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Thanks GaryBtrader! Well actually this is what I am coming from, and what should be improved further by the walk-forward-optimization: For each window, in-sample is what I called BWD and out-of-sample is what I called FWD. BR Seb

Hi RedDuke! Thanks for that recommendation; in fact I have studied their content a lot and I agree that it is the best Youtube content I ever found for Trading. But I did not find an answer to that particular question: although Martyn also recommends to keep the amount of optimization...

I think you might have misunderstood - both the FWD and BWD data are historic data. And the optimization is done each time only on the BWD data, not on FWD. The "best" strategy from each BWD dataset is then applied on the corresponding FWD dataset.

Hi! I am struggling to transfer the strategy development process from a backtesting approach (with a single forward phase to confirm the result) to a classic forward optimization process when there is more than a couple of parameters involved: General consens seems to be that optimizing too...