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Hey Nedko,
Glad to hear from you.
Your questions are very logical. But before I answer them, I would ask you to watch that video:
After that, if you still can not understand it, ask me again, and I will answer. It is not that I don’t want to write the answers, but I believe that by watching the video, you will understand even better how the Walk Forward works. Because it is visual, this is why I do inline courses, which is the easiest way to learn it all.
Please, watch it, and let me know if something left unclear.
Hi Petko,
I watched the video very carefully and I want to double check if I understood the Walk Forward process correctly.
1. In the reactor, a strategy to pass Walk Forward Validation is needed only to pass the segments validation.
2. In the reactor, a strategy to pass Walk Forward Optimization is needed to pass all 3 criteria (Segments validation, Common Acceptance Criteria and Is strategy better).
3. If we choose to EDIT the strategy after successful Walk Forward Optimization (all 3 criteria are green), we expect to have a new not over-optimized strategy, because the EDITED parameters from the Optimization are based on 70% in-of-sample optimization based on the last segment and are tested on 30% out-of-sample. Additionally the Common Acceptance Criteria in-and-out-of-sample are applied on the whole back-test, which additionally speaks for not over-optimized strategy.Please correct me if I am wrong. I am looking forward to see your comments.
Best,
Nedko
Hello Nedko,
Glad to hear from you again.
Yes, I think you got it all.
Just keep in mind that the Walk Forward optimization changes the strategy, and the Walk Forward validation doesn’t change it. It just validates it.
Also, when you have run one time the Walk Forward Optimization in the reactor, you are seeing in the collection the strategies that passed it. And if you run the test after that it will fail, because it does it over the new strategies(that already passed). That was a question in your previous post I believe.
Cheers,
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