Fool’s gold
One of the biggest issues facing algorithmic traders is recognizing and avoiding the data-mining / back-testing phenomenon of fool’s gold.
The problem is that the evidently improbable becomes incredibly less so when many instances are considered. One of the inevitable first reactions a would-be algorithmic trader has when first putting together a strategy and running it through a parameter-based optimizer is:
“I’m going to be rich!”
“How could it be otherwise? There’s no way such an improbable result could indicate anything but that my strategy is predictive – I have placed my finger on one of those oft-mentioned market inefficiencies and thereby created a little money machine!”
Happily, ours is an experimental practice, so it’s quite easy to test our hypothesis and (assuming you have a reasonable environment in which your back-tested strategy can be placed – unchanged – onto some real financial exchange) place our money where our mouth is…
And this is where it gets tricky – because you might even make some money! Maybe a lot. But unless you’re really really lucky, at some point your fortunes will turn and that strategy which over the past n months has been a demonstrable goldmine will suddenly start misbehaving. Your elation will turn to confusion and then chagrin and then – for the obstinate – pain and horror.
What is going on here? How did we happy miners find ourselves grasping bitter buckets filled with fool’s gold? This will be the subject of our initial series of posts…
