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Any opinions or experience on whether anchored forward optimization
(keeping the start date fixed) produces more reliable results than the more
common walk forward optimization, where the "in sample window is rolled
forward"
Most walk forward examples in books describe optimizing over 2 years for
example - trading the optimized parameters over the next six months - and
the rolling the whole two year window forward by six months and the
repeating.
My own testing has found anchored to be much more effective - I guess
building on the concept that if your going to optimize anyway then use as
much data as possible.
I have been doing some work on a Double Linear Regression slope system on
index futures where I optimize over the whole data range (3 years - as
before three years the market was traded on the floor - is now screen
traded for the last 3 years) trade the result on the next month and then
add this recent "traded" month to the data series - re-optimize, trade on
the following month etc. Therefore as time passes my in sample data length
keeps getting bigger and bigger.
On OUT OF SAMPLE trading - WITHOUT any stops yet - still doing the MAE
analysis the system is showing the following results using anchored
analysis.
Total Trades 143
% Winning 51.05%
Average Losing 2.95%
Average Winning 3.35%
Average Trade 0.31%
Largest Winner 18.63%
Largest Loser 10.6% (would obviously be stopped out as below)
Profit Factor 1.27
MAE average 2.31% (will be re-running results with a 2.50% stop
I think)
Any views on the above??
MK
(sorry about disclaimer)
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