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

Advertisements

2 thoughts on “Test 3: Targets and Stop Losses

  1. Useful article. Thank you. Can you explain why / how you have max drawdowns greater than 100%? I’m probably misinterpreting the max drawdown metric – I would have thought the max drawdown would not be able to exceed the amount risked given the iron condor strategy.

    Also, I want to validate my understanding of the profit factor. Would I be correct in saying, “If the profit factor is 2.6 over X number of trades, on average, I will expect to make $1.60 for each $1 risked.” True?

    • That’s a good catch. I looked at it yesterday. It is quite possible to loose more as you can buy back for any price and sometimes the unrealized loss could be larger; but clearly no one would sell at this point. I looked at a few examples where it occurred and I thought I fixed it, but I didn’t. It should have stood out since they should not perform better than the baseline (they are the baseline). I found the problem and I am recrunching the numbers now. I will update the article shortly as it significantly changes the analysis.

      The profit factor is = Sum of Gains/Sum of Losses. I don’t use it as an expected return of an individual trade as you illustrated above. I use it as a relative performance measure between different trades. For example, lets say you have a trade scenario that has all profitable trades and zero losses. The PF is infinite (my code caps it at 100). Clearly you are not going to make infinity on the next trade (if you do, let me in on the trade). But the infinite PF tells me that it might be better than the scenario with a PF of 2. You also have to look at the number of trades to be sure whats going on.

      But this is also why I look at and report the expected profit and max drawdown. These are two specific measurements that I can use in individual trades of a scenario. Some people might prefer average loss instead, but for me that is ultimately included in the expected return.

      Thanks for pointing out that issue. I appreciate it.

Leave a Reply to Dave W. Cancel reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s