This content explains how a confluence of nine different algorithmic trading strategies, each with unique inputs and conditions, generated entry signals for Nvidia stock, highlighting the power of diversified quantitative approaches in identifying significant market moves.
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So Nvidia stock has
created one of the biggest moves
post earnings
that shocked the financial markets.
Nine of our
algos were long on the stock prior
to this move.
Some of them few weeks ago.
Some of them just a few days ago.
One of them the day before the earnings.
Today, what we're going to discuss
is how the plethora of our algorithmic
trading strategies
create an anomaly kind of situation
where all these strategies
were asking for an entry signal
for Nvidia stock.
So all these strategies
have completely different
inputs, completely
different entry conditions
and exit conditions.
But somehow or the other,
all of this has come into confluence
to create an entry signal.
So as an algorithmic trader
or a quantitative trader.
These kind of signals
are extremely crucial
in picking up the right stock.
So what we're going to do
is we're going to discuss
all these nine strategies.
So in that nine strategies,
four of them are free strategies
and the free strategies
content can be available
on our YouTube
channel
and a few of them are from our course.
So the course content
codes are only available to the students.
The other four is available
for everybody.
You just have to go to the YouTube
channel and see
go check our videos
and we explain thoroughly
how the code was created.
And also,
if you want to download the
code, you can do it too,
so that you can input
into the trading viewpoints for codes.
So the first thing
that we're going to discuss
is that the reason for Nvidia
move is fundamentally
the earnings report came in great
and it was double the consensus report.
But as algorithmic traders,
we are not looking
at the consensus report.
We, we just looking at data
and we are trying to make a prediction
out of that data.
So the first thing that I'll discuss
is one of the oldest strategies
we create in my YouTube channel.
That was the stun whites, our strategies.
It was created like two years ago
and this one here.
And if I can go and look at that,
we are on some $0.01 strategy here.
So solid points
in strategy
call for an entry
two weeks back on eight May.
So at that time
Nvidia was trading at 280
and now it's trading at 379.
So if I can go to the code aspect of it
so I can just get that code area.
So I'm just going to minimize this.
And if I can go point group codes that
so stun watch and strategy
has got lots of input conditions.
It's just not based on price.
It's got volume into play,
It's got the comparative simple interplay
where we take
SB wise data as well
and we compare all these things
and then we add it all up.
So if the close is greater
than the moving average
and if the relative strength
is also taking into account,
so we take the relative strength of
the stock with respect to the SPX, why?
So it's a relative strength
higher than the relative strength
of this buy
and be able
to take the ball into account.
And then we enter for the long position.
And the exit is also kind of a strict
exit condition.
It's not based on a typical risk
management of three to 1 to 4 is to one.
So the entire code,
I've discussed it
thoroughly in the video.
So if you want to go deep into that,
you can go visit that video
and download the course from there.
So this strategy did pretty well
and it gave an entry signal two weeks
back, as you can see.
So now let's go into another
one of our free strategies.
We'll just go into the reason
free strategy that we did
and that was using GPT four.
So GPT four was one of the
I think to one month ago
we did that video.
So what we did in that video
was we actually compared
getting a giving ideas to chop cheap
and getting the code from there
and making minor changes to our strategy
and creating an entry signal.
So that also was on a weekly timeframe.
So I forgot to mention the second one to
our strategy
was on a weekly timeframe
and the GPT four strategy,
which is a momentum based strategy,
is also on weekly strategy as well.
So this gave a call
for entry this Monday.
So just like four days back
before earnings,
the entry
was asked for
and the trade has performed
spectacularly well so far
because this
some of the amazing things
about quantitative
trading have entry points in different,
frames, two different different time.
So even if you're using
just a couple of them
and your position citing the strategies
accordingly.
So we've discussed nine strategies.
So assuming
you're doing nine strategies
and you put 10% of capital
on each of these strategies
and let's say NVIDIA stock is only there
in one of those strategies,
then you are getting
into those big moves.
So this momentum trading strategy
is not only the entry
this Monday, it was also
had a good trade prior
to that on the floor from 13 January to
30 April and then from 30 was October
to 23 January.
So whenever we had like a really
small minor losses,
it got on very fast as well.
So here again,
we ended long and got out very fast here.
There's a long
and got out of the position there,
so I'll just go to the code
of the momentum trades
for again,
it's downloadable
on our YouTube channel on that video.
So just want to go down
and just click on this one
so the source code can be seen.
So again, this one has got a stop loss
in a take profit condition
as compared to the stun
Weinstein strategy.
This one is quiet fix.
So we've got like a
four is to one risk reward ratio
for the strategy.
And we use the momentum
based kind of an approach
to make the entry.
And this has worked very well as well.
So again,
the code is completely discussed
thoroughly on that video.
So you can go ahead and watch the video
if you want to understand it thoroughly.
So now let's go into
some of the course content strategies
which are available to our students.
But it be good for you guys,
to people who haven't bought the course
to get an idea on the performance
and on the results of it.
So.
Q One is a daily strategy
on a weekly strategy,
so I'm just going to change that into
daily and so I can go down
and this one call for a
long ending way back on January the 20th.
So it's been riding that trend
substantially for a long time.
So we've been running it from 169 to 279.
So the beauty of the Q1 strategy
is a very, very simple strategy,
but the success of the
strategy is to run the profits
as much as much as we can and to position
slices across multiple stocks
so that we can reduce the drawdown.
So I did a monte Carlo
simulation and comparison in Q1
in the GPT
four video
where I showed the Monte Carlo
simulation of the Q1 strategy
by applying it to 25
stocks in position sizing and also
90 stocks in precision slicing
and how we were able
to reduce the drawdowns considerably skew
and is a very simple strategy,
but the strength being positions
I see so I show the codes of Q1
because that's only exclusively available
to the course students
and we'll go into Q two now
Q2 is again
another one of the strategy,
which is also on the daily timeframe,
Q2 in the strategy
where we did optimization.
So we actually asked the computer
to tell us
which is the right variables
to use for our indicator
by doing a rigorous test
over the past 25 years
and using forward testing as well.
So we're using optimization
of the trading data
and we're doing forward
testing on the testing data
to get the best results.
So the Q two strategy
called for a long entry,
right there on 24th of February.
Again was able to
get into this good move on Nvidia.
So now you might be
wondering about this draw.
So when you assess individual stocks,
a draw down is going to be always higher.
So I've given a clear indication
how we can reduce the drawdowns
on the GPT four video
which is posted two months back,
be given a rough idea.
We also did it on the turtle
trading video as well.
How we can reduce a drawdown.
So I'm not going to go further into it,
but it's a it's a process which includes
lots of steps
from position sizing to rigid filters
to doing Monte Carlo simulation.
Everything is combined together
to reduce the drawdown considerably.
So we can
we can reduce a strategy
from the 64% as a portfolio to like 20%
or 30%.
And even lesser than that,
because there's
that strategies where we had
12% drawdowns as well.
So this one, this strategy
for Q2 also ended a long position.
I'm still writing that thing,
so we don't know how long
it's going to write.
Well,
the code has got a pretty good
exit condition as well.
So now let's go into
Q3 And so Q3 is not going to
be here
because Q3 is only meant for SP
index fund.
It's a mean reverting strategy.
So it has both long and short conditions.
So that means very strategy
has been performing tremendously
well past two years on that one.
Also, we have done optimization, so Q3
and Q4
are both mean
reverting strategies on the course
that's meant for SB VI ETF.
I generally don't like to use it
for stocks outright,
but it can give it a go if you want to.
And so now we've got Q force
A Q Q4 is a monthly strategy,
so I'm going to change this into monthly.
So it's called
Lazy Trend
Follower ETF strategy
and it's called lazy for a reason
because you just have to look
at the first day of the month
and make the trade on it
last for a especially long time.
So for example, this one here,
it made the trade
August 2019 and closed position
on May 2022.
And again,
this call for an entry on February 2023,
1st of February,
and it's still on that trade as well.
So this one is ideally meant for ETF,
but if you guys want to
try it on extreme, really
high market cap stocks,
I'm talking about
top ten or top five,
it's going to be okay as well.
So you've got to rebalance it as well.
So let's say if you're doing top ten
and one day
the stock is out of the top ten,
then it's better off
to avoid that stock completely.
So if you're if you're looking at Apple
or Amazon
and Microsoft
and things like that, it's
much more ideal.
But don't go into the mid-cap
small cap territory.
Stick to the highly capitalized
stock out there.
So this one as well, again,
picked a very good entry.
So now let's go back to the
some of the free strategies again.
So we did stay on Wayne Chance
where we did the GPT
four momentum trading strategies.
Let's look at the Tier two strategy.
So tier
two strategy is on a daily timeframe.
Turtle strategy
has got a big drawback
and one of the drawback
is on the drawdowns.
Again, I have talked about this
in the video in the turtle strategy.
So this one here
on how to reduce the drawdown.
In fact, two thirds of video
on how to reduce the drawdown,
the dirty deteriorating strategy.
So this one call for an entry
on 17th of March and it just closed.
Right? Yesterday's open.
So I'll tell you why.
So this one code,
we can go deeper into it.
So I'm just going to click on the
code here.
So as you
can see,
there is a take profit and a stop
loss condition of 4 to 1.
So we've achieved
a forward is still on condition
and that's
why we have exited the position.
So this is
what you call a positive slippage.
So we might have had a falls to one
just above that,
maybe somewhere in 350 or 345
or something around those nature.
But because the market opened above
that, the trade,
the algo closes of position.
So now
we have actually got more than a 4 to 1
was true.
What kind of a situation.
So sometimes a slippage affects
you positively
and sometimes a slip slippage affects you
negatively,
depends on where the gap happens.
So this is a very good example
of a positive slippage happening.
So trading strategy
against a very simple strategy,
you use the 20 day high and then you also
we also added in a kind of a filter
origin filter where we use this,
this one is to optimize value.
So another red flag,
all these free strategies
is that I haven't gone deep
into the free strategies
in finding the Monte Carlo simulation
or optimizing much of the values.
There's a lot of room for improvement.
So you can take this free strategies
and build up on it even further.
And you can also find
the flaws of the strategy.
So as compared to the core strategies
which I have thoroughly backtesting
over the past 25 years
and also optimize it,
I also showed
you have to optimize it
and also I perform Monte Carlo simulation
on many of the strategies
and the approach has been more pinpoint
as compared to the free strategy.
So the general strategy again
did one this again,
this was posted
this video was posted eight months ago.
So if you guys had the strategy
and if you did execute this
strategy, then congratulations on that.
So we did a video on top five a Stocks
to Invest
in 2023, and Nvidia was one of them.
There was another stock
which was kind of I wouldn't say
I would say
is more of a small cap stock,
which created like a 50% move.
So I hope you guys got into that.
And that's where we also picked
Microsoft and Google
as some of the AI stock.
And that too has moved tremendously
up since Oracle three months ago.
So if you haven't watched that video,
have a look on that.
Because fundamentally
when you look at it,
the Nvidia move is not only a move
for the earnings,
but also
there is that estimate
that we will need more chips for the A.I.
and also the chip generation.
And the NVIDIA has got
a lot of graphics, GPU units.
So all those things
are going to come into play
and Nvidia is best poised for that.
So we did a really good qualitative
assessment of many of the stock,
which we think for the long term,
not just one or two months,
but for the next ten years or something
could be pretty good investment.
So even if you want to do
like a simple dollar cost averaging,
that should work as well.
So again, that is the two strategy.
So now we will look into
we'll just finish off the course
before we come up into the money flow
index for your strategy.
So we did Q1 to Q2, we did Q4
going into Q six.
Now again meant for stocks.
So this one call for a trade on 1st
sorry, on the 2nd of May,
and we've been still on this trade
for a wide skew.
Six is also a very good
strategy applied for stocks
and it's been
perfectly created for stock moves
and I think that that strategy is also
for all stocks
has been Backtesting and Russell,
3000 stocks for the past 25 years.
So it's a pretty robust
a robust strategy as well.
So now I'm going to go in
to our last call strategy, which works.
So there's Q5 was Q3 and Q4 or B,
my ETF, Q1 Q to Q4?
Q six, q7q8 or all four stocks?
Q nine and Q ten
for crude oil and Bitcoin.
So the Bitcoin strategy is performing
very well.
Cool.
That was the only strategy on our course,
which was
underperformed
since the inception of the course
two years ago.
And
it's kind of like a good lesson
for me and also for the viewers
and of course
students that not all
strategies will work.
So you should never
depend on one strategy.
So that's one of the reasons
why we gave ten strategies and we advised
position sizing in different strategies.
So you get
even if one of the strategies fail,
the other strategies are performing.
So for example,
the mean reverting strategies of Q3
and Q4 of have
been outperforming the past two years
and everybody was losing money,
that strategy was performing well.
Some of the stocks were going down.
So the trend following
strategy is kind of in limbo.
So at that time,
the mean reverting strategies
perfectly work well.
So now I'm going to go to Q8,
which is again a mean reverting strategy.
So which supply to hide market
cap stocks.
So if I can go to Q A
if you can go deep into it, the call
for buying was given the day before,
I mean, the morning of the earnings call.
So the earnings call before the morning,
the long position was called for
and it made that big move.
So even
this is a mean reverting strategy.
So it's it's
kind of like get in, get out fast.
So we need to have highly liquid
high market cap stocks
so that we don't have much slippage.
But even then, you can see
there is this positive slippage
that is taking place.
So any negative slippage
that is taken
place for the past X amount of years,
it's probably we cancel out with this
big 30% move.
So that's it. With the core strategies.
Now we've got the final free strategy,
which is the MFI strategy,
which is a money flow index strategy,
which is here,
the money flow index strategy.
Again,
to download the coach's visit,
the video
recording is explained thoroughly.
So again, the Money Flow Index strategy
call for an entry on 14th of April
and we will be able
to write this down and
we exited the position
just on the opening
of the
big move
so I can go into the coach of the Money
Flow index because it's a free strategy.
Just click on that one.
So again, as you can see, the money flow
index is going to 30% stop loss
and take over.
So all these strategies, you can see
some of them are on a weekly timeframe,
some of them are on a daily timeframe.
Some of them have got a strict
risk reward, like 3 to 1 or four is one.
Some of them have got
strict exit clinical risk reward ratios.
Some of them entries
are completely different.
Some use volume,
some use relative strength.
This one uses money
flow index,
but all of them, all of them
somehow or the other,
gave us a clear signal of entry
and it gave us confidence
in NVIDIA stock is due for an entry.
So this gave an entry on
on 14th of April.
It was a big move to the upside.
So it's got like a 3 to 1 risk
reward ratio.
So it got out of that strategy again,
I've explained this score
thoroughly in the video,
so you can download that strategy
there as well.
So I hope you guys got an idea on
how whether you'd be a free strategist,
whether it be a core strategies.
The end of the day,
algorithmic trading
is created for fixed rules
and to give us signals that, hey,
this stock is going to perform well.
And even if it doesn't perform
well, there's a really
clear sign
that we can get out of the position
because of our rule based strategies.
And when you do it in
a plethora of stocks
like ten, 15, 20 stocks,
and when your position size is small,
if you don't have that emotional baggage,
you don't have that worry
that, hey, what if this doesn't work?
Or what if this works?
But when it works, it's
going to give you some great wall.
So even if this move hadn't happened,
this ride from here, from 263 to
almost 300 itself is a big deal.
You know, that itself is a big move
for normal traders out there.
And most of these trades, as you can see,
except for them
anybody finds
it takes minimal amount of trade.
So the cost of transactions
are very less.
For example, here
we ended a long position, 22nd February,
close position on 22nd of March.
I'm pretty sure there'll be
examples of Low Street as well.
So for example, here
we ended on a long position there
and then we had a minor
loss of we closed that position.
So there'll always be situations
where we have minor losses.
Well of course here
there was a choppy Peter,
so we ended out
exited our very aggressively.
But on the long term,
these kind of algorithmic
trading strategies
when you apply to it in good stocks.
So picking the stock is also good.
So if you pick rubbish stocks and
and you expect these stocks,
these strategies to work,
it will be not so ideal.
That's why
I stress in the course
there are certain strategies
where you can apply to
Russell 3000 stocks
and there are certain strategies
where you can apply
to top market cap stocks
and depending on the strategies,
are position sizing changes as well.
So if you are doing
an aggressive strategy
which takes more risk,
then it's better if you do it
on highly market cap stock.
Now you could do it in
low market cap stocks,
you could do it in small cap stocks,
but then your position size
should be so small
that it the losses,
even if it's big on one stock.
Ereli On the entire portfolio.
So I hope you guys got a gist
on how these algos worked
very well for the Nvidia moves.
If you guys have any doubts
or clarifications,
feel free
to leave a comment or send me
an email
and I will be more than happy
to help you.
If you guys want to check out our course.
It's on our website here
and it's got ten strategies
and the course price are here.
So the promoter is a strategy
which is consists
of all the ten strategies
that we discussed right now.
So I hope you guys enjoy this video.
Have a great, great day. Bye bye.
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