I agree so much on that this past year has given us some great data haha.

Also agree with the fact that a 5% in sample and 95% oos code that works great in both is a great algo lol.

And finally yes i agree with the fact that even tho we have the data we have, there is just so much more data to be had (talking about hour/minute charts now). For daily its different, not only do we not have all the data there is, but there is also the issue of electronic trading vs pit-trading. One could make the argument that electronic markets and increasing number of marketmakers and brokers and traders and funds etc, the markets have shifted into a sort of “turbo mode”. Although there are some similar traits that the pre-2000 and after-2000 eras both share, at least in my opinion. The two M’s: Mean reversion and momentum. There are also huge differences in data power and the amount of fucking competition. There used to be a few traders, now everyone with internet access can be a trader.. How this can or should or does effect your strategy or mine, i dont know.. I have some non optimized strategies for mean reverting in US 500 that seems to have delivered profitable results from the 1970’s to this day. Does this mean the same strategies that used to work, still works? Well simple answer is no. If we look at some of the “turtle strategies” that depended a lot on moving averages we can see that there is tons of more noise and choppy markets, making simple moving average strategies more shitty in the sense that they still work for those long nice trends, but they fail alot more often. At least this is my general opinion from comments from other traders, podcasts and just observing it myself, making strategies all day and night. What data to pick and choose from is a whole other level of crazyness, i try to just pick a bunch of data that has up, down, sideways, calm, volatile candles in it. Little bit of everything and hope for the best.

And i still got the idea of optimizing both the first half, and second half of data at the same time with a copy of your system, stuck in my head. If you can get a pretty similar match of variables in the top 10 best combinations of variables in each of the the 50% data-parts, shouldnt that speak confidence? Not sure..

I guess if you take that idea further, and leave small OOS samples out of each data set, your actually walk forward testing lol.. So i guess the conclusion i just thought of is that i need to optimize using walk forward and see if i can produce similar combination of variables to increase my confidence..