Ever wondered how market psychology shapes investment strategies? In our latest episode, we have the pleasure of hosting Laurent Bernut, whose extensive career spans from the diplomatic halls of the French Embassy to the fast-paced realm of Japanese capital markets and hedge funds. Laurent takes us through Japan’s economic landscape, describing the current inflation, a weakening yen, and an ongoing real estate surge. He also sheds light on the investment opportunities within Japan's craftsmanship industries and the evolving openness towards foreign capital. Whether you’re an investor or merely a market enthusiast, Laurent's insights offer a treasure trove of valuable information.
Shifting gears, we explore the intricate dance between bull and bear markets with a focus on sector rotation and understanding beta. Laurent details how different sectors, such as consumer staples and technology, react to market changes and why adjusting long and short positions is crucial for risk management. We delve into the concept of net beta versus net exposure, offering strategies to optimize investment performance amidst fluctuating markets. If you’ve ever been curious about the mechanics of stock performance and the importance of market regimes, this segment is packed with actionable insights.
To wrap things up, we delve into the psychological dimensions of trading, particularly the concept of toxic shame and its profound impact on traders. Laurent shares compelling personal anecdotes, showing how self-worth can either fuel success or lead to self-sabotage. We also tackle the challenges of short selling in volatile markets and why position sizing is vital. As a special treat, Laurent gives us a preview of his upcoming book and the invaluable lessons it promises. This episode is a must-listen for anyone keen on understanding the deep connections between market dynamics and trading psychology. Don’t miss out!
The content in this program is for informational purposes only. You should not construe any information or other material as investment, financial, tax, or other advice. The views expressed by the participants are solely their own. A participant may have taken or recommended any investment position discussed, but may close such position or alter its recommendation at any time without notice. Nothing contained in this program constitutes a solicitation, recommendation, endorsement, or offer to buy or sell any securities or other financial instruments in any jurisdiction. Please consult your own investment or financial advisor for advice related to all investment decisions.
Sign up to The Lead-Lag Report on Substack and get 30% off the annual subscription today by visiting http://theleadlag.report/leadlaglive.
Foodies unite…with HowUdish!
It’s social media with a secret sauce: FOOD! The world’s first network for food enthusiasts. HowUdish connects foodies across the world!
Share kitchen tips and recipe hacks. Discover hidden gem food joints and street food. Find foodies like you, connect, chat and organize meet-ups!
HowUdish makes it simple to connect through food anywhere in the world.
So, how do YOU dish? Download HowUdish on the Apple App Store today: Support the show
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:08):
My name is Michael O'Gaia, publisher of the Lead
Lager Board.
Joining me for the 40 minuteshere is Mr Lant Bernou, who's
kind of built a bit ofreputation on the quant side and
on the short selling side, aswell as the market psychology
side, as well as the marketpsychology side.
So, laurent, introduce yourselfto those who are watching and
listening.
Who are you, what's yourbackground, what have you done
throughout your career?
And are you a night?
Speaker 2 (00:32):
owl.
I'm actually an early bird.
I wake up at five, so this isgood.
I'm sorry if I won't be verycoherent.
I will try my very best.
So my name is Laurent Bernu.
I was born in New Zealand.
I grew up in New Colonia, whichis a French territory.
(00:52):
I've been living in Japan forabout 28 years.
I started with French Embassy,Then I worked as a Japanese
accountant, so I used to doconsolidation and all this in
Japanese.
Then I joined the capitalmarkets in 2001, right around
the time when because at thattime there was Enron and
WorldCom, so people wanted toknow what a balance sheet.
People finally discovered thatit's not only earnings per share
(01:16):
but it's also cash flow andbalance sheet.
And then I joined a hedge fundin 2003.
I worked with Trudelity.
At Trudelity, my mandate was toshort-sell, so my mandate was
to actually underperform theworst-performing market on
record.
And I published a bookAlgorithmic Short-Selling with
(01:38):
Python.
The second edition will come.
At that time I was a very poorprogrammer.
I'm still not great, but I'mtrying.
Also, I do real estate as wellin Japan, and that's it.
Speaker 1 (01:58):
So that's a lot.
We're going to cover a bunch ofthings in that.
Since you mentioned Japan atthe start, I feel like I want to
touch on Japan just a littlebit, because you're actually
living there.
Is there really an economicboom going on or is this just
nominal inflation?
What is the mood in Japan?
I mean the things I seeanecdotally around inflation and
(02:19):
in general that being a highsaving economy does not seem to
be all that positive in generalthat being a high-saving economy
does not seem to be all thatpositive.
Speaker 2 (02:26):
Oh yes, so that's a very good question.
I mean I had friends fromThailand, somebody from Thailand
coming over to Japan and saidI'll buy the sushi, it's so
cheap, thanks.
So yeah, the Japanese yen hasbeen as torpedoed, has really
sunk compared to all othernations.
(02:48):
There's a boom in, I meanthere's certain assets.
I mean, of course, the stockmarket is booming.
Inflation is always good forthe stock market, also real
estate, so there's a lot of, Imean the stuff that I do.
When I started real estate,people, japanese bankers and if
you want to solve the globalwarming, you send 100 Japanese
(03:10):
bankers to Antarctica and theNorth Pole and it will freeze
over.
And when I started real estate,they told me like, what's wrong
with you?
Good question, how much timeyou got?
Okay, let's go back to business.
And anyhow, the point was whenI started, people thought that I
was wrong about that and noweverybody wants to do real
estate.
Every other person wants to doreal estate, so there's an
(03:34):
ongoing boom.
Does it have legs?
I don't know, but when Istarted, when people thought I
was crazy, they were right.
Now people think I'm a genius,so I'm starting to unload or
lighten up my portfolio.
That's pretty much it.
The mood Japan is an agingcountry so the mood doesn't
change that much, but it's truethat there's more dynamism
(03:54):
Post-COVID.
There's more dynamism and aweaker yen helps with exporting
nation.
Speaker 1 (04:04):
That's what I see on the ground.
Do you get a sense that it'sit's fleeting the cycle or is
there something structurallythat makes the argument for
Japan to continue its economicstrength and stock market threat
?
I've been highlighting thewhole reverse carry trace since
August.
I've been wrong on that so far.
But I want to talk more kind oflonger term about the dynamism.
Speaker 2 (04:26):
That's a good question.
Well, since a lot of Japanesecompanies I mean a lot of global
Japanese companies havecurrencies overseas, it
naturally inflates that balancesheet and the income statement.
So, yeah, there's a carry tradethere.
As far as the dynamism of thecountry itself, Japan is much
(04:49):
more open to foreign investors.
I've been contacted and I'vetalked to a bunch of people
about there's a change ingeneration.
Some obscure Japanese companythat nobody has ever heard of.
They're making micro-micro,micro screws that are used in
the International Space Station.
There's apparently no one elsein the world who can do it.
(05:11):
So Japan has a knowledge ofself-welfare, a craftsmanship
that is unparalleled, andthere's a shit generation where
those companies are for sale.
I don't know if it's going tolast.
Honestly, I don't know.
I don't know if it's going tolast.
Honestly, I don't know.
I don't make predictions, I'musually not really good at them.
Speaker 1 (05:31):
Nobody is ever good at predictions Not me, not you,
not anybody, definitely not theFederal Reserve and definitely
not the BOJ.
I think is the truism Okay youmentioned.
Now there's one thing you canargue that there is you can
somewhat predict, at least overthe very long term.
You can predict that marketstend to go up.
And you talk about shortselling right.
And the issue, of course, ofshort selling is the odds are
(05:54):
just against you.
And you were in that profession, right, that was your mandates,
right.
So if your performance sucks,it's supposed to suck because
markets go up rates, right.
So if your performance sucks,it's supposed to suck because
the market's going up.
I'm curious in that experiencedid you kind of hate life a
little bit, meaning you knowmarkets just keep doing what
they're doing and you're tryingto bet against it and you're
(06:14):
compensated based on yourperformance.
But how much of it is the betaversus you?
Speaker 2 (06:19):
I'm glad you mentioned this.
I mean, my job was a shortseller in the worst bear market
in modern history, so I had todo worse than the worst market.
I mean I used to go down to theStarbucks on the ground I mean
the ground father Damn, I soenvy your job.
I don't envy your paycheck, butI do envy your job.
So it's a tough job.
(06:41):
With that said, I mean there'sa way to play short selling,
especially if you do relativeseries or cross-sectional
momentum.
Cross-sectional, which meansrelative to the index.
If you look at the index S&P,for instance, there's roughly
50% of the stocks that wouldoutperform, 50% of the stocks
that would underperform.
If you do it in absolute, it'sgoing to be real tough.
(07:03):
Actually, I can show a graph ifyou don't mind, mike.
Speaker 1 (07:08):
May I?
Yeah, yeah, please, let's trythis out and those that are
listening to this, I'll try andnarrate with Laurent here.
Let's experiment and see if wecan get this working here.
Speaker 2 (07:16):
Yes, this one, this one, this one, okay, sure, all
know, this one, okay, share Allright.
So here we go Does it work.
Looks like it's sort of mine,let's try it, there we go.
Okay, so this is chapter fourof the book.
Speaker 1 (07:40):
And the book is about coding quantitative strategies
using Python as a languagecorrect.
Speaker 2 (07:45):
Correct, correct, correct.
So I was a very poor coder.
So this is the S&P 500.
What I've done here is I'vedownloaded just off Wikipedia
this morning, the currentconstituents of the S&P 500, of
the S&P 500, ran a series overhowever many years 2001, I think
(08:10):
and counted the number ofissues that had touched 200 days
as just pure simple trendfollowing, nothing fancy.
So if we and just a lateralcount over time, so this
explains the lag here.
And basically, when it's a bullmarket, what you see is that
pretty much everybody is in bullterritory and very few of those
stocks are underperforming.
(08:32):
Of course, there's a built-insurvivorship bias.
Now, if you do it in absolute,on the other hand, if you do it
in relative series, which isbasically every price divided by
the index, the S&P, what youtend to see is basically the
number of outperformers isroughly 40% to 50% of
outperformers andunderperformers at all times.
(08:53):
So what it means there is thatit's more or less something that
you can do.
All you need to do is okay,let's look at what could
outperform on the long side andwhat could underperform on the
short side.
So we're going further down alittle bit, soft bank, blah,
blah, blah.
So the idea there.
The good news about doing inrelative terms is this is we're
(09:15):
going to okay, same story, butnow it's further broken down
into sectors.
If we look at sectors, you cansee the same dynamic in absolute
.
But if you look in relative,what you see here is a sector
rotation.
So instead of trying to timethe top and time the bottom,
looking at sector rotationreally makes more sense.
And the idea behind this is weall know about defensive sectors
(09:40):
and we all know about cyclicalsectors, which means defensive
would be consumer staples nomatter what you're going to eat
food, there would be utilities,no matter what you need
electricity or water.
Cyclical would be consumer.
Discretionary would beinformation technology and so on
and so forth.
So basically, this is what wehave in absolute and relative.
(10:01):
And then the interesting part isnow when we do the rotation.
So there's just an equal weightacross the board.
Nothing we find is very, Ishould say, naive.
It's very naive, but you cansee the sector rotation.
You can see the defensive inblue, the cyclical in yellow-ish
and then the rotation would bein red and there's a very, very
(10:24):
clear rotation.
That happens all the time.
So cyclical and defensive.
So just timing those andbuilding a very naive index like
this works.
Speaker 1 (10:36):
And right now the far right it's starting to turn.
It's kind of a slow process ofa turn Correct.
Speaker 2 (10:42):
And here's another version of it.
If we look at it here, forinstance, this is ugly.
So here I calculated the beta,and this one crushed my computer
this morning.
I was less than happy.
So same story.
This is chapter 11.
We're talking about the samestory, a download stuff.
(11:03):
I calculated the beta versus theS&P 500 over two years.
So what is the beta?
The beta is a covariance matrix.
So let's say, for instance, theindex moved by 1%, maybe Apple
or Nvidia would move by 2% or1.5%.
This is high beta.
But a utility stock would bemoved by maybe 20 cents, 40
(11:26):
cents so, and it's roughly thesame story.
So the sector that we mentionedbefore, the defensive and
cyclical they will start to makesense here.
Sorry for all the verbiage, myapologies for this.
So what we have here?
Information technology, andsurprisingly again, this is
equal weight across the world.
Very naive way to look at it.
It's not market cap weighted,it's, as of today, the
(11:49):
constituents of survivorshipbias built in Information
technology is 1.4.
Consumer discretionary 1.07.
So these are the cyclicals thatwe talked about before, and at
the bottom, low beta, isconsumer-stable utilities 0.4,
0.5.
All right, so then we built anaggregate by sector blah, blah
(12:11):
blah.
And what we see here.
So I'll calculate the gainexpectancy.
What we see here is that if youbuy high beta, the super stuff
that races a lot, you would beatthe index.
This is the S&P, the blue line.
You would absolutely trash theindex.
The problem is, if you do that,you would have zero customer.
(12:31):
You would have zero client,because every now and then you
take a 50% haircut.
Speaker 1 (12:38):
And nobody will stick around for the comeback.
That's exactly right.
Speaker 2 (12:41):
Exactly so.
It's a Bob Marley market.
What is Bob Marley market?
It's a redemption song, andeverybody would bail on you as
soon as this happens.
So how to do it?
So, basically, a long short canbe the combination of depending
on where we are in the regime,depending on what kind of market
we're talking about, it'sbasically keep the same leaders,
(13:06):
keep the information technologyand the consumer discretionary,
just switch sides when themarket turns bearish.
So how to do that?
Here we have basically a highlow, which is the net difference
between the cumulative returns.
And again, it's very naive.
I do not take this.
Please do not try that at home.
I mean, I would feel bad, butwhat we see is very naive is the
(13:31):
delta of the high beta minusthe low beta, and what we can
see is that when this the highbeta and the low beta goes
nowhere, it usually precedes themarket.
Speaker 1 (13:43):
Right, which is basically the idea that the low
beta defensive sectors will movein advance of risk-off
conditions.
Speaker 2 (13:51):
Exactly when there's risk-off, you can see that the
high beta stuff tends todisgorge a lot.
This is kind of cool to givehow to articulate the net beta.
Because of cool to give, whatshould I say to give how to
articulate the net beta?
Because a long short is notnecessarily a net exposure zero.
(14:11):
Net exposure is basically thenon-exposure all the arithmetic
sum of all the positions on thelong side minus the market value
of all the short side.
This is a net exposure.
The net beta is beta adjusted.
(14:34):
A net exposure, like delta zeroor market neutral, doesn't
necessarily mean that you haveactually net beta zero If you
truly, truly, truly want to behere.
This is why, for instance, in2008, a lot of the long shots
were tanking this oh, but lookat us, look at us, we're net
exposure zero.
Yeah, but you still long thevery high beta.
(14:55):
If you long the high beta,you're going to tank.
It's inevitable.
If you long the high beta,small cap and so on, you're
going to tank faster and fartherthan anybody.
So the lesson here is keep theleaders of the way up, keep them
in your portfolio, just switchsides.
Make sense, yes.
Speaker 1 (15:16):
From a sector perspective, are there certain
sectors where you are lesslikely to be whipsawed?
Yes, if you're trying to shortthem.
Speaker 2 (15:30):
Yes, of course.
Actually, what I think would beinteresting, I heard of
somebody who was doing a longshort in utilities and I thought
this is brilliant.
So, yes, of course, there aresectors where you're less
whipsawed.
For instance, if you look athow should I say industrial,
although industrial has its owncycle, some of them are early
cycles, some of them are latecycle.
(15:51):
So if we talk aboutshipbuilding, this is an early
cycle.
If we talk about machinery,this is late cycle.
So there's also the O1 markskind of cycle consideration to
be taken care of.
But if we look at stuff likehealthcare, yeah, of course.
And every time there's a bearmarket, don't worry, you can
always go after the financials.
No doubt about it.
Speaker 1 (16:14):
Financials.
They cannot get out of theirown way, like ever, since
they're just utility companies,basically, and they claim to
have software potential, butthey never really work that well
.
Yeah, the utilities I mean, Ialways talk about utilities
because it's the most bond-likesector, right, so it has certain
relative momentum, uniquecharacteristics, worked very
(16:35):
well in 2022, even though bondssold off, but that's just
because it's low beta anyway andthere was a big boom in energy
oil at that time.
How are you thinking about thatpoint, about this sort of
relative strength changing thattopping formation?
Are you starting to say toyourself, at least when it comes
to US markets, we're at a pointnow where risk is increasing,
(16:57):
that it's just kind of a slowmoving shift towards a risk off
cycle?
Or, and you just say toyourself, well, small caps are
the next thing to run.
So none of the sector analysis,or none of these, tells matter.
Speaker 2 (17:10):
That's a very good question.
I wish I could give you ananswer.
I mean, there are an increasingnumber of bearish signals for
small cap and very racy stocks,so as to why, I don't know.
I don't know and I'm not in.
(17:35):
I mean, the market will tell ussix months down the road, so
I'm sorry.
Speaker 1 (17:42):
No, no, no, I don't know the answer myself.
It's legitimate, but that'spredicting.
Nobody knows right?
That is the vulnerability now.
Speaker 2 (17:51):
Exactly, but I see more cautiousness.
I mean, I see more rotation.
This is the beginning ofrotation.
Maybe I don't know.
The thing is, when I see arotational weapon, I don't try
to predict how structural itwill be, I just measure it.
You see, for instance, thedifference in what I do is when
(18:20):
I see, for instance, a clusterof signals within a sector.
Oh, this is turning bearish,okay, fine.
Then I understand that thesector is falling out of favor.
But when I see one isolatedstock falling out of favor maybe
this is a stock that had agreat run and it needs to take a
break, needs to take a break.
Get off the highway, have a canof Coke, refresh yourself and
(18:43):
then go back oh, maybe there'ssomething that.
Oh, maybe this stock isactually.
Maybe there's something that,oh, maybe this stock is actually
.
There's something fundamentallywrong with it.
So these are the only three typeof questions.
If everything's moving togethersecond rotation If one stock is
moving out of sync witheverybody, okay, maybe there's
something fundamental, or maybeit's taken a break.
That's it.
Speaking of which, I think itwas a week or two ago you had
(19:07):
somebody you interviewed who wastalking about NVIDIA and, it's
interesting, I have a signalcalled floor and ceiling and
there was a signal that actuallythis one seems to lose momentum
or seems to lose steam.
I should say I don't know ifit's going to be forever, and
(19:29):
please do not go and sell yourNVIDIA and send me the
acquisition.
Speaker 1 (19:34):
We are such a piece of and definitely don't short,
as I say, nvidia, as much as Ihave all the stocks I had to
pick on last year, that was thestock I had to be loudest and
pick on the most.
I always said very explicitlydon't short it.
Even if you're bearish on thenarrative, as I still am, and I
obviously have been dead wrongon that you had so many DMs
saying one of the things youwant to address is market
(19:57):
psychology and the self-sabotagethat happens especially with
newer traders.
But I'd argue there's plenty ofpros that self-sabotage their
careers, their portfolios.
Let's talk about that because Ithink as much as you and I are
quant-oriented.
Quant means there should be noemotional bias.
You just can't help yourselfsometimes.
Speaker 2 (20:20):
Okay, that's interesting, because did you
know that actually, most of theI mean the best market
psychology books written on themarket?
Then, you see, there wasdiscretionary, fundamental
people, and then there arequants people.
Quants are supposedly thisdrawing machine, but the best
market psychology books werealways systematically written by
quants people, by systematicpeople, all of them.
(20:44):
I mean Ed Sekota, tom Basso,you name it.
All the best ones were writtenby people who actually had a
more quantitative approach.
My take on this is because theyare more emotional, they
realize the impact of emotions,they try to build systems and
then those systems they generatethis matrix of false positive,
(21:04):
true positive and false negative.
So we all understand falsepositive, true positive and
false negative.
So we all understand falsepositive and true positive.
But false negative is basicallythis is the bucket in which I
fish all the time as a shortseller.
What is false negative isbasically the concept of
structural short, so the idea ofself-sabotage.
I mean, where does it come from?
(21:24):
For that I always think of thisanecdote back in 2008.
There was a bar in Tokyo justdown from Lehman Brothers and
there were all these bondtraders.
These guys were popping DonPerignon like it was Pepsi Cola,
so of course all the girlswould flock to them.
And I remember there was thisguy who was very flamboyant,
(21:45):
very, very interesting fellowand I realized that actually
three to four months after Ireceived money, this guy filed
for personal bankruptcy.
I'm like, dude, I mean you'reprinting like $1, $2 million,
maybe more, a year, how comeyou're already filing for
bankruptcy?
And I remember to this day helooked at me and said you know
(22:07):
what, at the end of the day Iwas just a poor kid from Bombay.
So within him there was thissense of toxic shame, and toxic
shame is I'm not good enough andeverybody who's been on the
desk for a while is imposter,like it's rows of imposter
(22:28):
syndrome.
Right, I'm not inventinganything here.
Speaker 1 (22:35):
You can't blame them, right?
I mean, it's like if you gofrom not making very much,
suddenly you know a million anda half, two million and yeah, it
looks like it's going tocontinue.
There's no transition for yourpersonality to adjust.
Speaker 2 (22:49):
Exactly and deep down , there's this feeling that do I
deserve?
Am I worthy of it?
Am I enough?
And there was a book in the 80sby John Bracho called the Shame
that Binds Us, called the Shamethat Binds Us.
(23:10):
So the reason why I mention itnow is because I believe that
actually and I'm the first one,I mean I have all the bad
psychological traits.
You name it.
I have all of them in spades.
I did all the mistakes twice,at least twice, maybe three
times, and maybe over and over,and sometimes I even felt it in
me.
I made good money and then Igave it back, plus some, because
(23:37):
deep down, I believed that Ididn't deserve it and this is
part of a core identity.
So I'm not good enough.
This is something that exists.
And how do you fix it?
Because we have the other gameof all the techniques.
Okay, should I use a movingaverage?
Should I do this, should I dothat?
This is just technique.
Like, should I coach?
Should I visit companies?
Then we have the inner game.
Okay, like meditate, you know,like really be organized, and so
(24:02):
on and so forth.
But if, deep down inside, theimage in the mirror says, hey,
I'm good enough, and the mirrorsays no, you're not.
How do you fix this?
And this is something thatprobably I mean the market will
test the darkest corner of yourpsyche, and I believe that
making money in the market isnot about having a good system.
(24:23):
You see, I think it's RichardDennis.
I had this conversation withMichael Coburn and he said that
Richard Dennis, the turtletrader he said he could publish
his strategy on the cover of theNew York Times for two weeks
consecutively, or Wall StreetJournal for two weeks
consecutively, and 95% of thepeople would still not be able
(24:44):
to trade it, because between thesignal, between the system and
the trader, there's all thisdark psyche and all this toxic
chain that binds us.
And so the reason why I'mmentioning this and the reason I
wanted to talk about it isbecause I've worked with an
ethnotherapist and this guy sheowes it.
It turns out that actually,it's really, really interesting.
(25:07):
This is something that not onlymanifests in trading, but it
manifests in all aspects of lifeOur relationship to our body.
Dating, of course, is always abeautiful girl, but oh, we put
her on a pedestal because deepinside of us we have the I'm not
good enough.
In the market, there's alwaysthis feeling.
Oh, there might be a bad market.
It might be.
I don't feel safe.
(25:28):
Toxic shame again.
So I've worked with thisgentleman that we wanted to
publish something about how tocure this toxic shame.
For instance, we've seen itover and over, like the LTCM
classic case.
I was having a conversationwith Victor Ragone fantastic
gentleman was a trader with LTCMImmense respect for this
(25:51):
gentleman.
And Ubris Ubris is toxic shade.
We've seen fortunes lost before.
People put their ego aside.
So my belief is that makingmoney in the market is just a
byproduct of the alignment ofwho we are as an identity, all
(26:11):
the way down to the techniques.
You see, if deep inside like,of course I deserve to be rich,
of course I deserve to staywealthy, then you will do things
that are congruent with youridentity, then they will become
habit, they will become yourbeliefs, your beliefs will
become your actions, they willbecome your beliefs, your
beliefs will become your actions, your actions will become your
virtues, your virtues becomeyour habits, and so on and so
(26:33):
forth.
Does it make sense?
Speaker 1 (26:36):
Yes, and it's a very underappreciated aspect of the
long-term longevity of somebodytrying to trade, at least on a
discretionary basis.
But even if you're in theindustry, I mean there's the
shame part.
And then the shame part getsdangerous when you're at the
moment of burnout, becausethat's when you just say to hell
(26:57):
with everything and that's whenmistakes tend to get amplified.
Speaker 2 (27:01):
Absolutely, and there's a way to cure it.
I mean, we cure it via superneuroplasticity.
We've released something aboutit and it's actually Charlie.
It's not a walk in the park interms of hypnosis, but because
you need to connect with allthis deep shape in you.
And when I did a session withhim and since then we've become
(27:23):
business partners when I did asession with him I really saw
much.
The next day the trading waseffortless.
I didn't have all thesequestions.
The most volatile place in themarket is the space between this
yellow and that yellow.
And the next day it waspeaceful and trading became
(27:46):
again what is supposed to beboring.
Trading should make watchingpaint dry look like a thriller.
Speaker 1 (27:56):
That is a quote I'm going to have to steal from you.
Trading should be like dryweight, but I guess it's funny
when there's volatility, right,and that's what I think
short-sellers like to see,because there's a link between
downtrends, obviously, andincreased volatility.
So maybe for the remaining fewminutes here, let's talk about
(28:19):
dealing with volatility, becausethere's a challenge here, right
?
The problem is volatility meansit goes both ways, right?
So big downs tend to befollowed by big ups.
So if you see things arestarting to break down, you
start to short and then themarket just rips in front of you
just before it's about to godown again, and that space in
between the years suddenlystarts to really question a lot
(28:43):
about your skill sets.
But that's just being whippedaround by the markets of all the
time.
So let's talk about that,because I think this is what's
underappreciated by those thatwant to get into the short side.
Speaker 2 (28:53):
I mean, the short side is, by definition, volatile
, so the short side is not.
You see, on the long side, okay, the overwhelming majority of
people are trying to follow oneway or another.
Whether you follow earningsmomentum, whether you follow
technicals, whatever that is,you buy low and you sell high.
And it tends to be forgiving,because if you don't buy today,
if it's something that lasts fora couple of years, you're going
(29:14):
to be good.
The short side doesn't worklike that, the short side
usually.
For instance, michael wasmentioning NVIDIA and personally
I mean now I saw a signal Iwould short it, ent.
And personally I mean now I sawa signal I would short it.
Entry is I would short it.
When I saw the signal, I wantedto send a message to my kind of
that's probably, it probablydoesn't need that.
(29:37):
I would short it.
But the question is not if Iwould short it, the question is
how much and in the position,and this can be recaptured in
the position sizing.
The most underappreciatedformula in capital markets is
gain expectancy, simply said, ishow often you win.
Times are how much you win onaverage minus how often you lose
(29:57):
times, how much it goes onaverage, and for that what
really matters is how much youare you size your position.
The problem with very volatilestock is you can't take big
positions because you're goingto be whooped on.
So, and the good news aboutvolatility it's very difficult
to predict where the price isgoing to be in months, two
(30:18):
months, three months from now.
On the other hand, volatilitythe good news about it is that
it's highly predictable.
If it's volatile today, it'svery likely to be volatile
tomorrow.
Speaker 1 (30:29):
The term.
There is volatility clustering,right Cluster.
Speaker 2 (30:32):
Correct, correct, correct, correct, absolutely so.
Sizing positions withvolatility is very important.
Speaker 1 (30:41):
Yeah, and that's the problem, right?
Because if something you arebearish on starts to the whites
of the eye start to show up ofthe decline, and you've, if, if
something you are bearish onstarts to the white to the eye
start to show up the down of theclimb, and you've been waiting
for it for a while your firstinstinct is to go very heavy.
Speaker 2 (30:55):
Yes, the problem with this is successful shorts.
They shrink and it's verycapital intensive to go heavy on
the onset because the price isvery high.
So you can't have a bigposition size.
So I've not been able to, Imean unless you have an
(31:17):
intelligent use of margin.
But by definition, the positionsize, the market value of your
position or the capital, was atthe I know how to say that in
Japanese, but I don't know howto say that in English the cost
times, the number of shares orbase value, I think, is very
(31:38):
high to begin with, and as theprice starts to slim down then
it becomes easier.
But going big on the short sidein the beginning is probably
not the smartest idea In myexperience.
I mean people who are betterthan me, and they're lots of
them, they do better work, butI've never been able to do that
or at least sleep well, leastsleep while doing it.
Speaker 1 (32:00):
What about using inverse funds?
Right, the track 1X, theinverse or 2X.
That way it's doing it for youbecause the downside of it is a
lot of zero.
But let's talk about that.
Speaker 2 (32:11):
Okay, that's a good idea.
Actually, I did an inverseChina in 2008, and I held it and
the way those ETFs arestructured the inverse or the
double inverse I did a doubleinverse Asia in 2008, and I
managed to lose money.
I got the entry right, I gotthe exit right and I got taken
(32:35):
to the cleaner on those ones.
So the inverse is not a goodidea.
It's because of the mathematics, about the structure, so it has
nothing to do with the trend.
So, on the other hand, what Ido is I take regular ETFs and I
short them and then it's aquestion of borrow.
So that is much easier to dobecause these ones the
(32:56):
mathematics I mean how thosefunds are structured is very
easy and predictable.
The inverse funds is not a goodidea.
Speaker 1 (33:05):
I tend to share the same.
I always say path matters morethan prediction, and that is
unequivocally beyond when itcomes to inverse funds.
For the last couple of minuteshere, laurent, I am curious.
So I have my Fenix as part ofmy brand.
It's like my thing that I wearon all these videos.
You've got something too.
I can't quite tell what it is.
(33:27):
What's yours?
Speaker 2 (33:28):
Oh, this is a shark tooth from a Mako shark in New
Caledonia, and this piece ofgold is a Japanese friend of
mine, who is a jewelry designer,who made it for me.
So, yes, I like your phoenix,by the way.
Speaker 1 (33:45):
So waiting for it to fully rise from the ashes.
Hopefully it will soon, laurent.
For those who want to trackmore of your thoughts and read
your book and the second editionwhen it's available, where do
you want it to?
Speaker 2 (33:56):
So the second I'm actually the publisher.
Like me today, but come on, yougot to finish the outline, so
the publisher is packed.
You can find me on LinkedIn.
You can find me, I guess.
Yeah, LinkedIn is probably theeasiest way.
I don't have much social mediafootprint.
(34:17):
I used to write a lot on Quora.
I will probably start writingagain on Substack.
I took a little bit of a breakon the markets.
Oh, there's one thing I wantedto talk about.
May I share something?
Speaker 1 (34:33):
Let's do it.
Speaker 2 (34:34):
All right, this is cool, this is cool.
So this was a dream for me myentire life, when I joined the
market, and I'll show you andI'll share it with you.
All right, here we go.
So I always dreamed ofdeveloping a market indicator
that would be absolutelyagnostic of timeframe.
(34:56):
You see, like, for instance, oh, do you use a 100-day moving
average?
A 50-day moving average?
Blah, blah, blah, you name it.
And I always dreamed ofsomething that would be
completely agnostic and thatwould work across timeframes.
So I developed something calledthe floor and ceiling.
The floor and ceiling is verysimple Mark it and make some
(35:18):
advance.
It goes up at some point, itwould print a high and then
every subsequent high will belower.
That's basically the rightshoulder of the head and
shoulder pattern.
Okay, stops making new highs,stops making fresh highs and
then all the other ones, so that, basically, that the market
(35:39):
goes either sideways or bearish,vice versa, market reaches the
bottom and then subsequent lowsare higher.
So I coded this how I call thefloor and ceiling.
So ceiling is because it stops,the ceiling and the floor
because the market has just hitthe floor.
So that market saturated, andso I concatenated SPY.
(36:03):
There's a website called1MinuteDatacom.
So I concatenated SPY since2009.
That's much data on one minuteand I processed it and to
calculate the signal on theone-minute bar, overall it's
(36:24):
about 4 million bars altogetherone minute.
Blah, blah, blah.
From one minute to one week.
I resampled everything and ittook about less than four
minutes to calculate all this,including at which minute did
the signal change?
So you see, it might print abottom today, but we only know
(36:44):
about this bar, but we only knowa few bars on the road and if
we use fractals like this, theminute at which we find that the
market turned bearish on thedaily bar is probably two, three
months down the road.
So the farther, the more remoteit is, the higher the timeframe
(37:07):
, the longer the distance or thelonger the duration, and I
think I've succeeded.
So here is the one-minute chartand what we see here is every
floor, every ceiling and thehigher levels is level eight it
looks like a video game Levelseven and so on and so forth.
So every time it prints this,now it's the five minutes and,
(37:31):
as we can see, I won't bore youwith all the tables and so on
and so forth, just a visualrepresentation, but it's roughly
the same.
Now fast forward.
We have the one hour.
Still more or less the samestory.
Now fast forward to the daily,the daily, even the lowest
version, like the lower level.
You see, it's like a Matryoshka.
(37:52):
So level two, level three,level four, level five, even
these ones are congruent withthe one minute.
So technically, I havesucceeded in finding the minute
at which a daily bear market ora daily bull market stops or
starts, and I can find it inreal time, and this is something
(38:14):
that I've always dreamed ofdoing.
Now, are there applications inreal life?
I believe there are, but it's abit more complicated.
It's not exactly my level ofprogramming, but you see, for
instance, what can happen is, onthis minute, we have a bar that
could trigger level two, thatcould trigger level three.
So every time it's a level ofextraction, it's fractals
(38:37):
basically, and I've alwayswanted to do that and I found a
way to do it.
So it will be in the secondedition.
Speaker 1 (38:45):
Big deal.
Anybody should be pre-orderingthat once they're able to do so,
for exactly that reason, andLord's been very successful I
know that he's been verysuccessful and my DMM.
He responds fairly quickly andI think his experience and
knowledge of that is reallyquite unique.
So, everybody, please make sureyou follow Laurent, check out
his book and, given that it'sthe top of the hour, I will see
(39:06):
you all in the next episode.
Bye, thank you, laurent,appreciate it.
Speaker 2 (39:11):
Thank you very much, Michael.
This is an honor.
Thank you very much.
Thank you.
Speaker 1 (39:14):
Cheers everybody.
Speaker 2 (39:15):
You too, thank you.
My name is Michael O'Gaia, publisher of the Lead
Lager Board.
Joining me for the 40 minuteshere is Mr Lant Bernou, who's
kind of built a bit ofreputation on the quant side and
on the short selling side, aswell as the market psychology
side, as well as the marketpsychology side.
So, laurent, introduce yourselfto those who are watching and
listening.
Who are you, what's yourbackground, what have you done
throughout your career?
And are you a night?
Speaker 2 (00:32):
owl.
I'm actually an early bird.
I wake up at five, so this isgood.
I'm sorry if I won't be verycoherent.
I will try my very best.
So my name is Laurent Bernu.
I was born in New Zealand.
I grew up in New Colonia, whichis a French territory.
(00:52):
I've been living in Japan forabout 28 years.
I started with French Embassy,Then I worked as a Japanese
accountant, so I used to doconsolidation and all this in
Japanese.
Then I joined the capitalmarkets in 2001, right around
the time when because at thattime there was Enron and
WorldCom, so people wanted toknow what a balance sheet.
People finally discovered thatit's not only earnings per share
(01:16):
but it's also cash flow andbalance sheet.
And then I joined a hedge fundin 2003.
I worked with Trudelity.
At Trudelity, my mandate was toshort-sell, so my mandate was
to actually underperform theworst-performing market on
record.
And I published a bookAlgorithmic Short-Selling with
(01:38):
Python.
The second edition will come.
At that time I was a very poorprogrammer.
I'm still not great, but I'mtrying.
Also, I do real estate as wellin Japan, and that's it.
Speaker 1 (01:58):
So that's a lot.
We're going to cover a bunch ofthings in that.
Since you mentioned Japan atthe start, I feel like I want to
touch on Japan just a littlebit, because you're actually
living there.
Is there really an economicboom going on or is this just
nominal inflation?
What is the mood in Japan?
I mean the things I seeanecdotally around inflation and
(02:19):
in general that being a highsaving economy does not seem to
be all that positive in generalthat being a high-saving economy
does not seem to be all thatpositive.
Speaker 2 (02:26):
Oh yes, so that's a very good question.
I mean I had friends fromThailand, somebody from Thailand
coming over to Japan and saidI'll buy the sushi, it's so
cheap, thanks.
So yeah, the Japanese yen hasbeen as torpedoed, has really
sunk compared to all othernations.
(02:48):
There's a boom in, I meanthere's certain assets.
I mean, of course, the stockmarket is booming.
Inflation is always good forthe stock market, also real
estate, so there's a lot of, Imean the stuff that I do.
When I started real estate,people, japanese bankers and if
you want to solve the globalwarming, you send 100 Japanese
(03:10):
bankers to Antarctica and theNorth Pole and it will freeze
over.
And when I started real estate,they told me like, what's wrong
with you?
Good question, how much timeyou got?
Okay, let's go back to business.
And anyhow, the point was whenI started, people thought that I
was wrong about that and noweverybody wants to do real
estate.
Every other person wants to doreal estate, so there's an
(03:34):
ongoing boom.
Does it have legs?
I don't know, but when Istarted, when people thought I
was crazy, they were right.
Now people think I'm a genius,so I'm starting to unload or
lighten up my portfolio.
That's pretty much it.
The mood Japan is an agingcountry so the mood doesn't
change that much, but it's truethat there's more dynamism
(03:54):
Post-COVID.
There's more dynamism and aweaker yen helps with exporting
nation.
Speaker 1 (04:04):
That's what I see on the ground.
Do you get a sense that it'sit's fleeting the cycle or is
there something structurallythat makes the argument for
Japan to continue its economicstrength and stock market threat
?
I've been highlighting thewhole reverse carry trace since
August.
I've been wrong on that so far.
But I want to talk more kind oflonger term about the dynamism.
Speaker 2 (04:26):
That's a good question.
Well, since a lot of Japanesecompanies I mean a lot of global
Japanese companies havecurrencies overseas, it
naturally inflates that balancesheet and the income statement.
So, yeah, there's a carry tradethere.
As far as the dynamism of thecountry itself, Japan is much
(04:49):
more open to foreign investors.
I've been contacted and I'vetalked to a bunch of people
about there's a change ingeneration.
Some obscure Japanese companythat nobody has ever heard of.
They're making micro-micro,micro screws that are used in
the International Space Station.
There's apparently no one elsein the world who can do it.
(05:11):
So Japan has a knowledge ofself-welfare, a craftsmanship
that is unparalleled, andthere's a shit generation where
those companies are for sale.
I don't know if it's going tolast.
Honestly, I don't know.
I don't know if it's going tolast.
Honestly, I don't know.
I don't make predictions, I'musually not really good at them.
Speaker 1 (05:31):
Nobody is ever good at predictions Not me, not you,
not anybody, definitely not theFederal Reserve and definitely
not the BOJ.
I think is the truism Okay youmentioned.
Now there's one thing you canargue that there is you can
somewhat predict, at least overthe very long term.
You can predict that marketstend to go up.
And you talk about shortselling right.
And the issue, of course, ofshort selling is the odds are
(05:54):
just against you.
And you were in that profession, right, that was your mandates,
right.
So if your performance sucks,it's supposed to suck because
markets go up rates, right.
So if your performance sucks,it's supposed to suck because
the market's going up.
I'm curious in that experiencedid you kind of hate life a
little bit, meaning you knowmarkets just keep doing what
they're doing and you're tryingto bet against it and you're
(06:14):
compensated based on yourperformance.
But how much of it is the betaversus you?
Speaker 2 (06:19):
I'm glad you mentioned this.
I mean, my job was a shortseller in the worst bear market
in modern history, so I had todo worse than the worst market.
I mean I used to go down to theStarbucks on the ground I mean
the ground father Damn, I soenvy your job.
I don't envy your paycheck, butI do envy your job.
So it's a tough job.
(06:41):
With that said, I mean there'sa way to play short selling,
especially if you do relativeseries or cross-sectional
momentum.
Cross-sectional, which meansrelative to the index.
If you look at the index S&P,for instance, there's roughly
50% of the stocks that wouldoutperform, 50% of the stocks
that would underperform.
If you do it in absolute, it'sgoing to be real tough.
(07:03):
Actually, I can show a graph ifyou don't mind, mike.
Speaker 1 (07:08):
May I?
Yeah, yeah, please, let's trythis out and those that are
listening to this, I'll try andnarrate with Laurent here.
Let's experiment and see if wecan get this working here.
Speaker 2 (07:16):
Yes, this one, this one, this one, okay, sure, all
know, this one, okay, share Allright.
So here we go Does it work.
Looks like it's sort of mine,let's try it, there we go.
Okay, so this is chapter fourof the book.
Speaker 1 (07:40):
And the book is about coding quantitative strategies
using Python as a languagecorrect.
Speaker 2 (07:45):
Correct, correct, correct.
So I was a very poor coder.
So this is the S&P 500.
What I've done here is I'vedownloaded just off Wikipedia
this morning, the currentconstituents of the S&P 500, of
the S&P 500, ran a series overhowever many years 2001, I think
(08:10):
and counted the number ofissues that had touched 200 days
as just pure simple trendfollowing, nothing fancy.
So if we and just a lateralcount over time, so this
explains the lag here.
And basically, when it's a bullmarket, what you see is that
pretty much everybody is in bullterritory and very few of those
stocks are underperforming.
(08:32):
Of course, there's a built-insurvivorship bias.
Now, if you do it in absolute,on the other hand, if you do it
in relative series, which isbasically every price divided by
the index, the S&P, what youtend to see is basically the
number of outperformers isroughly 40% to 50% of
outperformers andunderperformers at all times.
(08:53):
So what it means there is thatit's more or less something that
you can do.
All you need to do is okay,let's look at what could
outperform on the long side andwhat could underperform on the
short side.
So we're going further down alittle bit, soft bank, blah,
blah, blah.
So the idea there.
The good news about doing inrelative terms is this is we're
(09:15):
going to okay, same story, butnow it's further broken down
into sectors.
If we look at sectors, you cansee the same dynamic in absolute
.
But if you look in relative,what you see here is a sector
rotation.
So instead of trying to timethe top and time the bottom,
looking at sector rotationreally makes more sense.
And the idea behind this is weall know about defensive sectors
(09:40):
and we all know about cyclicalsectors, which means defensive
would be consumer staples nomatter what you're going to eat
food, there would be utilities,no matter what you need
electricity or water.
Cyclical would be consumer.
Discretionary would beinformation technology and so on
and so forth.
So basically, this is what wehave in absolute and relative.
(10:01):
And then the interesting part isnow when we do the rotation.
So there's just an equal weightacross the board.
Nothing we find is very, Ishould say, naive.
It's very naive, but you cansee the sector rotation.
You can see the defensive inblue, the cyclical in yellow-ish
and then the rotation would bein red and there's a very, very
(10:24):
clear rotation.
That happens all the time.
So cyclical and defensive.
So just timing those andbuilding a very naive index like
this works.
Speaker 1 (10:36):
And right now the far right it's starting to turn.
It's kind of a slow process ofa turn Correct.
Speaker 2 (10:42):
And here's another version of it.
If we look at it here, forinstance, this is ugly.
So here I calculated the beta,and this one crushed my computer
this morning.
I was less than happy.
So same story.
This is chapter 11.
We're talking about the samestory, a download stuff.
(11:03):
I calculated the beta versus theS&P 500 over two years.
So what is the beta?
The beta is a covariance matrix.
So let's say, for instance, theindex moved by 1%, maybe Apple
or Nvidia would move by 2% or1.5%.
This is high beta.
But a utility stock would bemoved by maybe 20 cents, 40
(11:26):
cents so, and it's roughly thesame story.
So the sector that we mentionedbefore, the defensive and
cyclical they will start to makesense here.
Sorry for all the verbiage, myapologies for this.
So what we have here?
Information technology, andsurprisingly again, this is
equal weight across the world.
Very naive way to look at it.
It's not market cap weighted,it's, as of today, the
(11:49):
constituents of survivorshipbias built in Information
technology is 1.4.
Consumer discretionary 1.07.
So these are the cyclicals thatwe talked about before, and at
the bottom, low beta, isconsumer-stable utilities 0.4,
0.5.
All right, so then we built anaggregate by sector blah, blah
(12:11):
blah.
And what we see here.
So I'll calculate the gainexpectancy.
What we see here is that if youbuy high beta, the super stuff
that races a lot, you would beatthe index.
This is the S&P, the blue line.
You would absolutely trash theindex.
The problem is, if you do that,you would have zero customer.
(12:31):
You would have zero client,because every now and then you
take a 50% haircut.
Speaker 1 (12:38):
And nobody will stick around for the comeback.
That's exactly right.
Speaker 2 (12:41):
Exactly so.
It's a Bob Marley market.
What is Bob Marley market?
It's a redemption song, andeverybody would bail on you as
soon as this happens.
So how to do it?
So, basically, a long short canbe the combination of depending
on where we are in the regime,depending on what kind of market
we're talking about, it'sbasically keep the same leaders,
(13:06):
keep the information technologyand the consumer discretionary,
just switch sides when themarket turns bearish.
So how to do that?
Here we have basically a highlow, which is the net difference
between the cumulative returns.
And again, it's very naive.
I do not take this.
Please do not try that at home.
I mean, I would feel bad, butwhat we see is very naive is the
(13:31):
delta of the high beta minusthe low beta, and what we can
see is that when this the highbeta and the low beta goes
nowhere, it usually precedes themarket.
Speaker 1 (13:43):
Right, which is basically the idea that the low
beta defensive sectors will movein advance of risk-off
conditions.
Speaker 2 (13:51):
Exactly when there's risk-off, you can see that the
high beta stuff tends todisgorge a lot.
This is kind of cool to givehow to articulate the net beta.
Because of cool to give, whatshould I say to give how to
articulate the net beta?
Because a long short is notnecessarily a net exposure zero.
(14:11):
Net exposure is basically thenon-exposure all the arithmetic
sum of all the positions on thelong side minus the market value
of all the short side.
This is a net exposure.
The net beta is beta adjusted.
(14:34):
A net exposure, like delta zeroor market neutral, doesn't
necessarily mean that you haveactually net beta zero If you
truly, truly, truly want to behere.
This is why, for instance, in2008, a lot of the long shots
were tanking this oh, but lookat us, look at us, we're net
exposure zero.
Yeah, but you still long thevery high beta.
(14:55):
If you long the high beta,you're going to tank.
It's inevitable.
If you long the high beta,small cap and so on, you're
going to tank faster and fartherthan anybody.
So the lesson here is keep theleaders of the way up, keep them
in your portfolio, just switchsides.
Make sense, yes.
Speaker 1 (15:16):
From a sector perspective, are there certain
sectors where you are lesslikely to be whipsawed?
Yes, if you're trying to shortthem.
Speaker 2 (15:30):
Yes, of course.
Actually, what I think would beinteresting, I heard of
somebody who was doing a longshort in utilities and I thought
this is brilliant.
So, yes, of course, there aresectors where you're less
whipsawed.
For instance, if you look athow should I say industrial,
although industrial has its owncycle, some of them are early
cycles, some of them are latecycle.
(15:51):
So if we talk aboutshipbuilding, this is an early
cycle.
If we talk about machinery,this is late cycle.
So there's also the O1 markskind of cycle consideration to
be taken care of.
But if we look at stuff likehealthcare, yeah, of course.
And every time there's a bearmarket, don't worry, you can
always go after the financials.
No doubt about it.
Speaker 1 (16:14):
Financials.
They cannot get out of theirown way, like ever, since
they're just utility companies,basically, and they claim to
have software potential, butthey never really work that well
.
Yeah, the utilities I mean, Ialways talk about utilities
because it's the most bond-likesector, right, so it has certain
relative momentum, uniquecharacteristics, worked very
(16:35):
well in 2022, even though bondssold off, but that's just
because it's low beta anyway andthere was a big boom in energy
oil at that time.
How are you thinking about thatpoint, about this sort of
relative strength changing thattopping formation?
Are you starting to say toyourself, at least when it comes
to US markets, we're at a pointnow where risk is increasing,
(16:57):
that it's just kind of a slowmoving shift towards a risk off
cycle?
Or, and you just say toyourself, well, small caps are
the next thing to run.
So none of the sector analysis,or none of these, tells matter.
Speaker 2 (17:10):
That's a very good question.
I wish I could give you ananswer.
I mean, there are an increasingnumber of bearish signals for
small cap and very racy stocks,so as to why, I don't know.
I don't know and I'm not in.
(17:35):
I mean, the market will tell ussix months down the road, so
I'm sorry.
Speaker 1 (17:42):
No, no, no, I don't know the answer myself.
It's legitimate, but that'spredicting.
Nobody knows right?
That is the vulnerability now.
Speaker 2 (17:51):
Exactly, but I see more cautiousness.
I mean, I see more rotation.
This is the beginning ofrotation.
Maybe I don't know.
The thing is, when I see arotational weapon, I don't try
to predict how structural itwill be, I just measure it.
You see, for instance, thedifference in what I do is when
(18:20):
I see, for instance, a clusterof signals within a sector.
Oh, this is turning bearish,okay, fine.
Then I understand that thesector is falling out of favor.
But when I see one isolatedstock falling out of favor maybe
this is a stock that had agreat run and it needs to take a
break, needs to take a break.
Get off the highway, have a canof Coke, refresh yourself and
(18:43):
then go back oh, maybe there'ssomething that.
Oh, maybe this stock isactually.
Maybe there's something that,oh, maybe this stock is actually
.
There's something fundamentallywrong with it.
So these are the only three typeof questions.
If everything's moving togethersecond rotation If one stock is
moving out of sync witheverybody, okay, maybe there's
something fundamental, or maybeit's taken a break.
That's it.
Speaking of which, I think itwas a week or two ago you had
(19:07):
somebody you interviewed who wastalking about NVIDIA and, it's
interesting, I have a signalcalled floor and ceiling and
there was a signal that actuallythis one seems to lose momentum
or seems to lose steam.
I should say I don't know ifit's going to be forever, and
(19:29):
please do not go and sell yourNVIDIA and send me the
acquisition.
Speaker 1 (19:34):
We are such a piece of and definitely don't short,
as I say, nvidia, as much as Ihave all the stocks I had to
pick on last year, that was thestock I had to be loudest and
pick on the most.
I always said very explicitlydon't short it.
Even if you're bearish on thenarrative, as I still am, and I
obviously have been dead wrongon that you had so many DMs
saying one of the things youwant to address is market
(19:57):
psychology and the self-sabotagethat happens especially with
newer traders.
But I'd argue there's plenty ofpros that self-sabotage their
careers, their portfolios.
Let's talk about that because Ithink as much as you and I are
quant-oriented.
Quant means there should be noemotional bias.
You just can't help yourselfsometimes.
Speaker 2 (20:20):
Okay, that's interesting, because did you
know that actually, most of theI mean the best market
psychology books written on themarket?
Then, you see, there wasdiscretionary, fundamental
people, and then there arequants people.
Quants are supposedly thisdrawing machine, but the best
market psychology books werealways systematically written by
quants people, by systematicpeople, all of them.
(20:44):
I mean Ed Sekota, tom Basso,you name it.
All the best ones were writtenby people who actually had a
more quantitative approach.
My take on this is because theyare more emotional, they
realize the impact of emotions,they try to build systems and
then those systems they generatethis matrix of false positive,
(21:04):
true positive and false negative.
So we all understand falsepositive, true positive and
false negative.
So we all understand falsepositive and true positive.
But false negative is basicallythis is the bucket in which I
fish all the time as a shortseller.
What is false negative isbasically the concept of
structural short, so the idea ofself-sabotage.
I mean, where does it come from?
(21:24):
For that I always think of thisanecdote back in 2008.
There was a bar in Tokyo justdown from Lehman Brothers and
there were all these bondtraders.
These guys were popping DonPerignon like it was Pepsi Cola,
so of course all the girlswould flock to them.
And I remember there was thisguy who was very flamboyant,
(21:45):
very, very interesting fellowand I realized that actually
three to four months after Ireceived money, this guy filed
for personal bankruptcy.
I'm like, dude, I mean you'reprinting like $1, $2 million,
maybe more, a year, how comeyou're already filing for
bankruptcy?
And I remember to this day helooked at me and said you know
(22:07):
what, at the end of the day Iwas just a poor kid from Bombay.
So within him there was thissense of toxic shame, and toxic
shame is I'm not good enough andeverybody who's been on the
desk for a while is imposter,like it's rows of imposter
(22:28):
syndrome.
Right, I'm not inventinganything here.
Speaker 1 (22:35):
You can't blame them, right?
I mean, it's like if you gofrom not making very much,
suddenly you know a million anda half, two million and yeah, it
looks like it's going tocontinue.
There's no transition for yourpersonality to adjust.
Speaker 2 (22:49):
Exactly and deep down , there's this feeling that do I
deserve?
Am I worthy of it?
Am I enough?
And there was a book in the 80sby John Bracho called the Shame
that Binds Us, called the Shamethat Binds Us.
(23:10):
So the reason why I mention itnow is because I believe that
actually and I'm the first one,I mean I have all the bad
psychological traits.
You name it.
I have all of them in spades.
I did all the mistakes twice,at least twice, maybe three
times, and maybe over and over,and sometimes I even felt it in
me.
I made good money and then Igave it back, plus some, because
(23:37):
deep down, I believed that Ididn't deserve it and this is
part of a core identity.
So I'm not good enough.
This is something that exists.
And how do you fix it?
Because we have the other gameof all the techniques.
Okay, should I use a movingaverage?
Should I do this, should I dothat?
This is just technique.
Like, should I coach?
Should I visit companies?
Then we have the inner game.
Okay, like meditate, you know,like really be organized, and so
(24:02):
on and so forth.
But if, deep down inside, theimage in the mirror says, hey,
I'm good enough, and the mirrorsays no, you're not.
How do you fix this?
And this is something thatprobably I mean the market will
test the darkest corner of yourpsyche, and I believe that
making money in the market isnot about having a good system.
(24:23):
You see, I think it's RichardDennis.
I had this conversation withMichael Coburn and he said that
Richard Dennis, the turtletrader he said he could publish
his strategy on the cover of theNew York Times for two weeks
consecutively, or Wall StreetJournal for two weeks
consecutively, and 95% of thepeople would still not be able
(24:44):
to trade it, because between thesignal, between the system and
the trader, there's all thisdark psyche and all this toxic
chain that binds us.
And so the reason why I'mmentioning this and the reason I
wanted to talk about it isbecause I've worked with an
ethnotherapist and this guy sheowes it.
It turns out that actually,it's really, really interesting.
(25:07):
This is something that not onlymanifests in trading, but it
manifests in all aspects of lifeOur relationship to our body.
Dating, of course, is always abeautiful girl, but oh, we put
her on a pedestal because deepinside of us we have the I'm not
good enough.
In the market, there's alwaysthis feeling.
Oh, there might be a bad market.
It might be.
I don't feel safe.
(25:28):
Toxic shame again.
So I've worked with thisgentleman that we wanted to
publish something about how tocure this toxic shame.
For instance, we've seen itover and over, like the LTCM
classic case.
I was having a conversationwith Victor Ragone fantastic
gentleman was a trader with LTCMImmense respect for this
(25:51):
gentleman.
And Ubris Ubris is toxic shade.
We've seen fortunes lost before.
People put their ego aside.
So my belief is that makingmoney in the market is just a
byproduct of the alignment ofwho we are as an identity, all
(26:11):
the way down to the techniques.
You see, if deep inside like,of course I deserve to be rich,
of course I deserve to staywealthy, then you will do things
that are congruent with youridentity, then they will become
habit, they will become yourbeliefs, your beliefs will
become your actions, they willbecome your beliefs, your
beliefs will become your actions, your actions will become your
virtues, your virtues becomeyour habits, and so on and so
(26:33):
forth.
Does it make sense?
Speaker 1 (26:36):
Yes, and it's a very underappreciated aspect of the
long-term longevity of somebodytrying to trade, at least on a
discretionary basis.
But even if you're in theindustry, I mean there's the
shame part.
And then the shame part getsdangerous when you're at the
moment of burnout, becausethat's when you just say to hell
(26:57):
with everything and that's whenmistakes tend to get amplified.
Speaker 2 (27:01):
Absolutely, and there's a way to cure it.
I mean, we cure it via superneuroplasticity.
We've released something aboutit and it's actually Charlie.
It's not a walk in the park interms of hypnosis, but because
you need to connect with allthis deep shape in you.
And when I did a session withhim and since then we've become
(27:23):
business partners when I did asession with him I really saw
much.
The next day the trading waseffortless.
I didn't have all thesequestions.
The most volatile place in themarket is the space between this
yellow and that yellow.
And the next day it waspeaceful and trading became
(27:46):
again what is supposed to beboring.
Trading should make watchingpaint dry look like a thriller.
Speaker 1 (27:56):
That is a quote I'm going to have to steal from you.
Trading should be like dryweight, but I guess it's funny
when there's volatility, right,and that's what I think
short-sellers like to see,because there's a link between
downtrends, obviously, andincreased volatility.
So maybe for the remaining fewminutes here, let's talk about
(28:19):
dealing with volatility, becausethere's a challenge here, right
?
The problem is volatility meansit goes both ways, right?
So big downs tend to befollowed by big ups.
So if you see things arestarting to break down, you
start to short and then themarket just rips in front of you
just before it's about to godown again, and that space in
between the years suddenlystarts to really question a lot
(28:43):
about your skill sets.
But that's just being whippedaround by the markets of all the
time.
So let's talk about that,because I think this is what's
underappreciated by those thatwant to get into the short side.
Speaker 2 (28:53):
I mean, the short side is, by definition, volatile
, so the short side is not.
You see, on the long side, okay, the overwhelming majority of
people are trying to follow oneway or another.
Whether you follow earningsmomentum, whether you follow
technicals, whatever that is,you buy low and you sell high.
And it tends to be forgiving,because if you don't buy today,
if it's something that lasts fora couple of years, you're going
(29:14):
to be good.
The short side doesn't worklike that, the short side
usually.
For instance, michael wasmentioning NVIDIA and personally
I mean now I saw a signal Iwould short it, ent.
And personally I mean now I sawa signal I would short it.
Entry is I would short it.
When I saw the signal, I wantedto send a message to my kind of
that's probably, it probablydoesn't need that.
(29:37):
I would short it.
But the question is not if Iwould short it, the question is
how much and in the position,and this can be recaptured in
the position sizing.
The most underappreciatedformula in capital markets is
gain expectancy, simply said, ishow often you win.
Times are how much you win onaverage minus how often you lose
(29:57):
times, how much it goes onaverage, and for that what
really matters is how much youare you size your position.
The problem with very volatilestock is you can't take big
positions because you're goingto be whooped on.
So, and the good news aboutvolatility it's very difficult
to predict where the price isgoing to be in months, two
(30:18):
months, three months from now.
On the other hand, volatilitythe good news about it is that
it's highly predictable.
If it's volatile today, it'svery likely to be volatile
tomorrow.
Speaker 1 (30:29):
The term.
There is volatility clustering,right Cluster.
Speaker 2 (30:32):
Correct, correct, correct, correct, absolutely so.
Sizing positions withvolatility is very important.
Speaker 1 (30:41):
Yeah, and that's the problem, right?
Because if something you arebearish on starts to the whites
of the eye start to show up ofthe decline, and you've, if, if
something you are bearish onstarts to the white to the eye
start to show up the down of theclimb, and you've been waiting
for it for a while your firstinstinct is to go very heavy.
Speaker 2 (30:55):
Yes, the problem with this is successful shorts.
They shrink and it's verycapital intensive to go heavy on
the onset because the price isvery high.
So you can't have a bigposition size.
So I've not been able to, Imean unless you have an
(31:17):
intelligent use of margin.
But by definition, the positionsize, the market value of your
position or the capital, was atthe I know how to say that in
Japanese, but I don't know howto say that in English the cost
times, the number of shares orbase value, I think, is very
(31:38):
high to begin with, and as theprice starts to slim down then
it becomes easier.
But going big on the short sidein the beginning is probably
not the smartest idea In myexperience.
I mean people who are betterthan me, and they're lots of
them, they do better work, butI've never been able to do that
or at least sleep well, leastsleep while doing it.
Speaker 1 (32:00):
What about using inverse funds?
Right, the track 1X, theinverse or 2X.
That way it's doing it for youbecause the downside of it is a
lot of zero.
But let's talk about that.
Speaker 2 (32:11):
Okay, that's a good idea.
Actually, I did an inverseChina in 2008, and I held it and
the way those ETFs arestructured the inverse or the
double inverse I did a doubleinverse Asia in 2008, and I
managed to lose money.
I got the entry right, I gotthe exit right and I got taken
(32:35):
to the cleaner on those ones.
So the inverse is not a goodidea.
It's because of the mathematics, about the structure, so it has
nothing to do with the trend.
So, on the other hand, what Ido is I take regular ETFs and I
short them and then it's aquestion of borrow.
So that is much easier to dobecause these ones the
(32:56):
mathematics I mean how thosefunds are structured is very
easy and predictable.
The inverse funds is not a goodidea.
Speaker 1 (33:05):
I tend to share the same.
I always say path matters morethan prediction, and that is
unequivocally beyond when itcomes to inverse funds.
For the last couple of minuteshere, laurent, I am curious.
So I have my Fenix as part ofmy brand.
It's like my thing that I wearon all these videos.
You've got something too.
I can't quite tell what it is.
(33:27):
What's yours?
Speaker 2 (33:28):
Oh, this is a shark tooth from a Mako shark in New
Caledonia, and this piece ofgold is a Japanese friend of
mine, who is a jewelry designer,who made it for me.
So, yes, I like your phoenix,by the way.
Speaker 1 (33:45):
So waiting for it to fully rise from the ashes.
Hopefully it will soon, laurent.
For those who want to trackmore of your thoughts and read
your book and the second editionwhen it's available, where do
you want it to?
Speaker 2 (33:56):
So the second I'm actually the publisher.
Like me today, but come on, yougot to finish the outline, so
the publisher is packed.
You can find me on LinkedIn.
You can find me, I guess.
Yeah, LinkedIn is probably theeasiest way.
I don't have much social mediafootprint.
(34:17):
I used to write a lot on Quora.
I will probably start writingagain on Substack.
I took a little bit of a breakon the markets.
Oh, there's one thing I wantedto talk about.
May I share something?
Speaker 1 (34:33):
Let's do it.
Speaker 2 (34:34):
All right, this is cool, this is cool.
So this was a dream for me myentire life, when I joined the
market, and I'll show you andI'll share it with you.
All right, here we go.
So I always dreamed ofdeveloping a market indicator
that would be absolutelyagnostic of timeframe.
(34:56):
You see, like, for instance, oh, do you use a 100-day moving
average?
A 50-day moving average?
Blah, blah, blah, you name it.
And I always dreamed ofsomething that would be
completely agnostic and thatwould work across timeframes.
So I developed something calledthe floor and ceiling.
The floor and ceiling is verysimple Mark it and make some
(35:18):
advance.
It goes up at some point, itwould print a high and then
every subsequent high will belower.
That's basically the rightshoulder of the head and
shoulder pattern.
Okay, stops making new highs,stops making fresh highs and
then all the other ones, so that, basically, that the market
(35:39):
goes either sideways or bearish,vice versa, market reaches the
bottom and then subsequent lowsare higher.
So I coded this how I call thefloor and ceiling.
So ceiling is because it stops,the ceiling and the floor
because the market has just hitthe floor.
So that market saturated, andso I concatenated SPY.
(36:03):
There's a website called1MinuteDatacom.
So I concatenated SPY since2009.
That's much data on one minuteand I processed it and to
calculate the signal on theone-minute bar, overall it's
(36:24):
about 4 million bars altogetherone minute.
Blah, blah, blah.
From one minute to one week.
I resampled everything and ittook about less than four
minutes to calculate all this,including at which minute did
the signal change?
So you see, it might print abottom today, but we only know
(36:44):
about this bar, but we only knowa few bars on the road and if
we use fractals like this, theminute at which we find that the
market turned bearish on thedaily bar is probably two, three
months down the road.
So the farther, the more remoteit is, the higher the timeframe
(37:07):
, the longer the distance or thelonger the duration, and I
think I've succeeded.
So here is the one-minute chartand what we see here is every
floor, every ceiling and thehigher levels is level eight it
looks like a video game Levelseven and so on and so forth.
So every time it prints this,now it's the five minutes and,
(37:31):
as we can see, I won't bore youwith all the tables and so on
and so forth, just a visualrepresentation, but it's roughly
the same.
Now fast forward.
We have the one hour.
Still more or less the samestory.
Now fast forward to the daily,the daily, even the lowest
version, like the lower level.
You see, it's like a Matryoshka.
(37:52):
So level two, level three,level four, level five, even
these ones are congruent withthe one minute.
So technically, I havesucceeded in finding the minute
at which a daily bear market ora daily bull market stops or
starts, and I can find it inreal time, and this is something
(38:14):
that I've always dreamed ofdoing.
Now, are there applications inreal life?
I believe there are, but it's abit more complicated.
It's not exactly my level ofprogramming, but you see, for
instance, what can happen is, onthis minute, we have a bar that
could trigger level two, thatcould trigger level three.
So every time it's a level ofextraction, it's fractals
(38:37):
basically, and I've alwayswanted to do that and I found a
way to do it.
So it will be in the secondedition.
Speaker 1 (38:45):
Big deal.
Anybody should be pre-orderingthat once they're able to do so,
for exactly that reason, andLord's been very successful I
know that he's been verysuccessful and my DMM.
He responds fairly quickly andI think his experience and
knowledge of that is reallyquite unique.
So, everybody, please make sureyou follow Laurent, check out
his book and, given that it'sthe top of the hour, I will see
(39:06):
you all in the next episode.
Bye, thank you, laurent,appreciate it.
Speaker 2 (39:11):
Thank you very much, Michael.
This is an honor.
Thank you very much.
Thank you.
Speaker 1 (39:14):
Cheers everybody.
Speaker 2 (39:15):
You too, thank you.
Popular Podcasts
1. Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
2. Start Here
A straightforward look at the day's top news in 20 minutes. Powered by ABC News. Hosted by Brad Mielke.
3. Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations.