Like most system development, the journey determines the destination. In developing this system, we first collected data with our basic random entry system and used that data to optimize our initial rules (“Guide to system development,” September 2012). Next, we discovered that by revising our entry time, to 4 a.m. from 8 a.m., we could induce the system to be profitable. (Perhaps not coincidentally, 4 a.m. is the end of the first hour of the London forex session.) This change yielded a profitable system with a positive expectancy. We then could proceed with optimizing our initial stop loss and profit target parameters (“How to set up profit targets and control losses,” December 2012).
Optimizing the stop loss resulted in a reduction of the net profit by nearly 50%, but in return we gained the ability to limit and quantify our risk for each trade. As we shall see, the ability to quantify our risk plays an important role when we address possibly the most important step of system development: Money management.
Unfortunately, we didn’t fare as well with optimizing the profit target, which resulted in wiping out nearly all of the already reduced profit. This was unacceptable, and thus a predetermined profit target was removed from consideration. The original time-stop exit — that is, exiting the trade at the end of the trading session, or 5 p.m. — will be used in the money management phase (see “Time and trailing stops,” last page).
In the money management phase, a trade-size algorithm will be added to the random entry system with an initial stop loss. After that phase is complete, we’ll apply a simplified form of Monte Carlo simulation to determine if our profitable results (if any) truly are because of the system having an edge — that is, the ability to identify and exploit a repeating pattern of market behavior.