I recently asked chat GPT to give me a
trading strategy to turn 100 into ten
thousand dollars fast and it gave me
some tips such as focus on highly
volatile assets use technical analysis
beer disciplines yeah yeah yeah we all
know that nothing specific so I decided
to be more specific with my question I
went ahead and asked it to create the
best strategy using an AI based trading
view indicator code that the machine
learning this indicator is currently
going absolutely viral I also mentioned
that the strategy's goal is to turn 100
into ten thousand dollars in the
shortest amount of time possible it
provided me with a detailed strategy it
wasn't really perfect so I had to make
some tweaks here and there and here it
is the final setup to check if the
strategy actually works I will test it
100 times for that I will use the price
of ethereum on a three minute time frame
but before I do that let's actually open
the charts and add the indicators so the
strategy includes three free trading
view tools I will explain how each
indicator works as we add them one by
one sorry for the first indicator let's
add the machine learning k n based
strategy let's thank the Creator
capissimo for this amazing indicator the
machine learning strategy works by
analyzing historical Market data and
predicting the direction of future price
movements based on patterns in the data
K N is a classification algorithm that
determines the class of a data point
based on its nearest Neighbors in a
feature space in the context of trading
k n can be used to classify whether a
stock price is likely to go up or down
based on its historical data to use K N
for trading historical price data is
first collected and transformed into a
feature Vector the feature Vector can
include technical indicators such as
moving averages the relative strength
index and momentum indicators the k n
algorithm is then applied to the feature
vectors to classify whether the stock
price is likely to increase or decrease
this indicator is not repainting however
you do have to wait for the candle bar
to close before you can consider a
signal to be valid it is also very
simple to read the indicator basically
prints blue and pink labels which are
buy and sell signals depending on the
strength of the signals labels may have
lower or higher opacity of course we
cannot use this indicator on its own as
this will lead to a lot of four signals
that's why we need to add the next
indicator which is called the EMA ribbon
by Dominic osceleti the exponential
moving average ribbon is a trading
indicator that consists of multiple
exponential moving averages plotted on a
price chart this tool is used to
identify the direction and strength of a
trend in the market the EMA ribbon is
created by plotting several EMAs with
different time periods the moving
averages are then stacked on top of each
other creating a ribbon-like appearance
on the chart when the ribbon is sloping
upwards it indicates that the market is
an uptrend and when the ribbon is
sloping downwards it indicates that the
market is in a downtrend the EMA ribbon
will help us identify potential buy or
sell signals based on the direction of
the trend and the location of the price
relative to the moving averages as we
can see this EMA ribbon indicator comes
with buy and sell signals since we
already have a buy and sell indicator on
the chart which is the machine learning
let's actually disable those EMA ribbon
signals if we take a look at the chart
we can see that this indicator does
filter out a lot of fake signals but
there are still some left that's why
chat GPT is suggested using their
relative strength index as secondary
confirmation as you probably know the
RSI is used in trading to measure the
strength of a Securities price action it
is displayed as a line on a chart that
ranges from 0 to 100 when the RSI is
above 70 it is generally considered
overbought and when it is below 30 it is
generally considered oversold as part of
our strategy we will make the RSI more
sensitive this way we will get more
valid trade entries so open the style of
the indicator and change the RSI upper
band to 60 and the RSI lower band to 40.
foreign
now let's move on to the entry
conditions for a long trade the
following must be met first the price
must be closed above the 200 EMA the
ribbon must also be above the 200 EMA in
addition it must be green seconded the
price must pull back into the ribbon
without closing below the long-term EMA
the machine learning strategy must then
print a blue label lastly the RSI must
be either saw the prior to the Buy
Signal as soon as these conditions are
met you can open a long trade set the
stop loss below the recent swing low
Target two times the risk once you have
made a quarter of the profit or just the
stop loss to the break-even price for
example you risk five percent of your
account per trade in order to make 10.
the price moves in your direction and
the unrealized profit is running at 2.5
percent which is a quarter of your
target as soon as that happens adjust
the stop loss and secure the trade
[Music]
here's one more example just so you
fully understand the strategy we can see
that the price is in a clear up Trend
the RSI became oversawed which signals
that we can purchase the security at a
discounted price then the machine
learning printed a buy label we follow
the rules and execute the trade
[Music]
thank you
thank you
[Music]
do the opposite for short trades first
wait until the price and the ribbon fall
below the 200 EMA the ribbon must become
red the price must pull back into the
ribbon without closing above the 200 EMA
the RSI must become overbought during
the pullback after that wait for machine
learning to give a final confirmation
there is one more important note I
forgot to mention do not enter the trade
if the RSI turned oversawed at a time
the cell signal was issued open a short
trade only if all the rules are in place
set the stop loss above the recent swing
high and Target 2 times the risk move
the stop loss to the break even once a
quarter of the profit is made
foreign
[Music]
let's move on to the back testing
results so the starting account balance
was set at 100 and after 100 trades the
strategy increased it to 19
527 I find it funny that the strategies
one ratio isn't even the highest out of
all the strategies I've tested so far
the truth is this particular strategy
involves a bit higher risk than the
usual strategy you might find on my
channel you've probably noticed by now
that the risk per trade was set at five
percent instead of two it's no secret
that such risk involves higher drawdowns
but it also gives you a higher reward by
no means am I saying that you should
risk five percent of your account per
trade especially if you have a bigger
account but if your goal is to grow a
small account fast this risk per trade
might be appropriate so give the
strategy a try but don't skip the
forward testing phase on a paper account
I can't stress enough how important it
is anyway thanks for watching this video
I hope you enjoyed it if you want to see
more strategies for crypto check out
this playlist right here