Is this essentially a tuned version of the whole "Shannon's Demon" a.k.a martingale system that makes a run at the HN front page every six months or so?
People often think beating the market is impossible, and for an unaided human, it may be. But just like Magnus Carlsen cannot come close to defeating Stockfish at chess, sophisticated algorithms that analyze far more data than possible for a human are on an entirely different playing field. The ironic thing is the growth in the belief in the EMH and passive investing has actually made beating the market easier in recent years as there's simply much less competition and more money buying no matter what the economic conditions or monetary policy are to exploit. I've written a blog post on my take in depth on the subject here: https://grizzlybulls.com/blog/time-in-the-market-vs-timing-t...
I saw something it doesn't appear is present in your models, and I extrapolated from it into a program that chases that thing. Nonetheless it definitely seems like we've worked in a similar direction, as one potential application of my model is a simple long stock vs dollar trigger. And you've probably gleaned other insights I haven't. Offhand, would you be open to getting in touch and swapping strategies / pitfalls?
How long have you been running it live, and how far back does your backtest data run? How closely are you seeing real returns match backtest? After running live for over 2 years, I've seen up to 6 month periods where the model outperformed the backtest, but overall the models have underperformed to varying degrees as expected. Though I have spent hundreds of hours dedicated to removing noise and overfit bias, I've come to the conclusion it isn't possible to 100% remove it, which combined with expected market regime changes where legitimate patterns become unprofitable means that in the long run every model is essentially guaranteed to underperform its backtest, the question becomes simply to what degree. However, with a strong enough model, even underperforming the backtest can lead to substantial alpha which is what I and our members have experienced so far this year.
The testing data I'm using goes back to Y2K. Overfitting is definitely a concern. I've proven that a delta that worked one year doesn't work the next, or what worked for one five-year span doesn't work on the next five. But what's interesting is that the local delta mean can be broadly broken into distinct eras by looking at sliding time windows. e.g. From 1998-2008, the best overall fit scales down well to each year. 2008-2012, 2012-2020, 2020-now... the last one is the great unknown, of course, and too early to call if I've gotten close to it. Any test that covers the covid disruption or the 2008 crisis has a nexus that skews future results to the high side, so I feel those can't be trusted. If I can beat the market by 20% in the first year, I'll be happy.
I'll keep an eye on your progress. Best of luck!