3 things day traders refuse to understand about quant trading
Summary
TLDRIn this video, Coding Jesus debunks three common misconceptions about quantitative trading, often held by day traders and retail traders. He clarifies that large trading firms aren't hunting individual traders' stop losses, highlights the complexity of quantitative trading which requires large teams and specialized expertise, and explains that successful quant firms like Jim Simons' Renaissance rely on machine learning and advanced statistics, not simple technical analysis. With over 100 PhDs, these firms use highly sophisticated models that go far beyond the methods promoted by retail trading gurus.
Takeaways
- 😌 **Misconception 1**: There's a cabal of quantitative trading firms and large institutions targeting individual day traders. The truth is, these firms don't care about individual traders; they're not hunting stop-losses or targeting small players.
- 🏦 **Market Data**: Trades are published on market data channels in an anonymized form, making it impossible to trace them back to individual traders.
- 🚫 **Stop-Loss Hunting**: Claims of being 'hunted' are often just a coping mechanism for traders who consistently lose money, not a reflection of reality.
- 💡 **Quantitative Trading Complexity**: It's a misconception that a single person can implement competitive quantitative strategies on their own, as it requires a team of specialists and significant resources.
- 👨💻 **Specialization**: Quantitative trading firms have teams of experts, each specializing in a subdomain, such as risk systems or market data, rather than being generalists.
- 🤝 **Teamwork**: Success in quantitative trading is often a result of collaboration among experts, not the work of a lone individual.
- 🧐 **Jim Simons' Perspective**: Contrary to popular belief, Jim Simons and similar firms do not use technical analysis in the traditional sense; they rely on machine learning and advanced statistical models.
- 📈 **Predictive Models**: Predictive power in quantitative trading comes from sophisticated models, not from simple technical analysis patterns.
- 🎓 **Expertise**: Quantitative trading firms employ highly educated professionals, including many PhDs, who specialize in areas like machine learning and statistics.
- 💼 **Hiring Strategy**: The key to success in quantitative trading is hiring smart people and allowing them to work together to develop effective trading strategies.
Q & A
What is the first misconception about quantitative trading discussed in the video?
-The first misconception is that there is a cabal of quantitative trading firms and large institutions that are out to get individual day traders by hunting their stop-losses and running algorithms to catch them.
What does the speaker, Coding Jesus, reveal as an industry insider about the first misconception?
-Coding Jesus reveals that nobody at quantitative trading firms, proprietary trading firms, hedge funds, or banks is looking for individual traders to target, as they don't move the market and are not significant enough to be targeted.
What does the speaker mean when he says 'nobody cares about you' in the context of trading?
-He means that individual traders are not significant enough to be noticed or targeted by large trading institutions, as their trades do not have a substantial impact on the market.
What is the second misconception about quantitative trading mentioned in the video?
-The second misconception is that a single person can implement and be competitive with quantitative trading strategies on their own, like a 'jack of all trades'.
Why does the speaker believe it's futile for a single person to compete with large quantitative trading firms?
-The speaker believes it's futile because these firms have teams of over 50 people each working full-time, with virtually unlimited resources, and each person specializes in a subdomain, making it highly unlikely for an individual to outpace them.
What is the third misconception discussed in the video about quantitative trading?
-The third misconception is that Jim Simons and quantitative trading firms use technical analysis in their trading strategies.
How does the speaker debunk the idea that quantitative trading firms use technical analysis?
-The speaker debunks this by showing a clip of Jim Simons discussing the use of machine learning and advanced statistical models, not technical analysis, for making predictive bets.
What does the speaker suggest is the composition of people working in quantitative trading?
-The speaker suggests that quantitative trading firms are composed of highly educated individuals, including many PhDs, who specialize in fields like computational models, markets, machine learning, and statistical techniques.
What does the speaker recommend for those interested in breaking into quantitative trading?
-The speaker recommends reaching out to him one-on-one for guidance, as he offers his time for consultation via Calendly, and also suggests becoming a patron for early access to videos and an exclusive Discord community.
What is the speaker's stance on the idea that day traders can consistently make money by blaming losses on being 'hunted'?
-The speaker believes that blaming losses on being 'hunted' is a coping mechanism and an excuse for day traders who consistently lose money, rather than a reflection of reality.
What does the speaker imply about the role of specialization in the success of quantitative trading firms?
-The speaker implies that specialization is crucial for the success of quantitative trading firms, as each team member focuses on a specific subdomain, contributing to the firm's overall trading strategy.
Outlines
🚫 Misconceptions in Quantitative Trading
In this segment, Coding Jesus addresses common misconceptions about quantitative trading, particularly those held by day traders and retail traders. The first myth is that there's a conspiracy of large trading firms and institutions targeting individual traders. He refutes this by stating that no one in the industry is concerned with individual traders due to their negligible impact on the market. The second myth is the belief that a single person can effectively implement and compete with quant trading strategies, which he argues is unrealistic given the extensive resources and expertise required in the field. He emphasizes the specialization and team efforts within quant firms, suggesting that the idea of a lone trader being competitive is ignorant of the industry's complexity.
🧮 Debunking Quantitative Trading Myths
Coding Jesus continues by debunking another myth—that quantitative trading firms, including Jim Simons', use technical analysis. He clarifies that while historical price data is used, it's not in the way retail traders might think, such as looking for chart patterns. Instead, he points out that Jim Simons was referring to machine learning and advanced statistical models, not technical analysis. The use of machine learning and statistical techniques by quant firms, which involve complex algorithms and models developed by experts, is far from the simple technical analysis methods retail traders might use. He also mentions the composition of quant trading teams, highlighting that they consist of many PhDs with deep expertise in fields like machine learning and statistics, further emphasizing the sophistication of quant trading strategies.
Mindmap
Keywords
💡Quantitative Trading
💡Day Traders
💡Retail Traders
💡Stop-Losses
💡Market Data
💡Anonymized Trades
💡Quantitative Trading Firms
💡Machine Learning
💡Technical Analysis
💡PhDs
💡Misconceptions
Highlights
Misconception 1: There's a cabal of quantitative trading firms and large institutions hunting day traders.
Nobody at quantitative trading firms cares about individual day traders.
Day traders are not significant enough to move the market.
Claiming to be 'hunted' is often an excuse for losing money.
Trades are published anonymously on market data channels.
Misconception 2: A single person can implement and compete with quantitative trading strategies.
Quantitative trading firms have teams of over 50 people working full-time.
Specialization is key in quantitative trading; one person cannot do it all.
It's unrealistic for an individual to compete with large firms.
Misconception 3: Jim Simons and quantitative trading firms use technical analysis.
Jim Simons discusses using historical price data to predict future movements.
Quantitative trading uses machine learning, not technical analysis.
Predictive power is just one aspect of quantitative trading.
Quantitative trading relies on advanced statistical models and machine learning.
Reinforcement of the idea that quantitative trading does not use technical analysis.
Quantitative trading firms hire smart people with expertise in various fields.
Over 100 PhDs work at Jim Simons' firm, emphasizing the importance of expertise.
Debunking the idea that YouTube courses can compete with professional quantitative trading strategies.
Contact information provided for one-on-one consultation on quantitative trading.
Invitation to join an exclusive Discord community for those interested in quantitative trading.
Instagram account mentioned for following the creator's daily life.
Transcripts
what is up guys coding Jesus here guys
in today's video I want to talk about
three misconceptions that I hear all the
time about the world of quantitative
trading from day Traders and Retail
traders in particular so without further
Ado guys let's jump into the video the
number one thing that I hear about from
day Traders is that there is this cabal
of quantitative trading firms and large
institutions that are out there to get
them that usually comes in the form of
things like oh you're stu got hunted or
oh there's some quasi large group of
conglomerate banks that are out there to
get you and they have certain levels
that they put in and algorithms they run
at certain times of the market to try to
catch
you I actually initially heard this
really Preposterous claim from a client
of mine that wanted to discuss breaking
into the world of quantitative trading
and gave me a bit of background as to
his Experience day trading and it's a
some of the content that he's been
taught from some YouTube gurus out there
now this video isn't made to focus on
one Guru or another it's made to talk
about kind of the content that they spew
to Their audience that leads them to
believe these sorts of non- truths these
sorts of Lies what I can tell you as an
industry Insider that should not be
controversial at all is that nobody
cares about you now I don't mean that
your parents don't care about you you
don't have families and friends and dogs
that love you what I mean by that is
nobody working at a quantitative trading
firm proprietary trading firm a hedge
fund or a bank is looking for you is out
there to get you nobody's hunting your
stop-losses you aren't that important
okay you don't move markets your trades
don't move for size they don't matter
even if it were the case by the way that
there can be a strategy that involved
melting the pockets of day Traders and
transferring money from day traders to
large uh Ivory Tower institutions the
idea is totally rooted in ignorance as
to how markets work from a technical
component from the technological side if
you spend any time reading Market data
documentation which is pretty much part
of what I do for a living you notice
that all trades that you do are
published on Market data channels that
are anonymized there is identifiers out
there that are totally Anonymous
assigned to each trade and each order
that make them impossible to tie them
back to an individual Trader or
particular entity losing money to Big
players by saying oh I got hunted my
stops got hunted uh is really just a
cope and escapegoat for day traders that
consistently lose money there's another
misconception that retail Traders are
under that a single person in isolation
can Implement Quant strategies in other
words a single person can be competitive
as a jack of all trades in the world of
quantitative trading now I think these
people that parot this idea or parot
sounds a little derogatory hold this
idea rather
and they don't realize how much work
time and effort goes into the world of
quantitative trading firms literally
have teams of over 50 people each
putting in eight hours a day to compete
on a global stage against other firms
and institutions that have virtually
unlimited time money and resources to
invest in squeezing every drop of alpha
out of their trading activities not only
that but each software engineer in the
world of quantitative trading that
develops a career there starts by
specializing various subdomains in the
organization so you can literally be a
software engineer that specializes in
Risk systems which is like pre- trade
risk post-trade risk aggregation
reporting Etc and in theory you can have
10 plus years as of experience as a
software engineer doing that and never
work with order entry or Market data
that's how large some of these firms are
they literally have software Engineers
doing one thing and specializing in that
one field of expertise in their world of
quantitative trading such that they
never touch are exposed to other parts
of the organization now I'm fortunate
fortunate enough to have worked with
many services spanning from order
execution to Market data to internal
tooling to risk systems Etc but if you
were to tell me hey coding Jesus go
Implement those Quant
strategies that doesn't mean that I a
want to spend my time outside of work
building these sorts of systems from
scratch and B it doesn't mean that I'm
arrogant enough to think that I can
outpace these firms who have dozens of
employees working around the clock as I
mentioned so when somebody asks me a
question like why don't you just you
know go Implement your own Quant
strategies on your own that question is
really rooted in ignorance and I don't
blame somebody for asking that question
because the world of quantitative
trading is so mysterious but as an
industry Insider what you realize is
that the more you know the more that you
work on these sorts of critical systems
and conjunction with other bright
individuals the more you understand just
how futile it is to approach this
industry as a single person and compete
on the same playing field as an
individual all right now the last
misconception and I'm laughing a little
because this is actually the funniest
one in my opinion is that Jim Simmons
and quantitative trading firms use
technical analysis what I usually hear
from somebody maybe in the comment
section is huh quants don't use ta tell
that to Jim
Simmons okay when people say this
they're usually referring to like a clip
from something that Jim Simmons said
years ago without context and I'll fill
in the context for you guys don't worry
and so before I even continue let's look
at this clip together but gradually we
found more and more and more and more
anomalies none of them is so
overwhelming that you're going to clean
up on a particular anomaly because if
they were other people would have seen
them so they have to be subtle things
and you put
together uh a collection of these subtle
anomalies and you begin to get something
that will predict pretty well so so here
he's talking about predict pretty well
and what he's referring to is using
historical price data to predict future
movements and people in the world of
technical analysis will take the
statement and say well oh he's using
previous price data he's looking at I
don't know what they think like cup and
handle or whatever and he's using that
to tell where prices will be going based
off of you know previous historical
Trends now what these people usually
miss out on is the next literal 30
seconds of the interview so I'm not
going say anything I'm going to let Jim
Simmons debunk the own misconceptions
that day Traders have been spewing out
there that he and people like him and
other large quantitative trading firms
not even large I mean big or small use
technical analysis let's take a
look how elaborate are these things
because in my head I'm imagining you
know some equation like uh like
Pythagoras equation and you put a few
numbers in and something spits out but
are these giant beasts of equations and
algorithms or are they are they simple
things uh well the the system as it is
today is extraordinarily elaborate but
it's not a whole lot of you know it's
it's what's called machine
learning okay now he's talking about the
techniques that he uses in order to make
certain predictive bets okay machine
learning not technical analysis not cup
and handle not Head and Shoulders Knees
and Toes or whatever people use he's
talking about machine learning in
particular now he even goes into more
depth as to predictive power being just
one very small subdomain of quantitative
Trading in which machine learning not ta
is used but he also talks about other
subdomains it's mostly statistics and uh
some uh some probability Theory and but
I can't get into you know what things we
do do use and what things we don't use
we we reach for different things that
might come that might be effective uh so
we're very Universal we don't have any
any uh but it's a big computer model so
that's where he really drops the bom he
drops a bomb by clearly referring to
Advanced statistical models crafted by
experts in machine learning who have
spent decades collectively in their
field he's not referring to your
favorite YouTube getrich Qui grifter ta
seller cor seller whatever all right
there's one more piece at the very end
of this video that I think's worth
mentioning where he discusses the
composition of people that work in
quantitative trading and the techniques
that they use been proving it we have
about 100 phds working for the firm
that's what I me Ian how did you get to
that point did you start to think we
need this we need that what did we just
hired smart people my my algorithm has
always been you get smart people
together there you go a couple of
seconds he has over a 100 phds at the
firm and this was an interview from a
very long time ago so if you really
think that 100 PhD is equipped with the
most Cutting Edge understanding of
computational models uh markets machine
learning and statistical techniques are
using your favorite YouTube guru's $297
course on technical analysis then you're
beyond saving so hopefully you guys
understood about these three
misconceptions hopefully have debunked
each and every single one of them or at
least shed some light as to what they
are and why they're wrong if you'd like
to speak to me one-onone to break into
the world of quantitative trading guys
Link in the description box below you
can book my time via calendly if you'd
like to watch this video early you can
become a patron you get access to the
exclusive Discord where we just talk to
each other we do monthly calls Etc most
of the people there are very like-minded
and break into the space and if you'd
like to follow me outside of YouTube on
Instagram sharing my daily life almost
nothing Quant related disclaimer go
ahead and follow me on Instagram thanks
for watching this video guys cheers
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