Hi Petko,
I have a question about the Walk Forward optimization tool..
My understanding is that the Walk Forward tool is for finding out if a strategy performs well on OOS data, and that if it does, then it is likely to be a robust strategy, ready for demo testing (possibly after some Monte Carlo testing as well), am I correct in this?
In video 8: “Walk Forward analysis”, from what I can gather, the Walk Forward tool is being used to try to over-optimize a strategy, to see if the original strategy is already over-optimized or not?
If the strategy is better after all the segments of the Walk Forward optimization have been calculated, then the original strategy is not over-optimized, and therefore the preferable one over the “better” optimized strategy?
And vice-versa; If the strategy is worse after all the segments of the Walk Forward optimization have been calculated, then the original strategy is over-optimized, and therefore the not the preferable one over the “worse” optimized strategy?
Or have I got it really mixed up?…
Thanks,
Simon