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How our 9 Algo Strategies Predicted NVIDIA's Big Move: Cracking the Code

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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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