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Average Trade

аThis statistic will tell you what the average hypothetical trade has been. You must make certain that when you test your system, you deduct slippage and commission from your average trade. Commissions add up, even discount commissions. And slippage is an important factor when determining system performance. As a rule of thumb, I recommend deducting between $75 and $100 per trade for slippage and commission.

Once this has been done, you will often significantly reduce the average trade figure. As I pointed out earlier, you must also pay close attention to the largest winning trade and the largest losing trade when evaluating the average trade. The average trade figure is important, since it considers all profits, all losses, slippage, and commission.

Optimization

There has been considerable controversy about trading system optimization. What exactly is wrong with optimizing systems? Can you go too far? Is there a happy medium?

The real issues in system optimization are complex, and they've been exacerbated by the tendency of systems developers to optimize their programs above and beyond any reasonable degree. To optimize a system is to discover the parameters that provide the best results in hypothetical back-testing. In other words, optimization is a form of discovering what would have produced the best results using numerous if-then scenarios.

Before affordable computer hardware and software were available, optimization was a long and laborious procedure. To discover the best fit, the systems developer would need to repeatedly backtrack and test several variables. If the system parameters were numerous, the process was virtually impossible. Obviously, computers have made this a quick and efficient task. Now any trader with several thousand dollars can develop optimized systems.

Such ease of testing and optimizing is both good and bad. On the one hand, it allows traders to develop, test, and refine (i.e., optimize) systems much more rapidly. On the other hand, it has opened the door to what is called curve-fitting. The simple fact is that the powerful system-testing programs now available allow traders as well as systems vendors to repeatedly test a host of timing variables, stop losses, and other risk management schemes in order to determine which combinations would have produced the best results. In effect, this procedure fits the best parameters on past history to produce the best hypothetical results. However, the conclusions reached by such methods are often specious.

The trader who tests and retests to find the best fit will eventually reach his or her goal, but the goal itself may be nothing more than a reflection of the curve-fitted results. Tests tell us what has worked in the past but may not reveal anything worthwhile about

Once this has been done, you will often significantly reduce the average trade figure. As I pointed out earlier, you must also pay close attention to the largest winning trade and the largest losing trade when evaluating the average trade. The average trade figure is important, since it considers all profits, all losses, slippage, and commission.