All language subtitles for Stage 1.4 - Amt Part 4-1

Hello traders welcome to the

normal distribution section.

And yeah fortunately as you
can see I'm sure you've heard.

My dog in the background
throughout the foundation course and.

Yeah I'm sad to say that during the
filming of actually this section normal

distribution section.

And

she passed away he had to be.

Put down.

Because and.

Yet due to ill health from in you
can see shoes of she quite an old girl.

And a mentioned a
few times that you know.

I

bought in an ideal scenario.

That then really want to of she have
a dog snoring in the background Bob.

Obviously she's
been very old and.

Not necessarily.

Very poorly bought

obviously deteriorating
throughout the last.

Few months.

And.

Yea so unfortunately he
got to the stage where.

Whilst I was filming this.

And.

Yesterday she.

Her health had
started to really.

Go downhill she was unable to
urinate for about twenty four hours so.

I.

Had to unfortunately take her

to the vet and they said you
know she's of see developed.

Certain issues under.

You know is beyond the point of.

Being able to do
anything for her but term.

The thing is the funny
thing is and I hope

you don't mind me
spending a few minutes and.

Saying this because.

And are cheaper a bullet point

on the next slide

that had written

dog

and it was a prompt

because.

What happiness because she was deteriorating
choir beer how many wasn't obvious at

first she was just
getting very restless.

And she was very very
noisy in the background.

So obviously upper.

A note because.

I

going to leave her outside and I wasn't
one hundred percent certain what was.

Going on so our style the
filming an advantage he ran

the bullet point there.

And by got to the stage as of started filming
at I was obvious to me that she was in

law of discomfort so.

I took

the.

Decision to obviously take her.

To the vet and that was it so I thought
you know why would be quite a fitting.

For me to dedicate.

And initially of to let me
dedicate this section of the course.

To her her name was tiger about.

Herm.

And you can see she was obviously grey and
getting very old bar she was quite fit and

strong right to
the very end but.

Coming back to the point about dedicating
this section to her and then I realized.

Actually

she's.

Been and.

One of the core reasons why
have been able to put this together

and

a domino exaggerate the

that and that may sound
completely crazy but it's not.

Really she's been a mean
there's a bed behind me.

You know she's kept me company throughout
putting this whole thing together and you

can see that was a.

He's been quite long

course

and.

Yeah I'd never
realized just how much

good it was to have that
company because now I'm trying to.

Initially yesterday I
thought you know what.

I need to be
professional and just.

Carry on by yesterday
just was a lie.

Was almost at the point
where I thought was the point it

felt very empty.

Doing this.

The rest of or this section
even who is just a really

weird

feeling silent feeling almost.

And.

You know and

of she was that was an idea of
having her in the background some

Tom scratching
at the door it was.

Really yesterday when I realized how much
actually it was great having all of thy

brought character

to the cause he

kept me.

And.

Okay just felt like I had some one around
all the time keeping me company whilst I

was plowing through.

Doing all of this but look
at the end of the day.

Of now had one night
to reflect on it and.

I.

Paralyzed do you know what.

She was happiest

when I was talking.

And I realize this throughout the course
and forgive me I I won't take more than a

couple of minutes
to say that spot.

I realized because and were any time you
know she was of see making noise I used to

put her out.

And bought when she heard me talking
very enthusiastically in the course.

I put in this course together.

She would come to
the door and I think.

What it was his.

I don't think she
would have enjoyed.

Me just moping
around being silent.

I think she really enjoyed.

Hearing me talk

and hearing the
voice because she felt.

That you know.

More presence was here and I
was doing something I was really.

Passionate about happy
I think she could really

sincere and thus no
exaggeration of a really felt.

Thus when she was happy when.

She was sitting there
as you could tell.

She was very

peaceful and

went to

bed as she made clear
to US with her snoring so.

A genuinely think she wouldn't
have wanted me to really.

A mope around for the next week and whatever
think she would have wanted me to be

happy and.

And.

You know this comes to my

of.

Final point which is the.

Pino

dogs are very loyal and unselfish
the most incredibly unselfish.

And creatures are think and you know man's
best friend all of that is very true and.

I.

Have realized as well that you know human
beings are no offense to anyone but we we

can all.

Of inc will all agree

human beings can be

a little bit selfish
in the sense that.

You know or realize the odd.

There's no point me feeling
sorry for myself this isn't about me.

This is more about her and and.

Obviously yesterday's
decision to let her go was.

Really.

It was about her
to make sure that.

She wasn't suffering anymore and

and.

You know or realize she'll be
really should be much happier.

Without and.

You know just keeping
her going suffering and.

Being selfish

that sir Robin and feel
sorry for myself I'm going to.

Be positive and try my
best to really recognize that.

It was in her best benefit and.

You know find the just wanna say

obviously you may be watching this a few
years after I finished the filming of this

cause obviously all
the stuff in this causes.

And in are going to be ready even for
many years after I put this together bar.

You know as it stands of receive my career
has been sixteen years and it's amazing

for me to reflect and
think that she's been here.

Throughout the last fifteen of those years
are really she's been with me for every

relationship.

The whole of my career

there were points when I was working
obviously an institution environment and.

I used to work from around six in the
morning sometimes till ten at night so.

You know sixteen
hour days it was in

practical for me to have her
with me all the times I would.

Have she should
have stint staying with.

My sister or my parents bought.

In particular the last few years
you know she's been literally say.

Sleeping behind me through all my
trading and ever feel you know it's just.

Yeah I suppose he knows two ways to
look at it either as a sad thing or as her

said great thing that
she gave me lot since

she contributed massively
to this course and.

Obviously she's in a happy place now so
been brought them make you about me.

I think he is really about her
and that you know she she's

she's happier now she she's not suffering
or she is not in any discomfort so.

Really yeah thanks you know appreciate you
letting me put this into this section of

issues important for me.

Wanted to say a few words and.

You know dedicate really the whole thing
the program foundation to her I don't think

it would have been possible

of

the

of the

would have done
it bought one thing

and.

I would have done it with as
much vigor and and enthusiasm

I realized that now and I want
to make sure a complete this.

With the same.

Enthusiasm.

And you know in her memory so.

Yet shown a celebrate her life really
and appreciate you let me put this in and.

Less crack on and less get some.

You know real work thumb and in a of realize
armor professional I want to do the job

properly.

Thus the right thing to
do so yeah appreciate or

less move onto the next light.

Okay traders let's get
down to business so.

I.

Bought the purpose of this

particular section as
we've said several times.

In all the previous sections
only been working toward it to.

I.

Find a way that we can measure.

Value where the bulk
of transactions and.

Fit in a we're going to talk
about the in the second part

what thought be very
useful is for US to look

at the transition that
we've been through.

From the transition cool sry up
until now and remind ourselves.

Of exactly how we ended up at this
stage which I am I introduced in the.

Law section balance imbalance and I showed
you how I scrunch up the volume profile on.

What is at don't want people to.

Because coming forward.

Basically.

Thus it would
done with all of this

we're now going to be
looking volume profile.

And

am introduce market profile were too kabbalah
in that particular sexual will looking

at profile exactly la base

and I don't want people to a treat
the as an indicator could he isn't.

And be a want
people to not think

oh is something new
and get worried and.

If you've done all the depth of
market stuff of asked you to do

she

should basically
just be and natural.

Should feel very natural to be looking at
this cause is will you been looking at for

three months and as the point.

Said that's what
I wanted to just.

Show of

show that transition.

Just in case there
was any confusion.

Sur les stop banana market.

We had a look at in the
foundation example right.

At.

That essentially

banana market was having
transactions taking place around.

So of central value in every time do you
remember the market go over extended.

People were trapped him we came back and
when it went over extended to the downside.

Again

people.

Got trapped in the
sense that they had.

Over.

Got too excited and obviously some
of those positions ought to be unwound

and where did we come back
to we came back to fair value.

And.

Know didn't talk goodbye in the level of
detail the have talked about in the pro quos

bajo casino.

In hindsight looking back at it.

That.

Essentially we were
just coming back to some

so central value and
thus really important.

Gonna talk about this.

And.

Soul of central

tendency.

That markets have and
I'm going to show you how

and.

Thus actually quite
useful for US to find.

Probability.

Distribution of one particular type prompted
probability distribution that fits that

very well but.

Don't worry is not going to get very
mathematical when I talk a little bit about that

in the neck slide buff

and again I just wanted to remind you
what will we did in the foundation section.

Was we looked at market
orders in the banana market

actual physical.

Aggression taking place and.

You know that was
the volume professor.

Look on I don't want
to obviously go into a

unnecessarily should
be pretty obvious to you.

What happened and and
and transitioned you over

to the depth of marker.

I do.

We had.

Market all is taking place this time purely
on a financial market but as you saw as

the same thing.

Right order was happening is
market orders were taking place.

Up particular price levels

just a squeeze everything in a dog she
don't have all four columns bought you know.

You're going to be familiar with

beards market all his and then.

The supply side offers which I'm not showing
all of that here by as you know market

orders.

Every time a market order
took place our price level.

He got recorded as a transaction no
different to what was going on in the banana

care

and.

You know you said of and treasuries
and if you had a chance you may have

seen the exact same
thing is happening on.

Sep five hundred
pound dollar euro dollar

and and all I did

his US

squeezed the profiled in I

so ease exactly this.

This

this

vase

or even this.

Is this isn't it and it
was squeezed as I

showed you in the
balance imbalance section.

And

and.

Obviously what we're
trying to do now is just.

Find some sort of.

Area where we can say you

walk the majority of transactions
took place here because

you can see it yourself this tomb in
ieee transactions taking place here.

For US to realistically
as have been through.

Really to death and.

You know in great detail although obviously
if anyone doesn't get it I'm happy for

them to reach out to me by.

Not the majority should have.

Realized by now that while I was
saying about the webcam example and.

Businesses having the opportunity
to be very precise with price.

Over a day two days one
week because of the stickiness.

Just doesn't exist in financial markets I
mean you can see how many transactions.

Are taking place thousands upon thousands
of transactions or take the place.

At so many different price points
is difficult for US to be precise of.

We're trying to almost
equate that one price into just.

Be a bit more fluid and give it some sort
of leeway and say you know what roughly.

Price transacted
within this area now.

I dunno if some of you
know is this those of you

we're quite eagle-eyed and even if you
have and is okay thus the whole point by

wanted to do the slide quickly.

Is if you know east and.

When always trading.

Especially some of the
morphin or markets if

you saw was trading
the depth of market of.

Pound dollar.

In the exam poor I believe somewhere
in towards the end of module for.

And you saw me trading
the pound dollar earned

you may have no is
this yourself as well.

Have you know east
how on US treasuries.

And there tends to be choir.

Balanced profile and that
obviously to do with liquidity and

and

there's plenty of liquidity going
around to it's very easy for the market to.

Belly relatively speaking
easy for the market to do all.

Go through this process
of finding fair value.

Because there's so many
participants he has plenty of.

Transact options to.

Suit will find its way towards
where fair values going to be but

as you know is the
more liquid he gets.

You may have noticed
is that there was.

Not

there were little pockets of
value want that because of

profile was that
much more spread out

and you know that gonna make sense
you know euro dollar he can see very thin.

Will you Alma got
several profiles

there is a point
by mentioning this.

Even the snp here you see
you know there's little tiny.

Bit of and.

Balancing going on in that Parker that some
balancing going on here that a little bit

here.

That some here.

And

you know east German
but I was taking trades

almost key king of

sure if if the market go aggressive through
here came back then not be going that way

or a fit.

Sure failed to really get up there and
came back or be king of that level one.

Bringing it back into.

This value using this value or.

Mean I could potentially
use this value to.

So of key of

bring it back the all
these Leo pockets of value.

And can you see

the essentially you may
know of no is the spot.

This is one of the reasons that I scrunched
up you know as I got one in my career

because I recognized.

That all that was happening if you if
you look at what I pointed out here like.

This little value is this will valley here
which is what I was doing in that pound

example.

Impact peculiar and
then there's little bit here.

Lucas exactly the
same you can you see it

as a little bit there.

Is that little bit there
there's a little bit here

this what you're doing
on the depth of market

and then there's not much volume here
to the price would go straight through.

Because there's not many people
to obviously transact or interest

or straight through and then.

It will overseas
settle in this area

then you got little bit here

and so on and so forth

and the problem is.

When you're stuck
on such as small.

Or microscopic
basis can you see.

You cannot value every way you
know value hague and or value

in a valley here.

In of and here.

By scrunchie up was allowing US
to do this same process but look.

A vous.

Thus all I'm doing
is just allowing me.

To look at value.

Over the whole day.

And were fair values for
the whole day rather than.

Just for an hour or two
hours are times I'm really.

Taking a bird's eye
view but the point is

that I'm doing it was.

On the same market

so rather than
looking at these little.

Little pockets of just
decided that rather than.

Just to to re

iterate the point
of than looking that

the same way I was looking up.

In one the treasury market
little pockets of value here.

While might you doing
some st Jean or war.

Robin and being so focused
on microscopic values.

When I actually Luca.

Value like that and
put that allows me to do

is obviously get a

better.

Show of since
where the market is

what the mortgage
trying to achieve.

Over the whole day.

Over the whole week.

Over the two three days over a month and
we're going to took a lot more about this

but we actually get to
building trading strategy.

Because you are going to
see that different investors.

Have different time horizons yea to well
and good being a traitor on the depth of

market but US.

Really just looking at where.

Short term institutional
traders are looking.

Algorithms are trading

slot looking at were.

Obviously.

More

of of the medium term
traders looking and

we're going to get into
that I'm hesitant to mention.

You know all the names of
things like different types of hedge

strategies dark

and

institutions are employing or
real money funds pension funds.

Some of the more

longer term timeframe

and

investors.

And and will look it up

but obviously to do that.

You have to start to look at.

Fair value over longer
periods of time and.

That doesn't mean we're not using the
depth of market all it means is we're not.

Which has not been
some microscopic a by.

We're actually.

Getting off the
depth of Marquette.

Ba.

Scrunching up so in a way
really staying on it but which just.

Looking at it for much more
of a bird's eye perspective so.

I just wanted to make
that clear because going

for forward I'm only
going to be looking.

At profile from saw this level

upwards.

I'm no longer going
to be looking at.

Microscopic profile
which is what you've been

so used to doing now
for two three months

and body is is because I'm making
the transition they're just wanted to.

Make sure that
you understood look.

We're not really
changing anything

all with doing.

Is we're just.

Robbed than

drilling down be doing the
opposite were basically now.

Looking at a much more
bigger perspective so we can

because

and far enough said city have
already wants by just want to.

Reiterate because it
is important will not.

You know if you think about when you're
watching the depth of market you really

see was priced
trying to achieve from.

You know almost

say if is out of balance

back into balance you're talking
about what really a few takes.

You know as you saw
the treasury market

or

if that was.

This balance area

and we were

you not trying to get out and unable to
because we saw absorption and aggression

coming back in.

Was the market
trying to achieve well

she's moving a few ticks

back in.

Deceased were doing
the same process now.

But with doing over
the entire market

and thus gonna allow
US to transition on to.

Charts and really and.

What is the whole
investment community.

As a whole trying to achieve we
can't do that in the depth of market.

I hope that's clear to you

and why is really
important that.

You now shift your
perspective and.

We start to look at
volume profile from a.

Much and

soul.

Bigger perspective of and

we still recognize and respect
that all of this is going on.

Bob Robert and are pure
focus being on this we know

you know how you
saw me do the triangle.

This essentially
forms the five percent

you know the all the
flow the fine tuning the.

I.

Saw of

microscopic detail as
I've said several times

so that doesn't mean is no important
because at the end of the day.

You know we've said it before by

were to think of a real
world example think of tesco.

Yeah the end of the
month they might say you

know what we sold a
million loaves of bread.

But the end of the day.

Still matters dot individual.

People like missing
individual transaction hear.

How did that million get formed.

There were individual people going
to individual stores doing individual

transactions.

Now imagine some

never told you about that.

You can't just take this

big number a million at the end of
the month and just work with it because.

You wouldn't know how
was that million actually bill up

that's why I had
to get you on the.

Depth of market hope
you can see because.

If I to set you oh this is a volume profile
just believe me guys this is market orders.

Not going to make sense to you

unless you'd actually seen it
can you see how powerful is to.

Have actually spend time in the.

Depth of market because now

you can understand this

he can see this building
throughout the day

she's going to get it

going to know.

Ah I see what people are doing.

They're basically
when they're here.

They're either going
imbalanced or if they fail

and they come back in awe
get it now that going back into.

Balance.

You've seen on the
depth of market from

microscopic perspective
is exactly the same thing

but obviously this is going to allow US
know have to sit and stare at these numbers

up and down one day

and also general walk

one thing I have I mentioned

absolutely crucial
and you may have.

Picked up on it.

You could have
remember guys stop

and this is something that I never really
fully appreciated until obviously I became

a much better trader.

And this was you know

natural obviously
throughout time you pick

things up and you get
better as time goes on.

And one thing that did
occur to me is that look.

If you think about it

even if there's some
guy who's got some flow.

He's got and orders to fill.

Because he's got an investment horizon
of three days one week whatever it is.

At the end of the days and
they're gonna have an impact

on the market even from a
short term perspective of cooties.

Let's say you're sitting here staring
at ya depth of mulcair the prices.

You know you're looking at this
little poker value in the prices.

Somewhere in this region
and she huge absorption

coming in me see
aggression coming in.

War if you could know the
actually hang on a minute.

There's

you know this big ap.

Saw a value

there is some guy

who's actually
likely to come ina.

And.

This area because he's got a big

all the to fill because he's.

Taking a position for a longer
perspective can you see.

Best gonna impact this area.

If you are solely focused on.

Just looking at what's going on
here you are not going to see.

What the guys are
doing up above you

you know

and that type of order flow is.

Significant st and it
can move them all care.

Significantly more than
obviously a small algo playing.

A few take so

that's the reason I'm going to
move US away from la really get

US to start looking up.

And value from

obviously a bigger perspective

and

just find me to say that
you know to reiterate.

Obviously we need to
define what that value is

thus will be they're
going to move to next slide

and year which is going
to look at value from surrey

profile from this perspective

and larger now said Don get.

You know lacazette to
confused you shouldn't be

should really just understand that it's
just what we've been doing all along but

obviously we've just.

Scrunched up so we can start to figure
out what the market shauna achieve over.

The whole day

and a bit further so we can
start holding positions and.

We can be a bit more relaxed and have a bit
more of a feel for what the whole market

trying to achieve

so let's go onto the next slide.

Okay ladies and gentlemen
so what were they want a slide

his autonomy get too worried about all
these mathematical formula you see air will

discuss dunbar

in no way are we gonna.

You know I expecting you to know what any
of this is in fact the opposite and or come

onto the.

In a moment while

to do is additional a think it'd be
quite useful for US to do it very quick.

Recap of what we
were looking at in the.

Prior section

and which is that.

You know if you remember.

This was essentially.

The volume profile for that day.

In the evening s and p

and you know these were just
profiles obviously of prior day so.

You can imagine why i'm
doing this again because.

If I was on that little depth of market that
you see where the water tiny incremental

via these how on earth
am I going to know.

More investors are trying to achieve
over a few days is impossible right.

This is where you really going to
take your trading to the next level.

Because you're going to have
a brilliant understanding of what.

Investors one different
time horizons are

gonna do we're going
to build the up for you

but first we we need to measure
this this thing we've been talking about

for awhile now about
value value areas.

So you can see it here.

You know typically is kind of

obvious when you I bullet
that the mature surety of.

Transactions took place.

In these little

packets almost

and we need to define those
buckets because at the end of the day.

We want to be able to
compare them day to day so.

I'm gonna show you
how institutions at doing

that that you're saying
looked you know what.

That's what value is and this
is called actually of value area.

High

and of value area

low and I'm going to
talk about that choir bear.

High-value area high value area.

Below and

institutions are
using these areas to.

Determine whether the market is.

Balanced.

All.

In if it breaks out.

And it goes up.

Imbalanced

and then getting into
the next area of balance

and we've talked
about this quiet lot walk

imbalance means in the
obviously it's aggression.

In a more.

Aggressive one on one
side of market orders

more buyers and sellers

but in aggressive terms

not outright terms as
we've said many times.

Because buyers and sellers are always
going to be equal is is the aggression the

market orders.

Coming in and obviously there could be some
fundamental reasons behind it as I said

in my opinion.

Thus all saw affected
in already the.

But the point is is this staff.

We.

A are gonna find

this to

measure a measurement for

how we can define these levels

but also I just wanted to make
one point as well you know.

And a normal ways I say always apologize
I dunno why I'm apologizing ocean is not.

My fault that you know.

The forex industry
has created all this.

Garbage around

and.

Know

brito terms were trending and.

The reason I said
trending is because

you notice.

Caused the market never
trends it doesn't actually trend

there's no such
thing as trending.

All the market is doing is
imbalance seeing trying to seek war.

Value or is a marketplace.

He sure a match
buyers and sellers.

At this stage aggressive
buyers and sellers.

At this stage there's no saw of

and.

Match is there

were aggressive buying is being
countered by aggressive selling.

I e sellers a aggressively her.

He first seller is aggressive

he's more happy than
someone who's passive right.

That means is
very happy to sell.

A balanced market as you no will
have aggressive buyers and sellers

how do we know the

market orders

what happens in this space if market
orders it taking place in both ways.

Profile build
heavily doesn't it.

What happens in
imbalance there is where

they are on.

Aggressive buyers and sellers.

Does nothing

very thin.

No transactions
taking place is all.

Aggressive buying gratifying aggressive
buying and there's no aggressive selling to

meet if.

So.

Does what happens when markets.

When people see basically all all the markets
doing as as as of so do many times is.

Is happy.

Transacting whatever

and then

boom it goes up

imbalances

people call this
trending is not.

Okay

seeking value.

Is looking.

For areas where.

Where can I find
transactions take place

okay

really crucial you understand the that
the market never transit just constantly.

Seeking value
seeking areas of value

and your job as a traitor and
talk about this hello later is.

To find out.

Where do people
indifferent investment

horizons and classes.

Perceived value to be.

And it is a very very hard job to do
I'm not gonna lie to you by obviously

with the correct
tools at least you can.

Have a good chance
of being able to do that

lunatic a lot more about.

And.

And outlook or no have gone a little bit
off topic here but it's really important

because some term a lay some

seeds in your mind

I dunno just throw this
out you all of a sudden.

A few sections time and you'll
have walked as a lot for me taken.

One trying to do is certainly ladies seeds
in your mind you already starting to think

about them.

What will happen is you see.

At the end of the day what you
probably haven't realize you may have.

Is have you know is how

this.

Is

one two three four five six
trading session say about a week

for I just over a week.

This is actually a
depth of market

bought.

Broken out

so.

In theory think about it you could have and
Sierra jaw and all institution platforms

let you do this.

I don't necessarily do it

and.

On.

Five day or sorcery six day basis I do
look at it for a week but will get into the

stone a confuse you right now.

Is that what you could in
theory do is you could join.

If you think about it if you moved his
profile right to the edge of the screen you

may have this one in you
may have thought one in.

You may have that one n
you may have that one in

what would happen.

You'd have

thought and thus clen
emerged up here wouldn't you.

Should have a bit
of a bulge death

then there's not much

volume here so be thin.

Then you merge these two
together a bit of this and a bitter that.

And you'd have a big bulkhead
should have all this volume bright.

Then you'd have very little volume
in this space the space this space or

in again.

To need of a bulge again
because what you'd moved.

This

area into here.

Okay

and then you a very thin profile
because there's no volume me.

So can you see.

That is a volume pro false

but all you've done is.

You've just broken
a url into little pieces.

Can you see that.

It's almost like and.

Let me see here
think this should work.

Yeah kissing be so
much similar to obviously

this is this is actually
a day period but.

Imagine that was a
whole week all you've done

is you've just said
alright you know what.

I'm going to break the out.

He will take the
ominous break the out.

Taking this i'm
gonna break the out.

Okay

that is

that is basically what
you've got here is

you've got depth of
market from your page age

for whole week

she's broke canal.

Can you see the type of analysis
you can do if this is amazing.

Honestly I am really.

Still excites me to this day

I mean obviously as I said I was a depth
of market trader they really start looking

at profile.

And to a little bit later on into
my career which was around the.

Show of six to eight year period it which
have mentioned in the reality check video

believe so.

You know have been
of sheep in the business

sixteen years has only
been about eight years.

Eight years eight to ten years
below and return by eight years.

The of been.

Looking at this
type of analysis.

Really.

Getting off the depth
of mall can looking at

this and is still excites
me to this day how.

Amazing.

It is

the sort of things you can.

Work out about war investors
are trying to achieve by really.

Breaking profiles out
over longer periods of time.

And.

Understanding and

see actually do you know what.

Anything that was going on the depth
of market such you happening here.

It's happening.

Here I mean if I hadn't told you
that this was Friday this was Monday.

This was Tuesday
this was Wednesday.

This was Thursday for all
you know this is a day profile.

For you know that could have been an hour
of this day profile this could have been.

Another our this could
have been an hour.

Could have been an hour
here this could have been in

our few hours or whatever this
could have been a few two hours.

That made up this
entire you know

chunked out trump tower.

Trunks out here

that just made up to
stay in thus your day.

Broken up right

how do you know that I

a week Sunday cause
you could see it here.

Can you see enough.

Can really start to do amazing
things if you broaden your horizons

and just apply the same analysis you've
been doing on the depth of market but rather

than being so.

Microscopic and
looking at the menu shy.

Start to really understand
that you know what.

People are trying to achieve.

Fair value.

Over longer periods of time

and.

As you know it's a little bit this
the final put them in a mate here.

Before we actually
defined this some.

This area

that we want to
court fair value.

Is

this is what's actually unique and again
I'm just laying the see don't think i'm

talking for the sake of a apologize
that this has gone on a little woba.

Is important I mentioned this.

That difficult years and.

And of notice a lot of
people to find is hard to

accept I think they get it but
they don't want to accept it.

Is that generally.

In a consumer market like bread milk
chocolate eggs what have you have.

Would you agree people are buying
bread or buying eggs or buying milk.

I.

Don't look into silva in a year's time or
six months time or and one mumps time.

One is purchase

and then you consume
me as consumers.

The problem in financial markets is
the beauty of it but the problem from a

speculative perspective.

Is that think about it.

When you buy

the pound or you buy

the stock market
index or when you buy.

A commodity as a speculator.

As every single person.

View it the way that they view bread you
know you everyone buys bread and they eat it

stunt thus it.

Why do you think is
so easy for bread price.

Decline of be sticky to buy a pound everyone
oh kind of agree on it the whole world

or at least you're.

A general local market you
know like a country or whatever.

Doesn't work like the and financial
markets does it does the problem.

This different people

some people called low costs
which we're gonna talk about.

Who are proprietary trading
firms short term algorithms.

Then interested in holding
this thing for a week

but then you'll have medium
term investors certain.

Types of hedge

styles

that obviously
want to do walk take

risk into week risk.

That will take it for a week.

Right I mean if you've
gone algorithm.

As trading on the depth of
market is interested in a few

takes

who owner if he's going to
hold the market for a week.

For a few ticks obviously
they're looking for bigger moves.

Then you've got pension funds
who are holding for months.

Right got central bank chief go.

And obviously different types
of institutions that are looking

to play longer term.

They might be looking.

For five hundred critics.

Can you see

their perception of value.

Is gonna be very different.

Can I know I'm going
off topic here but a.

I hope you can
understand is important you

start to at least thought
to think about this.

Because I am going
to introduce slower so.

You know and

we talked about this before being
potentially the profile for the whole week.

If we were to merge all of these
together and scrunched 'em up.

Into this site side.

To see

someone with a longer
term perspective for a week.

His perception of value might
be this whole area he might be.

The market might be down
here and you might be for

Jenna walk.

I'm seeing aggression.

I'm seeing absorption
or whatever is he seeing

seeing some.

Supportive fundamental
factors and he's thinking you

often as a good chance it's.

Going to get back
into fair value.

For the whole week.

Therefore I'm gonna.

Play this to get
back into that area

right.

Very different to her.

Algorithm.

Who's looking at in that area
there as you saw me doing puddle.

But in theories the
same thing is just over.

A wider horizon but

she this is the difficult in

financial markets is.

This all the flow

is going to impact that

the flow

and then there might be
some medium term guy.

Over here who's looking at
these two buckets of value.

On the market you know.

Over obviously it's noise
over here at the time but.

You know something's happening
over here which makes him think.

Is going to be imbalanced
of what revenue.

And obviously this doesn't align
but you understand my point.

The saw the flow is going to impact
this all the flow is going to impact this.

These all the flows are all impact teaching
each of and I'm going to show you how to

navigate this.

Ba this is the beauty of.

Profile and.

Starting to look at it from a.

Bird's eye perspective so.

Of realize of basically
completely gone off topic their bar.

It was important I did the.

The want you to understand.

Why we've moved
away a really big son

of know is there's especially
feedback from the foundation courses.

Lot of people

and.

And Lucas a good thing I
really love the enthusiasm bark.

Could to be careful that you don't become
obsessed with a depth of market becoming

profitable under.

Some of the show you why

you know going to do it

you know the way the
algorithms are these days and.

I'm going to show you actually.

Some institutional guys trading
on a depth of market later as well.

Because I want to show you other
institutional causes you're not only me.

Quite nice to me to show are

other guys

and I'm gonna show you how.

Algorithms have really changed
known as very very difficult.

This

and on the other hand
a something where.

In a human beings can
really add edge because.

This very difficult trained and algorithm
on this type of analysis where we can

actually start to
look at value if.

We can look up

obviously what locals
are doing we can also Luca

de the intra-day value their.

We can look at value over

two three days
that type of investor.

As I said we can look at the bigger term
we can start putting these things together

and really.

Use our discretion and
as I said what you get paid

to really think

outside the box and.

That's what we can do so.

Anyway.

I.

Hope you can see that that was actually
done for a logical reason the I wanted to go

through that

and.

What we gonna do knows
who asked you going to look at.

How value is measured so.

Less

look at it from a

a saw of probability
distribution perspective.

So.

She going to talk
you through the slide.

We've done the rica and a little bit more
I went on a little bit of attention by was

very relative.

Lack I said I want you to start
becoming comfortable with this.

Type of profile no
longer of is she been.

So focused on the menu shy

and you know obviously the dog thing or
discussed with you and told you why there was

a bullet point there

and

so really are

start to talk a little about
this probability distribution so.

And as I said this is
no longer relevant to US

we've now transitioned.

Into

and.

Profile on a.

Of wider basis and.

What.

Essentially I've done is so we've got
the profile coming from top to bottom.

Right.

But all of today's
of just flipped it

okay.

So again

don't think always doing something
different I'm not the reason I flipped it is

because of this.

So what this is is is called
a belka distribution and.

Firstly I want to be quite
clear and tell you that.

I

have mentioned to you

when you go into
professional from.

I

bought

I would at why she sent you at the
start was the I would be very clear.

When you go into
a professional from.

Do.

What they're going to
teach on what they're not

this they're not going to
teach you can be absolutely

and

save that with hundred
percent certainty.

They don't teach you

about normal distribution
they expect you to know it.

Or not to any level of detail but
though and I think it's a mistake

and I'll show you why because settings
actually quite useful for you to know.

Because I've seen it time and time
again people just use this stuffers

almost indicate alike

and it should not that you go
to understand the limitations.

Go to understand

and.

Would you know the
measurements that.

So

this the sort of.

An area of value right.

Balance area.

That we define.

Do.

You need to know how that formed

to some extent.

In a anomalies just take my
word for it at the end of the day.

Probably makes more sense
warm what I'm trying to get a if.

We answered this question.

Is maths important.

Because I know there's
going to be some of you who.

Have never heard of an English
bhushan and maybe you know very little.

About.

Statistical mathematics.

And of Google news you.

You're an advantage and you won't even
believe me I know you'll be thinking nije

having US on you just say
no to make US feel better.

And at yaddo need to do that
you've already bought the course

you know.

You haven't asked me this question
before purchasing the course like.

I envy do I need
to know Matheson

on just telling you this
so you bought know.

On a m a very honest
person as you know very blunt.

And a tell you how he is.

And.

You know

so there's no reason for me to.

Mislead you

I'm telling you
frankly very genuinely.

That you have a
major advani age.

If you've

for

very little maths before

and thus going to be music
to years he is unless good.

Now

of put here is muffs
important to a depends.

Now there's a b.

What he is is I said I'm going to
be honest review of know is thin.

Social media circles.

There seems to be

mean it's

irresponsible anyway shouldn't be trading
things like gold and because he's a very

thin profile on you know.

And I'm going to
get into that Layton.

For exchanges oversee
one of those markets his well.

I'm sorry to say

but no professional firms
going to let you trade those.

Market because they
understand how thin the volume is

and how difficult it is for the market
to to you know how I said before.

In treasuries
you've noticed that.

The profile build very nicely

why

because way liquid

this people there.

Is the volume.

The process as I said before.

Price determination is
happening very quickly.

Because buyers and sellers are

in abundance.

Effects just not the case guys is grey
market you have to understand the.

Esteemed why did you think in.

Pound dollar

I was struggling German ball was always be
value here is beverley here's Beverly him

be very here

in treasury slot gallup's sulla
up and it's just nice and smooth.

To all over the place in effect.

Fried.

She does thus.

One thing but
that's not the point

point coming back
to mathematics.

Is the.

Are no is people
are very responsible.

And.

That we pushing options towards you have
no says big trend of people wanted to get

options complete and utter.

Bonkers absolute bonkers.

The end of that they go realize
the value of an option is driven

by time decay

by volatility

you know to
measure these things.

And.

People may

not want to accept this

but yeah you need to understand.

What on earth is going on in the
mathematics of all of that because.

You know you may not know this
and this isn't for my ego boost bot.

Is because I would
have bring things to life

and tell you the actually
experienced this myself.

So

at the start of mockery of little stint on
the options desk I worked in and options

desk and I used to.

Build incredibly complex
pricing models on.

Spreadsheets and.

Using.

Quite complicated mathematics so

there was a time when I
could read will you see here.

Is not English to me.

Is very straightforward because this
is why studied I was a mathematician.

About business
scorn you know at the

a bill

quite heavy

and

financial models

which is probably why I
got into investment banking.

Fairly easily

but.

You might be thinking
oh who does he think he is

and

please note that.

Actually won the regional telling on is
because it's work to my disadvantage.

Massively

because

for options structure products
I'm going to tell you bluntly

if you don't know.

And you know decent level of Madison
statistics forget it you should be touchy those

markets.

Bitcoin these of
vanilla products

these are not driven.

By.

All these different very

like I talked about time.

Decay volatility even.

Volatility of volatility you need to
understand quite a lot of things to trade.

Options in a certain way is very
important you understand that but.

More case.

Black the spot market
a futures market.

Nope they call vanilla
markets that driven by war.

Transactions

and

human beings it's a.

It's a very emotional field is.

You know maths is
not info solved at all

and in fact to make my point.

Because it's an important
point let's be honest

to to put people at ease
they need to know this upfront

hang Obama get myself into
should I go learning this stuff.

Know because

and I'm going to show your wife.

Will be taught to do

right which on a say that.

Okay.

Let's try and find out where balance his
in this may market based on transactions I

have taken place rather they.

Quite weak or realize is that

and.

The monkees very imperfect so.

What could have happened
here on this particular

that no two days
are exactly the same.

This market could have done this

to see critical night that could have gone
either and then it could have gone like

the then he could have.

Had these sort of emotional
spikes will over the place.

She to see these even
when you using maths

to define these values.

And.

In certain instruments like I said Murray
liquid instruments where you've got.

More sophisticated players
and it's purely institutional which.

Is typically tends to be the case in
things are structured products and.

Her options and
so on and so forth

it isn't such a broad market

so some of those mathematical
fact is a much more important here.

Cause honestly I can tell you.

Whether you Mark your value area
high here or whether you market here.

He

I can honestly and I

don't like to you

the stop or phrases but it's true
the marketed give a monkey's.

I can tell you

without.

Any hesitation.

That.

Any way in this region
is going to be okay

I'll tell you from experience.

Having been a
maths junkie myself.

I used to find it so difficult to accept
that the mathematical answer as this line.

But oh no actually
the market did war.

Can you see it decided to.

Turn around a little bit above where
I thought my exact line should be.

So

lemme just and

again is important I do this
for especially those of US.

And.

The kind of bit concerned about

what have been showing
in terms of muff makes.

So what easy so in a
balance market right.

Cause sometimes a market's
going to turn around here.

Okay

to gop

sometimes it's going to do
this and then it's going to go up.

Or back into balance sometimes is
going to go a little bit further and go

can you see it could be
anywhere in this region.

Okay.

But then why do we use a model because
at the end of the day I don't want to be

drawing over here

okay that's just ludicrous.

I'd only be drawing
a ride the edge

thus just ridiculous.

Donna be drawing over
here you know of wanna get.

Some sort of semblance
of standardized value.

The are can use to
just compare across.

And.

And

essentially.

That by looking at probably distribution
and you'll make sense in a second.

We can get a very
approximate idea and.

Like I said the guys

who have probably

have never heard of her
a normal distribution to

cause.

I sure you're going to
be a massive advantage.

So please don't go out
and you know going.

So send the next year of your life trying
to learn martial wasting your time you're

going to go backwards.

Because you are going to
make the mistake and I suffered

big time.

You know I

told you had this
two year period Rose

staggered url and.

I know have mentioned of
the reasons but you gotta

enough said it before
financial markets fast and.

There's a plethora of reasons and
actually this was an another major.

June boy told you that

always have found it difficult
to allow the market this

show of leeway to be very fluid

and precision kills people.

I saw it so many times.

Financial whiz kids coming in.

Thinking they could trade.

The

p five hundred or.

A minute a vote like
me that come from

a technical background

they got crushed.

Why is that.

Cause it she could accept it

if the market
had a little bit of a

and you know bad moment and
then came back in they will say nope

that is imbalanced I know
because my mathematical formula.

Tells me a has to be here.

Okay.

Proper nice.

The market doesn't give a
monkey's locks at is not perfect

and will show you
the in a moment.

It could just as easily be that
fair values in this region and.

So I kind of learn

to you know walk.

Let me read the volume in
the moment dynamically.

And this is where I of i'm
going to give a reality check

later than.

You know people find it
very hard to accept that.

There is no

magic tula indicator and
this in a nutshell is why

to market very
imperfect is not gonna.

Be precise

you have to be very
good at recognizing.

The markets doing this.

And.

And that's why I had your the

depth of market of

to build up some sort of understanding
of absorption and things either.

I'll show you how you can

start to read some of that without looking
at that depth of market you know the

cumulative doubter to be.

Certain tools we can use.

Footprint to an extent
and as well but.

To be ways you know
we can help to kind of

and identify that
potentially is is

is no actually gonna go imbalanced is
actually even though is broken out this.

Sort of.

Area that we called value
value area low value area high.

Actually.

Just kind of just faked.

Not fake spot in it's just
overshot slightly and.

Obviously these are things you
have to learn to read in the moment.

And the problem is if you have this
mathematical mindset that everything has to be

precise.

You've finished

I'll tell you right now

gonna be problems.

Cause I

can assure you
the market will not.

Stop at that exact line.

That we're about to define

using a probability
distribution model.

And.

Is going to be
imprecise so you know.

That's what I say
hope it's clear if you're.

Basically if you kinda just get the gist of
it massive advantage because you knock on

approach in that.

Precise sense and

I know I keep saying is because obviously
I hope you appreciate our auto have instant

feedback in an artist will
make sure everyone gets here.

That's why sometimes
I do repeat was

a few times.

But in a nutshell.

Basically

is ones you come away from
this knowing that you know what

seventy percent.

Of values.

Constitutes the majority is as
simple as that you'll be okay and then.

I'm Skinner basically show
some basic stuff like the mean.

The mode

which is literally just and you
seeing green is just the area with the.

Highest number of
transactions take place

on the mean everyone
knows what the averages

and if you can just accept.

That you know what.

When the bulk of transactions.

Ah.

This the sort of

bracket where the boat seventy
percent of the bulk of transactions for in.

Is my value area.

By he.

Seventy percent
of transactions is

this many

you know these are transit
market all is right to scrunched up.

Seventy percent fair in
here thus mobile years

but.

A go to do this section because at
the end of the day if I just tell you that.

You know I don't
want you to just say.

General walk.

Envy told me it will seventy percents
I'm going to use no no no no no no no no.

We don't we don't do that

who I said to you.

Any time someone told
me some even my boss

no.

I don't accept it.

He could.

He could have at
least to some extent.

Of you could understand
why is it seventy percent.

By the end of a more
point is going forward.

As long as.

You kinda just said you know what
seventy percent yet I'm okay with that.

You're going to be a mess the of
advantage to the other person who says no.

Is could be this particular level
because the probably distribution.

Says it has to be sixty eight
point eight percent of that

are you going to be in
big trouble doing that so.

Let's get on and
actually look at.

Normal distributions
which is the type of

promote he distribution

and then we can.

Do.

Saw of.

Get you to see why I talked
about seventy percent okay so.

This a final barrage
wanna see on

slide before we look
a real example is that.

Should this is something
called a a normal distribution.

Okay

and is very very very simple.

You.

Don't please don't look at this and
think oh my god I'm never going to get this

always present as you some of
you be familiar with that you'll know.

The standard deviations.

One two standard deviations

and.

From from obviously
the that soft mode.

Or the me which in and

in a normal distribution
that equal obviously.

But if that makes no sense yama
I'm going to go over the in a moment.

Would he eases and

the reason

that we used normal
distributions is because.

We're going to get out go over this in
the next slide but just notice one thing.

The

markets

in a balanced environment.

Behave exactly like.

A statistical
normal distribution.

And I know you've seen that thinking
war on earth is a statistical normal

distribution or all of you but
those of you are not familiar with it.

So warm you to do know is i'm
gonna go on the next slide side.

And and we're going
to discuss here and

this don't worry about it to
march all the series is is just.

Showing US why.

In this

type of environment which is actually
applicable to many scenarios in real life.

Doctors are using
normal distributions

for clinical trials governments
who use seeing them to forecast

certain characteristics are about the
population because obviously they clown.

Ask every single person

a question if they
want to find out.

Certain characteristics about the
population that live in the country and

so on and sofa

sofa sofa so they use.

Samples and then they will

try to figure out you know
what's the likelihood that certain.

Percentage fits.

Into.

A rage.

Unless essentially
or which trying to do is

we're trying to find out.

What ranged US the maturity.

Why he this seventy
percent I talk about.

Fitting to some
sort of range so.

What we're going gonna do next
is element of come back to this is.

An.

Essentially when I talk a little bit
about the normal distribution and boy is a

normal distribution

and

and in fact

and.

What are not just
quickly kicked out of here

and then we can go to the
next slide because his choir.

And thinking general war

I don't want anyone to be
left at the end of the slide.

With any short feeling
of credit their mind that.

You know I'm never
going to get this.

If you think of.

Do.

You actually

looked at normal distribution if you've
done the foundation and followed some of the

modules you about
probably realize it

to remember we had the
example where I said that.

And we were looking at milk.

And

we add the milk
price of one dollar.

Ah sorry one fifty wasn't it.

We had a at one fifty

and to remember I said to.

The oh if you go

and.

You know I'd take a survey

outside of the the high street
and everyone coming up to you

and gives you a price

well that.

He is source I doing it's highly

okay one two three
four five a price.

Dazzle you with the a
guys that is exactly what.

A normal distribution
is it's all it's doing is it's.

Basically sorting data.

Into something called
a histogram which is.

That if you've got your
one dollar fifty for milk

and I said to walk.

Every time someone buys

said this is just quantity here.

And every time
someone buys at one fifty

just record it

like that

but would you do.

You'd be recording recording recording
because everyone's going to be buying at this.

Kind of

central price very
close to one fifty what.

He going to have
some webinar zero.

Or ten p or twenty p very

unless they're very lucky and they get like
some so a bargain you're going to get the

odd person

but the closer you get to the.

Soft of general price of milk the more
transactions going to take place in you're

going to be recording
these by hand.

Right all the normal distribution is
doing is it's taking a line of best-fit.

Hunting

taseer

to see them.

Look can you see the shape.

Okay so does.

Our thought you know what let me

show you that
quickly so you see.

Very simple.

Is just literally a record

of data tally.

Her every single price point.

And a one you to recognize this

war is going on

and you know the reason I showed you this
is where is because I realized is probably

quite good for me to
show you the swaths of got

the old depth of the
market cause you can.

See that level of detail here
and you won't be able to.

See this.

Look instead of
one fifty what is it

just the price

of worcester.

Quantity.

Is exactly the same thing.

Can you see the
markets doing the.

Right of every price.

He just recording

and instead of you
recording on a piece of paper

the exchange is doing it few.

The exchange you saying

oh

one contract at three.

That could be one fifty row.

And one.

Transaction of milk took place will
just be one contract market order.

Instead

she just

financial market price.

The price at the end of the day

same thing's happening
and we're looking at best fit.

And he just so happens
and I'm gonna explain this.

Later on the

so you agree this
depth of market is that

and it's just that flipped over.

The

the behave your financial
markets in a balanced environment.

Visual majority of
transactions take place.

The center

from the center.

Milk

what does it do.

Bread all these products.

Have fluctuate

and.

In the sense that

they may but

at the.

Sort of

more extreme levels.

These areas very little transactions
take place in in the meet

the middle.

The main prize nice.

Lots of transactions take place.

So what mathematicians
have realized is that.

Things that have a

of.

Stand and see

to have this of central valley which
prey so many things as you know.

Pretty much every product you
see on the supermarket shelf.

Is approximately the same price all over
the country right yeah okay five p tempe

year and that.

Was financial
market during is it.

When a financial market

is moving

time and price.

Does he do that the

of course north.

He gyrates a little bit.

Five p m p here and there in the
same way a price of the good does.

The monkees doing that as well.

She's exactly the
same that that's why.

You know you might get your blip up there
you won't get the old blip down here but

does can have very little.

Tally numbers contracts volume.

Whereas here you can get turns.

Like you got here at one fifty.

Tons

tons.

Very little here was start
doing forming a distribution.

In the shape

and.

What it is as they just know
as mathematicians that.

Any and.

So of

and.

Sample or population
that has outcomes.

That tend to.

Congregate.

Around a central value

and is larger things
I'm gonna show you.

Where what they've
noticed is mathematically.

Within one standard
deviation which is.

Is a measure of
dispersion of also of

how much price
varies from the mean

in terms of all that I

is going to make
sense in the next slide.

Of we can standardize the and say across
all of these financial markets milk bread

and heights of children

sure shoe sizes whatever.

Within a one standard
deviation range either side.

Sixty eight thirty four plus
thirty four sixty eight percent.

I e.

The majority of values will fall

within that range

sir can you see why talked
about seventy per cent now.

Okay even market professionals.

To say genoa licious round

seventy percent because they
recognized the market imperfect.

Luscious use that.

Sort of standard deviation range

and.

As

seventy boggling sixty eight but

want to do is so.

Understand that may still not have been
clear to allow people to some of you looked

at normal distribution
of would've.

Why don't we go and see how
normal distribution works in real life.

Again I.

Am Hussein this speakers

for an ego reason
bar will you to know.

That you will not see this in a
branch trading environment.

In a professional training on the
luminous each this on doing this.

Because a.

Of really feel strongly the one a bridge
the gap of promised the bridge the gap

between retail unprofessional

and I'm going to do
that boehner do more.

On a do more than the and

of show you.

Some of the pitfalls

that people could fall into

and.

A because

this is and explain
to them properly.

But be even if they come from a
background where they know this inside out

they go to the other extreme

where they try to be too
precise with all of this.

Just get the gist of it and
you're going to be laughing.

And.

And you know don't
worry too much about.

All of that she told me to
know all this is telling US is.

Why within one
standard deviation

is thirty four by
one day for work

on as a who cares.

Luck I said ice to be obsessed and ice the
feel so good about myself that yeah I know

all of days when he came to.

Trading the markets
are my god are always

I wasn't a disaster
by US oh Sarah did.

Did stagnate you know and there were
guys around me don't so much better.

Who didn't have this
mathematical background and.

She drives me bananas
and then I realized why

because.

They will much more flexible.

What

they are accepted it

and I found the ought to accept.

That markets are imprecise her.

You know get all the staff at your head
don't worry about it is really not gonna do

any favors.

Get the gist of it less
gone to the next slide

and look at it in a real world example
cheers okay ladies and gentleman should just

to reiterate the point where I've done
here is of put together a quick summary.

Of

some of the things
that we've talked about

and you know what you
need to come away with

and boy such actually
really know that complicated.

Bought the reason I took her by in-depth
is because I like to do a good job at just

make sure that
covered all the basis

and

and you know I said
before it's better I say more.

And do some people's
heads in by talk so much.

Rather than not say enough and leave people
confused so you know our drivers a tumors

then too low so.

I.

Essentially thus one going
over this in so much detail

even though.

As you know is as we progress
into developing strategy.

A law of this.

Ring not going to be that important
luck I said as as long as you just.

Kind of

understand that you know what
proximately the majority of the values.

Seventy percent

is war.

Is considered the
value area is fair value.

But what he is is

of really

would like to.

Show you why there is.

And

why it is that institutions.

Are using a normal distribution
of this type of analysis

and the soft.

Equidistant on each side.

With a central location.

And.

So what

is fully profile of already
talked about this before don't.

Get confused by this and think is
beyond do it really is nice so basic.

All his his people are
collecting data rye and they're.

Basically parading
the data into.

And package on axes

from so here it
could be the price.

Ripe for example.

It could be

height.

Could be a q people's I
accuse it could be the weight.

Of a babies it could
be the shoe sizes.

And.

Obviously it could be the
price of his pound dollar bread.

As you saw in the exam portal to
about before guys can be anything.

And then he you're
simply looking at.

The frequency.

Okay.

And basically what you're doing is
you just collecting a histogram of data.

Were you simply saying.

Sir lucious go through these very quickly
you could be saying do you know what.

The majority of

height of

the

other know meiosis.

One hundred eighty centimeters or the
majority them at them is going to be here.

And and actually the might be some the
hundred and seventy the might be some the one

hundred and ninety.

Than this can be very few
the are you know either side.

And.

Is going to follow this

see what he is if you think about it how
many things in life of the central tendency.

We talked about it.

Pretty much everything
in the supermarket shelf.

Right.

A.

Of

and.

Sure of coke zero.

Look or I dunno how much is in the
states bomb we see on from the UK.

To by sixth the p these days.

Quite

good tesco go to a corner
shop you go here you go there.

Sweetie not gonna
vary by that much.

Go and do it go and do this
experiment go and build of probability.

Distribution a histogram.

And just go and bright out sixty p sixty
one p sixty two sixty three sixty four.

All the way up to like.

You know.

Two pounds maybe

and then zero here.

It's been have walk

a central tendency.

For you to agree.

Let's say you go to a thousand
stores throughout the country.

Less be honest.

Almost ninety percent of them.

Are gonna be somewhere
in this region right.

I agree somewhat
be sixty five p some

be fifty five p some
old ones might be fifty p.

Rights you going to have this.

Can see where we're going with this
and each one of these are no different to a

market order

to collect him

the

is that's all you're doing.

In the same way the exchanges

collecting this data.

To see so much of this
exchanges doing a survey and.

Looking at market orders that
are taking place in the marketplace.

Instead of diet
coke is just futures.

And they're just recording
it and the building up.

This of histogram.

And that you saying

know walk.

Lets you see

also shaped as it take

and he has a central
tendency these coach thanks.

Guys have.

Hardly anyone is going
to be lucky enough to.

You might get the odd person
where it's near expiry of something.

Or whatever

there's some stock his shoes or would
have I don't know a huge surplus and

the market it for five p
m p by less be honest.

I'm going to be anywhere near
the amount I get it for sixty piero.

She's going to be
the central tendency.

While in an equally hardly any

going to charge.

Two pounds for a can.

Of diet coke or whatever
is that we're looking at.

Central tendency can you see.

Could have realize he sent is a

phenomena that
takes place in most.

Wife.

And.

People's I q levels will follow
the same saw distribution.

Baby's weight

the not gonna vary by a mammoth amount
the gonna be approximately the same.

Shoe sizes for

certain ages.

And.

You know.

Paul.

Men.

The earth

though a five.

Go out there Austin
the shoe sizes.

He gonna find over thousands
and thousands and thousands

which we have here
thousands of market orders.

A colonel or be around.

You know

have shown

I only know UK sue shoe sizes by
say eight nine ten eleven docile region.

He's going to be out there
with the shoe size of one.

Hardly anyone they all tend to.

Congregate.

Around a central valley.

Right.

Causes so many examples
are could show you.

So what governments are doing hospitals all
clin clinicians claw what coughing of the

word but

you know the people during these
clinical trials and of if you try to.

Figure things out what they've
realized is that they can use this

as a sampling method

and

you know if

if

for example the government shallow
were cow was the average height.

Of people.

The snow is not

practical

to send the questionnaire out.

To six million people
ten million people

how many people
live in the country

to do a sample

and they'll just be trying to
figure out what's the probability.

That the majority

fit within of one standard
deviation range and we're going to

calculate the standard
deviation a moment.

That's all we're doing.

Can of coke.

Was the probability that the
majority fit within this rank.

How can I compare this.

To

ah

birth

to shoe size to pound dollar.

Because of you know east.

Coast

you'll need to take my word for it
thus the beautiful thing about this.

Look at what prices of
financial instruments at doing.

Human behavior.

Humans love.

Doing things are habitual
where they feel comfortable.

Body we talk about before
and e bay where we said.

Can a certain mechanical the.

iPhone.

Right.

If it's trading one
thousand pounds

and people can see that previous
transactions have taken place out.

And.

Bought bought.

A thousand pounds
or put one k here.

You agree the majority of transactions
going to take place there why is that

we can feel uncomfortable
going to two thousand came the

on a many of was training one
thousand one to everyone else does.

Can you see that

is going to be.

The central tendency.

Gonna get the odd lucky
guy you know happens.

Who just happens to catch
some one of god and a get if.

You're not for lot five six
hundred pounds very rare.

And then you might get
the old guy who has this

sure of desperation are needed to Morris
more wife's birthday I'm just going to pay

twelve hundred the
info in underpants.

Cause that's all bus available

why she'd get the odd.

Few people but the majority
of and to take place where.

The central valley of one
thousand pounds and look.

Same shape

guys.

Is the beauty.

Of this

and.

The the way that.

You can see why look
at the mock as his wife.

Cause you seen guys amr very.

Scientific person I need.

Proof.

Right this way he indicated cause
as soon as I look at the proof.

It's easy or can
see the garbage.

When I look at this

find it very hard.

To dismiss this because
I'm gonna hang on a minute.

The more care

I don't even need to

taking your word for it look
I'm actually looking at it myself

you tell me what shape

is.

The majority of transactions
are taking place.

Around.

Certain values and
we see that all the time.

We see markets get happy

and they do what.

They do this.

Okay they settle

around this

central valley

okay the majority transaction
has taken place her.

Another has taken a while for me to
explain but it's really important that you

understand because was
happened historically is.

To help solve this problem.

Of you know how can we make
forecasts and predictions about.

The likely height of the entire population
the I q the birth weights shoe sizes all

the saw of things.

Clinical trials as well.

Mathematicians
historically realized.

That you know what
if something has.

Central tendency.

As we've seen

so many things do.

Financial markets seem to
have the central tendency.

What they realized is.

There's this measure.

Called

standard deviation
and all that is is.

It's looking at how

and.

Spread out the
values saw does this

measurement that
when you actually

use US a measurement.

We're going to do it
together in a second.

That know no matter what you're looking at
heights I q birth way male shoe size pound

dollar financial transaction.

As long as they
follow this shape.

With distribution

values.

Then sixty eight percent or
for within the exact same range

when measured.

Excuse me

when measured.

In standard even she pups.

Okay.

So die is where the sixty eight percent
comes from or seventy percent or

so hopefully that make sense.

And

thus why.

We look at

standard deviation.

And

basically that is the value area

so it's called.

You know that will be
this standard deviation.

Here

and

a son.

Basically school
devalue area high.

A case of the standard
deviation their what you see here.

And then you see here with

sixty eight percent thirty four plus
that before we just round up to seven he.

He is we just say
look you know war.

Where

by calculating
standard deviation and.

The machine will do
this for you Sierra chop

zero automatically don't worry done to
do this why say don't worry too much about

this stuff.

I just like to explain
it to because only to.

Go home comfortable not thinking are
ambitious take it no don't never take my word

for things.

I want to explain this to
you so if you decided to

kind of work this out for yourself
you're not giving you an example year this

party tons of example for the.

Basics standard deviation calculations on
the Internet bach in our oneness to be the

best course in the market
so that's why I'm doing this.

And pixar are wanna

actually derive

this to some extent myself

and.

And obviously we're
not going to do the maths

on the previous
slide as irrelevant will

or day

trying to do the this is good enough
to show you was standard deviation is.

And.

So basically is
called a value area hi.

And the value area

love for obviously isn't

reasons thus the high.

With the value area unless the
low-value area and it's just these

standard deviations
and it's basically were.

Seventy percent
of the day to fall.

And and then you've got

the.

Mode

and the mode all the.

Is right.

So what happens
if you think about it.

In any statistical de acero or

any dataset.

Let's say your the government right and
you say to a worker lesser you work for the

government

and.

All these are is these a
descriptive statistics which.

I dunno maybe a doesn't
sound complicated

maybe it does some
is isn't is really basic.

All mean and is lesser you worked
for the Goldman the gm was a look into

go find out the height.

Of and.

Certain age of the
population male population

for shoe size of whatever.

And let US know.

And imagine they did say to you.

Go and find out from every single
person's I could be several million.

Might take you some
time whatever will.

She come up with a huge
database of value Troy.

Is it really going to help the government
if you say here you go here six million

values or even if you took a sample of one
hundred people three hundred people said.

He is three hundred value

to me

and going to be meaningless.

You need some way of describing

that data.

And.

I knew that is thus the average

okay

so the averages of
descriptive statistic.

So

the in his most simplistic
former could be like.

You know you've got

do.

Three numbers one two
three was the average is two

to describes.

Basically it's the average describes
these numbers in one number

just looking at the average

saying genoa

roughly

is to.

Basically.

If someone said you you know these three
day of which meant meant something in a way

to describe them in one number.

Can go for the average aren't
you can say lies approximately two.

And

and all the standard deviation is doing
and we're going to come back to this is

looking at the spread.

Because.

What is his let's take
another example.

So

a few.

For example where to look at.

And let's say you had
three numbers ripe for.

Five

and six.

Boost the average.

Five right pretty
straightforward.

Okay.

These are quite evenly
spread out but then

boy few had.

And.

Different numbers so less saw and again the
cottage on a script in is on making this

akbar.

Said could go could be a
disaster bar let's hope not.

Less you are two five and eight.

Right.

Cause the average

the same as any

five.

Three either side.

But if I tell you in one number.

A descriptive statistics
of these three numbers

as being five.

And same here it's five

as you say to me I can
only tell you one number.

Kissing by this could
be loads of values

right it could be loads
of values either side.

And.

No of shall only give you the data element
described as an average on average.

You know it's almost
like if you think about it.

You see all the time
in sport don't you were.

A football team soccer teams of shoe
in the u s is called choco he is football

or hockey or whatever.

Of ominous wiki
football terms cause.

Or cricket terms as
she less use cricket.

And.

A team

scores.

Over a season they
might play fifty matches

the mice

two hundred.

Over say fifty overs.

Two hundred three hundred one hundred
one fifty two hundred three hundred.

These liquid gone for fifty

matches.

How many times you say
on average they scored

hundred and.

She she is used all the time isn't it said
descriptive statistics docile the mean is.

At the point

is that look here.

Does he tell me

that the other values are much
closer in this scenario to this scenario.

Can you see four five
six a very bunched up.

Two five and eight

spread out

the means the same.

Rights you need some.

Descriptive statistic.

That tells you the
deviation is called

you know to deviate is is to
deviate how much does it move.

To the standard deviation
is just a measure.

Of how spread out values are obviously the
standard debate oceans going to be bigger.

Here because.

More spread out

here the standard
deviations going to be smaller.

So basically what
you're saying is that

and sixty eight
percent of values.

In one standard deviation in

this.

Set of numbers is going
to be in a small arrange.

Whereas here it's going to
be a wider array very the basic

and just a hammer
home this point.

We're now going into a real
example where we look at this.

I.

Bought just to sort of.

For completion sake

you know I said I want as long
as you come away from this

being comfortable that genoa

long as seventy percent
of the values for in here.

This couple of of things you just need
to know and the really honestly that very

straightforward.

And.

Is that

this is something
called the the pok.

Which is the mode

so the mode is

the most common

values in a.

Series of data points

and honestly the
mode and the mean

have different advantages
and disadvantages

and.

In.

When you using the web

which is.

Basically the mean.

All easy is literally just the average
by some weighted by volume.

And.

I'm going to show you that bit later
we don't really look at a volume profile

and

and

a local milk

to go into otherwise we will end
up having a statistics corpse right.

Is irrelevant you
honestly you can be.

Like I said you can get go down the rabbit
hole with math my aches and just going to

lose sight of what
yet she told to achieve

here we try to.

I saw figure out where you got bigger
problems to worry about as I said that

different values across
different time horizons and.

Got much bigger things to worry
about them how precise you of of here.

And so look if hello this is going
overhead had honestly don't worry about it.

I.

Keep going over this a few
times and I promise you will get it

if you don't let me
know obviously bought

and

you see that a really is no
important to be precise however.

I'm just going to tell you
again for completion said that.

I'm on a volume profile and he will become
obvious to you why we want to look at the

most common value.

Here.

Because think about it

you know like I said with the iPhone
example and so on and so forth.

We want to know where did the most
transactions take place and that is.

It's called a valid point of control
because in theory should have.

The most control
over price because.

Price should always wanted
one a glossary want to.

One

to reach their

right because luck in an eBay auction
the price always wants to go to to.

Were previous transactions have.

Taken place the most.

So that's why we look at that as the mode
which is just of most frequently occurring

as all in is honestly.

Don't overcomplicate is
nothing more than that is just.

And the system will do is

you just literally on your volume
profile where you saw those individual.

Contract numbers

just where the most
contracts took place

a price point

and is marked by a great number

and in theory thus where the market should
be very attracted you but honestly I tell

you from.

Years of experience.

And.

Is never going to work that way

more happiness.

This is why I tell people.

In need time to
learn the market.

Because you have to
observe it believe it for yourself.

You know is.

That you know if the market is
of balance say it down here and.

We get into the value area low.

And be start to test
their and test and then.

We break into it.

You know you're thinking you
want to go to balance cause is.

Is never gonna

be

like.

Boom to the point yet

brilliant

crystal ball a godless not gonna work
like that was actually going to happiness.

And.

Then again this will come
of experience will notice.

Is that what the market will do

it will do stuff like this.

Call up in am I stop there.

That

come off and then it.

Might get close on and come off and
then he my overshoot and and come off.

Can you see what's happening.

So proxima.

Be very roughly.

In this regenerate
people find out of except.

I'm sure he just gonna have to
accept it the market will never go

to this magical point is
going to be very rough.

And you know this is where discretion will
come in you'll have to be reading nation.

You know will do some
of that together but.

For now just and the
standard thus why we use.

The mode as a descriptive statistics are
the most common rather than the average.

The average doesn't
make sense here.

It makes sense to look
at the most common body.

As the major focal point

that why school
the point of control.

But with a v why up

and we're going to do
whole section on view up

the it makes more
sense for US to look up.

The average as a.

Of descriptive
statistics because

what's happening with
the v what is the vive up his.

Is a volume weighted
average price in essentially.

Is developing throughout
the days of much more.

Accurate measure of what the.

I.

Saw

average price

achieved by the Mark
as through that they.

Less leave it there because
otherwise we're gonna

end up a way of topic and.

We all gonna come back to
the fiba but just understand the.

In the following example
when we calculate the

mean which everyone
has donned the average.

Is the thing the I
refer to the view up.

From one we're working out the.

The mode it's
basically that the pok

which is there

and standard
deviation is essentially.

Just

you know how.

Distributed these these values
are because if you think about it.

If a distribution is very

much more.

You know here the the values
are quite scrunched up though.

If you get for example

and.

Let's look at this.

The polities we are just about
to move on to next stage.

Poverty are needed to

go through what are these.

Would you agree.

That.

Here.

Look it's obvious why.

Can you see the
standard deviation here.

The range.

Going to be smaller
isn't it than this.

Okay.

Because.

The

and more spread out.

So I don't mean in
absolute terms I mean.

In saw of.

Number of points range

tissue or me.

So let's say this was

one

hundred and one pound dollar.

This is one hundred pips.

Plus going to be more like.

Twenty to thirty pips one of them's
making of these numbers by you

you see my point.

And they're still one standard deviation of
parks that you telling US the same thing.

Seventy percent of the data.

Seventy percent of the
data but it's just more.

Spread out.

That's why we use
this standard definition.

Because if we didn't it'd be very difficult
for US to compare this to this which will

be able to compare the.

That's why we used a normal
distribution because it has this.

A mathematical property

when you square the variances and then you
do the square root of the average of those

which are going gonna.

Do in a second together.

You can.

Compare them on a
standardized bases so.

Let's go on and do the and.

Then we're gonna pretty much

end up finishing off the
chapters of see on the next slide.

Okay traders are we
going to quick early.

Or as quickly as
possible look at.

A real life exam or and.

Which can try and understand

how do we to calculate mean.

Mode and standard deviation and.

For completion there
is this thing called

the media and you may
have heard of a again.

Well.

Over exaggerate how
complicated was really know.

Just a middle value.

We don't really use it is meaningless
the middle value doesn't tell US anything.

Because it doesn't
take into account walk

and.

You know the amount of
volume has taken place.

The median is a little bit like
using technical analysis is very

soft linear awaited there's no.

Waiting given I
talked about this in.

One of the previous sections you Nora
towards the end or I said the when the nine

thousand.

Nine hundred and ninety nine transactions
taking place are one price or can remember.

It almost like you're ignoring all of that
so we don't want to do that we do actually

want to do what.

We want to acknowledge
that this price.

Price one.

Is that many transactions Anna.

Price to say this one.

Who is that many
transactions right obviously

ludicrous for US just to.

You know not take that
into account whereas

obviously the mode and the moon.

Takes.

Volume at each
level into account.

In the sense that mode

we already know is just the
most frequently occurring.

And then we're going
to look at standard

deviation of the sandwich
gives US some sort of.

Standard measure of how spread.

The values of

and

and we can compare
the equally across.

The same types
of distribution so.

Let's crack corn and
looker so I got this day

of the Internet.

I am someone did a
survey already where they

took the height of thirty.

Third year old male

not big sambal been
look at the end of the

day to prove the the
point we don't be here.

With a thousand day appoint
srinagar achieve much

will be able to achieve the
same thing just by looking at.

The a day a points and

I highly recommend you
do this yourself go and find.

You know if you want

if you want.

Is he even help you
become a bear trader.

Probably not

as if ominous review
lacazette those of you without.

The mathematical background
are probably better off because

you gonna.

Not take this stuff
in the precise way.

Luckily have managed to detach
myself many years ago from it.

But obviously if you don't face the issue
you don't have to overcome I'm in the first

place

cake.

You know

if you can get this

you find but

you know if you one and you got some time
in your hands do it by all means nothing

wrong with.

And proved yourself that
so many things out there.

Have

a central

tendency.

So what do mean by that
again of said a few times but.

So what this chap deed the needs and
as he asked thirty people random males

and.

Was the height.

And this are the results.

So basically what I did is I
just played it myself in excel.

I can show you how to do this

if you see my coronavirus.

Analysis that I
did on Instagram.

And which really really strong
analysis were looked at the range

and you remember
the range of the market.

He had wall.

A central tendency
truly unbelievable how.

This.

Soft.

Bell-shaped in a distribution.

Is heavy were in life.

And.

And by the way.

He

can help but of baba naka

technical analysis.

And I'm going to buy back it up

I know people who says weiss
bashing it so much by a backyard.

Fibonacci

people use fibonacci is

the

is just.

Honestly a boggles my mind because do
you know that how fibonacci numbers were

created it was to

solve this problem of.

Trying to pin predict the exp financial
growth rate in the rabbit population okay.

Poison when he's just nonsense
people are using mathematics that was.

Observable

in the reproductive rate of rabbits and
trying to apply it to financial markets.

Is complete

nonsense okay.

If you actually even
took two three minutes.

To look at it

properly.

You'd see the.

Thus why I'm doing this.

Because.

It's important

we prove it to ourselves

and for you need
to do is observe.

Boost the actual market
doing is it following.

The same rate of reproductive
production of rubbish.

Rubbish.

I'm not saying that fibonacci golden
ratio shows and whatever don't appear.

In.

Nature

they do.

The financial markets
no nature is not.

You know is not

nature guys.

You know if one of the
reasons why we've got.

This coronavirus issue
going on is because.

We're doing things that don't conform
to nature right we're human beings were

emotional all.

We do all these
irrational things.

And normal distribution.

Takes the into account
in the sense that.

Yet there is a central pendency

but you get these.

Old occasions where we go
out we go out we have these.

Emotional periods on it.

You know and
those periods or less.

Than the ones
that are in the bulk.

Okay

to normal distribution.

You could just
observe a he follows.

The pattern okay

she could be very careful this is what I
mean when someone tells you use fibonacci

use this

that.

Stopped for a moment
are naturally think.

That you know.

War is that
mathematics based on.

Soon.

Is useful for its purpose

but no.

You know

normal distribution

and.

The

balancing type of tendency

to think of the word balance
what does it mean central tendency.

The the tendency of markets
is very very closely aligned to.

Normal distributions and.

Proofs in the pudding.

Every single financial
institution the world

is using normal
distribution to look at.

And

measures of description

of their.

Data their

profits there are.

In of the financial market
analysis and so on and so forth.

The don't get me wrong is not

there's no modern in the world
as hundred percent perfect and

I now have gone a little
bit of topic here by heaven

is important you
understand this.

The

at the end of the
Dane an ideal world.

Transactions would
have taken place here.

He are.

Here.

Here.

Here.

To show a mean and it
would be very smooth

as we saw in.

I.

Hear.

Why

this area here.

But

that's as close as you're
going to get look how close is.

Deceased bought the problem was with me
being a mathematician is our are found her to

accept.

Know it has to be exactly
the perfect is Diana.

You know

of come to told you that many years ago
because I realized he was holding me back so.

Time

and I'm you know I hope you don't mind
me constantly saying this point is because

I do on a per our ease
a lot of people who.

And.

Think and or know there's
this perception that all.

People in institutional.

Environments are all these
clever whiz kids and their.

That's what the different
Jane for honestly is not.

Cause can you see you never
gonna find the perfect model.

And.

People from those
backgrounds including myself.

Causes big problems when you
try to be very very precise just.

Just get the gist of it which
I'm going to show you now.

Do

but at least understand why we're even
looking at any institutions are looking at

this and not fibonacci

cause of maps make sense

we see everywhere.

Every as a central tendency.

Know everything but many things.

But financial markets do that
showed it was time and time again.

And we've got this wonderful thing called
a standard deviation which has these.

Beautiful mathematical
properties where we can compare.

Everything that
has the same shape

and say within.

Two standard deviation range

seventy percent of values

are gonna fall

seventy percent is
approximately the majority.

Two standard deviations ninety
five percent of anything in a fall so.

And.

Less crack on with this
example so with these height sry.

Are plotted them

myself said this is a table
I made myself in excel.

Luck I said if you want me to help you
to do this I can but obviously of yourself

doneness.

Them in the intro as you can see
our like talk a lot to his or her time to

of see do the xo
example with you.

And can you see.

Central tendency guys.

That majority of miles

thirty.

All.

You know run about one seventy
nine one eighty make sense you know.

In the high five feet
stroke six foot range.

And.

Can you see we've got
the same problem though.

Do.

We need to figure out.

Kind of weird as
the majority he.

Wears the value area

was the majority of data.

Where is the range within which

seventy percent of
males in the entire country.

An.

Excuse me are likely to fall.

How can we do the.

Standard deviation right so how
do we calculate standard deviation.

And the mean right we
want to know like this

rough number on average I
talked about the cricket scores

on average.

Where are they.

And and

that's what we'll do not gonna work out the
mean mode standard deviation mean is the

v wap.

Is the

pot.

Cry from the stand evasion
is the standard deviation okay

or the value area
I beg your pardon.

Failure

okay

so

sister monitor

value area.

Epoch v white will be somewhere in
here but we don't use on volume profile we

actually use it.

As a line and
obviously don't get

to worry about willing
to a whole section on the.

The Vera though.

Less actually going calculate these these
values okay so here we are of poor the from

that the data together
nicely and I know my head.

Covers the spot really I think want to
get rid of the so just please excuse me for

one moment was my
head covers his table but.

Essentially don't worry about is
exactly the same table that he saw here.

Okay

is just

just basically here's
the same table when.

Obviously you can see

the distribution is
exactly the same.

A cape and.

So wall often done is.

Basically have worked
out the mean the average.

Be no sweat.

Punish the it's like taking
two numbers one and two.

And saying was to me

savage

complex five

it's that simple.

And

what we're doing
know when you have.

Volume weighted average price

because I don't really want to cover
this in the vive up section of thus I've

mentioned here they
want to cover here.

What we're actually doing is.

Honestly it's very simple.

What you see was a simple average does is
and is the problem of technical analysis as

I said to you.

Previously where you had a think in
one of the sections where I showed.

Was it pound dollar I think one fifty
one thirty five one twenty may be a car

remember exactly and I said.

There were nine thousand nine
hundred ninety nine here all.

We may have been down here
call remember the basically.

Facts I think it was
near the bomb was in it.

I said that there were bulk of transactions
here but and those very little up here.

Is like just saying
well as one fifty and.

One twenty and let's
just take the average

of one fifty over one twenty.

At of she's going to
get what one thirty five.

Star citizen it.

Every transaction took
place at one twenty.

So we really into do you need to write on
one twenty plus one twenty plus one twenty

plus one twenty nine thousand
one hundred and nine are tight.

Plus one fifty

and then divided
by ten thousand.

The numbers going to be like
one point two zero zero zero.

And a very small

number close to
one to is waited.

By volume.

And gorshkov understand thus the
right way to do it why do I say that.

Improve it too.

So would you agree

this is the
distribution of heights.

Can you see one hundred and eighty
sending me as their which was obviously the

central value.

Look.

Hundred

and eight underneath

underneath.

Hundred and eight.

Hundred and eighty.

The way that technical
analysis will do as it will just say.

Or the averages one
hundred and eighty plus.

So just do one seventy four plus
one seventy five plus one seventy six

one plus plus plus
plus plus these.

Etc etc will come up to one eighty
just say plus one eighty plus one a

one plus one a to.

Be garbage right

the kind of the day we can see
one ease up on one two three.

Four five six to

to me

there's been more than
one occurrence of it.

What happens in
financial markets.

Cry if you've got

the price.

The market

is moving

to get one occurrence
at this price the

acoustic will.

Get loads of occurrences.

To remember

get lots of

market orders.

Can you see our ludicrous he is
was happening with technical analysis.

Is basically ignoring

this.

Is ignoring

this

and you're saying no.

Everybody to place once

let's just take the
simple made no.

He taking into account.

That there were more.

At one eighty

and that was less at one of
the face of fairway to do it right.

Even exponential you
see some of these mood.

Complete garbage twice the.

Supplying more waiting to the.

Front numbers wrong
who does not mean.

Anything.

Tell her was at me dessert.

Known be more transactions taking
place more recently than before.

Complete ludicrous we
don't you think about it

and sorry I know I get animated
is because it's important to me.

You know a warm
people to start to see.

How.

Misled

FBI

you know.

And it really.

Cheeses me off

that the industry.

Is making a fool of
US thus was doing.

What.

Snake Kim a fool of US I
mean come on this this stuff is.

The correct waited the with we have to
take into account the number of occurrences

and thus all I've done ok.

And.

He is so what the volume weighted
average price is doing is it will just say.

Or are hundred and
eighty times six plus one

a one times three
plus one or two times to

do you see what I mean
it's just taking into account

all you can write
them all down both.

Hundred thousand contracts in a day at
different market orders are all different

price you.

You can if you want.

Right down one hundred
thousand different prices and.

General of actually done this.

Not hundred thousand but you may have
noticed there's a see me recent period where

the volume profile resets.

At the start of the day.

At the hate taking
people's word for it.

So I've actually
done this a few times

and.

Many years ago is

a

are calculated myself.

When the it had gone to like five
minutes ten minutes in there a few hundred.

Manageable.

I took the depth of mall can I actually
wrote down every single price and everything

rule number of contracts

and are divided it by the number

to prove to myself that Vera up.

All it's doing is instead of this being
heights of adults is the market price.

And then I looked
at the occurrences

voice this

to member on your.

Volume profile used to have
that number where he will tell you.

Ten thousand eight hundred
and two ninety six contracts.

Between mrs same fingers.

Ten thousand eight hundred
and twenty six contract.

To remember what
I mean this thing.

That look.

This is a frequency
distribution.

That is what this is.

So amazing isn't it is
exactly the same thing.

Okay.

So identical

that all we're doing.

Is we're just taking.

The weighted average and
that all the v wipe his okay.

So obviously I'm not gonna sit there and
I'm not going to add all these up and divide

by though he bought him

you can do it if you one.

Is basically hundred and
seventy nine point for so.

Can you see basically the

the mean.

A slightly different to.

The mode.

The fee poc is one
eighty can you see the.

Swan eighty

and what you find it or not
look or down going to get to.

Because again is
not really relevant.

Ba.

You know

obviously I'm quite
familiar with this because

I studied statistics
to a very high level

and but you don't need to honestly you
don't need to to even know what I'm about to

tell you.

You can probably do a bit of googling if
you want in your spare time again I'm not

here to.

Give anyone a statistics class
cause I really don't think is relevant

and ba

if this is slightly
skewed to this side

there will be
differences between.

Of obviously the most commonly occurring
and the mean because of she the means going

to be skewed.

By

more recurrence is taking place

on one side then the
Alpha there will be.

Excuse me slight
differences between.

The mode

and then the offing that's my body
trawler to me the have probably been.

Talking way too much and

on probably sending everyone.

Of into non concentrations one now
so try and be as quick as possible but.

And.

Yeah essentially.

That is the

v wap

is the weighted
average obviously here.

With heights.

Is nice because if you government
like I said says you look gone find out the

approximate height
of thirty he wrote.

You can say to the general.

Sir about hundred and
seventy nine point for.

Right.

You could say to them
is one hundred and eighty

in this particular circumstance
may be a better measure.

Is the weighted average.

But like I said in
volume profile.

For the reasons mentioned
in the previous page.

The market technicians anyway

but technicians bar in
the market profilers or

volume profile technicians do
like to and banks and institutions.

They do like to look at the v pok because
at the end of that they thus where the most

transactions took place so.

Makes more sense from a
financial markets perspective ball.

There's no royal romance and luck US at you
as long as you're roughly in the ballpark

that Kate.

And then we look at the
standard deviation okay so.

I'm not actually gonna sit here
and do the calculation with you.

But if you get a chance a
highly recommend you do it.

I.

Was basically the
standard deviation dossiers.

Honestly is not complicated.

It's a measure of.

Deviation.

How much does something
deviate from more.

The central valley to me

okay.

So we already said that the mean was
what hundred and seventy nine put for.

Remember the previous example
where I gave you with a thing five.

Eight and two

and five.

Six and four

and obviously the

six five six for had
a very small spread.

How do we measure this

would all we're doing is.

A light come.

And honestly can't remember exactly but
forgive me if I got a slight your own but I

think it was this
was a five eight and.

Two.

Can you see we just the mean
is five the mean is five here.

Would you agree.

Can you see it varies by one.

Here.

This varies by.

Three

this varies by one.

Spread out.

This is more spread out

right.

The problem is right

and attorney if you've

ever done any saw a basic statistics
before again if you haven't please.

Don't think I'm saying you need
to honestly don't worry about it.

You can get yourself up speed
pretty quickly and if you want to.

There's really no that typical
odd highly suggest you try it.

Is what you can do
is you can say look.

In this example
either side it's one.

The difference between the
mean for five and six is five.

And how much does do the
three values deviate from.

The average five with
it's one either side.

You see the
problem of doing that.

When you're doing
this for values

because we see it here ripe.

We can say okay.

In the first observation.

To hundred and
eighty five it was

he was quite fair distance.

Squire fair distance was quite fair
distance so that was a small distance.

Observation for was this

she just come preparing each in

in the same way of comparing
four to five and sixty five.

Just more values docile
we just comparing this.

Mcc

deviate from my average valley.

Because in an ideal
world everything would be.

Here

but it's not easy we know
financial markets to walk.

This

he see what they're doing.

Exactly what height Sidney.

They tend to vary a little bit.

And you see here of your
the distribution which is this.

And is he look like that.

She's the same thing ice.

Amazing isn't it the height.

Of thirty year old males

follows.

A balancing

financial market.

Okay.

And have shown in jury of privilege to
him you can prove it you saw quite easy

but you want to look at how def

dispersed of these.

To come back to this example
she poor of the problem is.

If you look at the
mean right here.

If you do six minus five

would you get

one.

If you do for minus
five would you get.

Minus one.

Was minus one plus one.

Zero.

What you'll find is.

If you you can do this yourself
a highly recommended two.

Hundred and five minus one said.

One seventy some.

Bitches what you're all you're
doing is thus one eighty five.

Minus one seventy nine put for.

You're comparing
the distance their

distance here.

If you added all
these distances op.

He's going to equal Sarah

okay.

Because

they all equidistant

on they they're all equidistant in
terms of dust whole point of the average.

And if you look here

was the difference here.

Eight minus five is three.

And you could to hear but thus more
than one hang on a minute we're about to.

To months five as minus three.

Was minus three plus three

zero.

Can see you call compare
zero zero to make sense.

So to overcome this what mathematicians
have done as they square these values and.

On moving to do this for every
single one by essentially what they've.

They do is.

They just multiply.

That the number
by each other so.

I.

Fear not familiar with the all you're
doing is you're saying one times one

is.

One

her minus one time
minus one is one so.

He actually becomes a positive
number when you add them up.

I'm going to do it for every single
one by essentially will you're doing is.

And.

You just square ring.

Each one of these deviations.

Right how much does the actual deviate
from the meat thus what's called a standard

deviation.

And actually walked mathematicians founders
if they take the square root of that.

It fits.

Perfectly.

Into.

A distribution were.

That number that you get
when you square root it.

Is called a standard deviation.

And it encompasses.

Sixty eight percent.

Y.

While thus why.

We just.

Pointless we don't
need to get into all of this.

There is a
mathematical reason by.

When you take.

The square

of

every variance and do this the.

Square root of it.

You come up with this number
called the standard deviation

to standard deviation

and

every single distribution.

That follows.

A frequency distribution
that follows this.

Soon on with distribution shape.

That standard deviation value.

Sixty eight per cent of

all your values will.

Always for within.

A standard
deviation either side.

Okay.

So.

Let me bring this
to lived for you.

So what I did is.

A did the square right so I took I
did one eighty five mind is wandering

the before one seventy seven months
once her not for one a team on US.

Blah blah blah if you do the
sum of all of these though number

you're going to get zero.

So I squared the

and then I took the square root.

Okay

and what I came up
with was a where is it.

So took the average variation

which I talked about ready.

Then.

And.

What did I do me some of the
square them set up the square root

okay

and the standard
deviation was two point six.

Turquoise guys let me
bring this life to life you

all he saying.

Is the standard deviation.

Right the

average deviation.

Is two point six centimeters.

So what is doing is it
same this value here.

Okay.

One

stand as the.

Symbol for sc a
standard deviation.

Is just saying that that.

Is two point six centimeters.

So what does at me

to do you remember he
said one standard deviation

all saying is if I add
two point six two.

The me

one.

Seventy nine point for
which is what one a to.

So can you see luck.

Hundred eighty two and look I drew it by
hand and an almost got the answer this is

why say.

Please don't get bogged down
in muffs honestly you're gonna.

Do I.

Just doing yourself no favors

pretty much got it

by I.

Locate

but I just wanted to show you
that this is what institutions at doing.

Because they get a machine to
be a little bit more precise and.

Truly sorry for them

and then what they

what you do is so

one standard deviation is.

Two point six centimeters

that way.

And.

We just do the same
the other side so.

We do one seventy nine point for
minus two is one seventy seven point four

and then you've got one
seventy six point a is in is so.

One seventy six
point a and days.

So I was almost rights it some
where in that region there.

To wasn't that far off.

Okay

so

all this is telling US.

This there's a seventy
percent chance.

Okay.

That male

heights.

Will fall built between just below one
seventy seven and of as he won eighty two

okay.

Now I know some guy is
watching is probably done

statistics to a very high level one say
have gone should have done in minus one

because it's a sample.

And.

And is not the whole population or
don't again taller or recognize that kaiba.

Listen winner

you know.

We're trading human emotions
here as we've seen the.

Doesn't matter

though I just want
acknowledge that.

As a side note to anyone who's
done statistics I know they're gonna.

Think that and

look I'm aware of the
okay but less some.

Not

get into that because
honestly defeats it just one

is irrelevant

and it doesn't.

Really matter the point is that.

In financial markets

and.

When we're looking at value areas especially
in a historical basis we are looking at

the whole population because.

We're both looking at
every single market order.

To has taken place okay.

So what's happening
basically is called the market

and.

Is doing and in fact I'll come
back to the same wanting to we are.

We're almost done now.

Is our wanna show you something.

On the neck slight that.

The standard deviation is incredibly useful
for the following reason to let's just go

to the next slide okay so what
I've done here is and honestly one.

I

mean I get what he worried about being
all my god was going on here honestly ish.

It is very very simple all
I've done is have taken this.

Of scrunched up a little
bear and have taken this data.

Showed the day a you see here

and this

is basic clearly

this.

Okay

to remember where it was one eighty a month
this is what we've just been looking at.

Of just

basically scale there

so I can compare it.

To the exact same
experiment done

whether valleys will
much more spread out.

Can you see

here.

Could you agree
compared to the mean.

Look it's almost like her.

Financial market I was
balancing in a very small range.

Okay.

That's what we've just been
looking at male heights.

They imagine you had a market

was much more spread out.

It transacted up much wider
values are more frequently.

Can see gonna
have a wider range.

Right.

This is wider
than that isn't it.

Right

and we said what standard
deviation with two point six.

Centimeters.

To remember in the previous example of just
been looking at just rewind day if you if

you don't remember.

And

and therefore.

Would it be saved we're
serious about wanting to then we.

Tumblr I just did that one
seventy nine point four plus to

sakes and obviously this was
just below one seventy eight.

Right have one standard
deviation one standard deviation.

Would you agree

that the standard
deviation therefore.

You don't even need to
know one standard deviation is

on any measure of spread.

Look at this.

Would you agree

this is more spread out

than this

right very thin.

Obviously

a measure

of spread

has to be bigger.

Or look.

When I did the same calculation
cause I can send you this data.

We can do it together if you warn if you
really interested of more than happy to do

that with someone.

Will you can work this out for
yourself or can send you the data.

And.

And in fact this is that they are
for the I believe this is the data for.

The me more
spread out know isn't

he is and other heavy hairball
consented to if you want.

All of Danny's of
tissue slimy more.

Spread out data

the corporate

I worked out the
standard deviation

from a taboo.

You see the.

So five point once lint

can you see the mean
is almost identical.

To remember in the
example where I had five.

And then we had to.

We had eight and then I had five

and then we at four and six

will have the means the same

someone says was the average.

Bright

and.

Is like in the cricket example if
someone if a team has three matches

and they scored to
have hundred runs

they score three hundred rounds
in the score one hundred rounds

one average the
school two hundred.

The with another team scored
one hundred and fifty runs.

Two hundred runs and
two hundred fifty runs.

Is to two hundred.

But you see it was it
was less spread out.

The volatility the variability.

Was a lot less in
the second example.

The I

we're measuring
here can you see.

By comparing the variability the deviations
in the way that I showed in the previous

example.

Do with this dataset ago
standard deviation of five point one

who does that mean.

We're doing is we just add.

One standard deviation this way

and we had one standard
deviation this way.

And you get five point one

from the mean.

Of let's just round up and say you
know it's about one eighty if you add five.

We're getting about one
a five as the valuer a high.

From one eighty minus five
his voice about one seventy five.

Steph.

And look here.

Can you see.

This is your value area.

For this data and look
how thinness value areas.

Compared to that.

Can you see it.

Makes sense right
because look at this range.

Smaller.

From this is wider.

Because of this
mathematical public.

Properties.

Which you don't need
to worry about but

can you see why they use them.

Because now we can compare this.

To this

and hope this find the
make sense cause I know

nobody can understand why
to explain it in this way slowly.

War you're saying is.

Seventy percent of the data
are the seventy percent chance.

In this distribution.

That and.

Values will fall within.

And.

Basically wherever it was
was at one by one a he five.

Price and one of
her seventy five.

How do we compare the but we want to see
where the seventy percent we can say here.

The seventy percent
probability the actually.

The same things going to happen but this
time in a small arrange has about one a two.

And just below one seventy eight

can you can compare them know.

I can compare them.

Do you now see what's going on.

Here

and why we use
standard deviations.

Because.

I'm going to leave the here because I
want you to see these two a comparable.

Or can now say hang on.

Thus one standard deviation.

Get her to this
little bit of in care.

This is.

Potentially arm-in-arm in Korea upon me
but the computer zero calculate is for you.

Value very high value

load.

Below are a.

Your your low

shocking stotts
compare them now.

Because I can say
that seventy percent.

The seventy percent.

Thus the v pok.

List of epoch.

The the mean I don't care
about pub the v wap a do care.

And and

we also care about standard
deviation and that is what

the bands will be.

Is just the standard
deviation but.

He no luck I said professional firms in
I'm going to explain this to a hope it was.

Helpful

to explain this to you if
you don't get a honestly.

Reach out to me I
love this stuff of train.

And explain it a different way of going
Google have a look at basic standard

deviation examples
if you really.

Want to get

but honestly really not gonna make a
difference as long as you can accept.

That.

Within a standard
deviation range.

Thus your value area and
gonna get sixty eight percent

and then.

When it comes to v
what you see we also look

at the second standard
deviation of days.

And ninety five percent.

Cause what it helps is it helps.

Obviously.

Institutions to see
are when are we.

Extremes are we are extremes.

Has the market.

Moved.

To where

you know

there's less than a five
percent chance that we're gonna.

Enter the so.

She can see probably wise.

Nor Greg back.

Were more likely
ninety five percent.

To do was.

Move into solve this
story this region here.

Perimeter truthful.

Ninety five percent chance.

That we're going to actually stay within
this region so if we start to go to extremes

see me trade this or to type.

Right would you see me
do when there's early of

the profile bump.

And I take it out

the

take it return back
watching them Dana

value areas.

Okay.

That's why I'm looking at

both the volume profile.

Appearance of you
Scott to the stage where

even I and approve it
two proofs in the pudding.

Do you see me Mark the value areas or
mobile very powerful not a more camp.

Prefer to visualize that because

of this theme.

Though keep

saying a nice.

The mathematics is too

precise

for something that is
imprecise I don't look up.

As long as it's

rough.

Is helpful to me I can just see it
because Sierra will throw it on and.

Other market.

Professionals I know they're
going to be looking at it.

But can you see
the problem already.

That's not a perfect.

Moment distribution
because look.

At daily one as
he values in death.

Here.

Of want to see
values they're here.

Till of accepted the

you know life's not perfect

I can't say to people

oh.

Do me a favor German transacting here
some or profile can be exact so I can draw.

Precise value snow
how mawkish work.

The imprecise so.

This

go to be some sort of.

Leeway given

to these.

File you areas.

Okay

now.

I'm going to be up from of you and
this is also going to give you some relief

those of you that gang a bit

too.

Worried about the maps
the have been talking about.

Cause what i'm
going to dubious right.

At first

I want you to look our value areas
but I'm going to be honest review.

I've recognized this problem.

Thy face daily my career
where I was very technical one.

Was a mathematician a nice to be
so obsessed with these value areas.

Have you noticed how
don't even have them on

I don't actually the true
them on my volume profiles.

I use them on market profile.

And.

I'm gonna come to that

when I

show you market profile because

what I'm doing is it with
market profile is I like to emerge.

So I can put this.

Area into here

and can you see him makes it.

It round to out.

And it helps me draw
nice smooth profiles.

That I like to look at
standard deviation because.

In the normal distribution
sense because it forms.

Nice smooth
distributions like this

and look I know for some of your lowest
you belong this is way over my head

may be among the
baby all of you get it.

Off some of you may not.

Honestly don't worry
keep practicing it will come

he will come.

Can expect to get

you know something
like this overnight.

Do.

You know it the have
never seen a up for anyone

takes time.

Take your time have
a go back watch year.

And.

A think unless I'm mistaken
that pretty much everything.

We've covered.

Thou wanted to cover.

And

Pierre or hope that was
help forward now shown you.

You know on.

The

re cupcakes my as well
taken so long anyway.

What was shown you have.

Shown you that.

How we measure this.

Is looking at the

average deviation
of every single value

to the mean.

From.

Of shown you shall surely what the standard
deviation is have shown you what the.

Bonnie point of control is hand.

I'm

sure he bought.

Of just realized one thing

and.

All eases fry

a have to say this because.

Technically.

Someone could pick
me up on this and

they're going to be right.

And unfortunately is going to confuse you
slightly but honestly he is not going to

make a difference.

So what is is when v
what is calculated bouquet.

And this will become more clear

longer to go over this again when we look
at view up in the standard deviation bands.

V web is just a measure of what
the volume weighted average prices.

When you see standard
deviation bands.

And on the Wii up

what they're doing is they're
doing exactly what we see here.

They calculate the average.

Deviation and then doing the whole squaring
and square room process to come up with.

One standard deviation

as it soft measure
of dispersion.

And das what forms the burned

why as the market's
going like this.

You get these little
value areas here

or loveseat thus two
standard deviations.

What the volume
profile dons and.

You know there's no
particular reason for

is just.

The ways been done
for a very long time.

Is.

Robyn and looking up.

This mean.

Sachi looking at.

The mode.

So the most
frequently occurring so

of.

This basically.

Say you see the mean is
one seventy nine point for.

Which actually isn't one
eighty is more like they're.

More volume profile as is

able to take.

The mode

and then it will just
keep going out from till it

spreads out seventy percents.

Because sixty eight

there's actually a setting in the volume
profile we can change it but the default is.

I think sixty eight

everyone uses seventy
are you seven he.

Was like I said.

She even on not being
presented as matter.

Sokoto makes this next point redundant i'm
only putting the in cause I know someone.

Under a within the
right to to do so they're

going to hang on envy
is in volume profile.

Done by calculating the
average deviation from.

The.

Mode

the point of control.

And.

Debbie be right so.

I'm just going to put the
in here that basically war

and.

Fourteen profile does.

He is and is called volume.

Value.

Area and

voice doing is is basically going through
the same process but rather than using.

One seventy nine
point for duty war.

Is she really is not going
to make a big difference

generally

in most.

Balanced profile shapes I'm gonna make any
difference but technically that's what is

doing.

And the v wap.

Is actually using the mean.

The variance.

Basically how much
do all the actual values.

Vary from the mean.

For the viva up and how
much the actual values vary

from the mood.

Okay.

For the.

Volume profile

that we see.

Said there is a
slight difference.

There's no right or wrong way of doing
it thus woman and sit here and justify it.

Doesn't matter honestly asleep.

You're going to realize this
as your career progresses.

The best traders in the world.

Look at this and
realize it for what it is.

Is perfect mathematics
trying to fit.

To US slightly imperfect market so you
know if you if you're off slightly here and

they're.

Going to make no difference.

Going to be a
better a traitor for it.

That's why actually say
and a genuinely meant it.

People who've never
done this before.

There are actually better off.

Because for me took
me a couple of years

to get it through my head.

That you know what in the

and.

Just.

Just

it worked pretty
well in real life.

By it doesn't work and.

Precisely

and this

is the final thing
I'm going to say.

That I'm going to
say because is true.

You

are moving to hold things back from you just
because we've been talking for two hours

and I'm thinking oh what on

leave that piece of information of has
taken me to do not I'm gonna tell you.

Because it's the truth.

And do.

That is

the final put 'em

me.

The reason why I wouldn't be too concerned
about you know the maps is because.

Louise this profile right is
fairly balanced on this day.

Look what's happened here.

She you've got balance here.

But you've actually got
different balance here.

So what probably happened
probably are done of her son bought.

And.

External marked the open or
close are opening profile but.

What

probably happened is the market

either opened here and
it was in the balance right.

Let something happened.

Maybe data or something
and it became in

and then a

balanced here.

As opposed to
here were balanced.

What happens is your software.

And.

It's not practical for you to keep
dropping ingenious actually here workout.

Standard deviation
he has done it know.

What your software is going
to do is is going to work and

every single institutional.

Platform algorithm whatever

when they're looking at

value areas.

He's gonna work out the
value area for the and tie a day.

To see the problem

is going to work
out the value area.

The entire day.

And give you these two.

Regions and.

You see over time.

Of recognize that.

This is nonsense.

In this type of distribution.

What does that
mean this value area.

The mean anything.

Because it's to
distribution tear.

The so much data
missing here that didn't

transact here we don't
have that problem so much

here we don't have that problem.

Here we've got the
same problem look.

Does she want I just I got rid of the
basically I'm going to be honest with you.

And have been very clear of said I'll tell
you what professional firms that doing.

While undoing slightly
differently sub to you.

This article give you the ones as I can take
your ninety four percent of the way that

can you see the.

The other five percent

you need to work I
was comfortable for you.

I can tell you on doing

by don't want you to do what
I'm doing just because I'm done.

I'm doing this visit to me from

years of observation I thought.

Logically

that make sense to me why
would I take a normal distribution.

Value area

but this.

Doesn't look like this.

Here it does

this day was balanced.

What happened here
would probably open like this

when imbalanced and
then we settled into a rank.

That's not the same as.

What.

If we do that assumes we had

we didn't do that

you didn't do that this day.

To see thus the limitations
and thus the problem of looking.

I think too much from the
precise mathematical lens.

Guys are to you right now.

Trading in the vanilla essence not the
option structure products or talked about.

He is

is an art is not science
he gotta be able to do.

Look at things.

From

a different perspective a different
angle then algorithm can't do.

And say to yourself do you know what
I'm gonna make a judgment call here.

That make sense to me.

He'll.

Probably the value
areas more like that

then we've got
a small one their.

Okay.

And then here.

You may be thus okay okay
maybe it's not I don't know.

To see more the guy sitting
next to me in a trading floor.

In a professional
environment he might decide.

Thus value and thus value or
as I might decide you know off.

And okay.

And this is where we come to wear
discretion sometimes has to be applied and.

Across different obviously time horizons
you could see that it can get quite.

Complicated so

look we've done enough.

A thing and will obviously revisit this
again and again and again about value areas

and there'll be
things I mention.

And to you just to
hammer this humble.

Hotel shrew to use for
you know understandable

value areas are boiling
point your control.

And how we measure.

Fair value

and what we gonna do is.

A belief don't quote me on the examiner
she'd built the section yep I think we're now

going to start to.

What was he will move away from
the theory and we're going to look her.

And.

Either market profile of volume profile one
of the profiles and we're going to start

developing.

And contextual level surround
and that we can try trade-off.

And we're going to
really start looking at.

Excuse me these value areas as.

Areas that we can
actually take traits from so.

You know is the
market balanced here.

And we see

and.

Social trading opportunities to get back
into balance which you saw me do an adapter

market all.

Is the market going imbalanced

and now you see with defined.

What the value area hiace.

We're leaving the venue area.

The market.

Obviously won't do in a
straight line let's be honest.

We're kidding ourselves
if that's what we think.

You will obviously doing in

in.

Not very jacket manner

but do than that he might
start to build some value air.

And

she the volume

profile bill which is why I do an
in-depth market cause when you see.

Plus he is on the
decalogue is building value.

White built and

the here both

the days value area.

When we can start
to think about taking.

Long positions

into an imbalance trade.

Or.

Could come back in we start to built-in
value before below the valuer harm.

She's not

learn let's take her.

Mean reversion trade.

Okay

so going to start to build
some of these contextual levels

and the nominal really help
you put together and develop.

Some edge.

Which

be know the solve things I was shown in a
professional environment in fact the exact

same things and better.

And then you can use that.

Obviously.

Towards the as the pro
course comes to the conclusion

and.

And how you can develop.

Trading strategies either using
what I show you and then making

of

are the ideal thing as you'd make slight
tweaks based on your observation so.

Yeah look forward
to next section

I wanted to put the answer you know that
some good stuff to look forward to or know

this was long

but I hope you can see I needed to get this
theory out the way really really important.

And thy was put somewhere
in the poor sander.

Yeah

maybe to again take
a little bit of a break.

Cause.

You know

there's only so much more voice can
pop with without needing a breaks her

and

finally when we appreciate you letting
you put the beer about my dog at the stars

well and.

Really wanted to.

Or say.

A dim want that to affect
the quality thought put into.

This section on any going
forward so if anything.

In our really gone all out
on the section because.

I want people to Rudy.

A understand.

The a genuine wanna I said don't worry
about it if you don't have a mathematical

background of really tried to
be honest with you and say.

Genuinely you are an
advantage as long as you can.

Generally get

warm saying when I talk about
deviation as in spread average spread.

Of she the mean

and mode.

Soon you can get that.

Generally the gist of it.

Your much further ahead.

Than someone like me.

Who used to be
so pedantic about.

Nope.

Is thirty four point one percents
than deviation it has to be this level.

And literally the market gave my backside
a kicking so many times until I got it.

Or I

gonna give this thing a

flex

and you have said the same
things over and over again

have a great day

and of see you
in the next section.