NT can optimize on any date range you pick. That works fine. The problem is that I want to find the best set of parameters that work on the out-of-sample data. This means you automatically optimize against the first data set, then find the best run against the out-of-sample data. Is this possible?
The only way I've thought of doing this is to save the parameter sets found in the first round, then backtest against those sets for the out-of-sample period.
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