zealousteedo

As a newbie to algorithmic trading, and having designed my first working algorithmic trading system (with hope of many more), I'm looking for experiential advice on controlling data mining bias (overfitting as it were). I'm not looking for textbook answers, but how do YOU as a system designer actually attempt to avoid data mining bias? As for myself, to get the ball rolling, on my last system, I developed my system against several different types of securities, performed out of sample testing on 20 percent of my historical data, as well as employed a modified version of White's reality check (one should note that introducing negative-return models to the RC will hinder it's effectiveness, and therefore one must remove them from the final calculation to make the test effective) to determine the usefulness of my system. Any experiences would be great!