All language subtitles for 4 - NoFearLosing EN

Okay folks.

Welcome back.

This is the fourth installment of month.

Two of the ICT mentorship, where we
specifically talking about why losing on

trades will affect your profitability.

What trading with fear of taking
losses actually does to your trading

Mustang concerned about taking a loss
promotes, fear based decision made.

Equity is managed by traders that
cannot take a loss can't profit.

Long-term

losing is inevitable.

Fear-based decision-making
keeps focus on the adverse.

Finally fear-based decision-making
fosters trade paralysis, or

inability to execute efficient.

Yeah.

Now why profits are achievable
despite taking reasonable losses, the

professional equity manager understands
that losses are costs of doing business.

Using sound equity management,
and high probability setups

yield, handsome percent returns.

Trading scenarios that encourage potential
three to one reward ratios provide initial

foundation only defining trade setups.

That frame five to one reward to risk
or more efficiently cover losses.

Okay folks, we're going to give a brief
overview on framing, a trade, just

for the context of this discussion.

Looking at this sample size of data,
as it relates to price action, really

referring to a specific concept,
known as market set up and framing

the risk to reward multiples.

Obviously we're going to use a
standard in my repertoire devotion.

As you can see here, the market returns
to a previous institutional area

of buying noted by the down candle
prior to the previous rally higher

by noting the down candle or
the bullet shorter block high to

open price defines the fair value
gap or most probable support.

Now, specifically inside of that
retracement into the water block, there's

a mean threshold and a hypothetical long
entry on the secondary Bush or block.

What I'm going to refer to is
this down candle here, the middle

of that candle, where are we
using that as a mean threshold?

In other words, we don't want to see.

Violated on a closing basis

using 20 pips as the trade stop loss,
easily frames reward round-tables of

three to one reward to risk and five
to one reward to risk or even higher

Nudie and old high 20 pips above.

It gives us a nice objective above
where price would be retraining.

No, having a simple trade ID.

Based on the things that we taught
in September on what to focus

on or what you should be focused
on right now in price action.

Let's take a look at some things
regarding those setups and how we can

frame good reward multiples, um, how
we can frame the ideas and justify why

taking, losing trades doesn't really,
or shouldn't have that much of a

impact on your long-term profitability.

We're going to assume that we're
using a hypothetical account size

of $5,000, and we're gonna start
with it low accuracy rate of 30%.

That means that you're
losing 70% of the time.

Me looking for trades debt, our
reward, the risk ratio of three to one.

That means we're hoping to make or
willing to hold on to a trade, to pay

out $3 gained for every $1 that we risk.

We're risking on each trade.

1% of our $5,000 account because
we're risking 1% and we're looking

for a yield of three to one reward
to risk our average wind wind trade.

It should be $150 and our
average loss should be $50 or 1%.

We're gonna be focusing on
a sample set of 10 trades.

Amarillo say that 30% of those 10 trades
are winners and obviously 70% would be

losing trades out of those 10 trades.

We are assuming that three wins in 10
trades and seven losses in 10 trades.

The average profit again is 150.

Yeah.

And the average loss again is $50
is up total for the three wins at an

average profit of $150 would bring us
to a $450 winning basis on the three

trades out of 10 that were winners.

And it's up total for the losses
would equate to $350 or seven

times 50 hours over an average.

Even in this low accuracy rate with a
multiple of three to one, you still can

marginally eke out in net positive profit.

It's not much.

And to look at that, it doesn't
seem like anyone would be

terribly excited about that.

But if you were doing 10 trades
over the course of a day,

And you needed the 2% return.

I can tell you that is an absolutely
amazing return for managed funds.

So if you're not going to be trading your
own capital, or if you're aspiring to be a

trader that manages other people's money.

So again, 2% while that's not terribly
impressive on a grand scheme of things,

2% compound that over the course of a
calendar year, 2% per month, that it's

an astronomical return for management.

let's assume for a moment.

Now we're going to start focusing on
reward your risk multiples of five to one.

That means we're trying to make
$5 for every $1 that we risk.

And we're keeping the same sample
set of looking at 10 trades.

And we're still looking at
the accuracy rate of 30%.

The only thing that's changed now
is reframing trades that have a

multiple of five to one reward.

Suddenly our three winning trades out
of 10 sample set, the average profit

becomes 250 hours or three wins at $250.

Average brings us a subtotal of $750.

The seven losses in the
sample set of 10 trades.

Average loss is $50 that still
leaves us at a subtotal of 350.

$750 minus $350 gets us a net
profit of $400 or a 8% return.

Now, again, if we're looking at 10
trades over the course of one calendar

month to see results like this, with
it very, very low accuracy rate of

30% still brings us an 8% return.

That's a wonderful
return for a monthly, uh,

now we're going to take a look at
having a low accuracy rate of 30% with

the reward, the risk multiple of $5.

And now we're going to be
risking 2% of our account.

So now the average win jumps to $500
and the average loss jumps to $100.

Again, keeping accuracy
at a low 30% accuracy.

That means we're losing 70% of our trades
out of a sample set of 10 trades over the

course of a calendar month, three wins.

At 2% risk portrayed multiple
a five to one ratio, three

I'm sorry, reward the risk.

Our average profit jumps to $500.

If our three winning trades at $500
average profit, this gives us a

subtotal of $1,500 or seven losing
trades at an average loss of $100 or

2% of our equity and the subtitle.

Would obviously be $700.

Now the average loss in average
profit would increase as the

equity increases or drops.

Uh, but for these examples, we're
looking at the sample size of data

and a sample set of 10 trades.

So the details are mentioned here with a
very hypothetical basis, but with subtotal

on three wins of 1500 hours and yeah.

Seven losses, subtotal or 700 that
would give us a net gain of 750.

Yeah.

Or 15% return again, crazy returns
with just a very low accuracy.

Now think about this for a moment.

When you first got into trading, you
were wanting to get 90% accuracy or a

hundred percent accuracy or 98% accuracy.

You can still make ridiculous returns
with having very low accuracy.

Okay.

You don't need high accuracy.

You need the framing of the reward,
that risks multiples in your face.

And we didn't really go crazy
with our risky, that we're

only doing 2% maximum portrayed

I said, now that we're going to
look at an accuracy increase to

40%, nothing's changed outside
of the previous example here.

So now we're going to say 40%
of a sample set of 10 trades.

Four of the 10 trades are winning
trades, average profit per trade.

Still at $500.

Or four trades at 500 hours.

Average profit brings
us a subtotal $2,000.

Our six losing trades as a 10
average loss is still remains

at a hundred dollars per loss.

Six of them would give us a total of $600
that would give us a net profit of $1,400,

which would be again, that's a 28% return
with just a 10% increase in accuracy.

The factor of 2% for real.

And reward the risk ratio again,
creamy on a model of five to one.

Now, we're going to look at an increase
in our accuracy to say we've been trading

for a while and we know our trading
model a little bit more intimately.

We know what we're trading.

We know how to frame our trades.

Uh, we've learned patients, uh,
we've been able to, uh, stick

to our rules and our parameters.

Are, uh, reward the risk framing.

Uh, we knew how to reduce our
risk while we're in a trade.

And our accuracy increases by default.

Uh, we're going to say we
jumped to a 50 50 basis.

In other words, half our trades
are winners and half our trades are

losers on a sample set of 10 trades.

The average Wednesdays at 500,
the average law stays at 100.

Yeah.

Uh, five wins at an average profit of $500
brings us to two us up total $2,500 while

five losses of the 10 simple set trades.

Average loss is a hundred
dollars or a subtotal of $500.

So $2,500 minus $500 loss on five losing
trades because it's a net profit of

$2,000 or a 40% return on 10 trades.

The factor of just increasing a 50 50.

We're reward to risk five, the
one with a risk portrayed, 2%.

The only thing we're doing is framing our
trade around a little bit more success.

In other words, our ability
to read price action.

Look how fast our multiples jump up and
we haven't increased the number of trades.

We haven't increased the risk per trade.

Either

a accuracy rate of 50 points.

Our rewards risk model stays at
five to one, but we're going to

lower our risk portrayed to 1%.

That means the average win
drops back down to $250 per win.

And the average loss
is down to $50 per win.

Our hit rate we're going
to say is 50 50 still.

That means five winning trades.

Average profit is $2,250 and
five winds at 250 hours brings

us a subtotal of 1,250 hours.

And in five losing trades out of the
sample set of 10 trades, average loss

being 1% of the $5,000 account or 50
hours in this case, five losing trades,

but an average loss of 50 hours,
it gives us a subtotal of $2,250.

So $1,250.

The five wins minus the subtotal
of $250 on the five losing trades

gives us a net profit of $1,000.

Now I want you to take a
look at this for a minute.

Okay.

Think about this for a minute.

You only have to be right half the
time or the other way of saying it

is you can afford to be wrong half
the time you're looking for trades

that pay him out five to one, and
you're risking 1% of your account.

Okay.

Think back to the moment when you
first started learning about trading

and you felt that you had to put big
risks on, we're not talking about 2%,

which is the industry standard here.

We're talking about 1%.

1% makes millionaires.

If you look at the 1% risk
portrayed, any accuracy rate of

only 50%, this by itself is exactly.

What everyone would dream of as
three to return 20% per month.

If you could get 10 trades per month,
half of them be wrong, but framed

all of them on five to one reward
risk with 1% risk only your rate of

return is 20% with only 1% at rest.

This is optimal trading goals.

This is exactly what you
should be aspiring to do.

You're not trading a lot.

You're not demanding a high
rate of success or accuracy.

You're not pushing the
limits on your risk.

You're keeping it at a low you're
doing half the industry standard in

terms of, uh, risk per, uh, portrayed.

Usually it's 2% maximum.

Okay, well, we're doing one right.

Let me ask you a question.

What if you were to drop that risk
portray down to a half a percent, would

you be upset with 10% return per month?

My question would be, why
would you be upset with that?

Now, imagine if we were to consider what
was 2% per month with 30% accuracy, 1%

risk portrayed with three to one reward
to risk model on our first example.

That's exactly.

Large funds look to do for their
clients over the calendar year.

They're looking for one to 2% per month.

And if they can compound that
over the course of a year, they

can give their investors a 20,
25 to 28% return on the year.

And believe me, there are millions
and millions of dollars sitting out

there that would love for someone
to be able to do that for them.

So you don't need to have these
astronomical rates or return per

month to manage other people.

Believe me, they will go crazy.

If you give them 1%, one and a
half percent, 2% per month, and

you only need to do three to one
reward risk to do that with 1%.

If you do 1% here and you have a
50% chance of being accurate and

you frame your trades around five to
one, look how easy it is to get into

a really high end yield for them.

20%.

You don't have to train every
single month if you're managing

our money or other people's money.

See, this is an optimal goal because
it gives you the cushion to do

basically half a year of trading.

There are some months in a year that
you don't really want to be trading.

So if you can do a multiple of five to
one and yield really handsome results,

and I'm not saying that everyone's
going to get 20% returns, right.

Every single month, but this should be
a good trading goal for you to frame

your trades around were expecting
only half your trades to be accurate

framing on five to one reward,
to risk keeping your risk low 1%.

By doing this, it gives
you the optimal objectives.

It gives you low-hanging fruit, it
doesn't force performance, and it

gives you an opportunity to relax
and actually enjoy the process.

There is no fear.

That's justified in taking losses.

They are all part of this business.

It's all part of the game.

It's all part of your job.

As an equity manager, you're
going to weather losses.

You're going to assume you're
going to assume losing trades.

That's all cost of doing business.

No one goes through their
career without taking losses.

You're going to have lots of them.

If you trade for a long time, if you
had a column of all your wins and all

your losses, your losses are going
to be very, very long in the list,

but does not dampen, or it does not
remove the profitability factor.

That's still available to traders
that know how to frame the trades

with good multiples of reward, to risk
keeping risk managed, and defined.

And thinking about how they're going
to trade with these parameters.

If we use the example we showed in
the beginning of this video with

a 20 PIP stop, all you have to do
is take well what's 1% of $5,000.

It's 50 hours.

So if you had a 25th stop,
you'd divide that by $50 and

I'll give you your dollar per.

Leverage and that's what you
would use for your trade.

And that would give you all of
these numbers that you see here.

Now, again, we can only speak in terms
of hypothetical, but it's a rule or

general principle that you're going to
build on as a trader highlighting the

fact that you don't need high accuracy.

I did not show 60% accuracy.

I didn't show 70% accuracy.

I didn't show 80 or 90.

None of that's necessary, but yeah,
as time goes on and you grow in

your proficiency and your, in your
understanding about price action, and you

as the trader by default, your accuracy
rate will increase and you'll never demand

or need for it to be higher than 50 50.

So until the next discussion
in next teaching, I wish you

good luck and good trade.