### Iron Condor Probability of Profit

Iron Condor Probability of Profit: Normal Distribution Vs. Reality. Which Model Tells The Truth?

SJOptions.com

In a recent study we performed using our Patent-Pending Instant Back-testing tools,

we found that the probability calculated by traditional software was up to

36% OFF FROM REALITY.

OUR CASE STUDY

In each test, we constructed an Iron Condor by selling near the -10 Deltas on the Put Side and +10 Deltas on the Call Side.

This trade architecture is known as the High Prob Condor.

According to traditional software the underlying asset has approximately an 87% chance of expiring between the short strikes to make the maximum profit of the trade.

Well, we ran nearly 500 random back-tests in our software to see how close the Bell Curve was, and the results we got were that 386 of 496 trades expired between the short strikes.

This would indicate that the real behavior of the underlying produced a Statistical Probability of 78%.

Then we performed another test. Instead of randomly choosing a large amount of days, we decided to only test trades that ended on Expiration Friday. Although we could only perform 83 tests, the results were eye-opening.

Only a mere 64% of the trades finished with a profit!

CONCLUSION

So, what's your opinion about this case study?

Is there or isn't there quite a difference between reality and theory?

Which model would you rather use in your trading?

If the Expiration Friday is the most accurate test, then the Normal Distribution

method of calculating probability is off by 36%. (23 points of 64%).

If we use the second test of nearly 500 random trades,

then the Bell Curve is off about 12%.

Either way, the Bell Curve can be VERY DIFFERENT

than reality and it exaggerates the probability in this case.

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and it's reflected in both our strategies and in our trading tools.

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### Video Transcript

Hi there everybody! This is Morris from San Jose Options. Welcome to this presentation on normal distribution versus reality: which model tells the truth? We have some eye opening facts about probability that we’re going to share with you guys today.

The statistics show the bell curve can be very different from reality. In a recent study we performed using our patent pending instant back testing tools, we found that the probability calculator by traditional software was up to 36% off from reality. Now think about that. If you’re trading options and you’re basing your trades on probability and you’re using the bell curve and the calculations are this far off from what really happens, from what the statistics add up to, just think about the complications.

In our case study, we constructed an iron condor. We sold near the 10 delta on the put side and 10 deltas on the call side. This trade architecture is known as the high probability condor trade. It’s very popular in the options trading industry. Now, depending on the volatility of the underlying asset, the probability of this type of trade can really range from about 70%, sometimes to the low 90s.

In today’s example, we were looking at the asset, the Russell the RUT. It’s a very popular instrument that people trade options with. According to the bell curve, this type of trade constructed in the Russell gives us about an 87% probability of profit at expiration. That means that the user would enter into this trade, analyzing it in a traditional way and they would believe that they have an 87% probability of profit.

What this translates to is that the underlying asset would need to stay between the short strike on the put side and the short strike on this side. Your breakevens are going to be somewhere between your short and your long strikes on the condor. If you’re not familiar with this trade, you’re buying one here, selling one here- this is typically the put side- then you’re selling one here, you’re buying one here on the call side. Your at the money is usually somewhere near the center of the trade.

We ran nearly 500 random back tests using our software. Actually, we had each of those trade expire on a Friday and we got 386 of 496 trades that expired between the short strikes or at least above the zero line as I was describing a few minutes ago. This would show a behavioral, a statistical probability of about 78%. You may think that’s pretty close to the probability that’s shown in traditional software, which would be about 87% but it’s not that close. It’s off about 12%. Twelve percent would be quite a bit different on your analysis. Now after we ran that test, then we ran a different one. We didn’t have as many tests to do ‘cause we limited the test ot expiration cycles only. This means that each 32-day tests we ran expired on expiration Friday. We did 83 tests. This case, only a mere 64% of the trades finished with a profit. The rest of the trades finished with a loss, many of them with the maximum.

What’s your opinion about this case study? Is there or isn’t there wide a difference between reality and theory? Which model would you rather use in your trading? If the expiration Friday is the most accurate test, then the normal distribution method of calculating probability was off by 36% in this case so it was really exaggerated. If we use the second test of nearly 500 random trades, these all expired on Fridays too but we just used all the Fridays that we could gather. Then the bell curve was off about 12%. That’s still quite different. Either way, the bell curve can be very different than reality. In this case, it’s really exaggerating that probability. Think about that for a moment. By using traditional probability calculating tools, you may be a little bit misled. You may think that you’re trading a trade that has a probability of 87% when in fact your probability may be in the 60s. I’m not saying this is always the case, this is just one case study but it sure is an eye opener. It makes you think twice about just relying simply on the bell curve.

That’s about all I wanted to say today folks. Thank you very much for watching this video demonstration and I hope you learned a couple new things about calculating your probability on your option spreads.