I was having a discussion with someone who runs a fund based on automated trading. I came up with a pretty good algorithm for trading. First he tested it, and then recommended I learn how to do backtesting on the computer. His feedback was that it works in the short run, but it has to work well in the long run to adopt it...I understand that level of conservatism. As for learning it, I went through that rite of passage this weekend, learned to code (somewhat) and started tweaking the algorithm. Now it works great (seems to).
But here's my long-winded question. Suppose you develop an algorithm that works really great in the short term (like over the last 6 months). But over the last few years, it would have lost money. Get that? I has blistering returns in back-testing now, but if I'd have started using it a few years ago, I would have lost money.
I know that some methods work and then stop working. My question to you is what would you do? How good would a method or algorithm have to be in the short run for you to adopt it, even if it didn't work well in the long run?
Just curious,
SM
But here's my long-winded question. Suppose you develop an algorithm that works really great in the short term (like over the last 6 months). But over the last few years, it would have lost money. Get that? I has blistering returns in back-testing now, but if I'd have started using it a few years ago, I would have lost money.
I know that some methods work and then stop working. My question to you is what would you do? How good would a method or algorithm have to be in the short run for you to adopt it, even if it didn't work well in the long run?
Just curious,
SM
