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How To Trade Iron Condors

Iron Condor spread trading is one of the more popular strategies when using stock options. It gives you the opportunity to make money provided the underlying stock or etf stays within a certain range, and the loss you may incur is well-defined and limited.

This strategy works very well when the markets are not trending hard... that means if you had used this strategy during the downtrend in 2008 it would not have worked. But the conditions in early 2009 seem ripe for iron condor trading. Why? Look at the past 3 months: nothing but chop. That means the option speculators who go long options have a lower probability of success, unless they have been quick in their trades.

Risk versus reward is a major consideration when you take on any trade; but when you trade iron condor spreads, it becomes even more valuable.

When we look at risk and reward, what we really want to see is our expected value. The expected value is just a fancy statistical way of saying the average. The EV is what you expect to make on an average trade.

Take a coin flip. It's either going to be heads or tails, and if it's not a loaded coin, it's going to be a 50% probability either way. So say you're betting on the coin, and you're risking $1 to make $1. You know that over a long enough period of time, you won't make any money--you'll just be breakeven. But there's an equation behind this:

EV = p(success) x reward - p(failure) x risk

So that means:

EV of Coinflip = .5 x 1 - .5 x 1 = 0

But say that your reward is actually 1.5:

EV = .5 x 1.5 - .5 x 1 = 0.25

That means for every coin flip you should be expecting to make .25 of your money.

So that's what defines what a successful trade is: positive expected value. But what if the risk was higher than the reward, but you had a higher chance of success? That's what condor trading is all about.

Say we had a loaded coin that turned heads 75% of the time. If the reward was 1, how much could we risk in order to be breakeven?

EV = 0 =  .75 x 1 - .25 x []

[] = 3

That means as long as we don't risk 3x the possible reward, we will not lose money. We can then apply that concept to iron condor spreads. But where do we get the statistical probabilities for success and failure? That's the tricky part.

We're going to take a theoretical example from SPY, since it's the simplest to trade and very liquid. Here's the trade:

Sell -1 Iron Condor Mar 90/92 Call 74/72 Put .71 or better

Here's the risk profile:

SPY Iron Condor

SPY Iron Condor

We can use the risk profile to determine our expected value. The reward is 71, the risk is the difference between the spread and the reward, so that's 129.

Now for the probabilities. In options pricing normal Gaussian distributions are used to predict the probability that the option will expire ITM. Normal Gaussian distribution just means bell curve. So in our risk profile we can set slices to ascertain the probabilities of expiring in that price. So our probability of success is given to us as 56.47.

With all of our information we can now calculate the expected value:

EV = .5648 x 71 - .4352 x 129 = -16

That means if we took this trade at random a million times, we would be losing money. But is it still a good trade?

But here's where using techincal analysis comes into play. If you think that the supply and demand characteristics of the market will give you a higher edge of success, then it's a better play. Let's look at the chart and place our breakeven areas:

SPY Chart with Breakeven Areas

SPY Chart with Breakeven Areas

Do you think that the price could expire in this area? Do you think that there's a higher probability than what the statistical distributions are telling us? If so, then this is a good play. If not, slowly back away and don't touch the "Trade Now" button.

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