4TB of Trading Data In 12 Minutes…
Summary
TLDRThe video script emphasizes the critical role of data in trading for long-term success, comparing it to essential business analytics. It dispels myths about mechanical trading and the importance of intuition and experience in making informed decisions. The speaker, drawing from extensive data analysis, argues against common technical analysis practices, advocating for a more data-driven approach that aligns with institutional trading strategies.
Takeaways
- 📊 Data is essential for long-term success in any business, including trading, as it helps in making informed decisions based on past performance and trends.
- 🤔 Not understanding data can lead to a lack of clarity on what is necessary for a hedge fund to succeed in trading and may result in taking unnecessary risks.
- 📈 The speaker emphasizes that data is not just about journaling trades or relying on personal feelings about trades, but rather on objective, institutional-grade analysis.
- 🔢 Data should be used to characterize the behavior of a currency or asset over the long term, helping traders understand market patterns and make better decisions.
- 🚫 The script refutes the idea that mechanical trading leads to consistent results, stating that it is not an institutional approach and can lead to poor outcomes.
- 💡 Institutional traders use intuition based on experience and data, rather than blindly following mechanical strategies or predetermined risk ratios.
- 📉 Cutting losses early is crucial in trading, and one should not cling to predetermined win ratios if the market conditions do not support the trade.
- 📈 Holding winners is more complex and requires understanding market movements and managing trades effectively, especially in markets that move quickly.
- 📚 Traditional technical analysis is considered less important by institutions, which prioritize data, fundamentals, and risk management over chart patterns.
- 🧐 The speaker shares personal insights from years of trading and testing, highlighting the importance of critical thinking and not just following popular opinion in trading.
- 🔑 The takeaways from analyzing terabytes of data stress the importance of understanding market behavior and using that knowledge to make trading decisions rather than relying on subjective observations.
Q & A
What are the four potential problems a viewer might have with data and trading according to the script?
-The script outlines four problems: A) Not knowing what data is and its potential for trading; B) Not understanding why data is essential for a hedge fund's success in trading; C) Having a misconception about what data is; D) Believing in mechanical trading and trading psychology without a clear understanding of data's role.
Why is data important for long-term success and growth in trading?
-Data is important because it is a requirement for long-term success and growth in any business, including trading. It helps in making informed decisions based on historical patterns and behaviors, which is crucial for consistent performance.
What is an example given in the script to illustrate the importance of data in business?
-The script uses the example of selling t-shirts, where observing which color sells out faster (black or white) helps in making data-driven decisions on stocking more of the popular color.
What does the speaker claim about mechanical trading and its results?
-The speaker claims that mechanical trading leads to inconsistent results and is not an institutional concept, suggesting that relying solely on mechanical systems without considering data and other factors can be detrimental to trading success.
What is the speaker's stance on the use of intuition in trading?
-The speaker suggests that intuition plays a significant role in trading, especially for institutional traders. It is used in conjunction with data and experience to make decisions about when to enter and exit trades.
According to the script, why is traditional technical analysis not sufficient for successful trading?
-The script argues that traditional technical analysis is not sufficient because it is typically used after considering data, fundamentals, and risk management. It should be a supplementary tool rather than the primary decision-making method.
What is the speaker's view on the common advice 'cut your losses and hold your winners'?
-The speaker agrees with the advice but emphasizes that it should be based on data and experience. Cutting losses should be done when the market conditions violate the trader's strategy, and holding winners should be managed carefully, especially in markets that move quickly.
What does the speaker suggest is a myth about trading based on liquidity and order block?
-The speaker suggests that the idea of 'liquidity plus order block equals a good trade' is a myth. This approach does not inherently guarantee good trades and is not a method used by institutions.
What is the speaker's opinion on the role of data in determining entry and exit strategies?
-The speaker believes that data is crucial for characterizing the behavior of a currency or asset over the long term. It helps in understanding the market's typical patterns and behaviors, which in turn aids in making informed entry and exit decisions.
What does the speaker mean when they say that data is not journaling trades?
-The speaker argues that journaling trades, or writing down personal feelings and thoughts about trades, is not the same as using objective data. Data should be based on market behavior and patterns, not on subjective observations or emotions.
What is the speaker's advice for traders who want to improve their trading strategies?
-The speaker advises traders to start testing their strategies with data, learn from experience, and not to rely solely on mechanical trading or traditional technical analysis. They should use data to understand market behavior and make informed decisions.
Outlines
📊 The Importance of Data in Trading
The speaker emphasizes the critical role of data in trading, comparing it to essential business analytics. They explain that data is necessary for long-term success, using the analogy of a business owner adjusting inventory based on sales data. The speaker clarifies misconceptions about data, stating that it is not merely journaling trades or relying on personal observations. Instead, data should be used to understand market behavior and make informed trading decisions. They also debunk the myth of mechanical trading leading to consistent results, arguing that institutional trading relies on a combination of data, intuition, and experience.
📈 Data-Driven Trading Insights
This paragraph delves into the speaker's personal journey and learnings from analyzing vast amounts of trading data. They argue against mechanical trading, asserting it leads to inconsistent results and is not a strategy used by institutions. The speaker shares insights from their experience, suggesting that traders should use data to identify patterns and behaviors in the market. They also discuss the importance of risk management, advocating for cutting losses and holding onto winning trades, but with a flexible approach that adapts to market conditions. The speaker criticizes the over-reliance on traditional technical analysis, suggesting it should be a secondary tool after considering data and fundamentals.
💡 Practical Trading Wisdom from Data Analysis
In the final paragraph, the speaker shares practical advice for traders based on their data analysis. They discuss the nuances of cutting losses and holding onto winning trades, especially in different markets like currencies and indices. The speaker stresses the importance of not rigidly adhering to fixed risk-reward ratios but instead using market conditions and experience to guide decisions. They also reiterate the limited utility of technical analysis in institutional trading, suggesting it's a supplementary tool rather than a primary strategy. The speaker concludes by offering to share more insights in a potential follow-up video, highlighting the depth of their data-driven trading knowledge.
Mindmap
Keywords
💡Data
💡Mechanical Trading
💡Intuition
💡Risk Management
💡Hedge Fund
💡Technical Analysis
💡Liquidity
💡Order Block
💡Risk Ratio
💡Journaling
💡Institutional Process
Highlights
Data is essential for long-term success and growth in trading and business.
Data helps differentiate what is necessary in an entry model or strategy and what is not.
Mechanical trading can lead to inconsistent results and is not an institutional concept.
Intuition plays a significant role in institutional trading, not just mechanical processes.
Risk ratios such as 1:3 or 1:5 are not inherently meaningful without market context.
Experience and intuition are critical in determining when to enter and exit trades.
Cutting losses early is a key practice in trading, supported by data and experience.
Holding winners is more challenging, especially in markets with quick movements like indices.
Traditional technical analysis is less effective without a foundation of data and fundamentals.
Institutions use technical analysis as a final step, not the primary decision-making tool.
Data is not about journaling trades, which is subjective and not an institutional process.
Blind observations without data can lead to incorrect conclusions and poor trading decisions.
Testing with data is crucial for understanding market behavior and improving trading strategies.
Data helps characterize the long-term behavior of a currency or asset for better trading decisions.
The importance of using data to prove theories and make informed trading decisions.
The speaker's personal journey from relying on technical analysis to understanding the importance of data.
A call to action for traders to start testing now to gain experience and improve their trading strategies.
The speaker's offer to create a second video to delve deeper into the insights gained from terabytes of data.
Transcripts
straight to the point here some of my
dat are right
here and I've got a lot more hair as
[Music]
well and I've got way more in the pages
in the background and I've got way more
than all of this back in my office in
East London I'm overseas at the moment
which is quite unfortunate but you click
this video for a reason and I'm going to
show you exactly what you
need so this is what you look like right
now and you got a few problems you've
got one of these four
problems a you don't know what data is
and you want to learn what it could do
for your trading that's number one B you
don't know why a data is required for a
hedge fund to succeed in trading um
number three or C whatever you want to
call it you've been saw a lie on what
data is you're a mechanical Trader and
you also believe in trading psychology
now I'm going to get more into these in
specific videos but today we're here for
one reason only
now why is data so important it's a
requirement when it comes to long-term
success and growth in every business so
many people aren't really aware that we
look at data for everything right when
it comes to a business you're looking at
the monthly requiring Revenue there is
going to be data within that imagine you
have two shirts right you've got a white
one and a black one let's say the black
one sells out really quickly you're
going to need to look at the data so you
don't order the same amount you're going
to need to order more black ones because
they sell out really easily and you're
going to want to be able to sell more of
those right that's going to be a very
simple form of data but you get my point
hedge funds know this all of the top
gurus know this but you don't but the
funny thing is what I'm telling you is
literally needed if you don't do this
you're not going to get anywhere you can
do technical analysis for 20 years it
doesn't matter you're never going to get
there if you don't do what I'm doing
well you're not here to have a a good
one month two months 3 months you're
here to have a good career right you
want to be able to literally go from
where you are right now perhaps you're
working a job perhaps you're you know
you have a few funded accounts you blown
a few funded accounts and you want to
become consistent I'm just going to be
brutally honest with you so subscribe
right now without data you're not really
aware of what is needed and what isn't
needed you're just taking a shot in the
dark I explain this quite well when it
comes to the t-shirts but you're just a
bit mad if you're trading something that
you don't have actual data on right just
looking up YouTube videos of high winway
strategy I remember back in the day you
know like 5 6 seven years ago retail
trading as you would call it was called
institutional at some point right people
were selling the program saying yeah
this is institutional this and that
which is obviously not true right and
then 3 4 years ago we were told that
funded accounts are actually given us
real Capital but now we obviously know
that they're not giving us real Capital
2 years ago people were saying ICT is
institutional but now we're quite well
aware that it's not right so how many
lives do you need to go through and how
many years does it need to take you to
get a clear picture that's real
question okay what is and isn't data
data is not journaling your trades right
this idea of people journaling their
trades and being like guys make sure
that you Journal this and that this is
not day it's a bunch of anyways
it's it's nothing really important tell
me what's objective about writing down
how you feel about that stupid trade
that you took today what's objective
about that you're going to feel
something different every day and it's
going to trickle into your Trading right
so what does that have to do with your
trading it doesn't make any sense and
the people that also say the reason why
you're not winning because you're not
journaling or stupid they really really
are because journaling isn't an
Institutional process I'm going to tell
you everything that's an Institutional
process journaling is just a substitute
excuse lousy excuse to not have data
data is not your blind observations
trust me guys when I tell you you can't
just look at your Trad in and be like
usually when this happens this happens
x equal y can't do that you got 10
losses and 10 wins 50% win rate right
here so here's the thing if you look at
your losses and you say why am I losing
50% of the time and I'm going to make it
relatable to your ICT people right
imagine let's say that you're short in
the market or trading the market to the
downside when there's liquidity above
your high why all this liquidity below
your low and you're trying to buy let's
imagine this the case right you you
might look at all of your trades and say
very often there's liquidity below or
above it based off of Just Pure
observation just first hand observation
you're going to try to get rid of
trading that way but the problem with
that is that you're going to lose
everything and the reason why is because
you didn't look at the wins you might
realize six out of 10 wins play out like
that right so it's not in your interest
to get rid of it but you might be like
there's 10 losses that you're getting
rid of just for six wins but remember
risk ratio if you're trading a 1: one
then yeah sure right but you're trading
like a 1 to three 1 to four it makes a
lot more sense to just keep it and it's
just going to harm your trading if you
get rid of it and you're not going to
have 10 wins and 10 losses you're going
to have hundreds to thousands I've got
like roughly 15,000 testing trades so
you're going to determine Things based
off of a larger number can't do that on
100 trades un less there going to be
historical price dat on Real Time data
I'm going to talk about the differences
sometime but we're going to talk about
this you're going to use data to
characterize the behavior of a currency
or asset longterm basically what you're
going to do is you're going to know what
your your see your SPX does most of the
time and how to trade alongside that
information you're going to go off for
pattern recognition you're going to look
at Behavior you can't determine nothing
about the market without data
institutions do this and if you don't
believe me about institutions not being
mechanical there's a university in
Milton keing called the open University
and they've actually written studies
about this and they prove this concept
so I'm going to put that right in front
of the screen real
quick so data is used to differentiate
what is needed in an entry model or
strategy and what isn't needed right
there's so many things that you think
are needed within your trading but
they're not if you look at every single
Theory from the beginning of time you're
going to see that data is literally used
in everything to prove
anything so here we are what I've
learned from fre terabytes of data these
are some of the most important things
that I've genuinely learned it's
literally taken me about 8 years and
15,000 or 25,000 testing trades to come
to this conclusion and this is some of
the most important things ever in
trading mechanical trading leads to
terrible inconsistent results this is
not an Institutional
concept now a lot of people are going to
be mad because they're going to be like
what but we're trading the algorithm no
you're not man it's an objective truth I
don't know why you would get mad and P
to that ego of wanting to be right it's
going to lead to you just staying in the
same position because you can't accept
anything whoever tells you that you
should be trading mechanically doesn't
know nothing I want you to rationally
think I want you to be critical thinkers
right I don't want you to just listen to
people right most of these gurus and you
know this are only one two steps ahead
of you they've got in a payout if
they're trading prop firm accounts or
they probably manage some sort of funded
account mechanical tra trading
is a + Bal X meaning and I'm going to
relate it to you liquidity plus order
block equals good trade assuming that we
do liquidity in the order block
correctly right this right here is a
stupid myth this right here does not
exist guys and we can go back to the
same study from the open University in
Milton keing if this was the case
trading would be a lot more easy number
one number two institutions were not use
intuition as their biggest factor to
them getting good trades so the second
one right here just putting random
numbers of one to three or 1 to five all
doesn't mean anything why you shouldn't
come into the market and be like I'm
going to catch a one to3 1 to five
because think about it everything that
you're doing should be inherent to the
market inherent to the market means you
didn't just come up with it yourself so
when we go back to Mechanical trading
you came up with that you decided that
that is what you should be doing you
didn't come up with that using your
critical thinking rather you just listen
to someone else and you just did it that
is what I mean so how do you know it's
inherent to the market how do you know
that the data can support that they
can't now when it comes to trading a 1
to three or 1 to5 a lot of people are
very fixed on the risk ratio here's what
you're going to do you're going to get
in the market when it looks good and
you're going to use your intuition to
kind of determine when it looks good
you're going to see it and you're going
to say yes it makes sense
why because you're going to lean into
your experience this is what
institutional Traders do if you don't
have experience start testing now and
you're going to get out of the market if
it doesn't make sense meaning the trade
could be in a 1 to two but you might
just want to hold it to a 1 to three but
you see it violate something it doesn't
look really promising so what do you do
you shouldn't be trading it why because
what's going to happen more often than
not you're going to see it just hit your
stop loss right and that goes with 1 to
three 1 to 5 Etc some trades you can
hold for very long you can hold them for
1 to 10 but it just depends you want to
make sure that you're on the safe side
and you're not really Clinging On to
these
numbers we've been told this many times
cut your losses hold your winners I did
not believe it until I started testing
if you're trading a currency pair you
shouldn't be taking a 1% loss if you're
risking 1% you should be taking
4.5 3214 and all these kinds of small
numbers you should be able to look at
the market and be like yeah that's not
going to work out I'm leaving the market
that's what you should be doing now it's
really easy to cut losses on currencies
and the reason why is because they don't
move as quickly as Industries do so this
is something that you should literally
be practicing what is it that violates
your trading and you like I don't want
to be in there when you determine that
you can start testing
that a currency it might be easier to
cut your losses when it comes to
currencies but to hold your winners is a
lot harder meaning a price fluctuation
on currencies is not going to be that
high generally speaking right if you're
trading the 15minute time frame and
you're like on year USD or something
you're not going to see it hit a 1 to
five a 1 to six 1 to 7 during the
session you're not going to really see
that but on an indic you could
definitely see that which means that you
can't cling on to your wins too much now
on indices you could do that really
easily you can hold 1 to 10 one to 15s
and stuff but you got to know how to
manage the trade because the market is
moving really quick
and you're going to get these erratic
price movements and it could be a very
good thing but it's much harder to cut
your losses traditional technical
analysis is garbage why do I say this
it's because an institution relies on
data relies on fundamentals and relies
on risk management and all these things
technical analysis comes when everything
else is finished that's when it's
effective institutions do everything and
then at the end of it they just put a
support and resistance line and they
just find a way to just get in on the
market that's what technical analysis is
for technical analysis is not to make
these crazy trading decisions off of
you're supposed to use it to kind of
tell where you can get in please don't
fall for this trap and the reason why
I'm saying this is because I spent 14 to
18 trying to figure this out I'm 22 now
it's been a few years and I've actually
become really really successful in the
market with my Daya these are the
general things I've learned there's
going to be a lot more if you want me to
make a second video I can go into the
additional two terab of the at I could
talk about one of these specific things
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