Hey everyone, this is Kirk here again at OptionAlpha.com,
and in this video I want to talk about correctly pricing your option strategies. You'll often hear the cry of failed traders
who say things like, "I did everything right and I still lost." "I won 80% of the time, but the biggest losers
overshadowed all the small winners." "You can't win trading options." "High probability trading just doesn't work." I can almost assure you that their failure
in most cases comes down to one major part that they're missing, and that is correctly
pricing trades. In today's video I want to walk through the
correct way to price your trades, specifically credit spreads, iron condors, and debit spreads,
based on the trades probability of losing and the overall risk. By the end of this video you'll see exactly
why two different traders who make the same high probability trade entry could have dramatically
different levels of success. It all comes down to, again, option pricing
and correctly pricing these trades. First let's use our classic coin flip case
study that I go through a lot with some of my premium members and coaching students,
and I think it really proves the point here that we're trying to make. Here's the game here that we're going to play. We're going to flip a coin, obviously heads
and tales. The odds of each side is 50-50, so the chance
of flipping a heads, 50%, chance of flipping tails, 50%, but the minimum number of flips
in this game is going to be 1,000. We're not going to flip it one time, we're
going to flip this coin 1,000 times, and that's going to be the end of the game. If it lands on heads you win $1. If it lands on tails you lose $1. Here's how it would play out. We start the trade, you end up either flipping
heads or tails, and then from there heads or tails, heads or tails, heads or tails. At the end of 1,000 flips, there's probably
a good chance that you have an equal number of heads and an equal number of tails. It might not necessarily work out the first
two flips that the trade makes, or the game makes, but at the end of 1,000 flips you're
going to have an even distribution of heads and tails. How much money, at the end of the game, would
you expect to make? Probably around $0, not making any money,
depending on the last flip. You might make $1 or lose $1 depending on
the last coin flip as you hit $1,000. Now let's change up the game just a little,
and keep in mind that you still want to make money with this game, because you still want
to make money trading options. Here's the new game there we're going to play. You're still going to flip a coin, it's still
going to have the same odds, and still the same minimum 1,000 flips before we end the
game. In this example you're going to win $0.70
every time that it lands on heads, and when it lands on tails you're going to lose $1.30. All we did is just change up the pricing of
the trade, or the pricing of the game, to where if it lands on heads you win $70, if
it lands on tails you lose $1.30. Do you still want to play this game? Who in their right mind would? Yet options traders do this all the time and
don't even know it's happening. The results of the new game would be 1,000
flips times the odds of winning, 50%, times the $0.30 edge that is lost in the game just
purely out of pricing, means that at the end of 1,000 flips you're going to have a $300
expected loss at the end of the game. Again, how long could you keep playing this
game before you went flat broke? Probably not long, right? But again, so many traders are playing this
game and don't even know it. LEt's use a very specific options trading
example to prove the point, and kind of start bringing this thing all together. At the time of this video, Twitter's stock
is trading at about $16.70. Selling the 13.12 put credit spread, which
is selling a put credit spread below where the stock is trading at $16.70, gives you
a credit of $16, and the risk in the trade, since it's only a $1-wide strike, is $84. So you could make $16 or you could lose $84. Based on option probability, we know that
the 13 strike has a 21% chance of being in the money at expiration in 46 days. That's a known number. We can find that number in the options pricing
table. Think about this: There's a 79% chance of
wining $16, and a 21% chance of losing $84. If we were to make this type of trade over
and over over and over again in Twitter's stock, or anything else that has very similar
pricing, we'd have an expected loss of $5 on each and every trade that we make. Every single time that we make a trade, we're
expecting to lose $5. So long-term, even with a high win rate we're
still winning nearly 80% of the time. You can't expect to make money just purely
based on the fact that there's really bad pricing. This is where you start to now see the difference
between a trader who can win often, and you'll hear traders often cry out and say, "I won
80% of the time," or, "I won 70% of the time, but I just didn't make any money." You can still win with a high win rate, but
your expected probability and the pricing of the trade can determine if you actually
make money at the end of the day or not. Now let's look at something different. Let's look at an iShares Brazilian ETF, which
is EWZ, an dis currently trading around $26.10. Very similar, low-priced security that you
can trade highly liquid, just like Twitter. Selling the 29.5/30.6 call credit spread,
so selling a spread above the market, you take in a credit of $21 and your risk is $79. In this case we also know, because it's a
known number that we can find, the 29.5 strike has a 21% chance of being in the money at
expiration in 46 days. If we made the EWZ trade the details would
be as follows: A 79% chance of winning $21, and a 21% chance of losing $79. At the end of the day, if we made this trade
over and over and over again, or a trade very similar to it, our expected win or loss would
be basically zero. This is where most people would come in and
say, "Aha, it's a zero-sum game." But now that you've built a trade that puts
you in a position to exit early for a profit and shift the odds in your favor, you can
now win out with a trade like EWZ, as opposed to Twitter. Because Twitter starts itself as a loser. Twitter has bad pricing on the entry of the
trade. You can't do anything about that. With a trade like EWZ, as long as you price
it correctly like we showed you here, where you're taking in enough money to counter the
actual risk of winning or losing in the trade, then having done nothing at all, so being
a completely total lazy trader, not exiting the trade early, not managing your position,
not adjusting it for a win or a loss, you end up with zero at the end of the day. You can't really hurt yourself, or you can't
really win or lose, if you place a trade correctly. Now that you've placed a trade correctly,
what if you closed just one of those trades early for a profit? What if you took one of those trades and cut
the loss by making an adjustment to that trade? Now you are taking that trade and you're starting
to increase, or shift, the odds in your favor long-term, which is exactly what we want to
do. Here's how we can do that, obviously and we've
talked about this here on track number two. We can close trades early, we can bank profits,
we can adjust trades to cut loss, and we'll naturally win on the fact that IV overstates
the expected move. Which means that a trade that has a 21% chance
of being in the money might actually only end up seeing 19% of the time being a loser. IV, implied volatility, always overstates
how far the stock might move at the end of the day, so we're going to win out a little
bit more. By pricing our trade efficiently in the entry,
gives us a lot more opportunity to do things with the trade that create profitable scenarios
at the end of the day. Yes, it's going to be hard to go through these
trades and do the math that's required, but what's the alternative? You just make poor decisions, you just make
bad trades? Do you just make trades like Twitter all day
where you're not making enough money, and every single trade that you get into, you
know you have lost a $5 edge no matter what happens? Yes, it's going to take a little work, but
I promise you it gets easier over time. The more you focus on your targeted probability
level, the easier it'll be to see good pricing. This is why we always harp on the fact that
you've got to choose a probability level that you're going to focus on. Focus on 70% winners, or 80% winners, and
price every trade off of that so it's very easy for you to see, over time, how much each
individual trade is going to be taking in, and if that's a good price. Because you're looking at the same type of
pricing every single time that you enter a trade. Yes, naturally higher implied volatility stocks
and ETFs will generally have much better pricing across the board, because higher implied volatility
means higher option pricing, which means that you're going to be compensated a lot more
for the same probability of success. Of course it's always good to double check. It's always a smart idea just in case option
pricing isn't really that high. Here's the formula that you need to follow. It's generally this, and again we'll kind
of get into it here in a little bit with more specifics, but it's generally this formula. The credit that you receive has to be equal
to the width of the strikes in a spread times the probability of that short strike being
in the money. Again, the credit that you receive has to
be equal to the width of the strikes times the probability of that strike being in the
money. To use our formula from the example above,
if we had a $1-wide strike, and there is a 21% chance of our short strike being in the
money, we need to take in a credit of at least $21 on that type of a trade for this trade
to be fair, equal, and balanced, and for us to get good pricing. If we had a $1-wide spread and there was a
15% chance of the particular strike price, that the short strike being in the money,
then we need to take in $15 on a $1-wide strike for the risk and the payoff to be equal and
fair. If we were trading a $1-wide spread and there
was a 30% chance of the short strike being in the money, then we need to take in a credit
of at least $30. YOu're starting to see this concept roll out. Now what happens if there's a $5-wide strike,
so now instead of a $1-wide strike we're looking at a $5-wide strike? Still the same 30% chance of being in the
money. Now we take that 30% of the $5-wide strike,
and now we need a credit of $1.50 for us to have a fair and neutral and kind of good pricing
on this type of a trade. Let's actually jump over real quick and look
at some examples here, because I want to prove the point in what we're trying to do here. This is a look here at CMG. CMG has a fairly high implied volatility right
now, so option pricing should be pretty good here on CMG. In this case, if we look at doing a trade
that has an 80% chance of winning, we want to get some pretty good and fair pricing on
an 80% probability trade. If we look at the short strike of the 5.20
calls, they have about a 20% chance of being in the money at expiration, so there's an
80% chance that it's out of the money, 80% chance of being a winner, 20% chance of being
a loser, or the strike being in the money. Again, I'm just rounding up here for even
numbers and simple math. If we do a credit spread, where we sell the
5.20 and buy the 5.25, this is a $5-wide spread. If we use our formula, the $5-wide spread,
times the probability of being in the money, which is basically 20%, means that we need
to be taking in a credit of at least $1 on this trade to have a fair and good pricing
balance on this trade. You can see the credit that we're taking in
on this trade right now is 1.05, so we're actually taking in a little bit more money
than is required to enter this trade. Meaning that this trade, even if we did nothing
at all, every single time that we enter a trade like this, we'd actually win out a little
bit of money. Before closing trades early, before managing
positions and adjusting losses, we'd win out money because this trade is actually paying
more than it actually should based on risk. This is a good entry because it kind of fits
our parameters here. If we look at a different strike price, so
let's say we look at doing the 4.95 calls, those have about a 30, 30% chance of being
in the money, so a 70% chance of being a winner on that trade, 30% of being a winner on that
trade, we would expect to take in a premium of about 1.50 on that trade to make it fair
and neutral and balanced. A $5-wide spread, which is exactly what we
have, times the risk of being in the money, which is about 30%, again I'm rounding down
just for simple math, means that we want to take in a credit of at least $1.50 on this
trade for us to have a good pricing on this trade, and for us to make money long term. You can see the credit that we're taking in,
or we could take in, is about $1.65. For a trade that wins 70% of the time we're
taking in $1.65 in credit. Now let's look at something a little bit different
that might not have as great of pricing. Let's look at, actually let's look at LinkedIn,
another high-priced security, and let's look at the same 20% probability of being in the
money level like we did with CMG on the initial trade. If we look at LinkedIn, the 1.35 call options
have about a 20% chance of being in the money at expiration, so about an 80% chance of winning. Again, it's a $5-wide spread, but notice with
the LinkedIn trade, the $5-wide spread, where we need to take in $1 of credit, is actually
paying out $93. It's not paying enough money to compensate
us for the amount of times that we're going to lose on this trade. Meaning that, if we make this trade, we're
not collecting enough money to break the zero-sum game, and to pay out on the winners what we're
going to lose when we do end up losing the 20% of the time. If we look at something a little bit closer,
just like we did with CMG, so let's look at these 1.29 calls that have a 32% chance of
being in the money, so roughly a 70% chance of being a winner trade on this one, and if
you look here, if we sell this spread, you can see that those are paying out just a little
bit less than what they should be. They should actually be paying out about $1.60,
$1.65 based on a 32% chance of being in the money. Again, all we're doing is taking our $5-wide
strike, we're timesing that by the probability of being a loser on this trade, or the probability
that the short strike is in the money, and those trades really need to be paying about
$1.60 per spread for us to want to make this trade. Very, very close, but not exactly the type
of pricing that we want. Again, this is why a lot of traders loose,
is because they don't take the time to do these calculations, and to figure out which
trade is actually paying out some really good money. Let's look at one more example here just to
kind of prove the point. Let's look at Netflix. Netflix is another high-priced security, so
we can use this one with $5-wide spreads. The 20% probability of being in the money
strike is the 1.20 call. If we sold the 1.20 calls and bought the 1.25s,
that's a $5-wide spread. Notice how again, just like with LinkedIn,
it's not paying enough money to actually make the trade. The Chipotle trade that has the exact same
probability of success as the LinkedIn trade and the Netflix trade pays out $10 more every
time that you win, with the same probability of success. Yes, we had to go dig for it, yes it took
a little bit more time, but the reality is that two traders who make the same high-probability
trade in either Netflix or Chipotle or LinkedIn, only one of those traders, who's making that
trade in Chipotle, is going to win more often, and win more money when they do, because of
options pricing. As we look at credit spread pricing guidelines
here, and hopefully that was a good example as we run through some different pricing scenarios
on our platform here, but when we look at credit spread pricing again, what we want
to see is, we want to see that the net credit received is equal to the width of the strikes,
whatever that ends up being, times the probability of the short strike being in the money. At least that amount. You can get very, very close to it, but you
want to at least have pricing that's within that range. For iron condors it's no different. What we're looking for is, again, a net credit
that is equal to the width of the strikes times the probability of being in the money,
on both sides. That's the one little caveat this time with
this one, is that if you have a iron condor that has a 30% chance of being in the money
on both sides, so maybe a 15% chance of being in the money on one side, 15% chance of being
in the money on the other side, you need to still take in a credit that's equal to the
width of the strikes. Let's actually price this out with an example
here, and this time we're going to look at Amazon just so we get a lot of different examples
thrown your way. You can see Amazon right now is trading at
about $5.92, but again, high-priced stock, so it kind of works with all the ones that
we've been looking at. With an iron condor we're going to build each
side at the 15% probability of being in the money. In this case, with Amazon, we'd be selling
the 500/495 put spread down below the market, again that's at the 15% probability for our
short strike. Then we go all the way up above the market
to about the 6.70 short strike on the top side, sell the 6.70, and buy the 6.75. Now we've created a nice, balanced iron condor
in Amazon. It's $5 wide on both sides, so that's the
strike price width that we're looking at. Again, you don't have to add these up because
you can't lose on both sides at the same time. You can only lose on one side or another. The $5-wide strike, times the probability
of losing on both sides, which is 30% overall, remember, 15% probability of losing on each
side, so we add those two together, that's how we get our 30% probability of losing on
both sides, meaning that we need to take in a credit of about $1.50 on this Amazon trade,
which is exactly what this iron condor is pricing out right now. In this case the Amazon iron condor actually
ends up paying exactly what the risk in the trade is, and that's because implied volatility
is very high in Amazon. Hopefully that was a good little example for
iron condors. If the trade was paying out say $1.35, we
wouldn't be getting enough premium to compensate us for the risk in the trade, so in that case
we would skip the trade, or not make it, or try to look for something different. If we're doing a debit spread, we want to
look for a net debit that's equal to the width of the strikes times the probability of being
in the money, which is very similar to everything else, except we're looking for a net debit
in this case. What's different about debit spreads is that
debit spreads are going to be directional in nature, which means that we usually make
these trades with about a 50% chance of winning and about a 50% chance of losing. We don't often use these as the core basis
of how we generate income with options. They're mainly used for hedging, but the same
principles apply, is that if you have a 50% chance of winning, and a 50% chance of losing,
then our risk and reward should mirror that 50-50 kind of strategy, just like that coin
flip that we talked about. You want to make sure that you're taking in
enough money on that type of a trade so that, if you don't end up winning on that trade,
or if you kind of make those trades over and over again, they don't really hurt your portfolio
because of really bad pricing. If we go back here and actually use Amazon
as a good little example here, you can see that Amazon stock is trading at 592.63 at
the time we're doing this video. If we want to use Amazon as a way to go long
or short, or whatever the case is, let's look at just buying a debit call spread on Amazon,
which is buying that at 590s, selling the 595s. You can see that that price for the debit
call spread right now is trading at 2.60, but the actual stock itself is trading at
592.74, so our break-even point on this thing is a little bit lower than where the stock
is trading, but notice that our risk to reward is not exactly the same. It's a little bit off. We are not exactly making about 250 for every
250 we have at risk. This trade really has about a 50% chance of
being a winner or a loser. Remember, this is a $500 stock that's off
in pricing and break-even points by $0.14 or so This is about a 50-50 shot trade, but
when we actually make this trade, our profit is not going to mirror that 50-50 that we're
looking for. We actually need this trade to be priced right
around 250 for us to be confident in the pricing, and for just to be confident in taking this
trade. If we enter this trade at 250, notice that
we can make 250 or lose 250, the break-even point would be about 592.50 again, which is
very close to where the stock is trading given that it's a almost $600 stock. That would be a more fair type of a trade
with the debit spread. We always try to get an even distribution
of max profit and max loss with debit spreads because again, all they are are 50-50 bets. They're not meant to be our high-probability
trades, so we want to make sure that we're pricing those really, really good when we
enter those. Strangle and straddle pricing guidelines. This is where it's going to be a little bit
different, obviously. You'll definitely want to base risk off of
the initial margin that's required, and again, this is something that's going to be different
for your account, so we can't necessarily give you any hard guidelines. We can talk about a little bit more, and we
often do in some our weekly strategy calls with elite members, but it's really hard for
me to say, "You have to do this," because a lot of people have different margin levels,
and improvement levels and brokers. Even different brokers on the street will
have different margin requirements for different trades, so I hesitate to give you ane exact
guideline and formula for correctly pricing straddles and strangles, because I don't want
you to follow it if your broker's a little bit different. Here's what I will tell you, is that it's
definitely gonna vary, and you have to remember that your break-even points are much wider
than regular spreads. For example if we go back here to, let's say,
Amazon, if we were to sell a naked put in Amazon at, say, the 655 strike, this naked
put has an 20% chance of being hit, 80% chance of being out of the money at expiration. I'm sorry, the 655 calls, not the puts. Has an 80% chance of being out of the money
at expiration, but if we're taking in a $10 credit to sell those naked options, then really
our break-even point is more around 665. You have to remember that, with a straddle
or a strangle, you're taking in a much larger premium because you don't have to buy options
on either side. That's going to naturally widen out your break-even
point, it's going to give you a little bit better overall win rate, and a wider range
to make money at the end of the day. Just keep that in mind. Again, there's no hard guidelines here. What I can tell you, obviously, is that with
high implied volatility, that's when you want to do these straddles and strangles, because
option pricing on both sides is going to be much more inflated, much more rich. You're going to get paid out a lot more for
the same probability of success by doing these when implied volatility is really really high. Obviously, remember, you'll always win more
than your initial probabilities show, and your break-even points are always a little
bit wider when taking in a credit, no matter if you're doing a straddle or a strangle or
an iron condor or a credit spread. That said, I hope this video serves as a great
guideline for options pricing, and just the idea that we need to be more cognizant of
how much money we're taking in, relative to the probability of actually losing on the
trade. Hopefully going through the coin flip example,
the Twitter, EWZ, all the examples with CMG and Amazon and LinkedIn, really kind of drove
home this point, because I think options pricing is really something that a lot of people really,
really miss in this industry, and it's very, very important to your overall long-term success. Thank you for checking out this video. Hopefully it's been really helpful. If you have any comments or feedback I'd love
to hear it. Ask them in the comment section right before
this video. If you loved it, though it was helpful in
understanding a little bit more about options pricing and how to correctly price some of
the strategies out there, I'd love if you could share this video out there online, help
spread the word about what we're trying to do here at Option Alpha.
