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A Guessing Game: FinTech, Hedge Funds & The New Normal (w/ Chris Alexander) | Tech Trends - YouTube
Channel: Real Vision Finance
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[music playing]
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CHRISTIAN ALEXANDER:
10 years ago you
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could go to a big hedge
fund and say, hey,
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how do you think about
allocating your broker wallet?
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And some of them might say we
don't know and we don't care,
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which is to say as long as we're
making money, it runs itself.
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Having had three years
of mediocre performance,
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that business model
doesn't work as people
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had to reconcile
specifically the stuff that
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doesn't necessarily drive
revenue-- so analysts, traders,
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and all of this stuff you might
generally class as the support
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apparatus, which means they
have fewer luxuries around,
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and those who provide those
luxuries are less in demand
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versus everybody is looking
to find the next best
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trader that nobody has spotted
yet that has the good track
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record, that has the sort of
clean reputational background,
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which is a big deal.
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And that means then
the hiring market
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has become a whole lot of
people who everybody has passed
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on that continue looking
in vain for work and three,
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maybe four celebrities that come
out per year from someplace--
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tried to start a fund.
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It didn't work.
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Go back into free agency and
land somewhere at a name brand.
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ROGER HIRST: The changes that
we've seen, do you think that--
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and probably most
people say, look,
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these are all interconnected.
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But things like the difficulties
that the traditional macro
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hedge funds have
experienced, is that the rise
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of passive investing?
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Is that the rise of--
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CHRISTIAN ALEXANDER: Yes.
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ROGER HIRST: --the
robots and AIs--
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CHRISTIAN ALEXANDER: Yes.
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ROGER HIRST: --the
rise of central banks?
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Are they all interconnected?
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What is the interplay
that's kind of--
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because we've seen, if you look
at the active versus passive
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and that massive flow--
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I think it was $3 or $4
trillion from active to passive.
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That's a big trend.
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What's been the
driver behind that?
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Because that whole
active universe--
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not just hedge funds but
the whole active universe
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is under duress.
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Which do you think
or do they think
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is the real driver behind it?
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CHRISTIAN ALEXANDER: Well
look, I think all of them
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are paranoid about
the presence of robots
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and artificial intelligence and
machine learning in the market,
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and one of them
specifically has said,
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hey, this is the time when
I think Kasparov starts
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to get beat by Deep Blue.
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So there isn't anybody out there
who isn't paranoid about it,
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aware of it, and either has
an ambition to totally replace
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themselves with server towers
or to have half of a business
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of server towers and half of a
business of human beings that
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look for the common
idiosyncrasies of the server
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towers to do what humans do
better currently than machines,
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which is to work around what
[inaudible] the programmed
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systems cannot operate by.
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ROGER HIRST: And with these sort
of trends we've been seeing,
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I think when I look
at that and when
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I think about the
difficulties that we've
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seen these trends propagated
by the central bank--
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now a lot of the sort
of bots is looking
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at kind of data behind us and
extrapolating out forward.
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Isn't the whole point
of where macro is great
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and where macro-hedge-fund
managers should kind of have
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their edge is the human emotion?
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It's human frailty,
weakness that
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create the turning points
where the big wins are.
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That's what these guys have
always been great at spotting.
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I mean, a computer
doesn't have an emotion--
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[interposing voices]
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CHRISTIAN ALEXANDER: If
you go back 15 years ago,
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there wasn't as much integration
in the global financial system,
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and so then central banks,
if they took action,
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might act on their own.
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So then you had idiosyncrasies
in the macroeconomic world that
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tied default-- the Asian
crisis, the Russian default.
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You had all of these things that
could happen and catch people
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by surprise.
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So those that had studied
it and knew about it
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and positioned for it, or
studied it, had an opinion,
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and portrayed on around it could
make extraordinary windfalls
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around specific events.
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After '08, there was such
a global rally to arms that
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central banking itself I think
became much more integrated
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because all of them now act in
synchronicity with one another
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and certainly consider what the
counterpoint of what they do is
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how does their move impact
their relative interest rate
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differentials, their
currency, all this stuff?
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And then if you
have to consider all
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of those things--
and further, you're
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in contact as part of a
generalized global support
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apparatus.
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It limits the ability
for central banks
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to act as autonomously
as they used to,
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and it means that
effectively there
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is much more of a
global central bank that
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is organized by a committee
of the big central banks.
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And then post '08 you had
this extraordinary amount
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of intervention, and that then
meant that the human impulse
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driven by policymakers
and markets became much,
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much bigger than it used to
be because now you have three
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decision makers, maybe
four decision makers--
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Fed, ECB, PBOC, BOJ.
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And to the extent
that those four
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are all in constant
contact and considering
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what their move means
for everyone else,
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I'd say it's kind of
like in university we
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used to play this
game called roshambo,
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and you do rock,
paper, scissors.
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And in time you become familiar
with the other guys' moves.
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And so if I know that when
I beat you with a paper
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you might throw a scissor,
then I might throw a rock.
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But then you know I
might throw a rock,
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so then you throw the paper.
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So then I throw the
scissors, and you
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play that game of
infinitely guessing
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what the other party is
doing, so like spy versus spy.
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And since 2015,
really the market's
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been reduced to guessing what
is that handful in the apparatus
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going to, and what
we've established
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is that even if you can predict
what they're going to do,
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the market move might be
contrary to your expectation
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because so many people
have predicted it,
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so then it just becomes
the roshambo game, which
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is my personal view on why
macro funds have struggled
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from that big ECB move where
everything went haywire
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at the end of 2015.
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From that point on, it
has been exceedingly
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difficult to make
money, and the places
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where people have have
been in day trading, which
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you can argue that robots
do better than humans now.
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