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