winner is larger, but because there’s only one winner for two losers, the average
profit per trade is affected.
Another important thing to remember is that this number also is highly influ-
enced by many trades made at the beginning of the testing period, when the mar-
kets were trading at considerably lower levels. The average profit per trade in
today’s markets (in dollar terms) is considerably higher.
Nonetheless, this system is a good example of how a steady stream of small-
dollar gains can accumulate significantly over time. Systems that profit in this way
can be considerably more profitable than a buy-and-hold strategy, or a trade
approach that shoots for the big bucks on every trade.Revising the Research and Modifying the System
This system really doesn’t have any optimizable variables to work with, except for
the exit levels (which we will leave for Part 3) and the option to work with a trail-
ing stop instead of a fixed stop loss. However, I decided to feature it here as an
example of a different testing methodology. The logic for researching the signals
in this system has already been discussed in Chapter 1. Therefore, I will only run
through it again very briefly.
During the initial testing of a system, we really shouldn’t concern ourselves
with the performance of the system, but rather the reliability of the signals it gen-
erates. To do that, you need to test all the signals generated, using standardized
stops and exits. Normal system testing usually only tests the first signal in a clus-
ter of entry signals, assuming the others can be ignored because you would have
been in a trade already. However, whether you would have been in a trade or not
depends on your stop-loss and profit-taking levels and how long the trade should
last if none of these levels is hit.
Therefore, when researching a system, it’s important to look at all signals it
generates, so that it can be trusted just as much on its second or third signals as it
can on its first signal. For example, assume that you, for some reason, missed a
signal one day. The next day you get a new signal in the same stock, despite the
fact that you should have been in this stock already had you been able to trade. If
you haven’t done your research properly, you have no idea whether the second sig-
nal is likely to be as valid and reliable as the first one.
Look at Figure 15.1, which shows a chart of all signals this particular system
generated in Microsoft during the fall of 2001. It shows that in early August 2001,
two signals indicated to go short only one day apart from each other. In late October
and early November, two signals two days in a row indicated to go long. The point
is that, in either case, the second signal most likely would have gone unanalyzed,
because you already would have been in a trade generated by the first signal.
The same reasoning holds for the exit techniques as well. To make the most
out of the chart pattern and its exit techniques, you need to have done yourCHAPTER 15 Expert Exits 175