Genetic programming-evolved technical trading rules can outperform buy-and-hold (PDF)
cs.ucl.ac.uk
cs.ucl.ac.uk
And these papers' results, in the interest of the authors who wrote them, will only tell you the best trial run that they have gotten - but the trouble is: out in the real world, judging your trading agent's performance is not by running hundreds of GA trials on historical stock data and publishing the best results; but you have gotta put your money where your GA technical rules tell you, whether the rules evolved are sub-optimal or not.
I know for a fact that some investment banks use these techniques; they just aren't using them to make a mechanical "trade/no-trade" decision.
What Joe Schmoe on the street reading these papers is interested in is the possibility of lucrative personal trading. The papers ostensibly claim to instead be examining market efficiency. Consequently reading these papers is kind of disappointing. But, the reason I submitted the paper was its unorthodox approach which differs from most of the other literature on applying evolutionary computation to mechanical trading.
I don't think it makes sense to play with your money unless you're very rich. Returns like 50% per year are quite unlikely in the longer run, yet very risky. Instead, consider starting a fund.
I'd be much more willing to tinker with it if I could do it with someone else's money. The hedge fund motto is "other people's lives, other people's money."
I am fascinated no end that a group of nerds is able to game the system to such an astounding degree. In this century, it isn't by gaming the casino that loads of cash can be made.
These guys run a hedge fund that is so successful it no longer accepts money from the public, and only manages the assets of its own employees. Using different secret strategies and to an extent human-supervised automatic trading. Its annualized return since its birth in the eighties has been on the order of 37%.