September 4, 2025 • 16 mins
In 2023, Ivan Scherman won the World Cup of Trading with a nearly 500% return in one year. How he did it is really quite a remarkable story, and it leads to today's Q+A: can algorithms beat humans at investing? Or, like artificial intelligence, is it the combination of humans and machines that wins?
Adam Lang is joined in studio by Ivan Scherman, Chief Investment Officer at SciTech Investments and the portfolio manager of the Ausbiz Capital SciTech Growise Fund, which is opening to retail investors for the first time.
This is general information only, and you should seek professional advice before making any investment decisions. The Ausbiz Capital SciTech Growise Fund is a supporter of this podcast.
Find out more: https://fearandgreed.com.au/
See omnystudio.com/listener for privacy information.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:06):
Welcome to Fear and Greed Q and A, where we
ask and answer questions about business, investing, economics, politics and more.
I'm Adam Langan. Today we're asking can algorithms beat humans
at investing? Or like artificial intelligence, is it the combination
of humans and machines that wins. Please note that this
is general information only and you should seek professional advice
(00:27):
before making any investment decisions. My guest today I'm delighted
to say is Ivan Sherman, chief investment officer at Siye
Tech Investments and the portfolio manager of the osbi's capital
sie Tech grow Wise Fund, a supporter of this podcast.
Originally from Argentina, Ivan holds a PhD and advanced certifications
from get This, London Business School, New York University's stern
(00:52):
ARPM Lab and University dad Polytechnica de Madrid. He's visiting
Australia now as the grow Wise Fund opens its door
was to retail investors for the first time. Ivan, Welcome
to Fear and Great.
Speaker 2 (01:04):
Thank you so much, Thank you for having me.
Speaker 1 (01:06):
You've made global news in twenty twenty three by winning
the World Cup of Trading with a nearly five hundred
percent return in one year. How did you do it.
Speaker 2 (01:20):
By trading the same trading systems I trade for my company,
but perhaps with a different tactical approach. What I wanted
to do is to combine different trading assets, different assets,
asset classes, with different trading strategies and different time frames
(01:43):
in order to create an equity curve as steady as
I can get. And that's what I did. The contribution
of each of the systems into the performance of a
portfolio took me to win the championship.
Speaker 1 (02:00):
As you're talking about it, and almost see that competitive
spirit come alive.
Speaker 2 (02:05):
Was it like a game?
Speaker 1 (02:06):
Was it like a full contact sport?
Speaker 2 (02:08):
Yes? And no. I mean I tried to stick to
my plan, tried to not be influenced by what was
happening around me, because there were a lot of competitors
who went up very fast and went down very fast
as well.
Speaker 1 (02:20):
It does sound, as you talk about it, like an
incredibly disciplined approach. So I looked at your resume of education,
and you've got that disciplined approach in the way you
approach things. You're also someone who embraces meditation, fitness, martial arts,
and horse riding. How do all these different disciplines shape
your investment philosophy.
Speaker 2 (02:41):
Martial arts. It gave me the insurance I would say
that nothing is impossible. You always have to find a
way to get to that point where you're going to
achieve what you want. There's always a way to achieve
what you want, but you need to keep working on
(03:01):
that in one way or another. But you can't. You
can't give up. There's a way and you have to
find it. You have to fight until you find it.
That's something I learned from from martial arts. Meditation helps
me to center my mind before I work, after I work,
and in my life too. I need it like I
(03:22):
need the air, especially in this kind of business, which
is very stress in business, and and I practice meditation
in order to stay focused, to connect with myself, to
in a way to connect with God because I'm a believer,
and it prepares me to start a day and to
(03:44):
finish the day as well.
Speaker 1 (03:45):
Yeah, wonderful markets in some ways are the sum of
many people's risk capitalized and their investment decisions, so they
therefore reflect to set a whole of human behaviors. How
do you design your systems so you can spot meaning
patterns they are getting lost in all of that noise.
Speaker 2 (04:05):
It's kind of a fear a great thing. The name
is perfect for this. Markets are driven by humans. We
all have the same behaviors, no matter whether we are
in the twenty oneth century, in the twenty first century,
in the nineteenth century, it doesn't matter. We all have
(04:28):
the same reactions, emotional reactions, and those common behaviors are
the ones that we try to detect with the metologies
we used to look for patterns. In a way, we
are using mathematics in order to get those patterns and
(04:50):
try to see where they take us, what kind of
outcome we can get from those patterns. And if we
can establish what outcome we can get in certain racial probabilities,
we know that we have a button that can be
exploited in the market. So sentiments from the people fed
on grid.
Speaker 1 (05:09):
Yeah, and turning really human behaviors into numbers and patterns
that you can recognize exactly. So early in your investment career,
before going global as you have, you managed money for
a family office in Argentina, growing your Latin American footprint.
What did that experience you know, if you think back
to that in those formative years and times, what did
that experience teach you about managing other people's capital?
Speaker 2 (05:32):
First of all, that you have to be extra responsible.
You're gonna be dealing not only with their money, but
with their psychology. Okay, there will be times when they're
gonna feel afraid because what's happening in the markets, because
what's happening with the portfolio, and you will have to
(05:55):
deal with that too and prepare protocols to deal with
that tool I mean risk management protocols to give them
an objective way to measure what you're doing so they
can see how you can You're going to deal with
the market with the noise in the in the portfolio.
So the first thing I learned is that you're not
(06:18):
only dealing with the money, you're dealing with the psychology
of the people. That takes you to the point where
when they say that they can stand at a certain
kind of bridgs, you have to consider that they can
stand a half of that risk. So I think those
are the most important things I have learned from my
job as a family office manager.
Speaker 1 (06:41):
Let's move to what is called quantitative investing. As you've described,
how does the ausb's capital side tect grow wise fund
differ from what investors typically expect from other fund managers.
Speaker 2 (06:53):
OSWEE is going to replicate what we have been doing
for the last eighteen years. So the Auspice grow as
Capital fund is going to be a multi asset, multi strategy,
multidirection and multi time frame fun That means that we're
going to use all kinds of asset classes in order
(07:18):
to try to look for patterns and as we trade,
patterns and patterns are a short definition of the data
series in time. So that means that we get in
from the into the data and were out and get
out out of the data when when the conditions are met.
(07:38):
That means that we're not in the markets all the time.
So if we are not in the market all the time,
we need multiple opportunities in order to avoid the under
use of our capital. Okay, so to do that, we
need to get as many as many opportunities as we can.
And that's something that it can be found if you
(08:02):
train multiple assets and multiple directions. That means long, short,
neutral strategies and multiple time frames, because you're going to have,
for example, different different behaviors, whether it's on a daily
time frame, when it's sixty minutes time frame where is
so you will see that in a certain time frame,
(08:23):
the prices of certain asset is going to have a
mean reverting profile, but in a lower time frame it
might have a trend follow wing profile. And that gives
you different opportunities, even in the same assets, to go
along to short and to take advantage of those assets
as independent p and ls, as independent performance providers.
Speaker 1 (08:47):
It's a fascinating matrix because in my head, I'm trying
to work a hell I possibly do that, as you know,
just align in my own mind.
Speaker 2 (08:55):
Now it can be done.
Speaker 1 (08:56):
You know, it's in practical So one thing that stands
out about to your business is the frame model. There's
no management phase, only a performance fee above high watermark.
Why did you go with that structure and how does
that align with your investors?
Speaker 2 (09:12):
I think I say that we don't charge the client.
We charge the market because we don't touch the client's capital.
But it reflects the philosophy of my of my fund
and of my life. I think that if I'm going
to offer you something and I don't provide you with
(09:33):
what I had offered, I couldn't charge you. It's it's
it's not moral in my opinion. So I have to
give you a performance and I will charge you. But
if I don't give you a performance, why would I
charge you? That's that's what I think. I don't criticize
the ones who does it differently, but I prefer to
(09:55):
do it that way. And secondly, that demonstrate that I
truly believe in what we do, because if I wouldn't,
it would it would have to be in another business.
Speaker 1 (10:11):
So let's talk about risk in everyone's mind, especially with
someone trailing across equities, commodities, currencies, digital assets. What you've
talked about there. We haven't specifically mentioned diversification, but it's
implicit in what you've already said in about multiple models
at the same time.
Speaker 2 (10:29):
How do you do that?
Speaker 1 (10:30):
How do you make that approach work to protect investments
during market downturns.
Speaker 2 (10:36):
The versification for me is the ancorrelation of different strategies,
are play tool, different assets classes, or different time friends,
or different directions. That means I don't I don't see assets,
I don't I don't see Google. That's good. It's not
(10:57):
a management no, no, it's there all data series. So
what I get from those data series are the patterns
and the p and l the performance of those patterns
mustn't be correlated. When they are not correlated, they are
diversifying because they're gonna be compensating the other system draw
(11:18):
down if they if it occurs, and they're gonna be
smoothing the equity curve in the in the long run,
and bye by trading different time frames. Perhaps you might
have a crisis in a daily time frame, but the
cricy doesn't exist in in the in a smaller timeframe,
for example. Or perhaps you have a very fast movement
(11:42):
in a in a lower time frame, but that correction
doesn't exist in a higher time frame. So by by
by trading different time frames in different directions and taking
care being sure mathematically, of course, the those strategies are
not correlated at all. You're adding diversification to a portfolio,
(12:06):
and you're protecting your portfolio against these kind of events.
Speaker 1 (12:10):
Let's talk about digital assets. There's not really the decades
of history available perhaps in other asset classes. How did
you adapt your strategy or did you even have to
model and try it effectively in markets that have a
short track record.
Speaker 2 (12:25):
First of all, to trade an asset asset or another asset,
we need the most important raw material. We have to
use the data. It should be quality data, and a
problem with crypto is that we don't have quality data
and the quality data is very new. So we can
(12:49):
take the history that we have in crypto right now.
In order to make statistical significant conclusions, we would need
more history. But that doesn't mean that crypto doesn't reflect
behaviors human behaviors as the rest of the assets do.
(13:11):
We have different systems. Systems that are good for just
one asset, systems are are good for a basket of assets,
and we have systems are are good for almost all
kinds of assets. As we trade cryptos, regulated cryptos through
regulated edfs, we apply a different system that we use
(13:32):
for interest rates, and we and some others that we
use for training universities of stocks. They have been tested
through thousands and thousands of patterns in different stocks and
they have survived, so when applying them to crypto, they
work very well as well.
Speaker 1 (13:52):
Now let's just wrap this up with every die investors
you might be listening in because this is fascinating material.
Speaker 2 (13:57):
Thank you.
Speaker 1 (13:58):
What is the biggest conception that you say about systematic investing.
Speaker 2 (14:05):
Most of the people think that by knowing how to
design a system. You just design a boat, an algorithm,
your robot, and you're gonna get into jump into the
market and start trading. And it doesn't work that way.
You're gonna end up adjusting your training conclusion to the
data in a point where you are going to overfeit
(14:28):
your model and you won't be able to transporlate your
model into the future. It's not going to produce good
performance into the future because human behaviors don't reput use
into the future in a very precise way. For example,
if we stand in front of the lion, your reaction
(14:49):
would be pretty similar to my reaction, but you would
end up running away after ten seconds. I would be
running away after fifteen seconds. So that gives us a
room for certain baby and there are different statistical techniques
to lead with that to look for robblesness in the
(15:11):
development of the of the models. And that's something that
is not understood in the new systematic traders. They need
to use different different tools in order tool deal with
over feeding Oberfiit is our first enemy as systematic traders.
Speaker 1 (15:32):
Okay, yes, that is fascinating. Ivan, Thank you so much
for joining us today on fear and greed Q and A.
Speaker 2 (15:38):
It's a pleasure, Thank you for having me.
Speaker 1 (15:40):
That was Ivan Sherman, chief investment officer at Sciente Tech
Investments and portfolio manager of the Osby's capital side Tech
grow Wise Fund, a proud support of this podcast. If
you've got something you'd like to know, send you a
question via LinkedIn, Instagram, Facebook, or head over to fearangreed
dot com dot au. I'm Adam Lang and this has
been Fearing great Q and A.
Welcome to Fear and Greed Q and A, where we
ask and answer questions about business, investing, economics, politics and more.
I'm Adam Langan. Today we're asking can algorithms beat humans
at investing? Or like artificial intelligence, is it the combination
of humans and machines that wins. Please note that this
is general information only and you should seek professional advice
(00:27):
before making any investment decisions. My guest today I'm delighted
to say is Ivan Sherman, chief investment officer at Siye
Tech Investments and the portfolio manager of the osbi's capital
sie Tech grow Wise Fund, a supporter of this podcast.
Originally from Argentina, Ivan holds a PhD and advanced certifications
from get This, London Business School, New York University's stern
(00:52):
ARPM Lab and University dad Polytechnica de Madrid. He's visiting
Australia now as the grow Wise Fund opens its door
was to retail investors for the first time. Ivan, Welcome
to Fear and Great.
Speaker 2 (01:04):
Thank you so much, Thank you for having me.
Speaker 1 (01:06):
You've made global news in twenty twenty three by winning
the World Cup of Trading with a nearly five hundred
percent return in one year. How did you do it.
Speaker 2 (01:20):
By trading the same trading systems I trade for my company,
but perhaps with a different tactical approach. What I wanted
to do is to combine different trading assets, different assets,
asset classes, with different trading strategies and different time frames
(01:43):
in order to create an equity curve as steady as
I can get. And that's what I did. The contribution
of each of the systems into the performance of a
portfolio took me to win the championship.
Speaker 1 (02:00):
As you're talking about it, and almost see that competitive
spirit come alive.
Speaker 2 (02:05):
Was it like a game?
Speaker 1 (02:06):
Was it like a full contact sport?
Speaker 2 (02:08):
Yes? And no. I mean I tried to stick to
my plan, tried to not be influenced by what was
happening around me, because there were a lot of competitors
who went up very fast and went down very fast
as well.
Speaker 1 (02:20):
It does sound, as you talk about it, like an
incredibly disciplined approach. So I looked at your resume of education,
and you've got that disciplined approach in the way you
approach things. You're also someone who embraces meditation, fitness, martial arts,
and horse riding. How do all these different disciplines shape
your investment philosophy.
Speaker 2 (02:41):
Martial arts. It gave me the insurance I would say
that nothing is impossible. You always have to find a
way to get to that point where you're going to
achieve what you want. There's always a way to achieve
what you want, but you need to keep working on
(03:01):
that in one way or another. But you can't. You
can't give up. There's a way and you have to
find it. You have to fight until you find it.
That's something I learned from from martial arts. Meditation helps
me to center my mind before I work, after I work,
and in my life too. I need it like I
(03:22):
need the air, especially in this kind of business, which
is very stress in business, and and I practice meditation
in order to stay focused, to connect with myself, to
in a way to connect with God because I'm a believer,
and it prepares me to start a day and to
(03:44):
finish the day as well.
Speaker 1 (03:45):
Yeah, wonderful markets in some ways are the sum of
many people's risk capitalized and their investment decisions, so they
therefore reflect to set a whole of human behaviors. How
do you design your systems so you can spot meaning
patterns they are getting lost in all of that noise.
Speaker 2 (04:05):
It's kind of a fear a great thing. The name
is perfect for this. Markets are driven by humans. We
all have the same behaviors, no matter whether we are
in the twenty oneth century, in the twenty first century,
in the nineteenth century, it doesn't matter. We all have
(04:28):
the same reactions, emotional reactions, and those common behaviors are
the ones that we try to detect with the metologies
we used to look for patterns. In a way, we
are using mathematics in order to get those patterns and
(04:50):
try to see where they take us, what kind of
outcome we can get from those patterns. And if we
can establish what outcome we can get in certain racial probabilities,
we know that we have a button that can be
exploited in the market. So sentiments from the people fed
on grid.
Speaker 1 (05:09):
Yeah, and turning really human behaviors into numbers and patterns
that you can recognize exactly. So early in your investment career,
before going global as you have, you managed money for
a family office in Argentina, growing your Latin American footprint.
What did that experience you know, if you think back
to that in those formative years and times, what did
that experience teach you about managing other people's capital?
Speaker 2 (05:32):
First of all, that you have to be extra responsible.
You're gonna be dealing not only with their money, but
with their psychology. Okay, there will be times when they're
gonna feel afraid because what's happening in the markets, because
what's happening with the portfolio, and you will have to
(05:55):
deal with that too and prepare protocols to deal with
that tool I mean risk management protocols to give them
an objective way to measure what you're doing so they
can see how you can You're going to deal with
the market with the noise in the in the portfolio.
So the first thing I learned is that you're not
(06:18):
only dealing with the money, you're dealing with the psychology
of the people. That takes you to the point where
when they say that they can stand at a certain
kind of bridgs, you have to consider that they can
stand a half of that risk. So I think those
are the most important things I have learned from my
job as a family office manager.
Speaker 1 (06:41):
Let's move to what is called quantitative investing. As you've described,
how does the ausb's capital side tect grow wise fund
differ from what investors typically expect from other fund managers.
Speaker 2 (06:53):
OSWEE is going to replicate what we have been doing
for the last eighteen years. So the Auspice grow as
Capital fund is going to be a multi asset, multi strategy,
multidirection and multi time frame fun That means that we're
going to use all kinds of asset classes in order
(07:18):
to try to look for patterns and as we trade,
patterns and patterns are a short definition of the data
series in time. So that means that we get in
from the into the data and were out and get
out out of the data when when the conditions are met.
(07:38):
That means that we're not in the markets all the time.
So if we are not in the market all the time,
we need multiple opportunities in order to avoid the under
use of our capital. Okay, so to do that, we
need to get as many as many opportunities as we can.
And that's something that it can be found if you
(08:02):
train multiple assets and multiple directions. That means long, short,
neutral strategies and multiple time frames, because you're going to have,
for example, different different behaviors, whether it's on a daily
time frame, when it's sixty minutes time frame where is
so you will see that in a certain time frame,
(08:23):
the prices of certain asset is going to have a
mean reverting profile, but in a lower time frame it
might have a trend follow wing profile. And that gives
you different opportunities, even in the same assets, to go
along to short and to take advantage of those assets
as independent p and ls, as independent performance providers.
Speaker 1 (08:47):
It's a fascinating matrix because in my head, I'm trying
to work a hell I possibly do that, as you know,
just align in my own mind.
Speaker 2 (08:55):
Now it can be done.
Speaker 1 (08:56):
You know, it's in practical So one thing that stands
out about to your business is the frame model. There's
no management phase, only a performance fee above high watermark.
Why did you go with that structure and how does
that align with your investors?
Speaker 2 (09:12):
I think I say that we don't charge the client.
We charge the market because we don't touch the client's capital.
But it reflects the philosophy of my of my fund
and of my life. I think that if I'm going
to offer you something and I don't provide you with
(09:33):
what I had offered, I couldn't charge you. It's it's
it's not moral in my opinion. So I have to
give you a performance and I will charge you. But
if I don't give you a performance, why would I
charge you? That's that's what I think. I don't criticize
the ones who does it differently, but I prefer to
(09:55):
do it that way. And secondly, that demonstrate that I
truly believe in what we do, because if I wouldn't,
it would it would have to be in another business.
Speaker 1 (10:11):
So let's talk about risk in everyone's mind, especially with
someone trailing across equities, commodities, currencies, digital assets. What you've
talked about there. We haven't specifically mentioned diversification, but it's
implicit in what you've already said in about multiple models
at the same time.
Speaker 2 (10:29):
How do you do that?
Speaker 1 (10:30):
How do you make that approach work to protect investments
during market downturns.
Speaker 2 (10:36):
The versification for me is the ancorrelation of different strategies,
are play tool, different assets classes, or different time friends,
or different directions. That means I don't I don't see assets,
I don't I don't see Google. That's good. It's not
(10:57):
a management no, no, it's there all data series. So
what I get from those data series are the patterns
and the p and l the performance of those patterns
mustn't be correlated. When they are not correlated, they are
diversifying because they're gonna be compensating the other system draw
(11:18):
down if they if it occurs, and they're gonna be
smoothing the equity curve in the in the long run,
and bye by trading different time frames. Perhaps you might
have a crisis in a daily time frame, but the
cricy doesn't exist in in the in a smaller timeframe,
for example. Or perhaps you have a very fast movement
(11:42):
in a in a lower time frame, but that correction
doesn't exist in a higher time frame. So by by
by trading different time frames in different directions and taking
care being sure mathematically, of course, the those strategies are
not correlated at all. You're adding diversification to a portfolio,
(12:06):
and you're protecting your portfolio against these kind of events.
Speaker 1 (12:10):
Let's talk about digital assets. There's not really the decades
of history available perhaps in other asset classes. How did
you adapt your strategy or did you even have to
model and try it effectively in markets that have a
short track record.
Speaker 2 (12:25):
First of all, to trade an asset asset or another asset,
we need the most important raw material. We have to
use the data. It should be quality data, and a
problem with crypto is that we don't have quality data
and the quality data is very new. So we can
(12:49):
take the history that we have in crypto right now.
In order to make statistical significant conclusions, we would need
more history. But that doesn't mean that crypto doesn't reflect
behaviors human behaviors as the rest of the assets do.
(13:11):
We have different systems. Systems that are good for just
one asset, systems are are good for a basket of assets,
and we have systems are are good for almost all
kinds of assets. As we trade cryptos, regulated cryptos through
regulated edfs, we apply a different system that we use
(13:32):
for interest rates, and we and some others that we
use for training universities of stocks. They have been tested
through thousands and thousands of patterns in different stocks and
they have survived, so when applying them to crypto, they
work very well as well.
Speaker 1 (13:52):
Now let's just wrap this up with every die investors
you might be listening in because this is fascinating material.
Speaker 2 (13:57):
Thank you.
Speaker 1 (13:58):
What is the biggest conception that you say about systematic investing.
Speaker 2 (14:05):
Most of the people think that by knowing how to
design a system. You just design a boat, an algorithm,
your robot, and you're gonna get into jump into the
market and start trading. And it doesn't work that way.
You're gonna end up adjusting your training conclusion to the
data in a point where you are going to overfeit
(14:28):
your model and you won't be able to transporlate your
model into the future. It's not going to produce good
performance into the future because human behaviors don't reput use
into the future in a very precise way. For example,
if we stand in front of the lion, your reaction
(14:49):
would be pretty similar to my reaction, but you would
end up running away after ten seconds. I would be
running away after fifteen seconds. So that gives us a
room for certain baby and there are different statistical techniques
to lead with that to look for robblesness in the
(15:11):
development of the of the models. And that's something that
is not understood in the new systematic traders. They need
to use different different tools in order tool deal with
over feeding Oberfiit is our first enemy as systematic traders.
Speaker 1 (15:32):
Okay, yes, that is fascinating. Ivan, Thank you so much
for joining us today on fear and greed Q and A.
Speaker 2 (15:38):
It's a pleasure, Thank you for having me.
Speaker 1 (15:40):
That was Ivan Sherman, chief investment officer at Sciente Tech
Investments and portfolio manager of the Osby's capital side Tech
grow Wise Fund, a proud support of this podcast. If
you've got something you'd like to know, send you a
question via LinkedIn, Instagram, Facebook, or head over to fearangreed
dot com dot au. I'm Adam Lang and this has
been Fearing great Q and A.
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