Investing and Trading in Sprints

Trading and Investing in Sprints

Recently, I wrote about how investors and traders alike could benefit from adapting a more agile mindset. Specifically…

By leaning to embrace uncertainty, and develop mechanisms to adapt, you can improve your performance, with less effort and less worry. Sounds pretty good, right?

Well, today I wanted to take that line of thinking one step further. Specifically, I want to talk about trading with and investing with a sprint methodology. Allow me to explain.

Trading in Sprints Explained:

In agile development, tasks are conquered in iterations called “sprints.” The basic idea is that you set a 2-4 week goal and work with your team to achieve that goal. These work intervals are called sprints.

At the end of the 2-4 week sprint, you review your progress, adapt to feedback from the market and plan your goal for the next sprint. Do you see where I’m going with this?

The Advantage of Trading in Sample Sizes:

In the amazing book, Trading in the Zone, author Mark Douglas talks about the idea of trading in sample sizes. He recommends that traders stick to a methodology for at least 20 trades before making any tweaks.

The idea here is that trading and investing happen in a very uncertain and random environment. Just by pure chance alone, you’re likely to have a broad distribution between winners and losers, as well as the magnitude of each.

So make your trades or investments in sets of 20 trades (or sprints of 20 trades) instead of judging each trade by it’s own merit. You simple need a sample size of trades to reflect a given methodology. After 20 trades, you should have a more robust idea of whether or not you’re going to be profitable.

Make sense?

The key difference between trading and agile sprints, is that in trading and investing you need to think of “Event-based-sprints” vs. “time-based-sprints.” Instead of watching your results over 2 week periods, watch your results over 20 trade periods.

So what do you think? Could you see yourself trading in sample sizes to try and isolate your edge in the markets?