Hey everyone, this is Kirk, here again at
optionalpha.com, where we show you how to
make smarter trades.
And today, we've got an awesome video tutorial
for you: Breaking down trading math, and specifically,
options trading math.
And it's basically a 101 course on why we
have the methodologies that we do about the
markets and about trading.
So, welcome back to statistics class.
And you're probably thinking, "Oh.."
But don't worry.
Undoubtedly, more important than understanding
the Black Scholes model for pricing which
we purposely don't cover in any video tutorial
that we have because it's pointless to cover,
you don't need to know it to be successful.
But besides that, your ability to understand
just basic statistics and probabilities is
paramount to your ability to be successful
in this business.
So, if you don't get the math behind the trades,
here's my promise to you: You will fail at
trading options long-term if you don't understand
the math behind it, and more importantly,
the statistics and the probabilities behind
it.
You can make a couple of trades here and there
and be successful.
But to do this long-term, to generate consistent
monthly income long-term, you've got to understand
the math.
So, swallow your pride, head back to school
with us as we talk in depth about standard
deviations, probabilities, and statistics
in this advanced tutorial.
But before we do that, let's first have a
talk about one real quick thing, and that's
market efficiency.
So, this whole idea about market efficiency
is really important, and you probably heard
us talk about it in the other videos that
we have to trade liquid products and liquid
underlying stocks.
But this whole idea of market efficiency is
this concept that the markets are super-efficient,
and especially in the US markets where there
are millions and millions of different market
participants, all with their own individual
ideas.
The markets are incredibly efficient and incredibly
fast.
Data or information that anybody receives
on a stock or a company is immediately priced
into the market.
And as a guy who's been on both sides of the
Chinese wall, basically, I was an M&A analyst
in New York for Deutsche Bank, and so, I was
on the private side, dealing with mergers
and acquisitions.
And then, I was on the other side of the Chinese
wall in Tysons in DC and dealing with the
retail side as an analyst.
So, I've been on both sides of the wall, and
I can definitely tell you, the markets are
incredibly efficient.
There's no edge that you can get a knowing
information about a company in advance or
having some sort of insider knowledge.
In most cases, most CEO's have no clue where
their stock is going to go or how it's going
to react to the market, regardless of how
well they think they might be doing.
So, to that end, we have to understand that.
As we said before, we have no clue where a
stock is going to go.
And nobody else does either.
Myself included, I have no idea where a stock
is going to go in the future.
I might have an assumption, an opinion.
But at the end of the day, we're all no better
than 50/50 on our guesses.
So, what this leads to then is to this probability
distribution.
And what we call a normal distribution or
you probably have seen before as a bell curve.
Now, this is really important because this
is how distributed, or this is how a efficient
market distributes its returns.
So, basically, what you have here is you have
most of the returns are probably somewhere
around even or par.
And that's basically what this kind of zero
line here is.
But it's saying that most of the time, the
distribution of returns will be within a certain
confidence range or within about one standard
deviation.
This is what this one standard deviation is
that I'm kind of highlighting here on the
chart.
So, this is saying that 34.1% of the time
up, and 34.1% of the time down, we might see
this confidence within this given range.
And we can define that range in stocks, in
every particular stock that we look at.
And we'll show that to you later on here.
But you just have to understand that when
a market has normal movements and an efficient
movement, it's going to have a normal distribution
of returns.
Now, this means that most stocks are going
to kind of land inside of that normal distribution.
Sure, you're going to have the stocks that
go outside of that distribution, so they make
a three standard deviation move, so whatever
most stocks are doing, they do three times
that move.
These are going to be stocks that are really
high flyers, right?
The one in a million stock that goes from
$5 to $500 or whatever the case is.
And then of course, you're also going to have
stocks that make a three standard deviation
move to the downside.
So, these are going to be your stocks that
go from $100 down to $10.
It's the one in a million chance that the
stock goes bankrupt or the company goes bankrupt,
whatever the case is.
Remember, this is a normal efficient market,
so most of the time, stocks are going to return
some sort of normal average in the middle.
And that bulk average here is what we're working
for when we start to place trades, just understanding
that this is how a stock is distributed.
Now, when we look at the same graph and kind
of tilt it on its side here, we can see that
this same concept applies to a stock distribution
of its price movement over time.
So, I'll say that again.
The same distribution will apply to a particular
stock's price movement, going forward in the
future.
So, what I always like to do is I always like
to say, "Okay, at certain points in the future.."
And let's just draw a line down here and say,
"Okay, at this point in the future versus
this point in the future, we can estimate
based on the entire trading history of the
stock going back in time, how likely the stock
is to rally or fall within a given range."
Again, we can use the data from the stock
going back all the way to its beginning, as
much data as we have on that stock, to automatically
and accurately calculate how far the stock
is likely to move in a given range by a certain
date.
So, in this case, if we're looking at this
stock which is just the S&P at some point
in the future that we've taken this chart,
then you can see that by the time that we
reached this date or this line here, this
expiration date, as a stock is trading, it
might end up trading somewhere in this range,
okay?
And that's a good likelihood of happening
because the stock doesn't have that much time.
And so, based on its entire trading history,
it's not likely to make a move all the way
up here or all the way down here, given such
a short time period.
So, we know we can calculate that.
As we go further out in time, the stock is
likely to make more of a volatile move.
So, it's as more time here - And so, you can
see it can widen out its breath of movement.
And again, that's true because as you can
see, going forward here on the S&P, the longer
we went in timeframe, the more the stock could
move over time.
And so, that happens here too.
And again, just continuing now into the future,
you can see the stock can then really move
as we start to go further and further out
on the expiration cycle.
So, this same type of distribution can then
be applied to where the stock moves over time.
Now, most of the time, the stock is going
to move with the inside of this one standard
deviation movement.
And this one standard deviation movement is
about 68% of the time.
Now, we can exactly calculate this probability
inside of most broker platforms.
So, I'm going to show you how we do it at
the end of this video.
But again, just trust me that this one standard
deviation move is about 68% of the time.
And so, it's really, really helpful to understand
where a stock might move 68% of the time because
then, we can build a strategy around that
movement or take advantage of that possible
movement, and this is how we get to high probability
trading.
Now, as we go forward, let's first do a quick
review of volatility because all of this normal
distribution and stock distribution stuff
has a hinge, and that hinge is a volatility,
and volatility in option pricing.
So, let's take two stocks in this example.
Both stock start out at the same price which
is $100.
So, in this case, stock A is the stock that's
in black on this chart.
And you can see it has very little volatility
which means that it moves more or less right
around $100, give or take maybe $5 or $10
in the opposite direction.
So, it's moving very, very slowly around $100.
It has low volatility.
The frequency and the magnitude of its moves
are very small.
Compare that to stock B which is going to
be the stock that's in blue.
You can see they both start out and end at
the same price, but stock B has much higher
and much more volatile moves in its price
as it gets to that average of $100.
So, you can say that stock B which is again,
the one here in the blue, has higher implied
volatility than stock A. Again, stock A which
is the one here in black, lower implied volatility,
still the same stock, still around $100.
It's just the level of movement or the frequency
of movement that that stock makes.
Now, this drives us to our next topic which
is Implied Volatility.
Now, implied volatility is basically an expectation
of where the stock might move in the future.
And depending on how volatile or not a stock
is, that will cause option pricing to increase
or decrease as a result to compensate for
that implied volatility.
So, we take our normal distribution graph
which is really the one here in blue.
This is that one from one of the other screens.
So, again, just a normal distribution or kind
of average volatility in the market.
You might see the stock have a range of between
here and here, right?
So, the two extremes with again, something
around the median or the mean as far as its
distribution going out into the future.
Now, if implied volatility for that stock
is a lot lower - So, remember option A or
stock A from the slide before?
That black line that was kind of hovering
around $100?
If implied volatility is a lot lower, then
that creates this distribution graph to get
taller and skinnier, and that's this red graph
here.
And so, you can see that it still has a normal
distribution, but it's much more centered
on the stock making very small movements out
into the future.
So, instead of movements all the way out here,
now the extreme movements or the kind of three
standard deviation moves are much, much closer
to the mean of the stock.
Again, our standard deviations have moved
in from a further out area.
So, the implied volatility in the stock is
lower, and that means that the likely range
of the stock going forward is going to be
much smaller.
It's not going to have the greatest magnitude
of movement.
Now, if we have a stock that has implied volatility
that's extremely high.
So, it's making a lot of jagged and very quick
moves like that stock we looked at in the
slide before, that blue line.
It's all over the place, still centered around
$100, but all over the place.
And what that does is that slams down this
distribution graph and it makes it much shorter
and fatter.
And so, this distribution graph looks like
this.
It's much more distributed this way.
It's very flat, very wide graph.
And you can see because it's very volatile,
the stock can rally really high.
It can go that high or it can go that low.
Now, most of it is going to be around some
sort of average or mean, but you'll notice
that the average and mean has expanded.
And now, 68% of the time, it trades within
this range which is all the way out towards
the end of its shading.
So, 68% of the time in high implied volatility,
the range of the stock is much lower.
Compare this with 68% of the time when implied
volatility is low.
It's going to have a much shorter or narrow
window to trade within.
So, you can see now that implied volatility
is a critical ingredient to your ability to
be successful.
But it's also this understanding of how implied
volatility shapes and molds this distribution
graph that we used.
So, as implied volatility increases or what's
commonly called "Vega" in option pricing,
an options price will increase as well to
compensate for the higher probability of being
in the money at expiration.
Remember, as a stock starts to make more frequent
moves, that options price is going to increase
because now, these options at the further
extreme have an opportunity to be in the money
at expiration.
And the options down below also have a further
chance of being in the money at expiration
because the stock is making huge, huge moves
in either direction.
Now, this is why we specifically suggest that
you sell options when implied volatility is
high, because option pricing is going to be
very much expensive and rich and swollen because
of implied volatility.
And this is also why we suggest that you buy
options generally when implied volatility
is low.
And that's because option prices are generally
going to be really low and have the propensity
maybe to increase in the future.
Now, with all of this hard data behind both
volatility and possible ranges in the stock,
we can actually build option strategies that
target any probability of success we want.
And this is really the key ingredient here.
It's that with the options, you have the ability
to target any possible win rate that you want.
If you're trading stocks, your win rate is
50/50.
You have a 50% chance that the stock goes
up.
You have a 50% chance that the stock goes
down.
But with options, we have the awesome ability
to target any probability of success that
we want.
So, let's look at a really specific example
here.
This is a trade tab of SPY which is the S&P
500 index.
And currently, SPY is trading right at 20423.
Now, in the next month, (these are the February
contracts, the next month out is February
contracts which are 29 days out) you can see
that we are in a position right now where
we're selling a spread or selling options
above the market at the 208 strike price.
So again, the stock is trading at 204 and
were trading options all the way out at 208.
Based on all the trading history of SPY at
this point and all of the volatility in SPY
at this point, the probability of our option
being in the money at expiration - Again,
using that distribution graph that we looked
at a couple sides ago.
The probability right now, hard numbers that
our option is in the money at expiration and
loses is 29.35%.
So, the probability that a stock goes up to
our level and closes above that level is 29.35%.
So, let's use that same probability, and again,
go back to our stock distribution graph.
And let's just say that the SPY which is currently
right about here is trading at about 203,
204, right where I was in slide before.
Now, if our strike price is up here at 208,
if this is the level that we don't want SPY
to cross or breach, because we want SPY to
close anywhere below this level for us to
make money, then what we're saying here is
with this distribution graph, is that there's
about a 30% chance that that happens.
Now, we again, showed you where we got that
number from and how we derived it.
But there's a 30% chance the SPY from where
it's at right now, goes up to and closes beyond
our strike price by expiration.
Now, if there's a 30% chance of this happening,
that also means there's a 70% chance that
it doesn't happen.
And so, a 70% chance that SPY never makes
it up there and closes beyond that level at
expiration.
And this is where we get our very high probability
of success trade.
In this instance, the trade that we are actually
truly in right now (and you can see this with
the position markers) is a trade that has
a 70% chance of success as it stands right
now.
Now, the beauty of options, like we said,
is that you can pinpoint your chance of success
at any level that you want.
In this case, if you want a higher level of
success, you can go out to these options which
are the 210 options.
Those have about a 19% chance of being in
the money or losing at expiration.
That means if they have a 19% chance of losing
at expiration, then they basically have about
an 81% chance of being a winner at expiration.
Now, of course, the market is going to compensate
you and reduce a little bit of the money that
you make because you have a little bit higher
chance of success.
So, with these options, we sold those for
$145 and we only have a 70% chance of success.
And I say 70% chance of success like it's
some lower number.
But you know it's like an extremely high probability
versus going out to the 210 strike which is
over here.
The 210 calls have about a 20% chance of losing,
so at 80% chance of success and you're only
going to get $78.5 for the option.
So, again, you can see the markets are extremely
efficient.
They know that that further out option has
a higher likelihood of winning, and therefore,
you're not going to make as much money.
So, there's definitely a sweet spot in there.
But you can see, you can pin your probability
of success anywhere you want.
Again, just to drive home the point again,
we can go all the way out to the 212.5 calls
and you can see the probability of losing
on those is 9.56%, so about 10%, meaning that
this is about a 90% chance of success trade.
So, it's really, really powerful how we can
use these probabilities when trading to pinpoint
our chance of success, and we cannot replicate
this with stocks because stocks always have
a 50/50 probability of success.
So, with all of this said, (I'm kind of wrapping
up here) your only goal moving forward to
be successful in trading options is to make
as many small high probability trades as you
can on the right side of volatility.
Period.
End of story.
That is the ultimate goal with trading.
It's to make as many small, (very small positions,
you don't take on too much risk) high probability
trades like we just showed you that have a
high likelihood or chance of success on the
right side of volatility.
Just understanding if implied volatility is
low or relatively high, so that you'd know
if the market could expand in price or can
contract in price.
Remember that we want to sell options when
implied volatility is high, and we want to
buy them when implied volatility is low.
So, I really hope you enjoyed this video.
I know it was a more advanced tutorial, but
we're getting into a lot more concepts as
we get through this part of the course here.
And as always, if you have any comments or
questions, please ask them right below.
Until next time!
Happy trading!
