@mistermonster You would think so, but no, no overfittering, I used different test sets to help avoid that, and the actual principles of the algorithm is actually not that complicated. I'd be hesitant to give away the specific details as to why/how but after seeing the results I applied it to other stocks and timeframes and it consistently gave the same performance. Its a day trading algorithm and trades anywhere from once every day to a few times a day, it rides the peaks and bumps.
Made 15,000 in profit today on 150,000 in investment, whcih is better than the historical results which would have had me at around 8K a day on that level of investment. Keep in mind thats no margin use.
@mistermonster well you can calculate one from the other.
Historic testing shows 0.8% profit **daily**... thats over 18x/1800% yearly... Real world results have been higher (partly because i pick some trades not to execute if there is a reason to speculate against it).
@mistermonster I do, but it isnt needed. the 0.8% per day 1800% per year figures is the result you get without manual intervention. If you just let the algorithm run.. that includes a little slippage and commission fees (I overestimated both costs).
the 10% figure I saw today was with manual intervention. I had one set of stucks I let it go at completely automated (those on real world seem to get about 1.5% daily), then I use it on stocks I personally like to tell me when to enter and exit on them, so in that case it is just an assist, on those stocks with the algo as a helper it is netting me 10% so far daily (those this last fifgure will likely come down as today was an exceptionally good day for one of the stocks I keep my eye on)
@mistermonster Well anythign that is truly and completely random by definition cant be predicted. so not sure any algorithm could do better than 50% on stochastic data if by that you mean full random.
So im not really sure those two statements are different things... But it was designed for the purpose of the stock market, though should be applicable to any data stream with similar characteristics,.
@mistermonster Its a tricky place I'm in. If i explain it enough to replicate it then I risk loosing the investment advantage. Moreover if i dont explain enough to replicate it I wont be saying anything useful.
@mistermonster There are aspects I can share, like the profit results from historic testing, some examples of it making predictions on a chart with a limited time span... but that isnt likely to be helpful for you to get anything useful out of it.
@mistermonster Anything I can say in public i can say in private. If you'd like to continue discussing it, or for a link to some of the results, we can do it in public here.