I’m often asked about program trading, and whether computers make better traders than people. The theory seems sound. If execution is everything, and if our own psychology is our biggest barrier to success, then why not remove the human element altogether and let a machine do the work?
The answer, as I’ve touched on before, is that a good human trader can usually beat a computer algorithm, because humans are infinitely adaptable. Where a machine sees fixed rules, we see the nuance in every potential trade. We can bend the rules. Sometimes we can bend them to get into a trade earlier than our rule says we should. Sometimes we stretch a rule to stay in for longer because the probability is that doing so will yield a higher profit. And sometimes we can look at a trade that should, according to the rules, be a perfect entry, and say no, this one clearly isn’t going to work. Bending and adapting rules on the fly can keep us out of bad trades and make winning ones more profitable.
But more than just being able to bend rules, human traders are able to learn new things as we trade. We can spot new patterns, learn to see the small differences between stocks that a computer is unlikely to be able to pick up on (I say unlikely because I know ‘machine learning’ is a hot topic these days, and perhaps computers are getting better at this stuff).
Anyway, all of this is by way of introduction to the trade I wanted to post today, on Tesla:
Anyone who has read my stock trading book will recognize the setup here. It is, well, textbook. What’s interesting is the exit. My strategy offers a number of ways to determine when to exit a trade of this type (so already it’s something a computer would have trouble with). As I trade Tesla more often, I’m learning more about how the stock behaves on a micro level, and I’m able to use that new knowledge to fine tune my exits. I’m far from perfect — technically I could have gained an extra couple of hundred dollars on this trade — but I’m squeezing out a little more than if I just mindlessly followed my own rules.
TSLA is just a stock like any other of course, and it behaves largely like any other. But there are small details about it that I am noticing again and again. Combined, these are enabling me to take short sharp trades like this one, which netted $1,600 profit in a shade over five minutes.
Learning to read individual stocks is definitely not necessary to succeed in day trading, and indeed I would advise against trying to do so until consistently profitable (and possibly at all). But once day trading hits the ‘boring’ stage, the stage where every day is much the same and we’re just going through the motions, studying a stock and learning its ins and outs can inject some new interest and motivation to the job.