Jim - I have dabbled in mechanical system development for a good 25 years. What you are describing is one very specific “walk-forward optimization” and I would be very careful regarding the results. Meb Faber is probably a bright guy but “A Quantitative Approach to Tactical Asset Allocation” was touted as a very strong approach to asset allocation and was tested in many different markets. However, it really didn’t work well out-of-sample.
Automated walk-forward optimization doesn’t refer specifically to relative strength but can be any set of factors. And I believe that it is important to establish the ground rules for selecting the best factors and their combination. It is in no way apples-to-oranges. If you don’t establish some common-sense ground rules upfront then you just end up with another hack at extreme optimization. It becomes very convenient to hit a button and watch the computer chug away printing out spectacular results that are simply wishful thinking. If you don’t get the results that you want then make an adjustment and repeat…
I think you are right about that. In fact the possibilities are literally infinite.
Indeed, I think jsk was referring to a possibility outside of relative strength. Something I think is worth investigating.
I think Korr123 probably was not referring to relative strengh either but I am not sure.
Having only tried a few walk-forward optimizations myself I am hesitant to disagree with Korr123. Maybe he has experience with something that I don’t. Almost certainly he does.
There are enough papers for people to form their own opinions on relative strength (if they have not already). I was just illustrating that people have already (probably) seen an example of a walk-forward method.
Everyone here on the site optimizes. There is not a single person on this site who has not “thrown out” a backtest. How you optimize is based on technology (or lack thereof) and the quality of your research. Every successful quant fund optimizes. Citadel optimizes, RenTec optimizes, etc, etc.
Walk forward just optimizes based on the most information available at that time. I don’t really see how or why this is controversial. I hope that explains my remark.
P123 already tried and discarded AI because it “didn’t work”. I’m simply trying to avoid that situation again by suggesting that the criteria for selecting an optimized system may more complex than going with the best %return. At least we should have the option for making it more complicated than that if walk-forward optimization is ever implemented by P123.
NEW QUESTION: OPTION BASED. So I very frequently buy very long naked calls. Sometimes the cost of the option is so high I will spread by shorting an higher strike call against my long at the money call to lower the total risk exposure (net premium) but of course if the underlying stocks is a long term home run the higher strike call accretes value very fast.
Here is the question; in the above situation do you have a strategy as to when, if ever, to cover the higher strike long call?
Mike - the problem that I have always had with regards to options is that the premium takes on a life unto itself. You end up not buying/selling based on business fundamentals but on the volatility of the stock. It is a different world and P123 may not be suited for that kind of trading.