Test 5: Targets, Stop Losses and Min Premium

Now its going to get more interesting. We combine Profit targets, Stop Losses and Minimum Premiums together to see if combined they are greater than individually.

For this test, I am going to use the same Profit Target and Stop Loss parameters in the past tests. I am also going to use the historical average premiums as an entry point into the trades (i.e. the minimum premium is set to the average historical premium).

High Level Breakdown

The breakdown suggests that once again the front-month trades are harmed by these trade parameters, but the 2nd and 3rd month trades find improvements.

1 Month 2 Months 3 Months All
Improved PF 211(23%) 558(62%) 657(73%) 1426(53%)
Improved MaxDD 900(100%) 900(100%) 900(100%) 2700(100%)
Improved ExpRet 218(24%) 359(40%) 553(61%) 1130(42%)

Profit Factor Improvement

A heat map of the profit factor improvement (over the baseline) shows much more detail. Generally speaking, all parameters decrease performance for front month trades. The high delta trade for the front month does show marginal improvement consistently, but not enough for me to be confident.

TSP-Heatmap-PF

The second and third month trades are a different story. It is hard to find an exact pattern, but we can claim that generally adding these parameters improves performance of these trades, with substantial gains for lower delta trades (i.e. Delta 10). The Delta 10 trades in the second month and some of those in the third month have massive improvements in performance compared to the baseline. Ideally I would like to see the neighboring trades (i.e. Delta 15) also experience similar but diminished gains in order to point to a possible pattern, but that is not the case (it could be that my resolution is not fine enough and that Delta 12 trades show that diminished improvement).

Looking deeper at the specific trades of one neighboring trades (all things being the same except the delta), its trades experienced 6 losses instead of one. This may add to the credibility that the low delta trades improvement was not just due to luck.

Expected Returns

A heatmap of the expect returns of each scenario shows that generally speaking

  1. High Delta trades still perform poorly regardless of month
  2. Very Low target trades perform poorly,
  3. Low stop loss trades perform worse
  4. Front Month trades perform best when the target is > 70%, Deltas <= 25, and stop losses > 30%
  5. Second and Third Month trades perform best when Target >= 30%, Stop Losses >= 20%, and Deltas <= 25%

TSP-Heatmap-ExpRet

We can also look at the top three trades for each expiration period so gain similar insights.

Month Delta Target StopLoss ExpRet MaxDD PF WinRatio Trades AvgDays
1 1st 0.10 90% -90% 6% -127% 2.2 93% 89 20.8
2 1st 0.10 90% -100% 6% -127% 2.2 93% 89 20.8
3 1st 0.10 90% -60% 6% -127% 2.2 92% 90 20.4
1 2nd 0.10 40% -60% 6% -71% 10.4 99% 115 19.1
2 2nd 0.10 40% -70% 6% -71% 10.4 99% 115 19.1
3 2nd 0.10 20% -70% 3% -71% 8.7 99% 180 10.1
1 3rd 0.10 20% -70% 3% -78% 7.1 99% 151 15.2
2 3rd 0.10 20% -80% 3% -100% 5.5 99% 151 15.2
3 3rd 0.10 20% -90% 3% -100% 5.5 99% 151 15.2

Those are some impressive win ratios. Those with a 99% win ratio only experience a single loss, and it was during the Oct 2008 market crash.

It is also interesting to note that as the expiration period increases, the expected return decreases by so does the average duration of the trade. Trades with shorter duration may be sitting on the sidelines frequently.

Conclusion

The combination of targets, stop losses and minimum premiums seems to substantially improve low delta trades in the second and third month, and to a lesser degree most of the other trades in those expiration period. But again, while the risk in the front month trades was reduced, the overall profit factor of almost all trades was also reduced.

Test Stats

Permutations 2700
Profitable Scenarios 1745 65%
Total Trades 526411
Profitable Trades 229165 44%
Expired 59983 11%
StopLoss 48866 9%
TargetMet 417562 79%
Test Duration 2.60(min)

Test Files

Excel Test Results

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Test 3: Targets and Stop Losses

Profit targets were found to be helpful, and Stop Losses less so, but can the combination of the two be greater than the sum of the parts?

Test Setup

For this test I create scenarios that include all profit targets and all stop losses from the previous two tests. Targets and Stop losses from 10% to 100% will be used. Ultimately this creates 2700 unique scenarios across the first three months.

Now that we have four input parameters (Delta, Days to Expiration, Profit Targets, and Stop Losses) for every scenario, analyzing the general trends is much harder. Ideally I need a holographic projection to show the data in three dimensions – but the budget here at Option I/O is low, so we will have to make due.

Highlevel BreakDown

We start by looking at the high-level break down of the tests.

1 Month 2 Months 3 Months All
Improved PF 200(22%) 645(72%) 713(79%) 1558(58%)
Improved MaxDD 900(100%) 900(100%) 900(100%) 2700(100%)
Improved ExpRet 202(22%) 441(49%) 573(64%) 1216(45%)

This are pretty surprising results to me. There was no question that adding stop losses and targets limits should improve the risk for every trade since we saw that in the last two tests. But I thought the combination of the two would help with the over all expected return as well. But what we see is the Front Month trades are resoundingly impacted by adding stops and limits, however the 2nd and 3rd month trades have a definite improvement.

Looking at a heatmap of this data shows more detail.

This heatmap is a little complicated to read. The major columns are the expiration months of the trades, the minor columns are the deltas. The Major rows are the profit targets, and the minor rows the stop losses.

This heatmap is a little complicated to read. The major columns are the expiration months of the trades, the minor columns are the deltas. The Major rows are the profit targets, and the minor rows the stop losses.

This data does not mean that any of these trades are necessarily bad trades. This is simply a comparison to the baseline test. The red indicates the trade is worse than holding to expiration based on the Profit Factor. Green is an improvement.

Here are some of the takeaways from this data:

  • Front-month trades are heavily impacted until the profit target is ~100%. Even then adding stop losses seem to help some, but not all the trades. And most gains or losses are marginal.
  • Almost all CTM trades in the 2-3 month time frame were improved.
  • Very low stop losses are stopped out a lot and are generally detrimental to the trade.

Looking at the heatmap in another way (not posted here but in the data file), I see a rough pattern where in the 2-3 month trades, the largest benefit is received by high delta/low target trades though to low delta/high target trades. There seems to be a sweet spot depending on the delta of the trade. You can see in the data that as the delta is decreased the sweet spot moves.

One final point in this section, the largest benefit goes to the CTM trades. This can easily be seen in the following chart. The DiffPF is the improvement in the Profit Factor over the baseline.

TS-diffPF-vs-delta

Expected Returns

With 2700 points, this is also a little hard to read, but this graph shows the general trends based on the delta and month of the trade. Most Delta 10 through 20 trades appear to have a positive expected average. While most with 30 and above do not.

TS-expRet-delta

Top 3 Trades for each Month

The following table shows the top three trades (by Profit Factor) for each of the different expiration months.

Month Delta Target StopLoss ExpRet MaxDD PF WinRatio Trades AvgDays
1 1st 0.10 90% -90% 6% -100% 2.5 95% 112 21.7
2 1st 0.10 90% -100% 6% -100% 2.5 95% 112 21.7
3 1st 0.10 90% -70% 5% -100% 2.2 94% 112 21.6
1 2nd 0.10 90% -40% 7% -100% 2.7 92% 102 41.7
2 2nd 0.10 90% -80% 7% -100% 2.7 95% 100 43.2
3 2nd 0.10 90% -90% 7% -100% 2.6 95% 100 43.2
1 3rd 0.10 30% -90% 3% -100% 3.3 99% 136 24.9
2 3rd 0.10 30% -100% 3% -100% 3.3 99% 136 24.9
3 3rd 0.10 60% -90% 6% -100% 3.2 97% 90 44.6

What is interesting to note is that many of these trades are very close to the baseline test. It’s also interesting to note that all the trade are with a delta of 10. Personally I would have thought that all the top trades for any month would have been slight variations of each other, but two trades stand out as different. The 2nd month 90/40 trade and the 3rd month 30/90 trade.

Top 3 Trades by Trading Style

I thought it would be interesting to also start listing the best trades by style.
(See my previous article about trader styles here.)

Month Delta Target StopLoss ExpRet MaxDD PF WinRatio Trades AvgDays
FrontMo-FOTM 1 1 0.10 90% -90% 6% -100% 2.5 95% 112 21.7
FrontMo-FOTM 2 1 0.10 90% -100% 6% -100% 2.5 95% 112 21.7
FrontMo-FOTM 3 1 0.10 90% -70% 5% -100% 2.2 94% 112 21.6
FrontMo-CTM 1 1 0.15 100% -30% 8% -112% 2.0 82% 113 23.3
FrontMo-CTM 2 1 0.18 100% -40% 9% -120% 1.9 79% 114 23.1
FrontMo-CTM 3 1 0.15 90% -30% 6% -124% 1.8 82% 114 21.9
BackMo-FOTM 1 3 0.10 30% -90% 3% -100% 3.3 99% 136 24.9
BackMo-FOTM 2 3 0.10 30% -100% 3% -100% 3.3 99% 136 24.9
BackMo-FOTM 3 3 0.10 60% -90% 6% -100% 3.2 97% 90 44.6
BackMo-CTM 1 2 0.15 90% -70% 11% -200% 2.4 92% 103 47.4
BackMo-CTM 2 2 0.20 30% -40% 6% -100% 2.4 91% 141 22.1
BackMo-CTM 3 2 0.18 50% -40% 8% -141% 2.4 88% 116 29.2

Again we see that for Front-month trades, the best scenarios are the same or close to the baseline. The back-month CTM trade however shows there may be an advantage with a 50% target and a 40% stop.

Conclusion

Surprising, Profit Targets and Stop losses do not have a major impact on the front month trades, but they do on the 2nd and 3rd month trades. They reduce the risk in every scenario. There is a sweetspot for the stop loss, but it is dependent on the delta of the trade.

Test Stats

Permutations 2700
Profitable Scenarios 1845 68%
Total Trades 679984
Profitable Trades 298187 44%
Expired 65216 10%
StopLoss 66814 10%
TargetMet 547954 81%
Test Duration 2.57(min)

Test Files

Excel Data

Test 2: Stop Losses

What level of stop losses are effective for managing iron condors? Our baseline test effectively had a 100% stop loss on all scenarios. Will adding stop losses based on the at risk margin (See the test on Profit Limits to learn why I use this metric) improve the performance of Iron Condor trades?

My guess before looking at the data is that stop losses will be shown to drastically reduce the maximum risk, and should be able to improve the effective expected return. Because some tests will be stopped out quiet frequently (i.e. those with a 10% stop loss threshold), I expect many tests to have a higher number of trades compared to the baseline.

Test Results

The test scenario use stop losses on the margin at risk for the following values:

10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%

The following summarizes the performance of the test run:

1 Month 2 Months 3 Months All
Improved PF 32(36%) 28(31%) 28(31%) 88(33%)
Improved MaxDD 90(100%) 90(100%) 90(100%) 270(100%)
Improved ExpRet 34(38%) 26(29%) 25(28%) 85(31%)

As expected the risk was substantially reduced in all cases. The vast majority of scenarios actually experienced lower expected returns and lower and lower profit factors. Meaning that the gains in risk were still outweighed by the loss in expected returns.

Profit Factor Improvement VS Delta

Looking at a histogram of the difference in profit factor compared to the baseline, we can see some patterns, but its not as clear cut. Very small stop losses perform poorly on average. And High Delta trades appear to perform poorly on average, although there is a cluster in the 3 month range and Delta 35 that does well. The clusters between the 30 to 60% stop losses and deltas under 22 seem to consistently outperform as well. But again, no very clearcut patterns emerge.

sl-hist-pf

 

sl-diffPF-vs-delta

Expected Returns

Looking at the expected returns, we can see that there appears to be a sweet spot between -30% and -60%, and Deltas less than 22. Similar to what was displayed in the profit factor tables.

sl-hist-expret

We can also see that regardless of the stop loss, high delta trades perform poorly. This is not surprising given the construction of the test.

sl-expRet-delta

Conclusion

Traders may often hold the Front Month trades to expiration but also use stop losses. This test shows that many of those scenarios can be improved marginally, but using a 30% to 50% stop loss on 15 to 20 delta trades seem to gain the most benefit.

The second month, low delta trades with a 30% to 50% stop loss may also be marginally improved.

The tests with Stop Losses between 10% to 20% are significantly impacted across all deltas and all months. These trades are just stopped out to frequently.

Most other tests are only marginally impacted either positive or negatively.

Test Stats

Permutations 270
Profitable Scenarios 174 64%
Total Trades 41402
Profitable Trades 17911 43%
Expired 19394 47%
StopLoss 22008 53%
Test Duration 1.52(min)

Test Files

StopLoss Excel Data