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This raises a interesting point.
If some objective functions are poor predictors of out of sample performance, are there other objective functions that are good predictors of out of sample performance? Or at least better?
It seems like this is the kind of problem where there should be a optimal answer. I wish that I had the math background to find it.
The best that I could come up with is that there needs to be a measure of performance and a measure of risk to balance it. There are several such measures in common use and they will each tend to favor different solutions.
Since I am not able to pick one on a theoretical basis, I had to resort to empirical testing using Ami's walk forward feature. As a result, I found that net profit performed the worst of all of the objective functions I tried in terms of out of sample profit. In my simple test, UPI performed the best. CAR/MDD also performed well. I don't recall how the others did. I believe that Sharpe was somewhere in the middle and k-ratio didnt do well at all.
However, this is just one simple system and I really wish that I had a theoretical basis to hang my hat on it. Results for other systems may be very different and it might be different if I repeated the test now, with a extra year of test data.
-Doug
--- In amibroker@xxxxxxxxxxxxxxx, Howard B <howardbandy@xxx> wrote:
> It is also interesting to note that some objective functions tend to reward
> / select values for the logic and parameters that result in trading systems
> that do not trade well out-of-sample. In particular, be careful using net
> profit, sharpe ratio, and so forth. By all means, define your own custom
> objective function metric, program it, and tell AmiBroker to use it.
>
> Thanks for listening,
> Howard
>
>
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