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Julius  I dont think specifically.

Like you I have pondered this topic at leangth from a logic rather than mathamatical view. My thoughts were very similar to your own which I have highlighted in italics.

In the end I have come to the following conclusion (Not saying its right or wrong just my conclusion).

If I chose a set of parameters and assign variables to them that are fixed,test and accumulate results,I can expect that the re application of them on forward data will return results within the Devaition parameters returned from any MonteCarlo analysis,provided the data doesnt step outside the boundaries of that which it was tested against.

If I optimise parameters and or Variables then I am un realistically expecting results to perform as well as they have on PAST optimised results working forward.What I have in reality is a set of parameters that are chosen by optimisation rather than "randomness" which when re applied forward will not be the optimised "Best" results looking BACK after a period of forward trading.

They are no better than random.

I have infact tested this to my best ability by optimising over a period then applying the optimised parameters over another forward period.The results are not as good as the optimised original results.

re optimising THOSE results return very different variables than those selected

from the initial optimisation.

An endless futile search for the very best selected variables.

You just wont find them as they will always alter through time.

The best you can get is an expected performance based on the "given" parameters selected for testing---wether they be optimised or randomly selected.Derived by allocation of parameters and variables tested against a data set which return a likley set of performance results deviating from the mean high and low.

If acceptable you trade if not you keep searching.

I know the explaination is circular but so is the exercise.

but hey I'm happy for my LOGIC to be challenged!