>
>
> My heat map consisted of just a few short lines, as I had to increase the
> parameter steps because I ran put of heap memory. But I thought perhaps the
> map results could be interpolated, like the do in climatology sites, using
> 'kriging' or some similar method.
>
>
You may want to try the "divide-and-conquer" optimizer, instead of the
"brute force" optimizer. The "D&C" optimizer makes a trade-off between the
time needed for optimization, and the density of the map.



> Looking at the heat map it seemed the performance Island was off the upper
> right corner in the parameter space. Panning the ranges I centered the
> island (sorry I don't know how else to describe it) as a blob within a
> window  from 3600-4600 in period and in 22.5 to 26.5 in scale, from 98 to
> 101 in Entry and -6 to 6 in Exit.
> Choosing the centroid of the blobs as Period 4100, Scale 24, Entry 98,
> Exit 0, I got improved performance back testing as $2092 net profit, 2.0
> PI, after 61 trades
> This is how one is supposed to choose parameters, right?
>

Yes, that's the right methodology.



>
> P.S.: This thing is really interesting, I bet the island moves and changes
> shape as time goes by, and conditions change. I would like to explore an
> algorithm that continuously updates the 'centroid' of the island.
>
>
Yes, the "optimal" set of parameters would change, as you add more training
data.




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