter. There were also some
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drawdowns post 2008 and othertimes where things were took a while,
the drawdown was very long.And then there are other times where
it's very sharp and, or therecovery is very long. So we then
plot all of these differentdrawdowns, how long they took to
occur and how long they tookto recover, where recovery means
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that you get back to the placethat you were. And that just shows
that there's a lot ofvariation across different drawdown
periods. So sometimes you canhave something like what happened
now and then it is eitherpossible that it's going to be a
short recovery or a longrecovery. This led us to ask the
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next question, and the nextquestion was, when we're in a drawdown,
what is the typical state ofthe world? So, you know, is it when
everything is good or is itwhen things are neutral or is it
when things are bad? And wesimply use equity returns to define
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this. And I have this, I lovebubble charts, you know me, three
dimensional, multi, multicolored pictures that kind of visualize
data. I love datavisualization. But in this picture,
basically you look at how faris the drawdown, how long did it
take? So how long did youendure the pain? And then the lower
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down on this picture, it's thedeeper the drawdown. And in this
particular graph, what sticksout very clearly is that equities
tend to be doing very wellwhen things are difficult for us.
And you can see thatthroughout the entire history of
the SG trend index, obviouslythere's some variation, but, you
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know, there's a clear themethere that, you know, when things
are good, trends are maybe alittle bit more difficult. What was
interesting is when you lookat recovery, so if you start a recovery
from the bottom of thedrawdown until the point you get
back to where you're madewhole, the longer it takes. And we
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also plotted across how, youknow, how far you have to go to get
there. So, like, a deeperdrawdown means it's going to take
you longer. But what's veryinteresting in this graph, and you
know, we're on a podcast, so Ican just talk about it. I can't actually
show it to them, but they canlook later, is something really pops
out. And it's the point thatit tends to be really challenging
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environments. Recovery is alot faster. So if the world goes
into a state of stress and,you know, then recovery periods tend
to be shorter, equities tendto do poorly. On the other hand,
if the world is good and like,equities continue to make new highs
and everything's awesome,then, then the recovery time can
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take longer. Which, you know,for most investors, I'd say I think
they have a big equityexposure. So either way, you know,
trend looks good coming out ofa drawdown in the sense that, you
know, if things are great,it's going to take longer, but your
portfolio is going to be doingwell. On the other hand, if things
are not great, you havesomething there that actually does
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really well to recover thedrawdown that you had before and
is sort of doing relativelywell, conditional. So that was kind
of the main conclusions of thepaper and just kind of giving a sense,
standing at a drawdown. Whatkind of expectations of scenarios
should you consider goingforward for managed features?
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This is another way of lookingat it, but it kind of also answers
the question that I think isrelevant because what you see right
now is that there is a, howshould I say, a steady stream of
new products being launchedrelated to portable alpha, where
you of course, add the returnsof equities to managed futures and
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the product looks fantastic.This is not new, but it is relevant
because it's another way ofhelping people, I think, understand
why these two investments arevery well suited together. And I
often make this example andpeople will open their eyes really
when they see it on a chart.And that is usually when you blend
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two investments together, saya 5050 allocation, you tend to get
some kind of average of thetwo. But actually when you do it
with trend following and, andThe S&P 500, for example, and of
course I'm referring toblending it with, with the, with
our own numbers, but youalmost get the sum of the two, meaning
both returns on top of eachother, which is obviously Outstanding.
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Right, so. So there issomething that it also. I don't know
if you listen to theconversation I had with Rob, I think
it was a couple of weeks agowhere we talked about bonds and stocks.
It was based on an AQR paper,I think Anti illman and had written
it where it turned out thateven though people think of say fixed
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income as more mean reverting,it actually has any more of an inbuilt
momentum. That's how Iremember it. And while the opposite
is actually the case withequities and how people think about
equities, while they alwaysthink about them being kind of a
momentum trade moving higher.But actually from a trading point
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of view, they have all thesereversions and corrections and V
shape this, that and theother. And it makes it very difficult
for trend followers to captureperformance. So when you look at
your return distributions, ifI look at our return distributions,
we would note that fixedincome has done by far better in
the portfolio, in the trendportfolio than equities. So I don't
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know if I have a questionthere but maybe give you some ideas
to explore it a little bitfurther before I move into something
a little bit further in your paper.
Well, I like that and we cantalk about it later but we have a
great paper where we talkedabout fixed income. And I also think
fixed income can be veryresilient. So it depends on where
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you are in the cycle, whetherrates are rising or falling, whether
the yield curve is inverted,steep or flat like that kind of gives
a sense of it's a verydifferent market environment. So
trend has done very well in afalling rate environment, especially
when the curve is steep andthen trend does very well short given
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this paper as well, when thecurve is inverted right now we're
kind of in a flattishenvironment, so that's a little more
mixed. So it's very consistentwith what we see historically. I
think it can really depend onregimes, particularly for fixed income.
And that also depends oninflation. So it's complex. We just
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went through a regime of time,especially for trend where you could
just head, you know, a lot offalling rates. And it was a great
trend for many years.
Yeah, a couple of things stoodout in some of the charts that you
put together. One thing is, asyou rightly say, that you know, when
you have the, the trendfollowing drawdown duration versus
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drawdown recovery, the worsttwo are really the trade war number
one, which is Trump's firstterm and then now the liberation
day. I mean there's definitelysomething about Trump and CTA performance
that maybe not go so well handin hand, I'm really hoping that's
going to change in the lastthree years of his term for sure.
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The other thing that stood outto me and it relates to something
that Alan talked about lastweek, even though we had some awful
technical issues. So I don'tknow how many people sat through
that episode. But he didmention that, that this time around,
the recovery that we've seenin the S&P 500 since Liberation Day
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of a 20% or more drawdown isthe quickest recovery on record.
I think 57 days I think iswhat he's mentioned. And this is
even without the Fed steppingin, which is kind of really surprising
in some ways. So putting thatinto perspective as well, I mean
you can understand why longterm, specifically trend following
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strategies are not built forthat kind of market behavior. So
that's something that is alsoworth just mentioning for those who
say why are we strugglingduring this time? Well, it's very
unusual times in some respect.
No, I definitely agree. I meanwhat's interesting to me is that
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I don't necessarily think thatthe longest drawdown was particularly
just linked to that particularpresidency. It was just appeared
with very low rates as well.So that, that was another factor.
I think some of the shocksfrom Trump I remember actually funny
we were, we were doing a, astudy of Trump's tweets and we just,
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just didn't find that muchtrends that he could Trump. So like
Trump the trends and this timeI feel like it's different like this
presidency. And I think that'swhy we had such a big shock is that
people were expecting Trump2.0 to be the same as Trump 1.0,
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where it was a talk aboutmedals and this and that and we did
see moves in medals in thefirst presidency, but I think it
actually signified a muchlarger global change in geopolitics,
a larger change in supplychain and trade dynamics as well
as sort of a change in evensome of the alliances and the way
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people see things. And I thinkthat is one of those situations for
trend where the initial shockis often bad because it's based on
rhetoric and people realizingthat change is coming. What I'm looking
for is much more fundamentalbased information. So for example,
you mentioned copper, likesaying that you have a tariff on
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copper fundamentally shoulddirectly linked to copper. And so
as we see that sort offundamental data sort of show us
where the new direction is,then we should see trends in asset,
asset classes that as thatTrickles out. Not a shock.
No, but my point is. Yes, butfor me, although it feels nice right
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now because managers along andcopper's going up because it's not
a fundamental. In my world,it's just Trump saying this and then
next week he might say, oh,no, we don't need that tariff anyway.
And then it's going to. So I'mhoping for something a little bit
more substantial than atariff, frankly. But it does lead
me into one thing, I thinkthat is in your paper and also, and
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that is that recoveries areoften linked to kind of an real narrative
change, kind of not just, youknow, a few data points. It's kind
of we're going in a differentdirection here in a broad range,
and that kind of leads to thenthe recovery. Maybe one way I could
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explain that or visualize thatwould be you mentioned that the CTA
winter, the change that led toa very, very strong recovery was
of course, the change ininterest rates and how they had been
behaving for so long. Andsuddenly we realized, oops, they're
heading higher and they'reheading a lot higher.
While we're dating ourselves.The CTA winter was in 2010-2014.
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Niels.
Oh, that's the winter. Ithought it was the 15 to 19.
No, no, no. What do we callthat? We actually called the CTA
winter because that's thesecond longest drawdown was that
period before 2014, beforeenergies exploded. It's hard to remember
it, but it was post GFC wherethe world had recovered and everything
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was good and then everythingchanged in 2014.
What do we call then, the 15to 19 period? If it wasn't a winter?
Was it like Autumn Trade War 1.0?
Oh, that's the. Okay, ofcourse. Yeah, fair enough.
I mean, aren't these greatnames? I love them.
Yes, yes. Well, it getsconfusing when you have to put labels
on every drawdown or flatperiod of return.
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It does. There's a lot of backand forth coming up with these names
because you have to kind ofthink about what is going on in the
world. And it's not equityfocused, it's CTA focused. So.
Yeah, no, and one thing I willsay the main. One of the key takeaways
that kind of shows up when youlook at your, like the first chart,
I think in your, in your paperthat, that you look at, I think it.
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Which is really importantactually. And that is when you look
at CTA drawdowns and they arelisted next to drawdowns in equities
I mean CTA drawdowns are somuch smaller than equity drawdowns.
So I mean there's nocompetition here and I think give
us a hard time because theindex is down 20%. This is nothing
compared to a 55% drawdown inthe S&P 500. Let's be real. And so
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I think CTAs do a good job inmanaging the downside. Generally
speaking, of course individualmanager returns will be different,
but I think as an industrywe've always done pretty well because
and this was a statistics thatI mentioned last week with Alan,
which I think was reallyinteresting and that is if you look
at the rolling and this isfrom the recent man paper. I don't
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know if you read that, but ifyou do, give me your thoughts afterwards.
But the rolling 12 monthsreturn that are less than minus 15%
for the CTA index and this wasat the end of April, that could be
the number was two, but itcould be three now or four. I don't
know. But it's pretty small.Compared to the rolling 12 months
number that are more than plus15%. I think that number is like
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59. So I think we are in goodshape even though we get a little
bit of heat at the moment interms of the return. But feel free
if you have anything that youtook away from the man paper. Otherwise
I have one thing before wemove on to the next topic that I
wanted to put to you.
I mean, I think for me this isa really good question. I mean I'm
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just going to finish one pointon drawdowns. And I think people
always ask me, you know, howto time trend. They say like, oh,
you know, is there a timewhere you can find predictability
and this and that? And I say,you know, that's a really tough thing
to do, especially from theoutside. I call it trend following
squared. So trend following,trend following. I do not advise
(31:48):
it. The only thing that I tendto talk about is this concept more
of rebalancing because thestrategy tends to be mean reverting
over longer time horizons. Andthe reason this paper is helpful
is there's plenty of timeswhere the strategy has had a 20%
(32:08):
drawdown. There's plenty oftimes when it's been 15 to 17%. And
if you look over longerhistories, the strategy has done
well. So the key is youshouldn't time, but you should rebalance.
And that's what we see a lotof institutions understand is that
when they've made big profitsin a 2022, they adjust their allocations
(32:31):
and buy equities when equitiesare low. And then you know, in a
time like this we've actuallyseen, you know, definitely why investors
are not moving managed futuresor you know, understanding that is
that this is exactly the timewhen you don't, you know, want to
get out of managed futuresbecause it's mean reverting over
long time horizons. Ifanything, it might be an opportunity
(32:53):
and to, to kind of rebalanceto prepare for potential recovery.
And that's what the end of thepaper finishes with is just kind
showing how incredibly strongthe recovery period were once they
started. So I think our bigquestion, Niels, is when does it
start?
Oh yes.
So if you can tell me that I'msuper happy, I can have a nice vacation
(33:16):
this summer.
Yes, we'll definitely explorethat as we go along. But you're absolutely
right. I will say though frommy 35 years of experience in this
industry, I will say I don'treally see many investors rebalancing
like you talk about,unfortunately. I would love to see
(33:37):
a lot more. It is just a hard.
I see some on the upside forsure. I think there's an asymmetry
there.
I've seen the opposite. I seethe opposite. I see people selling
trend after it's done well. Irarely see people buying trend when
it's done poorly. But thistime might be different as they say.
(33:58):
I do want to finish withsomething along those lines and that
is, and this is a little bitof a left field thing. Right. But
there's a lot of quote unquotewrite ups at the moment about the
challenges of CTAs and trendfollowers. On the other hand, if
you're looking from theoutside and you kind of say okay,
(34:20):
how do I put together aportfolio of different strategies
with my bonds with myequities? I still have not seen a
paper that has come up with abetter alternative to trend following.
So maybe you can spin on thata little bit because I think it is
important to remind peoplethat this is still pretty valuable.
Yeah, I mean I think thechallenges and it was interesting
(34:42):
because you had flagged thisinteresting man paper to me about
regimes and sort of thisconcept that you, you have a non
parametric approach todetermine what regime we're in. Talking
with some of my peers aboutthis, the only one thing that really
stands out when you look atthe data as something that kind of
(35:02):
naturally connects nicely withequities where most people are holding
growth and equity exposure istrend following because it's fundamentally
very different so if you lookhistorically, and even my drawdown
paper kind of shows that isthat it's one of the few things that
tends to, on average, do wellduring periods of distress or challenging
(35:25):
equity markets. And I thinkthat kind of shows that, you know,
and it's not, you know, asilver bullet. You know, that's why
you see a lot of theseinstitutions that have, I think,
rightfully had a morediversified approach to that. They
say, you know, I have my, youknow, my first responders, my second
responders, my thirdresponders, and they're just trying
(35:46):
to put together portfolios ofthings that are different that might
be offensive in a defensiveenvironment. So really, I haven't
seen a lot of. Besides,obviously there's always papers that
find P values that aresignificant, but there's really few
things that have therobustness of a trend strategy combined
(36:10):
with equities as acomplementary investment. And I think
even CFM had some greathistorical papers on that as well,
talking about skew. And Imean, it's just really one of the
few. It's just sometimes it'shard to hold a trend. And I think
that's why people have to justlook at the empirical evidence to
kind of understand why they'redoing it, why you and I have been
(36:34):
in this space for a long time.
Why you and I are still doingit. Because nobody else wants us,
Katie. That's why we're stilldoing it. You know, that, that. Anyways,
no, but, but listen, if youare combining your equity portfolio
with something, isn't itfantastic that at least typically
that something does poorlywhen you are doing so great on your
equity port? I mean, youcouldn't ask for more, really. I
(36:56):
mean, it would be a lot worseif it always did poorly when your
equities were doing poorly.Frankly speaking. I mean, that's
just common sense. So, yeah,I. But you know what? It is also
because a lot of people liketo look at individual line items
rather than looking at whatthe effect on the portfolio is doing.
And they use sharp forsomething they should never use sharp
for and all of that stuff. Soanyways, we will. We'll continue
(37:20):
our little fight, Katie, tohelp people perhaps appreciate more
this little space. So beforewe move to that paper you just mentioned,
regimes, which I do think youwant to say a few words about, there
(37:41):
is this other thing that Ithink is somewhat relevant maybe
for people to understandwhat's going on. And I think cfm,
some years ago, Jean PhilippeBourgeois wrote about exogenous shocks
and impacts on cto. CTAperformance versus endogenous. So
(38:01):
things that comes from insidethe system and not from the outside.
And in a sense, what isinteresting is that what we've seen
this spring with LiberationDay and so on and so forth, these
are kind of coming from theoutside. This is in this case Trump
coming up with tariffs and soon and so forth. And comparing that
(38:24):
to something that, forexample, happened in the 2022 recovery
of CTAs, where this was reallymore structural. It was positioning
that was, you know, on the, onthe wrong side in a big way between
expectations of interest ratesand where they were going and so
on and so forth. So what areyour thoughts? Or is it something
(38:46):
you even take into accountwhen you talk to people about the
different types of impact tomarkets and how that reflects back
on the CTA industry? Is itimportant to understand the difference,
do you think?
I mean, I think it'simportant. I think each. I do agree
that exogenous shocks are muchharder to predict. But there's also,
(39:13):
they're sort of, sometimesthey can be gray swans as well, you
know what I mean? So like, youknow, an exogenous shock is something
that's not with, based on yourdefinition, something that's not
inside the financial systembased on sort of of, you know, NPV
and you know, monetary policyand whatever. But I do see that,
(39:33):
you know, exogenous shocks canactually, depending on how they propagate,
can be positive for CTAsometimes if they extend. So what's
challenging is I think anexogenous shock that is not sustainable
in shorter term, that just issort of a whipsaw. Those are the
worst. And so, you know, ifyou think about certain exogenous
(39:58):
shocks like Covid, it was notanywhere as bad as say Liberation
Day for CTAs. And why is thisthe case? So Covid, even though we
didn't understand themagnitude of that, people did start
to understand before that thatthere was going to be issues with
supply chains. They did startto understand that people would be
(40:19):
afraid, so they started buyingbonds. So there were some interesting
trends that actually leakedout in other asset classes in Covid,
whereas that exogenous shockreally was an equity specific exogenous
shock. I would say the recentexogenous shock from Liberation Day
was perhaps more pervasive inthe fact that it really went across
(40:42):
multiple asset classes in away that kind of completely showing
like, okay, trade policy ischanging completely and, and that
really affected the dollar. Itaffected sort of people's perception
of what was to expect of theNew administration. And I honestly
think right now, even thoughwe have these shocks like copper
(41:03):
tariff this and that, themarket is much more reticent to react
because the change and theshock has already occurred. So I
think the endogenous shocksare coming based on what you said.
So the endogenous shocks ofmaybe a change in monetary policy,
maybe inflation, that has tobe control or. And that's where,
(41:24):
you know, endogenous shockstend to be more positive for trend
perhaps because it's, it'sreally a fundamental based shift
in sort of how people arevaluing assets and what they're worth
based on sort of fundamentalmacro regime. And so I think that's
for me why, you know,exogenous shocks are sort of, we
(41:45):
always remember those dates. Imean, I remember really weird things
like, like, you know, oneweekend where Italian bonds blew
up. You know, any exoticshock. You, you remember them? They,
they. We wrote a great paper acouple years ago on turbulence and
actually that man papermentioned the turbulence metrics
and you can think of those asmagnitude shocks actually. Yeah,
(42:10):
magnitude surprise.
Yeah. And I also think, andthis is something that obviously
goes to kind of why trendfollowing works. And this is the
thing about that. Well, we allget the news at the same time, but
we kind of digest it atdifferent speeds. And I think a tariff
announcement is probablyeasier for everyone to understand
(42:32):
straight away. Oops, thingsare getting more expensive. Covid,
I think was more difficult toquite understand quickly what that
would mean. And it gave us alittle bit more time to position
ourselves in that case,getting short energies and so on
and so forth. So you'reabsolutely right. There's a couple
(42:53):
of things where I'd like tojust mention, and that is you would
think that within the CTAspace, short term models, short term
managers would handleexogenous shocks better than long
term. I think that seemsreasonable and vice versa this time
(43:14):
around. We saw it play outreasonably well in April, short term
doing better like it shouldcompared to long term. But actually
it's kind of completelyreversed in the last couple of months.
Now you may run different timeframes. I know you're not a short
term manager, but you may runmodels with different time frames.
I mean, is that also kind ofhow you've seen it internally rather
(43:37):
than what I can see in theofficial performance numbers between
managers that it has beensomewhat harder to deal with?
For short term, it's all abouthow long. Right. I mean, because
we saw short term work reallywell in Covid, because I'm not talking
like intraday I'm talkingabout, you know, shorter term, like
(43:58):
a month or two. But inLiberation Day it was really just,
you know, a three day move.Two or three days, I mean, and that
is very hard to statisticallyto adjust to with data. So I think,
you know, from a horizonperspective, it's very hard to find
(44:19):
significant signals based onsuch time horizons, depending on
what your trading horizon is.So I think that was why it was so
hard. It was very hard too. Itjust, it wasn't like three days and
then the trend continued, itwas three days and then it bounced
back and you know, and thennow we're back to everything's up
(44:39):
again.
So yeah, we certainly are.Well, you kind of alluded to it already
and you will probably haveread this a little bit more carefully
than I have, but I do think itwas an interesting concept because.
And I'm talking about thepaper regime written by some of our
previous guests, Cam Harvey,Otto Van Hermit, both link. Well,
(45:03):
Otto is at AHL and Cam islinked to Agile, but there's a few
other people involved in thepaper so I'm only mentioning them
because they have been linkedto the podcast anyways. But of course
it is interesting becausewouldn't it be wonderful if we could
(45:25):
detect in advance what kind ofenvironment we were going to be in
as trend followers? We couldsay, oh, if it's a web soaring environment,
let's reduce our risk a bit.If it's something that with lots
of momentum, let's increaseour risk. Now in a way our models
are actually trying to do thatin their own way. But in this paper
they're taking a verydifferent approach which I'd love
(45:48):
for you to explain. I'd loveto hear your opinion about what you
think this could do or not ina trend following world. But yeah,
I'll give you the floor.
I really like the paper. Imean I'm obviously a big fan of anything
non parametric, which is trendis supposed to be a little bit more
(46:09):
non parametric in some sense.
Can you explain that? What doyou mean by non parametric?
So non parametric means thatyou're not sort of defining parameters
to define regimes. So becauseit's really easy for us to go back
and I do it myself like andsay this is rising rate regime and
this is a falling rate regimeand by defining those things you
(46:30):
automatically create sort ofbias in your results and it's all
over in academia. So it's, youknow, it's sort of like everywhere.
I do appreciate their idea tokind of Just say like, we don't know
what these regimes are, but weknow that there's some key variables
that are important. Of course,your first question, if you were
(46:51):
reviewing this paper was, andthey talked a little bit about this,
is what are the importantstate variables? And the reason they
get criticism about this isbecause when you're looking for important
state variables, you alreadyknow which variables are important
after you live through theseenvironments. Like Copper was one
of their factors. Right. Soeither way. But the idea is very
(47:12):
simple and it works like this.If you look at this month and you
take these key seven statevariables, and so it's things like
equities, it's the shape ofthe yield curve, it's volatility,
it's seven of these sort ofcommon things like also your friend
Copper's in there too.
Yes, Dr. Copper's in there too.
Yeah, so exactly. And you takethose values, of course they do Z
(47:37):
scores and they look atrolling adjusted volatility as a
function of the changes inthose variables. And then they look
at sort of what are the levelof these key variables. And then
what they do is they look atwhat they call what is known as a
Euclidean distance measure ora measure of similarity. So you can
imagine a seven dimensionalstate space with those seven variables
(48:00):
on seven dimensions. I can'tsee in seven dimensional space. I'm
trying to imagine that, butwhy not? So imagine you have this
seven dimensional space andthen you look at every single point
in history and you measure howfar away is that seven dimensional
dot of this month from all themonths in the past based on those
(48:21):
state, state variables likeequities, whatever. And the fun thing
with this is you're kind ofdefining how similar is this month
to any historical month inhistory. And then you kind of can
rank based on the distancemetric, you know, any months that
are closer to what's happening today.
So let's say, so in mysimplified world, that means if we
(48:44):
look at Liberation Day, thatperiod, and they will go back and
say, okay, have we experiencedsomething similar before?
Exactly. But they're going touse some math to define what that
similarity is. And it's notthat complicated, but it's like basically
a distance metric. And so youtake this particular distance metric
and you look at all ofhistory, it's basically a filtering
(49:04):
mechanism, right? So like yousay June, which months are most like
June based on some keyimportant variables. And then you
take those similar variables,those similar periods of time, and
if you're looking at aparticular strategy, this is where
it gets a little complex, thispaper, and there's a few details
that I would like to grillthem on to understand implementation.
(49:29):
But basically you look andsay, okay, in a month like June,
does value do well? Does trendfollowing do well? And then they
look historically at thosesimilar events, see, so it's a little
bit of a filtering strategy,right? And then you use those similar
events and then you determine,well, if it did well in all those
(49:50):
past events. We assume thatregimes are somewhat persistent.
So for next month, let's saythat value's gonna do well instead
of trend, for example, or theopposite, depending on what historical
performance is. And so it's away to kind of classify whether or
not it's a positive ornegative state for a particular strategy.
(50:13):
But this is pretty complex,right? Because you're basically like
looking at all history andthen you're going to say for all
the times where the world waslike today, let's go long, miss.
Right. If it worked in thepast. And so it, I was just going.
To say I've come up with abuzzword for this while you've been
talking. It's regimereplication. I mean, replication
(50:35):
is so, you know, it's so up.Everyone loves that one in our time.
Everybody loves replication.So this is regime replication, right?
Well, I would just say, Imean, it's just a method of historical
filtering.
Sure.
Right. And it's a method thatdoesn't require you. Because here's
what I meant by nonparametric. You could come up with
(50:56):
rules, right? So whenever theS and P is up and the yield curve
is above a certain steepnessand the VIX is here, you come up
with all these huge parameterspace of decisions. You're very likely
to fit history and look likeyou're the smartest person ever.
Because basically you couldpick like, well, whenever the VIX
(51:18):
is about to go up, then we'regoing to be long equities. I mean,
you got to do that on a walkforward basis. So I think there's
the positive and why I thinkthey wrote this paper is they like
the non parametric approach aswell. My concern, and I think I have
a homework assignment fromthis is I would like to see how trend
(51:39):
to do a very similar analysisand look at trend because I'm pretty
certain you're going to seesome regime connection between trend
and certain sort of morerecessionary regimes. And that goes
back to the paper that Italked about for fixed income where
we actually showed like, youknow, trend tends to do well. And
this is just for Fixed incomeduring an inverted yield curve environment.
(52:03):
And so you could see thatconnection to those state variables.
But this is done in a more nonparametric way than the way that
I did it, which is more ofsort of a historical study. It wasn't
a trading strategy, it wasjust a historical analysis.
Yes, I mean, in a sense, andcorrect me if I'm wrong here, what
makes it kind of interestingalso is that this is not really kind
(52:28):
of macro analysis. It's morebehavioral analysis of what actually
happened.
Yeah.
Would you say.
I would say that it's notmacro in the sense that it's basically
data filtering, Right?
Yeah.
So it's using, I guess theonly macro side you might say. And
that's where if someonereviewed this paper, the first thing
(52:50):
they'd say is you have theseseven variables. But how many did
people try to use? And youknow, maybe you tried 70 and those
seven work. Right. If youtried 10 and those seven work, then
that's a little better. Butyou know, they try to make the argument
that people knew that thoseworked much more historically. I
(53:11):
don't know, I didn't talk tothem about this. But you know, you're
correct. There is still somelike macro connection. It's just
done in a purely empirical way.
Yeah, Katie, thanks for doingthat. I have one other little small
surprise that I didn't tellyou about. So you may not want to
comment on it, and that'sperfectly fine. But one thing that
(53:34):
also could have been under my.What I've noticed this year is of
course that replicationstrategies have done quite a lot
better than the benchmarksthey're trying to replicate. And
last month I think was prettynoticeable, frankly. And I know Andrew
(53:56):
is coming on in a couple ofweeks, so I'm going to tease him
a little bit by saying this,but hopefully it'll inspire him to
push back, I'm sure. And thatis my understanding of replication
is that it's trying to givepeople benchmark returns, hopefully
a little bit better because ofsome cost savings. Great. Fantastic.
(54:19):
Okay. Well if you're trying toreplicate that, it also introduces
another question that is howaccurate can you actually replicate
the benchmark? I think thatwould be a natural question to ask.
Now the fact that they haveoutperformed this year is fantastic.
(54:40):
It's great for the investor.So well done on that. But it does
introduce two questions forme. So either we must admit that
there is a big tracking error.Right. So either they're not tracking
well enough or we could startthinking about this as another alpha
(55:01):
Strategy, it's just using adifferent input. So instead of really
saying, well, this isreplication, no, this is kind of
competing with everyone else,it's an alpha strategy. We are just
choosing to use a differentinput, you know, based on historical
returns, et cetera, et cetera.But really there shouldn't be a difference.
So I don't know if there is areal question. I don't want to put
(55:22):
you on the spot, but I dothink this is really interesting
to me.
Oh, I think it's superinteresting. I mean, this is why,
you know, actually we had arecent paper that we talked about
before as well a couple monthsago where we looked at replication
techniques. So I candefinitely point any investors to
that because it actually talksabout some actual metrics. I mean,
(55:45):
you put me on the spot andthat I don't, I didn't memorize the
results. So like, I don't, Idon't remember the exact tracking
error, but we actually doreport tracking error for index rep
for replication. And you know,something that, you know, when thinking
about replication, trackingerror is something that we're actually
monitoring in our space. WhatI would say about the relative outperformance
(56:11):
of replication recently, it'snot that extreme for the index for
some of the methods that thispaper looks at, for example. But
what you do see is replicationhas a few key features. First of
all, it tends to be a littlebit more slower. So it kind of, you
(56:31):
know, and this paper actuallytalks about the pros and cons of
different types ofreplication. So anybody wants to
nerd out on it, it's a greatone. But basically, you know, most
of the replicator strategiesout there are a little smaller in
asset set. They also aretending to be more slow in terms
(56:51):
of, of, you know, how theymove. And so if you look at some
of the environments of thelast year, you've had some really
big exogenous shocks. And Ithink being, you know, if you think
about yourself like your ownequity portfolio, hopefully you didn't
trade around Liberation Day.That's a very slow moving strategy.
(57:12):
So if you're slower, youprobably didn't react as much to
some of the data that occurredin, in the Liberation Day shock,
which helped to kind of becloser to kind of the average return
of the space. And what we'reseeing is, you know, tracking error
is kind of within range for,for what we expect based on the methodologies
(57:34):
that we talk about in thatpaper. So I'll definitely turn anybody
to that paper who wants tolook at that. We haven't updated
it. But let me ask you, let me.
Follow up on this a littlebit, if you don't mind. And that
is two things. Things. One is,well, if it's just because by definition
replication is slow because ithas to wait for the data, etc. Etc.
(57:56):
You could also say, well,okay, it's luck, right? They've just
been lucky this time aroundthat they were slow and next year
it could be different. So,okay, I understand everybody's lucky
sometimes. Absolutely. Ofcourse, I don't mean to say that
they're weak. We can be luckyas well, being on the right side
of a move.
(58:17):
I would say, okay, I want tomake one clarification point about
the slow part. For me, thespeed, and that's why we talked about
this in our paper, is there'sdirect implication. We call it mechanical
replication versus indexbased, regression based replication.
And so regression based isreally sort of looking at the past
(58:39):
and that is, is the slowestapproach. If you combine some of
these approaches, you getsomething that's a little more hybrid,
that can be faster ifnecessary to try and track the index
or track, you know, typicalCTA performance or of large CTAs.
Whereas, you know, I thinkwhat we have just seen is that there
(59:01):
has been, you know, extremeshocks which maybe was, is just better
positioned in those type ofmoves and the smaller, like the market
set, which is much more. Thedeveloped markets has outperformed
too. So there's a couple offactors in there. I wouldn't say
call those things luck becauseI think then everybody gets lucky
(59:22):
sometimes. My view is thatthere's just different market regimes.
If you were trying to tradeCoco two years ago, like replication
cannot pick that up. So Ithink it just varies over time.
Yeah. Okay, final question,promise. And that is should investors
think about some kind of bandplus minus x percent quote unquote,
(59:46):
tracking error? When is ittracking error? When is it just,
you know, within the norm, soto speak? Because I do think we need
to define it a little bit moretightly as we see more and more of
these products coming out.Because as I said, I'm starting to
feel a little bit that some ofthis could be regarded as a separate,
(01:00:08):
just alpha engine because Ifeel that it's very loose in terms
of replication or in terms oftracking error. But how should I
think about that in your view?
I definitely think it's verywell defined. We explain it in the
paper and we actually documentthe tracking error. It's something
(01:00:29):
we monitor. It depends on howyou implement it. Of course. So the
challenge for the investor isreally understanding how the replication
techniques are implemented,what type of things, their kind of
inputs and how they're tradingso that they can actually measure
tracking error. And you willsee variation in tracking error as
(01:00:52):
a function of your approach.So let's say that for example, if
you're using a wider marketsize debt, like let me give you a
simple example. True, ifyou're running a replicated replication
strategy that has no Europeandebt and only trades us, you're going
to see variation where youdon't capture those European moves,
(01:01:13):
so your tracking error will behigher. There's sort of a dance though
between like how many marketsare necessary or not. And that's
why that paper, you know, Inerded back to that paper again there.
We see pretty consistentresults out of sample for us within
tracking and replicationtechniques. And I'd say that it's
(01:01:35):
just a very different product.Especially what we've seen is some
clients say it's just anotherstrategy that can be combined with
other CTAs that might smooththe overall dispersion that you see
across even replication techniques.
All right, well, this wasgreat as always, thank you so much
for writing, writing the paperand for all your thoughts and insights.
(01:01:59):
As usual, Katie, I'm sureeveryone listening right now feels
the same. And if you do, whydon't you show that appreciation
by going over to your favoritepodcast platform and leave a rating
and review praising Katie tothe moon. Of course. Next week we've
got another great guest. It'sJim Kassang, who's back. I'm sure
(01:02:20):
people will be interested tohear what he's thinking right now.
He's made some very bold callsthis year. Not that we spend too
much time about predicting thefuture, because of course, in the
systematic world we realizethat we can't predict the future.
Anyways, if you have aquestion for Jim, then it's your
chance to email it to me,infooptoptraders unblocked.com and
(01:02:40):
I'll do my very best to bringit up with him. With that said, from
Katie and me, thanks ever somuch for listening. We look forward
to being back with you nextweek. And until next time, take care
of yourself and take care ofeach other.
Thanks for listening to theSystematic Investor podcast series.
If you enjoy this series, goon over to itunes and leave an honest
(01:03:02):
rating and review. And be sureto listen to all the other episodes
from Top Traders Unplugged. Ifyou have questions about systematic
investing, send us an emailwith the word question in the subject
line toinfooptoptradersunplugged.com and
we'll try to get it on theshow. And remember, remember, all
the discussion that we haveabout investment performance is about
the past, and past performancedoes not guarantee or even infer
(01:03:24):
anything about futureperformance. Also, understand that
there is a significant risk offinancial loss with all investment
strategies, and you need torequest and understand the specific
risks from the investmentmanager about their products before
you make investment decisions.Thanks for spending some of your
valuable time with us, andwe'll see you on the next episode
of the Systematic Investor.