I am very interested in Self Tune strategies, especially Self Tune Trend Signal - Anti WhipSaw +ROC + Expectancy V12 ( ST TS V12), while it can not be used after translated. It is very complicated, do you have it on WLD v6? tx.
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ST scripts can not be properly translated because of their dependency on Equity series (which is not available) and/or ClearPositions (which functions following a logic of its own in WL.NET).
I'm no expert on ST scripts but IMHO you can reach the same purpose by simply using the Walk-Forward Optimizer (which wasn't available in WL4).
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Sorry, but I don't understand what you mean. What is IMHO please? Is there any solution for me to apply the above strategy on WLD v6? Thanks.
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The idea of self-tuning systems is to adjust their internal parameters in order to best fit some function like the maximization of equity or other performance metric. Walk-Forward Optimization solves a similar problem by repeatedly finding a set of optimum parameters with regard to an optimization metric (any one from Scorecards installed in Wealth-Lab) in the in-sample testing and applying them to the out-of-sample data.
The proposed workaround for you is to code the system's core rules (except all the ST stuff) and use the WFO Optimizer.
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That is out of my expectation. It is too complicated. I have to give it up. Thanks any way.
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The system's core rules are pretty simple. It's a combination of daily/weekly MACD:
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As can be seen, the Daily/Weekly MACD block can be shortened by using SetScale* with the built-in MACD series.
It's the Self Tuning logic that really makes the script complicated. What I'm proposing is to consider the WFO a viable replacement for ST.
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thanks for your help. Do you have any information for these strategies? I will try to go deeper.
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thanks so much. They are great!
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