Ultimate Algorithmic Trading System

Walk-Forward Test Procedure
1998 1999 2000 2001
2002 2003 2004 2005 2006 2007 2008
In-sample data (IS) - Optimization
Out-of-sample data (OOS) - Verification (backtest)
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COMPLETE TRADING ALGORITHMS
FIGURE 3.4 Walk-forward testing begins with a backtest used to derive the desired parameter.
Then, it applies that parameter going forward.
Source: AmiBroker
AmiBroker’s walk-forward optimizer (WFO) derived the best parameter set from
January 1, 2006, to January 1, 2010, and then carried those parameters forward
from January 1, 2010, to January 1, 2011. In this test, the algorithm netted $35,330
for 2010. It then included 2010 and backed up to January 1, 2007, and then carried
those parameters forward through 2011. However, this time the algorithm lost a
whopping −$56,532. Keep stepping through the figure and you can see how the
system performed through the present. What’s really interesting is the shift in the
parameter sets. You would think by adding just another year to the backtest during
the periodic readjustment the parameters wouldn’t shift that much. Take a look at
Figures 3.5 and 3.6.
The first year in our OOS window is 2010. The WFO picked the parameter
set [72 day, 1.5 std. devs., 3000 stop] to apply to 2010 and the results looked
great. Notice the wide shift in the parameters for 2011 [111, 0.25, 6000]. These
parameters performed horribly, losing over $56,000. The parameters for 2012
shifted some more [143, 0.25, 3500]. These parameters didn’t do much better.
2013 also shows a dramatic shift, [45, 3, 3500], but at least the algorithm made
a little money. The parameter set stayed constant for 2014, and the algorithm
really brought it home, with almost $72,000 in profit. The end result with periodic
reoptimization beat the pants off of the static set with $45,000 in profit and a little
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