I started using the Analysis Series visualizer. But there's a problem. The independent variable is %Profit, which is a function of both the entry and exit strategy. So even if one had the perfect DataSeries (or indicator) for the entry strategy, it might perform poorly with this visualizer.

What's needed is a methodology that evaluates the merits of a entry-trigger DataSeries solely on its entry strategy merits (without confounding the evaluation with the exit strategy performance, which is a separate issue). (Aside: The same evaluation problem is also needed for the exit strategy, but that's a separate topic.)

The question remains, what independent variable should be used (instead of %Profit) for the Analysis Series visualizer, which only evaluates the merits of the entry strategy without being affected by the performance of the exit strategy, which is a separate issue? I don't know. That's a tricky question. It's hard to separate the entry strategy performance from the exit strategy performance since the two are intertwined by the Wealth-Lab simulation, but it's a requirement to make the Analysis Series visualizer useful.

Bottom line, the DataSeries employed for the entry-trigger is likely to be different than the one employed as the exit-trigger DataSeries; therefore, these need to be modeled independently with different independent variables that discriminate between the two.