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I am using the walk forward backtest in order to obtain a realistic CAR data, but I am thinking, since some time ago, that perhaps the walk forward study is not as good as everybody say.
I have a system that gets, during the last 10 years, a 68% annual profit, and a 16% DD.
Of course, I obtain that CAR optimizing one variable, during the last 10 years, and using simultaneous stocks; I mean, is a very very big sample..
The system has few variables, most of them comes from the only indicator I use, with the standard parameters.
Another variable is what I optimize, obtaining the best result in 0.96.
When I perform a walk forward simulation, the CAR goes down to 29%.
Mr Howard Bandy say in his very good book `Quantitative Trading systems' that the in-sample studies are not useful, and we have to consider only out-of-sample studies.
But when I see my in-sample backtest, with a result of 68%, I see that the value of 0.96 has a very good performance every year.
I mean, if I optimize only from 99 to 2003, e.g., the 0.96 value of the variable has a very good performance. And occurs the same in 2003-2007, or in 2007-2009.
In the last two years, that has been so volatile, the 0.96 value is not the best value by far. But, it still has a very good CAR of 105%, although another values has better results.
So I wonder? Is really worth the walk forward? If an optimized variable has a good performance over many years, not always the best, but always a good performance..
Is preferably to use it instead of the madness of changing continuously the variables using the walk forward with a 1 month step???
Thanks, and sorry for my English..
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