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Hello!
I think Pardo's WFE is questionable. How can you compare IS CAR with OOS CAR
if the concatenated IS and OOS periods are completely different? As an example,
let's assume that you're doing a walk-forward test with the first IS period
starting on, say, 01/01/1996 and ending 31/12/1999 and, consequently, the first
OOS period starting on 01/01/2000. Considering how the markets developed from
2000, it's very probable that the IS CAR is completely different from the OOS
CAR until today as market conditions changed dramatically. So comparing both
CARs as absolute figures is like comparing apples with oranges as different
market condition will also affect the performance of your trading system and,
hence, the CARs over the concatenated IS and OOS periods.
In my opinion, a better and more reasonable (but still no perfect) approach is
comparing IS *Relative* CAR with OOS *Relative* CAR. The formula would be:
WFE=(IS CAR/IS Buy&Hold CAR) / (OOS CAR/OOS Buy&Hold CAR)
Just my 2 cents.
Thomas
On Saturday 09 May 2009 05:03:16 dloyer123 wrote:
> --- In amibroker@xxxxxxxxxxxxxxx, Rajiv Arya <rajivarya87@xxx> wrote:
> > I like to compute a ratio of the out-sample metric and divide it by the
> > in-sample metric.
> >
> > And I like to look for multiple runs of out-sample/in-sample ratio to be
> > above 0.5 and with little fluctuation.
>
> That is similar to Pardo's WFE (Walk forward efficiency), or a measure of
> how much curve fitting inflated test results. Pardo suggests taking the
> concatenated out of sample returns and divide by the result treating the
> entire combined data set as in sample. Anything below 0.65 will probably
> not trade well live. The higher, the better.
>
>
>
>
>
>
>
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