3 things day traders refuse to understand about quant trading

Summary

In 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

00:00

🚫 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.

05:00

🧮 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.

Keywords

💡Quantitative Trading

Quantitative trading refers to the use of mathematical models and algorithms to make trading decisions. It is a method that relies on quantitative analysis and data to predict future market movements. In the video, the speaker debunks misconceptions about this practice, emphasizing that it is not about large institutions targeting individual traders but rather a sophisticated field that requires advanced knowledge and technology.

💡Day Traders

Day traders are individuals who buy and sell financial instruments within the same trading day. The video discusses how day traders often believe they are being targeted by large trading firms, which the speaker refutes by stating that such firms are not interested in individual traders' activities.

💡Retail Traders

Retail traders are non-professional traders who trade for their personal accounts. The script mentions that retail traders often have misconceptions about the world of quantitative trading, such as believing they can compete with large firms on their own.

💡Stop-Losses

A stop-loss is an order placed with a broker to sell a security when it reaches a certain price. The video mentions that retail traders often believe they are being 'hunted' by large institutions targeting their stop-losses, which the speaker dismisses as a misconception.

💡Market Data

Market data refers to the information on the timing, price, and volume of transactions in a security. The speaker explains that all trades are published on market data channels and are anonymized, making it impossible for large institutions to target individual traders.

💡Anonymized Trades

Anonymized trades are transactions where the identities of the traders are hidden to protect privacy and prevent market manipulation. The video script uses this term to explain why large institutions cannot target individual traders' stop-losses.

💡Quantitative Trading Firms

These are firms that specialize in quantitative trading, using complex mathematical models to analyze market data and make trading decisions. The video script clarifies that these firms are not out to get individual traders but are focused on sophisticated trading strategies.

💡Machine Learning

Machine learning is a subset of artificial intelligence that provides systems the ability to learn from data without being explicitly programmed. The video mentions that machine learning, not technical analysis, is what quantitative trading firms use to predict market movements.

💡Technical Analysis

Technical analysis is the study of historical market data, primarily price and volume, to predict future market movements. The video script clarifies that contrary to popular belief among some retail traders, quantitative trading firms do not use technical analysis in the traditional sense but rather more advanced statistical models.

💡PhDs

PhDs, or Doctor of Philosophy degrees, are the highest academic research degrees. The video mentions that quantitative trading firms employ many PhDs, indicating the level of expertise and advanced knowledge required in the field.

💡Misconceptions

Misconceptions are false or inaccurate beliefs. The video's main theme revolves around debunking three common misconceptions about quantitative trading held by day traders and retail traders.

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