For the week, the Power Dip was up 0.53% while the [[SPY]] gained 1.52% (from last Friday’s to this Friday’s close).
Discipline is perhaps the most overlooked factor when considering how to successfully trade a mechanical system. For example, what should one do when his or her system is under-performing a benchmark? Should it be tossed to the curb? Does the under-performance mean it is broken? It may or may not be obvious, but I ask these questions more for rhetorical value, as the Power Dip continues to under-perform the indices. It is during these times that it is most important that one possess the discipline to stick with the system.
Control charts can be used to better understand what is happening with a system. Control charts give a “look under the hood,” allowing the mechanical trader a deeper understanding of system performance. If the control charts show everything to be within normal expectations, one may find it easier to stay disciplined when the system has difficult periods.
System Health Control Charts
Below I present two charts.
The first shows two averages: the Total Average percentage gain/loss and the 20 Trade Average percentage gain/loss.
The second also shows two averages: the Total Average win percentage and the 20 Trade Average win percentage.
Note the Law of Large Numbers in action as system takes 80 trades before the average trade approximates the backtest generated average trade. In other words, the TotalAvg is volatile until it is smoothed by more and more data.
The 20TradeAvg remains volatile as it will only average the last 20 trades.
The chart shows that the system has seen a worse period, where 20 trade average dipped to ~2.6%. The system recovered quickly and peaked with an average trade near 3.5%.
The Win Percentage graph is interesting as it shows that the system beat historical expectations of percentage of winning trades for a span of approximately 70 trades (or half the number of trades made since I’ve tracked in on the blog).
How To Interpret the Charts
The charts show that the Power Dip oscillates between over and under-performing. This is normal. Think of it as reversion to the mean. As long as the total average is consistent with historical expectations, and the 20TradeAvg is oscillating above and below the total average, everything is okay.
To get an even better understanding, we would use the data generated from backtesting and then add our real-time data for comparison. The results will not match, due primarily to slippage, but it will give a long history so that we get an idea of what is normal in terms of the oscillation of the short average around the long average.
These types of calculations can also be used to turn systems off and on, but that is beyond the scope of tonight’s post.
Current Trades
Below is the updated spreadsheet, with the metrics for all trades on top and October’s trades below.
The system has open Flowers Foods, Inc. [[FLO]] , DISH Network Corp. [[DISH]] , and Silver Standard Resources Inc. (USA) [[SSRI]] . It will add two more positions on Monday’s open.
I like the Law of Large Numbers reference. Your system seems, for the moment, to be beating the odds. Nicely done.
Thanks for noticing Mr. Thaler. Obviously my control charts, which I thought were very cool, were not so very cool to anyone, except perhaps to you and me.
It’s just the nature of a system. The mathematics behind it is very interesting, but the outputs of those systems tend to blur in front of the face.