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Back to the Future
Perhaps one of the most interesting questions in this regard is: How
can you determine what you actually may be able to achieve in real
trading? 
The answer to this question makes sense only when you under-
stand the factors that affect performance loss, the need for robust
measures, and the need for a sufficient number of representative
samples. Once you have this, you can start to think about the likely
effect of drift and change in the markets and how even excellent
systems that have been built by experienced traders fluctuate in
terms of their results. The reality is that you do not know and can-
not predict how a system will perform. The best you can do is use
tools that provide a sense of the range of potential values and the
factors that affect those values.
Lucky Systems
If a system has performed particularly well in the recent past, it may
have been a matter of luck or there may have been ideal market
conditions for that system. Generally, systems that have done well
tend to have difficult periods after those good periods. Do not
expect to be able to repeat that lucky performance in the future. It
may happen, but do not count on it. You are more likely to expe-
rience a period of suboptimal performance.
Parameter Scrambling
A very good exercise one should always perform before considering
trading with any particular system is what I call parameter scram-
bling. Take a few system parameters and change them by a consid-
erable amount, say, 20 to 25 percent of their value. Pick a point that
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Way of the Turtle

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is considerably down the side of the optimization curves shown in
Figures 12-1 and 12-2. Now look at the results for this test. Using
the Bollinger Breakout system, I decided to see what would happen
when we moved from the optimal values of 350 days and –0.8 for
the exit threshold to 250 days and 0.0 for the exit threshold. This
decreased the RAR% from 59 percent to 58 percent and the R-
cubed value from 3.67 to 2.18: A fairly dramatic change. This is just
the sort of dramatic change one might expect to get when going
from testing using historical data to actual trading in the market.