Way of the turtle

Rolling Optimization Windows
Using rolling optimization windows is another exercise that is more
directly parallel to the experience of going from testing to real trad-
ing. To do this, pick a date perhaps 8 or 10 years in the past and then
optimize with all the data before that point, using the same opti-
mization methods you normally would use and making the same sorts
of trade-offs you normally would make, pretending that you have data
available only up to that point. When you have finished determining
the optimal parameter values, run a simulation of those parameters
using data for the two years after the years of the optimization. How
did the performance for the subsequent several years hold up?
Continue this process with a date a few more years into the
future (about six or eight years in the past). How does this compare
with your original test and the first rolling window? How does it
compare with the test using your original parameter values, the
optimal values based on having all the data available? Repeat the
process until you have reached the current time frame.
To illustrate this, I ran an optimization of the Bollinger Break-
out system in which I varied each of the three parameters across a
On Solid Ground
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Table 12-4
Rolling Optimization Window Test versus Actual RAR%
Period
MA
Entry
Exit
RAR% Test
RAR% Actual
%
R
4
Test
R
4
Actual
%
1989 to 1998 
280 
1.8 
–0.8 
55.0% 
58.5% 
6.3% 
7.34 
5.60