Michael Gutmann’s Futures magazine article: Minimizing loss: Run-length trade statistics
I read the article in Futures Magazine last month by Michael Gutmann; he goes into a lot of detail on how you can know if your automated trading system is doing what is expected, or if it has broken down. How can you know? When you run an automated system, you will have (or you should have) statistics from back testing that show the percentage of wins versus losses and the maximum number of consecutive losing trades. That second number, the number of consecutive losing trades, is a pain threshold for traders watching their automated system trade and lose. How many trades can you watch your system lose before you pull the plug? Is there a way to determine this number for a particular trading system?
As it turns out, there is. Using some statistics math, Gutmann shows how you can determine the most probable number of losing trades you should have to endure, providing an objective measure to determine if you should stay with your system, or bail. (Or at least, re-tune the parameters.)
In the article, Gutmann shows a nice table of trade statistics, based on 250 trades; the rows are runs of length N and the columns are the probability of that number of consecutive runs for a 30%, a 50% and a 70% win ratio system. For example, with a system that wins 30% of the time, you should expect to see 9 losses in a row 60% of the time; with a system that wins 70% of the time, expect to see 5 losses in a row 25% of the time. Gutmann uses some heavy math to show how he arrived at those numbers, but the table captures much of the data in an easy to read format.
So, if your automated system presents you with a 9-loss losing streak, you can take a look at the chart and see that that should only happen 5% of the time; it might be time to toss that particular strategy.
The article also states that you can write Mr. Gutmann and request the C++ code for running the numbers on your own trades. I did write him, and I received a nice reply from him with the C++ code. I have yet to run it on my trading data, but I plan to do so soon, and will provide an update here when I do so.
See also Michael Guttman’s book: The Very Latest E-Mini Trading, 2nd Edition: Using Market Anticipation to Trade Electronic Futures